Study of the properties of red mud-waste incineration ash composites

Study of the properties of red mud-waste incineration ash composites | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Study of the properties of red mud-waste incineration ash composites yuxiang Song, mingyang Jiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3800561/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aiming at the environmental problems caused by waste incineration ash, a reuse solution was proposed to use waste incineration ash and red mud for the preparation of Controlled Low Strength Material (CLSM), to determine the effect of each parameter on the performance of the material by using a one-way test and to determine the reasonable interval of each parameter, and to design the test by using the Box-Behnken Response Surface Method. Three factors, namely, red mud percentage, water-gum ratio, and glue-sand ratio, were used as test variables, and 14d unconfined compressive strength, mobility, and cost were used as response values to optimize the objectives. The heavy metal toxicity and micro-morphology of CLSM were investigated by using microscopic means such as heavy metal leaching concentration, XRD, and FTIR. The results of the study showed that the optimal mixing ratio of CLSM was 0.5 for red mud percentage, 0.667 for water-gum ratio, and 0.45 for gum-sand ratio, which can effectively utilize the waste incineration ash and reduce environmental pollution. It was found that under alkali activation, the red mud-refuse incineration ash cementation system would change and produce new substances, with crystals as the framework and gel as the filling, forming a dense structure. Earth and environmental sciences/Environmental sciences Physical sciences/Engineering waste incineration ash CLSM response surface methodology reaction mechanism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 1 Introduction Red mud is a kind of strong alkaline industrial waste generated from the refining process of alumina, which is easily discharged directly into the environment and causes water and soil pollution [ 1 ] . Red mud is mainly generated by the Bayer method and sintering method, which contains a variety of metal elements, the presence of a large number of trivalent iron ions, and red color [ 2 ] . A typical production of 1 tonne of alumina is estimated at between 1.0 and 1.5 tonnes of red sludge.In 2021, our production of alumina was 77.475 million tons, an increase of 5% year-on-year, with continued production growth. Red mud has high alkali content but is not active enough [ 3 ] . CLSM can be prepared by adding lime or gypsum to red mud [ 4 ] . In recent years, the utilization of industrial solid waste for CLSM preparation has been steadily progressing both domestically and globally. According to the American Concrete Institute's (ACI) definition of CLSM, controlled low-strength material (CLSM) is a self-consolidating cementitious material mainly used as a backfill, instead of compacted fill, and is designed to manufacture self-consolidating cementitious mixtures with compressive strengths of 1200 psi (8.3 MPa) or lower [ 5 – 7 ] .The properties associated with controlled low-strength materials (CLSM) have been well studied and proven to meet the relevant specification requirements [ 8 – 11 ] . Riviera P P et al [ 12 ] conducted a study to evaluate the practicality of incorporating controlled low-strength materials (CLSM) into road tunnel pavement foundations. Waste incineration fly ash is an off-white or dark gray fine powder, with a low water content, generally rod-like, polygonal, cotton-wool, spherical, and other irregular shapes, uneven particle size, high porosity, and large specific surface area. From the surface of the fly ash particles, the internal composition of the mass fraction of elements, Si, Ca, and Al as the main elements, in addition, also contains more K, Na, Cl, Fe, Ti, and other metals, belongs to the Cao-SiO 2 -Al 2 O 3 (Fe 2 O 3 ) system [ 13 ] . Fly ash particle size is not uniform, by the particles, reaction products, unreacted products, and condensation products aggregated irregular objects, basically in the 100 µm or less, the surface is rough in the form of polygonal angularity (irregular angularity); high porosity than the surface area is large, for the heavy metal enrichment attached to provide convenient conditions [ 14 – 15 ] . Municipal waste incineration fly ash contains active components that can be utilized to create novel eco-cement mixed materials [ 16 ] .Li Chunlin [ 17 ] attempted to prepare a geopolymer curing body with excellent performance by using MSW incineration fly ash as raw material and alkali excitation with modulus 1. Qiao et al [ 18 ] explored that the addition of an appropriate amount of domestic waste incineration fly ash as a filler into asphalt mixtures can effectively improve the high-temperature stability performance and water stability of asphalt mixtures.Naganathan S et al [ 19 ] assessed the characteristics of controlled low-strength materials (CLSM) produced from industrial waste incineration bottom ash and quarry dust, and it was evident that industrial waste incineration bottom ash and quarry dust could enhance the properties of controlled low-strength materials (CLSM).Guangyin, ZHEN et al [ 20 ] employed sewage sludge and waste incineration bottom ash instead of sulpho Calcium Aluminate Cement (CA) to produce Controlled Low Strength Materials (CLSM), affirming the potential of using sewage sludge and bottom ash in the production of CLSM. R Taurino et al [ 21 ] studied the sintering process and technological properties of a new type of sintered bricks based on large quantities of reprocessed Domestic Waste (WMS) bottom ash and refractory clay. P Aggarwal et al [ 22 ] studied the use of different percentages (0–50%) of bottom ash instead of fine aggregate to prepare concrete with compressive strength comparable to that of normal concrete.WF Tan et al [ 23 ] mixed municipal solid waste incineration (MSWI) ash with shale and sludge for washing pretreatment, used it for the production of lightweight aggregate, and processed it into ceramic particles. Y Bai et al [ 24 ] explored the application of solid wastes red mud (RM), carbide slag (CS), and MSWIFA in the production of eco-friendly geopolymers. Yuancheng Li et al [ 25 ] proposed an innovative method of mechanically activating red mud, in combination with municipal domestic waste incineration fly ash (MSWIFA), to generate red mud-based mass polymer materials (RGM). J Xie et al [ 26 ] stimulated a combination of 70% municipal solid waste incineration (MSWI) fly ash and 30% kaolin clay using potassium hydroxide as an activator, during which the maximum geopolymer strength was achieved. Wisitsak Tabyang et al [ 27 ] examined the utilization of municipal solid waste incineration fly ash (MSWI FA) geopolymer in pavement applications to stabilize the strength of recycled concrete aggregate (RCA).C Fan et al [ 28 ] compared the physicochemical properties, compressive strength, microstructure and morphology of coal fly ash based geopolymers and silicate cement cured MSWI fly ash and showed that fly ash based polymers can be effective in achieving the resource utilization of MSWI.Lei Zheng et al [ 29 ] investigated the alkaline activator The effects of dosage and Si/Al molar ratio on the compressive strength and microstructure of MSWI fly ash based mass polymers were investigated.Municipal solid waste incineration residues contain a large number of toxic substances, and if their precipitation can be effectively reduced, the degree of resource utilization of waste incineration ash can be effectively improved [ 30 – 35 ] . X Tian et al [ 36 ] effectively enhanced the coagulation of MSWI fly ash by using waste glass as an additive, and the immobilization efficiency of Cr increased with the addition of waste glass. BHNLA B et al [ 37 ] examined the impact of employing a permeable column test and demonstrated that regular rainfall (15 mm/h) exerted a more significant influence on the leaching of ions (Cl, Na, K, and Ca) and total organic carbon (TOC) from BA (< 10 mm particle size) in contrast to intense rainfall (25, 50 and 100 mm/h). Xiao R et al [38] examined how waste glass affects the release of ions (Cl, Na, K, and Ca) from BA (< 10 mm particle size) when compared to heavy rainfall (25, 50, and 100 mm/h) using an electron microscope (SEM), X-ray diffraction (XRD), and thermodynamic simulations. The microstructure and phase combination of CLSMs were created using GP-CH binders through electron microscopy (SEM), X-ray diffraction (XRD), and thermodynamic simulation. A comprehensive analysis of CLSM from multiple angles has been undertaken, examining the influence of various materials and dosage adjustments on the engineering features of CLSM, as well as the effect of single factor changes on the performance of CLSM. A concise description of the direction of comprehensive utilization of red mud and waste incineration products is provided, offering a novel approach to combining red mud and waste incineration fly ash in the fabrication of roadbed materials. In this paper, a new CLSM composite material was developed with alkali-excited red mud-refuse incineration ash-river sand, and the ratios of red mud and refuse incineration ash-based materials were optimized using the response surface method. The leaching method of toxicity of solid waste leaching was implemented with sulphuric acid-nitric acid solution as the leaching agent [ 39 ] to evaluate the heavy metal leaching of CLSM, and the microforms and chemical compositions of hydration products were evaluated through a combination of X-ray diffraction (XRD), scanning electron microscopy-energy spectroscopy (SEM-EDS), and Fourier transforms infrared spectroscopy (FTIR), and the microstructure formation of CLSM was evaluated. 2 Materials and Methods 2.1 Raw materials 2.1.1 River sand River sand (RS) as shown in Fig. 1 (b) was obtained from Fuxin City, Liaoning Province, from the sand quarry of Fula with less than 1% mud content, and the particle size curve obtained by particle size sieving of the river sand is shown in Fig. 1 (a), in which 50% of the particles have sizes of 0.425 mm or less and 90% of the particles have sizes of 1.099 mm or less, and the fineness modulus of the river sand was calculated to be 0.99 by sieving. 2.1.2 Red mud Red mud (RM) Fig. 2 (b) from the waste produced by Shandong Aluminum Company for the production of alumina, is an earthy red solid with a density of 2815 kg/m 3 , which is dried and ground and then sieved for use, with a particle size distribution curve as shown in Fig. 2 (a), and its chemical composition as shown in Table 1 . Table 1 Composition of the main elements of red mud(%) Fe 2 O 3 SiO 2 CaO K 2 O Al 2 O 3 TiO 2 MnO 2 78.41 4.99 1.93 0.2 4.22 8.12 0.07 2.1.3 Waste Incineration Ash Waste incineration ash (MSWI) Fig. 3 (b) is the waste product generated from the incineration of municipal domestic waste by Fuxin Zhangwu County Alpha Huaneng Bioenergy Co. Ltd. with a density of 1965 kg/m 3 , and the particle size distribution curve is shown in Fig. 3 (a), and its chemical composition is shown in Table 2 . Table 2 Main elemental composition of waste incineration ash(%) CaO SiO 2 Al 2 O 3 Fe 2 O 3 MgO Na 2 O K 2 O P 2 O 5 TiO 2 ZnO BaO MnO CuO 37.95 20.213 9.146 5.956 4.015 2.811 2.361 2.2 0.869 0.29 0.202 0.158 0.093 2.1.4 Calcium hydroxide Calcium hydroxide (Ca(OH) 2 ) Fig. 4 (b) is produced by Tianjin Dengfeng Chemical Reagent Factory, the density is 2243kg/m 3 , the particle size distribution curve is shown in Fig. 4 (a), and its chemical composition is shown in Table 3 . Table 3 Calcium hydroxide major element composition(%) calcium hydroxide Hydrochloric acid insoluble substance chloride sulfuric acid iron heavy metal Magnesium salts and alkali metals deposit 95.26 0.046 0.01 0.2 0.01 0.001 0.4 0.21 2.2 Test methods The Box-Behnken response surface method was used to optimize the design of the CLSM's mix ratio, with the percentage of red mud, water-gum ratio,and glue-sand ratio as variables, and 14-d UCS, mobility, and cost as response values. In accordance with the ASTM C192 / C192M-19 [ 40 ] specification, cylindrical specimens measuring 50 mm×100 mm were meticulously prepared using the conventional curing technique at a temperature of 20 ± 2°C and a humidity exceeding 95%. The ASTM-C39/C39M-21 [ 41 ] unconfined compressive strength test technique ensures the CLSM specimen's top surface is even and even, utilizes the WDW-100E universal testing machine to carry out the UCS test, performs parallel experiments, and takes 3 tests in each group to guarantee that the coefficient of variation is less than 15%, and determines the arithmetic mean value. Concrete mobility test method concerning ASTM-D6103 [ 42 ] , using Ф75mm×150mm open cylinder mold full of CLSM, quickly (2-4s) lift the mold so that the CLSM free expansion, after stopping in the orthogonal direction to measure the diameter of the expansion to the average value of the diameter of the CLSM as the degree of flow [ 43 – 45 ] . To determine the cost, begin by gauging the apparent density of CLSM, which has a unit mass of (kg/m 3 ), then refer to the raw material-related website to check the material price, and finally, after conducting an inquiry, determine the total cost of each cubic meter of material in CLSM. Micro-experiment: select the specimens that meet the criteria of XRD, FTIR, SEM-EDS test, and heavy metal leaching test, immerse them in anhydrous ethanol to halt the hydration reaction, remove the specimens and place them in the drying oven at 70°C for 3 hours, and select the appropriate surface or specimens according to the test specifications. 3 Results and Discussion 3.1 One-factor experiments This study evaluates the effect of three elements on compressive strength and slump by employing a one-way test, with varying red mud percentage (A), water-gum ratio (B), and glue-sand ratio (C) as the evaluation criteria, so as to determine a suitable value range for the test parameters. 3.1.1 Effect of percentage of red mud on compressive strength and mobility The preparation of CLSM specimens involved the utilization of a water-gum ratio of 0.68, a glue-sand ratio of 0.4, and a red mud percentage of 0.5, 0.55, 0.6, 0.65, and 0.7, respectively, followed by the examination of the corresponding data. 3.1.2 Effect of water-gum ratio on compressive strength and mobility The CLSM specimens were prepared using a red mud percentage of 0.6, a glue-sand ratio of 0.4, and water-gum ratio of 0.66,0.67,0.68,0.69,0.7, respectively, and the corresponding data were examined. 3.1.3 Effect of glue-sand ratio on compressive strength and mobility The CLAM samples were made with a red mud percentage of 0.6, a water-gum ratio of 0.68, and a glue-sand ratio of 0.35,0.375,0.4,0.425,0.45, respectively, and the relevant information was verified. 3.1.4 One-way trial analysis Based on one-way test data, it can be concluded that the main factor affecting the UCS of CLSM after 14 days is the water-gum ratio. However, it is important to note that the water-gum ratio has a limited value and that the amount of water should not be too low as it may result in a lack of mobility and make it difficult to mix. The mobility of composites is mainly affected by the water-gum ratio and the glue-sand ratio, while the effect of red mud percentage on mobility is weak. 3.2 Regression modeling The response values for the one-way test in 3.1 were determined to be 14d unconfined compressive strength (Y1), mobility (Y2), and cost (Y3), with the percentage of red mud (A), the water-gum ratio (B) and the glue-sand ratio (C) being used as the factors for examination,17 groups of tests were generated by using Box-Behnken in the response surface methodology, and the levels of the design factors are displayed in Table 4 . The experimental program and results are displayed in Table 5 , which were used to generate a regression equation.The obtained data were entered into the software and the regression equation was obtained after quadratic regression analysis. \({Y}_{1}=21.1675+10.6625A-140.625B+157.525C+5AB+26.5AC-170BC-21.125{A}^{2}+140.625{B}^{2}-72.5{C}^{2} （1）\) \({Y}_{2}=-1105.80882-18.75A+1500B+587.5C\) (2) \({Y}_{3}=-119.4425+199.7625A+768.125B-154.875C+52.5AB+229.5AC+960BC-262.625{A}^{2}-984.375{B}^{2}-864.5{C}^{2}\) (3) Table 4 Box-Behnken design factor levels Factor Level -1 0 1 A 0.5 0.6 0.7 B 0.66 0.68 0.7 C 0.35 0.4 0.45 Table 5 Box-Behnken experimental groups and results No. A B C 14d Ucs /Mpa Slump /mm Cost /Yuan 1 -1 -1 0 3.03 120 108.95 2 1 -1 0 2.88 100 111.61 3 -1 1 0 2.46 180 102.88 4 1 1 0 2.34 165 105.96 5 -1 0 -1 2.67 105 108.67 6 1 0 -1 2.29 115 108.35 7 -1 0 1 2.35 160 100.52 8 1 0 1 2.48 170 104.79 9 0 0 -1 2.81 75 114.72 10 0 1 -1 2.58 140 106.25 11 0 -1 1 3.16 145 107.46 12 0 1 1 2.28 195 102.83 13 0 0 0 2.8 135 110.26 14 0 0 0 2.9 140 110.23 15 0 0 0 2.86 135 111.25 16 0 0 0 2.73 135 110.09 17 0 0 0 2.85 130 110.02 3.3 Regression model analysis The model relevance is determined by the coefficient of determination (R 2 ), with a larger value indicating a better fit; the correction coefficient of determination (R 2 adj ) and prediction coefficient of determination (R 2 pre ) have a higher value, and the difference between the two is less than 0.2, indicating a better interpretation of the model; the coefficient of variation (CV) is an index that reflects the degree of variation, with a coefficient of variation of less than 10% indicating the test's reliability; precision (adeq precision), also known as the signal-to-noise ratio, reflects the model's ability to resist interference, generally greater than 4 that is reasonable. Table 6 , Table 7 , and Table 8 illustrate the 14-day UCS, mobility, and cost ANOVA.14-d UCS regression model R 2 = 0.9816, R 2 adj = 0.9579, coefficient of variation is 2.08% and precision is 20.7341; while the mobility regression model R 2 = 0.9579, R 2 adj = 0.9481, R 2 pre = 0.9179, with a coefficient of variation of 5.01%, and precision of 35.4007,the cost regression model R 2 = 0.9917, R 2 adj = 0.9811,R 2 pre = 0.9354, with a coefficient of variation of 0.467% and a precision is 36.8671. It can be seen that all the indicators of the model are in line with the requirements, the model fit is very high, and this model can be applied to analyze and predict the changes of 14d compressive strength, mobility, and cost with parameters. The F-test with a 95% confidence level is employed to ascertain the model's significance; if the probability of significance P ≤ 0.05, it implies that the corresponding factor has a noteworthy influence on this response value; if P ≥ 0.1, it implies that the corresponding factor has no noteworthy influence on this response value.As can be seen from Tables 6 , 7 , and 8 , the 14-d UCS, mobility, and cost response surface regression models all reached the level of significance. The F value of the out-of-fit term for 14-d UCS (P = 0.8067 > 0.05) and the F value of the out-of-fit term for mobility (P = 0.0661 > 0.05) demonstrate that the experimental design is satisfactory and the experimental data correspond to the model, as evidenced by Tables 6 and 7 . Table 6 14-d UCS analysis of variance Source of variance Sum of square Df Mean square value F-value P-value Significance Model 1.24 9 0.1372 41.45 < 0.0001 Significant A-A 0.0378 1 0.0378 11.42 0.0118 B-B 0.6613 1 0.6612 199.73 < 0.0001 C-C 0.0006 1 0.0006 0.1850 0.6800 AB 0.0004 1 0.0004 0.1208 0.7384 AC 0.0702 1 0.0702 21.21 0.0025 BC 0.1156 1 0.1156 34.92 0.0006 A² 0.1879 1 0.1879 56.76 0.0001 B² 0.0133 1 0.0133 4.02 0.0849 C² 0.1383 1 0.1383 41.78 0.0003 Residual 0.0232 7 0.0033 Lack of Fit 0.0046 3 0.0015 0.3280 0.8067 Not Significant Pure Error 0.0186 4 0.0046 Cor Total 1.26 16 R²=0.9816 R 2 Pre = 0.9187 Adeq precision = 20.7341 R² Adj =0.9579 CV = 2.08% Table 7 Mobility Variance analysis Source of variance Sum of square Df Mean square value F-value P-value Significance Model 14131.25 3 4710.42 98.5 < 0.0001 Significant A-A 28.13 1 28.13 0.5881 0.45.69 B-B 7200.00 1 7200.00 150.56 < 0.0001 C-C 6903.13 1 6903.13 144.35 < 0.0001 Residual 621.69 13 47.82 Lack of Fit 571.69 9 63.52 5.08 0.0661 Not Significant Pure Error 50.00 4 12.50 Cor Total 14752.94 16 R²=0.9579 R 2 Pre = 0.9179 Adeq precision = 35.4007 R² Adj =0.9481 CV = 5.01% Table 8 Cost Analysis of Variance Source of variance Sum of square Df Mean square value F-value P-value Significance Model 213.61 9 23.73 93.43 < 0.0001 Significant A-A 11.74 1 11.74 46.20 0.0003 B-B 77.00 1 77.00 303.14 < 0.0001 C-C 62.66 1 62.66 246.68 < 0.0001 AB 0.0441 1 0.0441 0.1736 0.6894 AC 5.27 1 5.27 20.73 0.0026 BC 3.69 1 3.69 14.51 0.0066 A 2 29.04 1 29.04 114.32 < 0.0001 B 2 0.6528 1 0.6528 2.57 0.1530 C 2 19.67 1 19.67 77.42 < 0.0001 Residual 1.78 7 0.2540 Lack of Fit 0.7712 3 0.2571 1.02 0.4718 Not Significant Pure Error 1.01 4 0.2517 Cor Total 215.39 16 R²=0.9917 R 2 Pre = 0.9354 Adeq precision = 36.8671 R² Adj =0.9811 CV = 0.4670% 3.4 Analysis of the alternating effects of factors Through comparison and analysis of different factors, we can obtain influence curves that show the significance of each factor's impact on response values clearly and intuitively. The main factor influencing the three response values is the water-gum ratio, followed by the glue-sand ratio and red mud percentage. The degree of influence of the glue-sand ratio and red mud percentage on the unconfined compressive strength is similar. However, the influence of the glue-sand ratio on mobility is much higher than the influence of red mud percentage on it. The response values in the 3D response plots range from small to large, represented by the color blue to red.The contour plots can be obtained by the response surface projection. The largest response value is located at the center of the smallest circle.The circle indicates a weak interaction between the factors, and the oval indicates a strong interaction between the factors.The 3D response plots of the interaction between red mud percentage and water-gum ratio, red mud percentage and gum-sand ratio, and water-gum ratio and gum-sand ratio on 14-d UCS are shown in Fig. 5 (a), (b), and (c), respectively. The largest interaction on 14-d UCS is between the red mud percentage and gum-sand ratio, followed by the interaction between the water-gum ratio and gum-sand ratio with red mud percentage and gum-sand ratio on 14-d UCS. As water consumption decreases and the amount of red mud increases within the selected range, the materials can react more fully with the appropriate amount of water. This reaction produces cementitious materials after mixing and homogenizing, which allows for better consolidation of the river sand and results in higher strength. When a certain amount of cementitious materials is used, excess water should be avoided as it does not participate in the reaction and can lead to an increase in the CLSM specimen urination rate. This can result in a loss of a small amount of OH- and a reduction in strength. The response surfaces of the interaction effects of red mud percentage and water-gum ratio, red mud percentage and glue-sand ratio, and water-gum ratio and gum-sand ratio on mobility are shown in Fig. 6 (a), (b), and (c), respectively, and there is a good interaction among the factors, but the water-gum ratio and glue-sand ratio have a stronger interaction on mobility, and the red mud percentage and water-gum ratio, the red mud percentage and glue-sand ratio have a weaker interaction on mobility. The response surfaces of the interaction of red mud percentage and water-gum ratio, red mud percentage and gum-sand ratio, and water-gum ratio and gum-sand ratio on cost are shown in Fig. 7 (a), (b), and (c), respectively, and the interactions of red mud percentage and water-gum ratio on cost are good, and the interactions of red mud percentage and gum-sand ratio and water-gum ratio and gum-sand ratio on cost are not too weak. The interaction of the water-gum ratio and gum-sand ratio is the more critical factor affecting the cost, and the red mud percentage has the weakest effect on the cost. 3.5 Optimization of CLSM Physical and Mechanical Properties In the response surface optimization of CLSM proportioning, compressive strength belongs to the desired characteristic response value, mobility belongs to the desired large characteristic response value, and cost belongs to the desired small characteristic response value. The optimization interval of compressive strength was set to 2.8-3.2Mpa according to the requirements, and the optimization results of the final CLSM were obtained by using the response surface method and verified by the test, and the ratio-optimized 14-d UCS was 2.85Mpa, the mobility was 145mm, and the cost was 100 yuan/m3, with an error of less than 0.05, which was close to the predicted value of the model as shown in Table 9, which indicates that the response surface method and the established model formula is reliable. Table.9 Response surface optimization results (point prediction) Source red mud percentage water-gum ratio gum-sand ratio 14dUCS /Mpa mobility/mm cost/Yuan Desirability Optimum value 0.5 0.667 0.45 2.8 149.278 101.744 0.752 4 CLSM metal leaching and microanalysis Analyze the amount of heavy metal leaching and the minuscule characteristics of CLSM specimens, and evaluate the concentration and microscopic properties of the products at different conservation ages through the utilization of solid waste leaching toxic leaching techniques, XRD, FTIR, SEM + EDS, and other testing and experimental techniques to measure and evaluate the products at different ages. 4.1 Heavy metal leaching experiment The "Solid Waste Leaching Toxicity Leaching Method - Sulfuric Acid Nitric Acid Method" (HJ/T 299–2007) was utilized to assess the leaching toxicity of CLSM specimens, and it was determined that the leaching concentrations of heavy metal ions, such as Cd, Zn, and Cu, in CLSM specimens kept for 14d of age met the IV standard of groundwater quality classification [ 46 ] , which was significantly lower than the pollution control standard [ 47 ] for domestic waste landfill.The specific metal ion leaching concentrations are shown in Table 10. Table.10 CLSM specimen heavy metal leaching concentration(mg/L) age heavy metals Cu Hg Cd Ni Zn 3d HJ/T 299 0.50 0 0 0.12 0.93 14d 0.48 0 0 0.07 0.29 4.2 X-ray diffraction (XRD) The XRD spectra of CLSM specimens in 3D, 7D, and 14D are depicted in Fig. 8 . It is clear from the illustration that the XRD spectra display numerous wide and distorted characteristic peaks between 20–30°, suggesting that after the ionization of calcium hydroxide in water, the reactive alumino-silicates break down when exposed to OH − to create Si(OH) 4 and Al(OH) 4 − monomers. Subsequently, the polymerization reaction occurs with the slurry's Ca 2+ , Na + and other ions supplied by the exciter, resulting in zeolite-like substances and C-(A)-S-H gels [ 48 ] .In the analysis of the hydration products at all ages, the characteristic peaks of calcium feldspar (CaAl 2 Si 2 O 8 ), sodium feldspar (NaAlSi 3 O 8 ) quartz (SiO 2 ), hematite (Fe 2 O 3 ), and calcite (CaCO 3 ) can be found, and some amorphous materials also appeared, and the characteristic peaks are relatively sharp, indicating a good crystallinity. Analysis of hydration products at different stages of development revealed that, by the time they reached 3d, CLSM had 45.8% calcium feldspar and 22.1% quartz, the primary substances produced and remaining from the reaction, and calcite (CaCO 3 ) was also detected.In addition, calcite (CaCO 3 ) was also found. It was not found in the raw material, indicating that in the early stage of CLSM hydration, the reactive silica and aluminum components in the red mud and waste incineration ash were polymerized under the action of calcium hydroxide, and polymerized products such as calcium feldspar, sodium feldspar and calcite were generated, and it was found to contain hematite (Fe 2 O 3 ), which indicated that in the early stage of hydration, the hematite in RM was not completely dissolved in the alkaline solution. As the age of conservation increases, according to the results of semi-quantitative analysis, the proportion of both minerals, hematite, and quartz, decreases, and, the content of calcite grows. The evidence points to an increase in the amount of C-S-H and C-A-S-H gels in hydration products. This implies that the red mud-waste incineration ash cementation system was altered when calcium hydroxide was activated, and a portion of calcium feldspar and quartz were slowly dissolved in an alkali solution and changed into new substances. The XRD patterns at 7d and 14d still exhibit the presence of hematite and quartz, suggesting their limited involvement in the subsequent hydration reaction and incomplete dissolution in the alkali solution. 4.3 Fourier Transform Infrared Spectroscopy (FTIR) In order to gain a better understanding of the phase composition of CLSM and distinguish between C-S-H and C-A-S-H amorphous gels, samples of CLSM that were optimally prepared in the preceding section were given in 3d, 7d, and 14d sizes, and ATR-FTIR infrared spectra were obtained with a TESCAN MIRA LMS LMS Transform Infrared Spectrometer between 4000 cm − 1 and 400 cm − 1 , and the alterations in the chemical structure of CLSM at different ages were studied using FTIR. The FTIR spectra of CLSM at different ages are shown in Fig. 9 . It can be seen that the broad fronts at 3330 cm − 1 and 1640 cm − 1 are indicative of the characteristic peaks of bound water, with the peak at 3330 cm − 1 being caused by the deformation vibration of O-H, the peak at 1640 cm − 1 being caused by the stretching vibration of O-H, and the peak at 1430 cm − 1 being the result of the absorption peak of C = O stretching vibration created by the presence of carbonate.The sample was attacked by CO 2 during conservation and reacted to form CaCO 3 [ 49 – 50 ] . The presence of a distinct peak near 872 cm − 1 in the meso-[SiO 4 ] tetrahedron of the C-S-H gel, which is a result of the Si-O-Si bond's vibration, suggests that a copolymerization reaction has occurred, confirming that the CLSM reaction product is mainly a C-S-H gel [ 51 ] .The bending vibration of T-O (Si-O or Al-O) [ 52 ] , which is mainly found in the silica-aluminate component of the product, has produced many small absorption peaks between 400 cm − 1 and 600 cm − 1 . 4.4 Scanning electron microscopy, energy spectrum analysis (SEM + EDS) The internal structure of the specimens was studied using XRD and FTIR analyses, and then the microscopic morphology and chemical composition of the hydration products in the composites were determined by combining the results with EDS. The SEM morphology of CLSM specimens hydrated for 3 d, 7 d, and 14 d is depicted in Fig. 10 . As the hydration age increases, the internal pores of the specimens become smaller and crystals fill the pores. These fillers are mainly the alkaline exciters in calcium hydroxide and red mud that react with the reactive SiO 2 and Al 2 O 3 in the waste incineration ash to produce C-S-H and C-A-S-H, which are the main contributors to the CLSM strength of the composites. It is evident from Fig. 10 (a) that 3d has produced a great deal of C-S-H and C-A-S-H gels, and Fig. 10 (d) shows two raised surface particles that have been examined by EDS. The main components are C, O, Al, Si, and Ca, and the mean concentration of O element is 47.26%.From Fig. 10 (b), it can be found that a large number of C-S-H and C-A-S-H gels were generated by the age of 7d with dendritic and needle-like crystals mixed and lapped to form a structure, which made the structure of CLSM samples become denser, and the hydration products were closely connected, and the voids between particles within the polymer were greatly reduced, and only a small amount of pore structure existed. The combination of XRD analysis and the existence of irregular crystals, particularly silicate or silica-aluminate, implies that the active components in the geopolymer and the components in the red mud have a substantial impact on the hydration reaction by activating calcium hydroxide, leading to the creation of multiple C-S-H gels. In Fig. 10 (e), the surface particles were examined and analyzed using EDS, and the elemental Ca concentration was determined to be 14.68%.In Fig. 10 (c) at 14d the hydration product already has a high densification, and the C-S-H and C-A-S-H gels fill most of the inter-particle voids and gradually form a whole, which makes the material have a certain strength. The EDS analysis of the crystals in Fig. 10 (f) reveals that the Ca element content is 21% and the Al element content is 5.76%, suggesting that when calcium hydroxide is activated, the silica-aluminum precursor material dissolves in an alkaline solution, resulting in the formation of silica-aluminum molecules. Additionally, the Al partially replaces Si and enters the C-S-H gel, leading to the formation of the hydrated silica-aluminum acid calcium [ 53 ] , thus generating a C-A-S-H gel. In addition, the iron content at point D was 14.69%, indicating that the red mud dissolved more fully with increasing age of conservation. Analysis of the energy spectrum of Fig. 11 samples of different ages indicates that the CLSM samples contain minimal amounts of Fe and Mg.As the hydration time is prolonged, the majority of hematite is dissolved in an alkaline solution, and the heavy metals are present in a more stable form due to the solidification of the heavy metals inside their lattice through C-S-H ion exchange [ 54 ] . 5 Conclusions (1)Through the one-factor test, it was found that the factors affecting the 14-d UCS of CLSM from large to small are water-gum ratio > gum-sand ratio > red mud percentage, the water-gum ratio is negatively correlated with the 14-d UCS, and the water-gum ratio has a limit, If the water-gum ratio is too large, the sample will precipitate a large amount of moisture to produce a large amount of OH-, resulting in the loss of alkali, and if the water-gum ratio is too small, the material is not easy to mix, and the cementitious materials can not be completely wrapped around the sand particles, thus affecting the strength of the CLSM. (2)The influencing factors on the mobility of CLSM were ranked as water-gum ratio > gum-sand ratio > red mud percentage, the water-gum ratio was positively correlated with the mobility, and the larger the amount of water doped, the better the mobility of CLSM, and the effect of red mud percentage on the mobility was relatively weak. (3)The best mixing ratio of CLSM is 0.5 for red mud, 0.667 for water-gum ratio, and 0.45 for gum-sand ratio. After the test, the optimized 14-d UCS is 2.85Mpa, the mobility is 145mm, and the cost is 100 RMB/m 3 , the error is less than 0.05, which is close to the prediction of the model, and it shows that the model established by the response surface method is reliable. (4)The microscopic analysis results show that with the prolongation of the hydration age, the heavy metals are gradually solidified in the compounds, the leaching concentration is reduced, and the 14d age can reach the groundwater quality classification Ⅳ standard.The alkaline-excited red mud cementation system produces new substances as the hydration age increases.The alkali-excited red mud-slag cementation system produces new substances with the increase of the age of conservation, and the Fe 2 O 3 in red mud hardly participates in the hydration reaction in the middle and late stages and has low solubility in the alkali solution. The SEM and EDS analysis showed that the specimens' strength was mainly due to the presence of clusters of hydrated calcium silicate (C-S-H) and hydrated calcium silica-aluminate (C-A-S-H) in the CLSM, which created a dense structure with the crystals forming the structure and the gel serving as the filler. Declarations Dear Editorial Board of Applied Composites， Please find enclosed the manuscript: Study of the properties of red mud-waste incineration ash composites by Yuxiang Song et al，which will be submitted to Scientific Reports as an original research article. All co-authors have read and agree with the contents of the manuscript and have no financial interests to report. We certify that the submitted manuscript has not been reviewed in any other publication. In this manuscript, we report the results of a study of heavy metal leaching concentrations and properties of red mud and waste incineration ash composites. We believe that the readers of Scientific Reports will be interested in our findings as they may have a significant impact on the design of mix ratios, application and environmental protection of red mud and incinerator ash. Our data in this paper show that the properties of red mud and incinerator ash composites meet the relevant specification requirements and offer new possibilities for road construction materials. In addition, together with the depth of our research, red mud and waste incineration ash have been widely used in the engineering materials industry to contribute to environmental protection. Therefore, this study may have a breakthrough in civil engineering materials and bring new important insights into the field of road engineering materials, and we hope that the editorial board and reviewers will agree on the significance of this study. Sincerely yours, Yuxiang Song and Mingyang Jiang on behalf of the authors. Corresponding author: Mingyang Jiang at Department of Civil Engineering,Liaoning Technical University, No. 88 Yulong Road, Xihe District, Fuxin City, Liaoning Province, China. [email protected] . Author:Yuxiang Song at Department of Civil Engineering,Liaoning Technical University, No. 88 Yulong Road, Xihe District, Fuxin City, Liaoning Province, China. [email protected] . 1、No funds, grants, or other support was received. 2、Author 1 (Yuxiang Song): research proposal design, research proposal feasibility analysis, data analysis, paper writing, paper revision, documentation; Author 2（corresponding author：Mingyang Jiang）: proposal of research ideas and research plan, data organization, paper writing, paper review and editing. The authors have no competing interests to declare that are relevant to the content of this article. Data availability statement All data generated or analysed during this study are included in this published article，or data sets used or analyzed in the current study may be made available upon reasonable request by the corresponding author or author. 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6","display":"","copyAsset":false,"role":"figure","size":325653,"visible":true,"origin":"","legend":"\u003cp\u003eResponse plot of Mobility for (a)\u003cem\u003eAB\u003c/em\u003e;(b)\u003cem\u003eAC\u003c/em\u003e;(c)\u003cem\u003eBC\u003c/em\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/4a3bc641168a445c9d7161ac.png"},{"id":49022159,"identity":"4e90fdad-7572-4812-a937-97deaed0fa44","added_by":"auto","created_at":"2024-01-01 10:02:17","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":397469,"visible":true,"origin":"","legend":"\u003cp\u003eResponse plot of \u003cem\u003eCost\u003c/em\u003efor (a)\u003cem\u003eAB\u003c/em\u003e;(b)\u003cem\u003eAC\u003c/em\u003e;(c)\u003cem\u003eBC\u003c/em\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/f0028d092ee9ee44470aab5f.png"},{"id":49021883,"identity":"cf94524e-06c9-4bba-8d3d-3d522cb9502d","added_by":"auto","created_at":"2024-01-01 09:46:17","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":122194,"visible":true,"origin":"","legend":"\u003cp\u003eXRD analysis of CLSM specimens with optimal mix ratio at different ages\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/aca1605b28fdb929410992f3.png"},{"id":49022158,"identity":"a6e4ce77-bb11-4d56-bfd7-84edea6cb446","added_by":"auto","created_at":"2024-01-01 10:02:17","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":96802,"visible":true,"origin":"","legend":"\u003cp\u003eFTIR of CLSM samples with optimal fit ratio at different ages\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/21e9f0824af566889060da4a.png"},{"id":49021887,"identity":"7bbeb599-c744-4816-a327-fa880e8bece8","added_by":"auto","created_at":"2024-01-01 09:46:17","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":851804,"visible":true,"origin":"","legend":"\u003cp\u003eSEM results of CLSM samples with optimal mix ratios of different ages\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/fd1362af07d7c8532402b40f.png"},{"id":49021880,"identity":"8cd0ddb9-014e-41fc-8ad2-fe24333535e6","added_by":"auto","created_at":"2024-01-01 09:46:17","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":87112,"visible":true,"origin":"","legend":"\u003cp\u003eEDS analysis results: (a) point212, (b) point 55, (c) point 2\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/1ec62efbdffb7b777f15d501.png"},{"id":55272650,"identity":"fe20ffd5-7c60-4f28-ac11-37234b0a895d","added_by":"auto","created_at":"2024-04-25 03:50:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4573299,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3800561/v1/efc7638b-e129-46b1-979a-1571fc00b7fa.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Study of the properties of red mud-waste incineration ash composites","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eRed mud is a kind of strong alkaline industrial waste generated from the refining process of alumina, which is easily discharged directly into the environment and causes water and soil pollution\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Red mud is mainly generated by the Bayer method and sintering method, which contains a variety of metal elements, the presence of a large number of trivalent iron ions, and red color \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. A typical production of 1 tonne of alumina is estimated at between 1.0 and 1.5 tonnes of red sludge.In 2021, our production of alumina was 77.475\u0026nbsp;million tons, an increase of 5% year-on-year, with continued production growth. Red mud has high alkali content but is not active enough\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. CLSM can be prepared by adding lime or gypsum to red mud\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. In recent years, the utilization of industrial solid waste for CLSM preparation has been steadily progressing both domestically and globally. According to the American Concrete Institute's (ACI) definition of CLSM, controlled low-strength material (CLSM) is a self-consolidating cementitious material mainly used as a backfill, instead of compacted fill, and is designed to manufacture self-consolidating cementitious mixtures with compressive strengths of 1200 psi (8.3 MPa) or lower\u003csup\u003e[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e.The properties associated with controlled low-strength materials (CLSM) have been well studied and proven to meet the relevant specification requirements\u003csup\u003e[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Riviera P P et al\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e conducted a study to evaluate the practicality of incorporating controlled low-strength materials (CLSM) into road tunnel pavement foundations.\u003c/p\u003e \u003cp\u003eWaste incineration fly ash is an off-white or dark gray fine powder, with a low water content, generally rod-like, polygonal, cotton-wool, spherical, and other irregular shapes, uneven particle size, high porosity, and large specific surface area. From the surface of the fly ash particles, the internal composition of the mass fraction of elements, Si, Ca, and Al as the main elements, in addition, also contains more K, Na, Cl, Fe, Ti, and other metals, belongs to the Cao-SiO\u003csub\u003e2\u003c/sub\u003e-Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e (Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) system\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Fly ash particle size is not uniform, by the particles, reaction products, unreacted products, and condensation products aggregated irregular objects, basically in the 100 \u0026micro;m or less, the surface is rough in the form of polygonal angularity (irregular angularity); high porosity than the surface area is large, for the heavy metal enrichment attached to provide convenient conditions\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Municipal waste incineration fly ash contains active components that can be utilized to create novel eco-cement mixed materials\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e.Li Chunlin\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e attempted to prepare a geopolymer curing body with excellent performance by using MSW incineration fly ash as raw material and alkali excitation with modulus 1. Qiao et al\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e explored that the addition of an appropriate amount of domestic waste incineration fly ash as a filler into asphalt mixtures can effectively improve the high-temperature stability performance and water stability of asphalt mixtures.Naganathan S et al\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e assessed the characteristics of controlled low-strength materials (CLSM) produced from industrial waste incineration bottom ash and quarry dust, and it was evident that industrial waste incineration bottom ash and quarry dust could enhance the properties of controlled low-strength materials (CLSM).Guangyin, ZHEN et al\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e employed sewage sludge and waste incineration bottom ash instead of sulpho Calcium Aluminate Cement (CA) to produce Controlled Low Strength Materials (CLSM), affirming the potential of using sewage sludge and bottom ash in the production of CLSM. R Taurino et al\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e studied the sintering process and technological properties of a new type of sintered bricks based on large quantities of reprocessed Domestic Waste (WMS) bottom ash and refractory clay. P Aggarwal et al\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e studied the use of different percentages (0\u0026ndash;50%) of bottom ash instead of fine aggregate to prepare concrete with compressive strength comparable to that of normal concrete.WF Tan et al\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e mixed municipal solid waste incineration (MSWI) ash with shale and sludge for washing pretreatment, used it for the production of lightweight aggregate, and processed it into ceramic particles. Y Bai et al\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e explored the application of solid wastes red mud (RM), carbide slag (CS), and MSWIFA in the production of eco-friendly geopolymers. Yuancheng Li et al\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e proposed an innovative method of mechanically activating red mud, in combination with municipal domestic waste incineration fly ash (MSWIFA), to generate red mud-based mass polymer materials (RGM). J Xie et al\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e stimulated a combination of 70% municipal solid waste incineration (MSWI) fly ash and 30% kaolin clay using potassium hydroxide as an activator, during which the maximum geopolymer strength was achieved. Wisitsak Tabyang et al\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e examined the utilization of municipal solid waste incineration fly ash (MSWI FA) geopolymer in pavement applications to stabilize the strength of recycled concrete aggregate (RCA).C Fan et al\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e compared the physicochemical properties, compressive strength, microstructure and morphology of coal fly ash based geopolymers and silicate cement cured MSWI fly ash and showed that fly ash based polymers can be effective in achieving the resource utilization of MSWI.Lei Zheng et al\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e investigated the alkaline activator The effects of dosage and Si/Al molar ratio on the compressive strength and microstructure of MSWI fly ash based mass polymers were investigated.Municipal solid waste incineration residues contain a large number of toxic substances, and if their precipitation can be effectively reduced, the degree of resource utilization of waste incineration ash can be effectively improved \u003csup\u003e[\u003cspan additionalcitationids=\"CR31 CR32 CR33 CR34\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. X Tian et al\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e effectively enhanced the coagulation of MSWI fly ash by using waste glass as an additive, and the immobilization efficiency of Cr increased with the addition of waste glass. BHNLA B et al\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e examined the impact of employing a permeable column test and demonstrated that regular rainfall (15 mm/h) exerted a more significant influence on the leaching of ions (Cl, Na, K, and Ca) and total organic carbon (TOC) from BA (\u0026lt;\u0026thinsp;10 mm particle size) in contrast to intense rainfall (25, 50 and 100 mm/h). Xiao R et al [38] examined how waste glass affects the release of ions (Cl, Na, K, and Ca) from BA (\u0026lt;\u0026thinsp;10 mm particle size) when compared to heavy rainfall (25, 50, and 100 mm/h) using an electron microscope (SEM), X-ray diffraction (XRD), and thermodynamic simulations. The microstructure and phase combination of CLSMs were created using GP-CH binders through electron microscopy (SEM), X-ray diffraction (XRD), and thermodynamic simulation.\u003c/p\u003e \u003cp\u003eA comprehensive analysis of CLSM from multiple angles has been undertaken, examining the influence of various materials and dosage adjustments on the engineering features of CLSM, as well as the effect of single factor changes on the performance of CLSM. A concise description of the direction of comprehensive utilization of red mud and waste incineration products is provided, offering a novel approach to combining red mud and waste incineration fly ash in the fabrication of roadbed materials.\u003c/p\u003e \u003cp\u003eIn this paper, a new CLSM composite material was developed with alkali-excited red mud-refuse incineration ash-river sand, and the ratios of red mud and refuse incineration ash-based materials were optimized using the response surface method. The leaching method of toxicity of solid waste leaching was implemented with sulphuric acid-nitric acid solution as the leaching agent\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e to evaluate the heavy metal leaching of CLSM, and the microforms and chemical compositions of hydration products were evaluated through a combination of X-ray diffraction (XRD), scanning electron microscopy-energy spectroscopy (SEM-EDS), and Fourier transforms infrared spectroscopy (FTIR), and the microstructure formation of CLSM was evaluated.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Raw materials\u003c/h2\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 River sand\u003c/h2\u003e \u003cp\u003eRiver sand (RS) as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(b) was obtained from Fuxin City, Liaoning Province, from the sand quarry of Fula with less than 1% mud content, and the particle size curve obtained by particle size sieving of the river sand is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(a), in which 50% of the particles have sizes of 0.425 mm or less and 90% of the particles have sizes of 1.099 mm or less, and the fineness modulus of the river sand was calculated to be 0.99 by sieving.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Red mud\u003c/h2\u003e \u003cp\u003eRed mud (RM) Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(b) from the waste produced by Shandong Aluminum Company for the production of alumina, is an earthy red solid with a density of 2815 kg/m\u003csup\u003e3\u003c/sup\u003e, which is dried and ground and then sieved for use, with a particle size distribution curve as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e(a), and its chemical composition as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComposition of the main elements of red mud(%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCaO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eK\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMnO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e78.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 Waste Incineration Ash\u003c/h2\u003e \u003cp\u003eWaste incineration ash (MSWI) Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(b) is the waste product generated from the incineration of municipal domestic waste by Fuxin Zhangwu County Alpha Huaneng Bioenergy Co. Ltd. with a density of 1965 kg/m\u003csup\u003e3\u003c/sup\u003e, and the particle size distribution curve is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e(a), and its chemical composition is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMain elemental composition of waste incineration ash(%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMgO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNa\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eK\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eZnO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eBaO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMnO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eCuO\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.1.4 Calcium hydroxide\u003c/h2\u003e \u003cp\u003eCalcium hydroxide (Ca(OH)\u003csub\u003e2\u003c/sub\u003e) Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(b) is produced by Tianjin Dengfeng Chemical Reagent Factory, the density is 2243kg/m\u003csup\u003e3\u003c/sup\u003e, the particle size distribution curve is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a), and its chemical composition is shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCalcium hydroxide major element composition(%)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecalcium hydroxide\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHydrochloric acid insoluble substance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003echloride\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esulfuric acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eiron\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eheavy metal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMagnesium salts and alkali metals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003edeposit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e95.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Test methods\u003c/h2\u003e \u003cp\u003eThe Box-Behnken response surface method was used to optimize the design of the CLSM's mix ratio, with the percentage of red mud, water-gum ratio,and glue-sand ratio as variables, and 14-d UCS, mobility, and cost as response values.\u003c/p\u003e \u003cp\u003eIn accordance with the ASTM C192 / C192M-19\u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e specification, cylindrical specimens measuring 50 mm\u0026times;100 mm were meticulously prepared using the conventional curing technique at a temperature of 20\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and a humidity exceeding 95%.\u003c/p\u003e \u003cp\u003eThe ASTM-C39/C39M-21\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e unconfined compressive strength test technique ensures the CLSM specimen's top surface is even and even, utilizes the WDW-100E universal testing machine to carry out the UCS test, performs parallel experiments, and takes 3 tests in each group to guarantee that the coefficient of variation is less than 15%, and determines the arithmetic mean value.\u003c/p\u003e \u003cp\u003eConcrete mobility test method concerning ASTM-D6103\u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e, using Ф75mm\u0026times;150mm open cylinder mold full of CLSM, quickly (2-4s) lift the mold so that the CLSM free expansion, after stopping in the orthogonal direction to measure the diameter of the expansion to the average value of the diameter of the CLSM as the degree of flow\u003csup\u003e[\u003cspan additionalcitationids=\"CR44\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo determine the cost, begin by gauging the apparent density of CLSM, which has a unit mass of (kg/m\u003csup\u003e3\u003c/sup\u003e), then refer to the raw material-related website to check the material price, and finally, after conducting an inquiry, determine the total cost of each cubic meter of material in CLSM.\u003c/p\u003e \u003cp\u003eMicro-experiment: select the specimens that meet the criteria of XRD, FTIR, SEM-EDS test, and heavy metal leaching test, immerse them in anhydrous ethanol to halt the hydration reaction, remove the specimens and place them in the drying oven at 70\u0026deg;C for 3 hours, and select the appropriate surface or specimens according to the test specifications.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results and Discussion","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 One-factor experiments\u003c/h2\u003e\n \u003cp\u003eThis study evaluates the effect of three elements on compressive strength and slump by employing a one-way test, with varying red mud percentage (A), water-gum ratio (B), and glue-sand ratio (C) as the evaluation criteria, so as to determine a suitable value range for the test parameters.\u003c/p\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.1 Effect of percentage of red mud on compressive strength and mobility\u003c/h2\u003e\n \u003cp\u003eThe preparation of CLSM specimens involved the utilization of a water-gum ratio of 0.68, a glue-sand ratio of 0.4, and a red mud percentage of 0.5, 0.55, 0.6, 0.65, and 0.7, respectively, followed by the examination of the corresponding data.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.2 Effect of water-gum ratio on compressive strength and mobility\u003c/h2\u003e\n \u003cp\u003eThe CLSM specimens were prepared using a red mud percentage of 0.6, a glue-sand ratio of 0.4, and water-gum ratio of 0.66,0.67,0.68,0.69,0.7, respectively, and the corresponding data were examined.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.3 Effect of glue-sand ratio on compressive strength and mobility\u003c/h2\u003e\n \u003cp\u003eThe CLAM samples were made with a red mud percentage of 0.6, a water-gum ratio of 0.68, and a glue-sand ratio of 0.35,0.375,0.4,0.425,0.45, respectively, and the relevant information was verified.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003e3.1.4 One-way trial analysis\u003c/h2\u003e\n \u003cp\u003eBased on one-way test data, it can be concluded that the main factor affecting the UCS of CLSM after 14 days is the water-gum ratio. However, it is important to note that the water-gum ratio has a limited value and that the amount of water should not be too low as it may result in a lack of mobility and make it difficult to mix. The mobility of composites is mainly affected by the water-gum ratio and the glue-sand ratio, while the effect of red mud percentage on mobility is weak.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Regression modeling\u003c/h2\u003e\n \u003cp\u003eThe response values for the one-way test in 3.1 were determined to be 14d unconfined compressive strength (Y1), mobility (Y2), and cost (Y3), with the percentage of red mud (A), the water-gum ratio (B) and the glue-sand ratio (C) being used as the factors for examination,17 groups of tests were generated by using Box-Behnken in the response surface methodology, and the levels of the design factors are displayed in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. The experimental program and results are displayed in Table \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e, which were used to generate a regression equation.The obtained data were entered into the software and the regression equation was obtained after quadratic regression analysis.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Y}_{1}=21.1675+10.6625A-140.625B+157.525C+5AB+26.5AC-170BC-21.125{A}^{2}+140.625{B}^{2}-72.5{C}^{2} （1）\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Y}_{2}=-1105.80882-18.75A+1500B+587.5C\\)\u003c/span\u003e\u003c/span\u003e (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({Y}_{3}=-119.4425+199.7625A+768.125B-154.875C+52.5AB+229.5AC+960BC-262.625{A}^{2}-984.375{B}^{2}-864.5{C}^{2}\\)\u003c/span\u003e\u003c/span\u003e (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBox-Behnken design factor levels\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"char\" class=\"colspec\"\u003e\u003cstrong\u003eTable 5 Box-Behnken experimental groups and results\u003c/strong\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e14d Ucs\u003c/em\u003e/Mpa\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSlump\u003c/em\u003e/mm\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCost\u003c/em\u003e/Yuan\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e108.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e104.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e114.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e106.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e107.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e111.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e110.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Regression model analysis\u003c/h2\u003e\n \u003cp\u003eThe model relevance is determined by the coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e), with a larger value indicating a better fit; the correction coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e) and prediction coefficient of determination (R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003epre\u003c/sub\u003e) have a higher value, and the difference between the two is less than 0.2, indicating a better interpretation of the model; the coefficient of variation (CV) is an index that reflects the degree of variation, with a coefficient of variation of less than 10% indicating the test\u0026apos;s reliability; precision (adeq precision), also known as the signal-to-noise ratio, reflects the model\u0026apos;s ability to resist interference, generally greater than 4 that is reasonable. Table \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, Table \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, and Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e illustrate the 14-day UCS, mobility, and cost ANOVA.14-d UCS regression model R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9816, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9579, coefficient of variation is 2.08% and precision is 20.7341; while the mobility regression model R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9579, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9481, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003epre\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9179, with a coefficient of variation of 5.01%, and precision of 35.4007,the cost regression model R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.9917, R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eadj\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9811,R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003epre\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9354, with a coefficient of variation of 0.467% and a precision is 36.8671. It can be seen that all the indicators of the model are in line with the requirements, the model fit is very high, and this model can be applied to analyze and predict the changes of 14d compressive strength, mobility, and cost with parameters.\u003c/p\u003e\n \u003cp\u003eThe F-test with a 95% confidence level is employed to ascertain the model\u0026apos;s significance; if the probability of significance P\u0026thinsp;\u0026le;\u0026thinsp;0.05, it implies that the corresponding factor has a noteworthy influence on this response value; if P\u0026thinsp;\u0026ge;\u0026thinsp;0.1, it implies that the corresponding factor has no noteworthy influence on this response value.As can be seen from Tables \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e, \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e, and \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e, the 14-d UCS, mobility, and cost response surface regression models all reached the level of significance. The F value of the out-of-fit term for 14-d UCS (P\u0026thinsp;=\u0026thinsp;0.8067\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and the F value of the out-of-fit term for mobility (P\u0026thinsp;=\u0026thinsp;0.0661\u0026thinsp;\u0026gt;\u0026thinsp;0.05) demonstrate that the experimental design is satisfactory and the experimental data correspond to the model, as evidenced by Tables \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003e14-d UCS\u003c/em\u003e analysis of variance\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource of variance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSum of square\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean square value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSignificance\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA-A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB-B\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e199.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC-C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1850\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA\u0026sup2;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB\u0026sup2;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0849\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC\u0026sup2;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0232\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of Fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3280\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot Significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePure Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCor Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u0026sup2;=0.9816\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePre\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" rowspan=\"2\"\u003e\n \u003cp\u003eAdeq precision\u0026thinsp;=\u0026thinsp;20.7341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u0026sup2;\u003csub\u003eAdj\u003c/sub\u003e=0.9579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u0026thinsp;=\u0026thinsp;2.08%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eMobility\u003c/em\u003e Variance analysis\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource of variance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSum of square\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean square value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSignificance\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14131.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4710.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA-A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB-B\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7200.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7200.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e150.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC-C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6903.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6903.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e144.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e621.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of Fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e571.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0661\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot Significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePure Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCor Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14752.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u0026sup2;=0.9579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePre\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" rowspan=\"2\"\u003e\n \u003cp\u003eAdeq precision\u0026thinsp;=\u0026thinsp;35.4007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u0026sup2;\u003csub\u003eAdj\u003c/sub\u003e=0.9481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u0026thinsp;=\u0026thinsp;5.01%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eCost\u003c/em\u003e Analysis of Variance\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource of variance\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSum of square\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean square value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eF-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSignificance\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e213.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSignificant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA-A\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB-B\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e303.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC-C\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e246.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1736\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBC\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eA\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e114.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eC\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eResidual\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLack of Fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot Significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePure Error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCor Total\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e215.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u0026sup2;=0.9917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ePre\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.9354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" rowspan=\"2\"\u003e\n \u003cp\u003eAdeq precision\u0026thinsp;=\u0026thinsp;36.8671\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u0026sup2;\u003csub\u003eAdj\u003c/sub\u003e=0.9811\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCV\u0026thinsp;=\u0026thinsp;0.4670%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 Analysis of the alternating effects of factors\u003c/h2\u003e\n \u003cp\u003eThrough comparison and analysis of different factors, we can obtain influence curves that show the significance of each factor\u0026apos;s impact on response values clearly and intuitively. The main factor influencing the three response values is the water-gum ratio, followed by the glue-sand ratio and red mud percentage. The degree of influence of the glue-sand ratio and red mud percentage on the unconfined compressive strength is similar. However, the influence of the glue-sand ratio on mobility is much higher than the influence of red mud percentage on it.\u003c/p\u003e\n \u003cp\u003eThe response values in the 3D response plots range from small to large, represented by the color blue to red.The contour plots can be obtained by the response surface projection. The largest response value is located at the center of the smallest circle.The circle indicates a weak interaction between the factors, and the oval indicates a strong interaction between the factors.The 3D response plots of the interaction between red mud percentage and water-gum ratio, red mud percentage and gum-sand ratio, and water-gum ratio and gum-sand ratio on 14-d UCS are shown in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e(a), (b), and (c), respectively. The largest interaction on 14-d UCS is between the red mud percentage and gum-sand ratio, followed by the interaction between the water-gum ratio and gum-sand ratio with red mud percentage and gum-sand ratio on 14-d UCS. As water consumption decreases and the amount of red mud increases within the selected range, the materials can react more fully with the appropriate amount of water. This reaction produces cementitious materials after mixing and homogenizing, which allows for better consolidation of the river sand and results in higher strength. When a certain amount of cementitious materials is used, excess water should be avoided as it does not participate in the reaction and can lead to an increase in the CLSM specimen urination rate. This can result in a loss of a small amount of OH- and a reduction in strength.\u003c/p\u003e\n \u003cp\u003eThe response surfaces of the interaction effects of red mud percentage and water-gum ratio, red mud percentage and glue-sand ratio, and water-gum ratio and gum-sand ratio on mobility are shown in Fig.\u0026nbsp;6 (a), (b), and (c), respectively, and there is a good interaction among the factors, but the water-gum ratio and glue-sand ratio have a stronger interaction on mobility, and the red mud percentage and water-gum ratio, the red mud percentage and glue-sand ratio have a weaker interaction on mobility.\u003c/p\u003e\n \u003cp\u003eThe response surfaces of the interaction of red mud percentage and water-gum ratio, red mud percentage and gum-sand ratio, and water-gum ratio and gum-sand ratio on cost are shown in Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e(a), (b), and (c), respectively, and the interactions of red mud percentage and water-gum ratio on cost are good, and the interactions of red mud percentage and gum-sand ratio and water-gum ratio and gum-sand ratio on cost are not too weak. The interaction of the water-gum ratio and gum-sand ratio is the more critical factor affecting the cost, and the red mud percentage has the weakest effect on the cost.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Optimization of CLSM Physical and Mechanical Properties\u003c/h2\u003e\n \u003cp\u003eIn the response surface optimization of CLSM proportioning, compressive strength belongs to the desired characteristic response value, mobility belongs to the desired large characteristic response value, and cost belongs to the desired small characteristic response value. The optimization interval of compressive strength was set to 2.8-3.2Mpa according to the requirements, and the optimization results of the final CLSM were obtained by using the response surface method and verified by the test, and the ratio-optimized 14-d UCS was 2.85Mpa, the mobility was 145mm, and the cost was 100 yuan/m3, with an error of less than 0.05, which was close to the predicted value of the model as shown in Table\u0026nbsp;9, which indicates that the response surface method and the established model formula is reliable.\u003c/p\u003e\n \u003cp\u003eTable.9 Response surface optimization results (point prediction)\u003c/p\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSource\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ered mud percentage\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ewater-gum ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003egum-sand ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003e14dUCS\u003c/em\u003e/Mpa\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emobility/mm\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ecost/Yuan\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDesirability\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOptimum value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e149.278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.752\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 CLSM metal leaching and microanalysis","content":"\u003cp\u003eAnalyze the amount of heavy metal leaching and the minuscule characteristics of CLSM specimens, and evaluate the concentration and microscopic properties of the products at different conservation ages through the utilization of solid waste leaching toxic leaching techniques, XRD, FTIR, SEM\u0026thinsp;+\u0026thinsp;EDS, and other testing and experimental techniques to measure and evaluate the products at different ages.\u003c/p\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Heavy metal leaching experiment\u003c/h2\u003e \u003cp\u003eThe \"Solid Waste Leaching Toxicity Leaching Method - Sulfuric Acid Nitric Acid Method\" (HJ/T 299\u0026ndash;2007) was utilized to assess the leaching toxicity of CLSM specimens, and it was determined that the leaching concentrations of heavy metal ions, such as Cd, Zn, and Cu, in CLSM specimens kept for 14d of age met the IV standard of groundwater quality classification \u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e, which was significantly lower than the pollution control standard \u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e for domestic waste landfill.The specific metal ion leaching concentrations are shown in Table\u0026nbsp;10.\u003c/p\u003e \u003cp\u003eTable.10 CLSM specimen heavy metal leaching concentration(mg/L)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eheavy metals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCu\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNi\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eZn\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHJ/T 299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14d\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.2 X-ray diffraction (XRD)\u003c/h2\u003e \u003cp\u003eThe XRD spectra of CLSM specimens in 3D, 7D, and 14D are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003e. It is clear from the illustration that the XRD spectra display numerous wide and distorted characteristic peaks between 20\u0026ndash;30\u0026deg;, suggesting that after the ionization of calcium hydroxide in water, the reactive alumino-silicates break down when exposed to OH\u003csup\u003e\u0026minus;\u003c/sup\u003e to create Si(OH)\u003csub\u003e4\u003c/sub\u003e and Al(OH)\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003emonomers. Subsequently, the polymerization reaction occurs with the slurry's Ca\u003csup\u003e2+\u003c/sup\u003e, Na\u003csup\u003e+\u003c/sup\u003e and other ions supplied by the exciter, resulting in zeolite-like substances and C-(A)-S-H gels \u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e.In the analysis of the hydration products at all ages, the characteristic peaks of calcium feldspar (CaAl\u003csub\u003e2\u003c/sub\u003eSi\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e8\u003c/sub\u003e), sodium feldspar (NaAlSi\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e8\u003c/sub\u003e) quartz (SiO\u003csub\u003e2\u003c/sub\u003e), hematite (Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e), and calcite (CaCO\u003csub\u003e3\u003c/sub\u003e) can be found, and some amorphous materials also appeared, and the characteristic peaks are relatively sharp, indicating a good crystallinity.\u003c/p\u003e \u003cp\u003eAnalysis of hydration products at different stages of development revealed that, by the time they reached 3d, CLSM had 45.8% calcium feldspar and 22.1% quartz, the primary substances produced and remaining from the reaction, and calcite (CaCO\u003csub\u003e3\u003c/sub\u003e) was also detected.In addition, calcite (CaCO\u003csub\u003e3\u003c/sub\u003e) was also found. It was not found in the raw material, indicating that in the early stage of CLSM hydration, the reactive silica and aluminum components in the red mud and waste incineration ash were polymerized under the action of calcium hydroxide, and polymerized products such as calcium feldspar, sodium feldspar and calcite were generated, and it was found to contain hematite (Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e), which indicated that in the early stage of hydration, the hematite in RM was not completely dissolved in the alkaline solution.\u003c/p\u003e \u003cp\u003eAs the age of conservation increases, according to the results of semi-quantitative analysis, the proportion of both minerals, hematite, and quartz, decreases, and, the content of calcite grows. The evidence points to an increase in the amount of C-S-H and C-A-S-H gels in hydration products. This implies that the red mud-waste incineration ash cementation system was altered when calcium hydroxide was activated, and a portion of calcium feldspar and quartz were slowly dissolved in an alkali solution and changed into new substances. The XRD patterns at 7d and 14d still exhibit the presence of hematite and quartz, suggesting their limited involvement in the subsequent hydration reaction and incomplete dissolution in the alkali solution.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Fourier Transform Infrared Spectroscopy (FTIR)\u003c/h2\u003e \u003cp\u003eIn order to gain a better understanding of the phase composition of CLSM and distinguish between C-S-H and C-A-S-H amorphous gels, samples of CLSM that were optimally prepared in the preceding section were given in 3d, 7d, and 14d sizes, and ATR-FTIR infrared spectra were obtained with a TESCAN MIRA LMS LMS Transform Infrared Spectrometer between 4000 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 400 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, and the alterations in the chemical structure of CLSM at different ages were studied using FTIR.\u003c/p\u003e \u003cp\u003eThe FTIR spectra of CLSM at different ages are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e. It can be seen that the broad fronts at 3330 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 1640 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e are indicative of the characteristic peaks of bound water, with the peak at 3330 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e being caused by the deformation vibration of O-H, the peak at 1640 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e being caused by the stretching vibration of O-H, and the peak at 1430 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e being the result of the absorption peak of C\u0026thinsp;=\u0026thinsp;O stretching vibration created by the presence of carbonate.The sample was attacked by CO\u003csub\u003e2\u003c/sub\u003e during conservation and reacted to form CaCO\u003csub\u003e3\u003c/sub\u003e \u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e. The presence of a distinct peak near 872 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in the meso-[SiO\u003csub\u003e4\u003c/sub\u003e] tetrahedron of the C-S-H gel, which is a result of the Si-O-Si bond's vibration, suggests that a copolymerization reaction has occurred, confirming that the CLSM reaction product is mainly a C-S-H gel \u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e.The bending vibration of T-O (Si-O or Al-O)\u003csup\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e, which is mainly found in the silica-aluminate component of the product, has produced many small absorption peaks between 400 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 600 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Scanning electron microscopy, energy spectrum analysis (SEM\u0026thinsp;+\u0026thinsp;EDS)\u003c/h2\u003e \u003cp\u003eThe internal structure of the specimens was studied using XRD and FTIR analyses, and then the microscopic morphology and chemical composition of the hydration products in the composites were determined by combining the results with EDS.\u003c/p\u003e \u003cp\u003eThe SEM morphology of CLSM specimens hydrated for 3 d, 7 d, and 14 d is depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e. As the hydration age increases, the internal pores of the specimens become smaller and crystals fill the pores. These fillers are mainly the alkaline exciters in calcium hydroxide and red mud that react with the reactive SiO\u003csub\u003e2\u003c/sub\u003e and Al\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e in the waste incineration ash to produce C-S-H and C-A-S-H, which are the main contributors to the CLSM strength of the composites.\u003c/p\u003e \u003cp\u003eIt is evident from Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e (a) that 3d has produced a great deal of C-S-H and C-A-S-H gels, and Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e (d) shows two raised surface particles that have been examined by EDS. The main components are C, O, Al, Si, and Ca, and the mean concentration of O element is 47.26%.From Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e (b), it can be found that a large number of C-S-H and C-A-S-H gels were generated by the age of 7d with dendritic and needle-like crystals mixed and lapped to form a structure, which made the structure of CLSM samples become denser, and the hydration products were closely connected, and the voids between particles within the polymer were greatly reduced, and only a small amount of pore structure existed. The combination of XRD analysis and the existence of irregular crystals, particularly silicate or silica-aluminate, implies that the active components in the geopolymer and the components in the red mud have a substantial impact on the hydration reaction by activating calcium hydroxide, leading to the creation of multiple C-S-H gels. In Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e (e), the surface particles were examined and analyzed using EDS, and the elemental Ca concentration was determined to be 14.68%.In Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e (c) at 14d the hydration product already has a high densification, and the C-S-H and C-A-S-H gels fill most of the inter-particle voids and gradually form a whole, which makes the material have a certain strength. The EDS analysis of the crystals in Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e10\u003c/span\u003e (f) reveals that the Ca element content is 21% and the Al element content is 5.76%, suggesting that when calcium hydroxide is activated, the silica-aluminum precursor material dissolves in an alkaline solution, resulting in the formation of silica-aluminum molecules. Additionally, the Al partially replaces Si and enters the C-S-H gel, leading to the formation of the hydrated silica-aluminum acid calcium\u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e, thus generating a C-A-S-H gel. In addition, the iron content at point D was 14.69%, indicating that the red mud dissolved more fully with increasing age of conservation.\u003c/p\u003e \u003cp\u003eAnalysis of the energy spectrum of Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e11\u003c/span\u003e samples of different ages indicates that the CLSM samples contain minimal amounts of Fe and Mg.As the hydration time is prolonged, the majority of hematite is dissolved in an alkaline solution, and the heavy metals are present in a more stable form due to the solidification of the heavy metals inside their lattice through C-S-H ion exchange \u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003e(1)Through the one-factor test, it was found that the factors affecting the 14-d UCS of CLSM from large to small are water-gum ratio\u0026thinsp;\u0026gt;\u0026thinsp;gum-sand ratio\u0026thinsp;\u0026gt;\u0026thinsp;red mud percentage, the water-gum ratio is negatively correlated with the 14-d UCS, and the water-gum ratio has a limit, If the water-gum ratio is too large, the sample will precipitate a large amount of moisture to produce a large amount of OH-, resulting in the loss of alkali, and if the water-gum ratio is too small, the material is not easy to mix, and the cementitious materials can not be completely wrapped around the sand particles, thus affecting the strength of the CLSM.\u003c/p\u003e\n\u003cp\u003e(2)The influencing factors on the mobility of CLSM were ranked as water-gum ratio\u0026thinsp;\u0026gt;\u0026thinsp;gum-sand ratio\u0026thinsp;\u0026gt;\u0026thinsp;red mud percentage, the water-gum ratio was positively correlated with the mobility, and the larger the amount of water doped, the better the mobility of CLSM, and the effect of red mud percentage on the mobility was relatively weak.\u003c/p\u003e\n\u003cp\u003e(3)The best mixing ratio of CLSM is 0.5 for red mud, 0.667 for water-gum ratio, and 0.45 for gum-sand ratio. After the test, the optimized 14-d UCS is 2.85Mpa, the mobility is 145mm, and the cost is 100 RMB/m\u003csup\u003e3\u003c/sup\u003e, the error is less than 0.05, which is close to the prediction of the model, and it shows that the model established by the response surface method is reliable.\u003c/p\u003e\n\u003cp\u003e(4)The microscopic analysis results show that with the prolongation of the hydration age, the heavy metals are gradually solidified in the compounds, the leaching concentration is reduced, and the 14d age can reach the groundwater quality classification Ⅳ standard.The alkaline-excited red mud cementation system produces new substances as the hydration age increases.The alkali-excited red mud-slag cementation system produces new substances with the increase of the age of conservation, and the Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e in red mud hardly participates in the hydration reaction in the middle and late stages and has low solubility in the alkali solution. The SEM and EDS analysis showed that the specimens' strength was mainly due to the presence of clusters of hydrated calcium silicate (C-S-H) and hydrated calcium silica-aluminate (C-A-S-H) in the CLSM, which created a dense structure with the crystals forming the structure and the gel serving as the filler.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eDear Editorial Board of Applied Composites，\u003c/p\u003e\n\u003cp\u003ePlease find enclosed the manuscript: Study of the properties of red mud-waste incineration ash composites by Yuxiang Song et al，which will be submitted to Scientific Reports as an original research article. All co-authors have read and agree with the contents of the manuscript and have no financial interests to report. We certify that the submitted manuscript has not been reviewed in any other publication.\u003c/p\u003e\n\u003cp\u003eIn this manuscript, we report the results of a study of heavy metal leaching concentrations and properties of \u0026nbsp;red mud and waste incineration ash composites.\u003c/p\u003e\n\u003cp\u003eWe believe that the readers of Scientific Reports will be interested in our findings as they may have a significant impact on the design of mix ratios, application and environmental protection of red mud and incinerator ash. Our data in this paper show that the properties of red mud and incinerator ash composites meet the relevant specification requirements and offer new possibilities for road construction materials. In addition, together with the depth of our research, red mud and waste incineration ash have been widely used in the engineering materials industry to contribute to environmental protection.\u003c/p\u003e\n\u003cp\u003eTherefore, this study may have a breakthrough in civil engineering materials and bring new important insights into the field of road engineering materials, and we hope that the editorial board and reviewers will agree on the significance of this study.\u003c/p\u003e\n\u003cp\u003eSincerely yours,\u003c/p\u003e\n\u003cp\u003eYuxiang Song and Mingyang Jiang on behalf of the authors.\u003c/p\u003e\n\u003cp\u003eCorresponding author: Mingyang Jiang at Department of Civil Engineering,Liaoning Technical University, No. 88 Yulong Road, Xihe District, Fuxin City, Liaoning Province, \u003ca href=\"mailto:[email protected]\"\u003eChina. [email protected]\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eAuthor:Yuxiang Song at Department of Civil Engineering,Liaoning Technical University, No. 88 Yulong Road, Xihe District, Fuxin City, Liaoning Province, \u003ca href=\"mailto:[email protected]\"\u003eChina.\u003c/a\[email protected].\u003c/p\u003e\n\u003cp\u003e1、No funds, grants, or other support was received.\u003c/p\u003e\n\u003cp\u003e2、Author 1 (Yuxiang Song): research proposal design, research proposal feasibility analysis, data analysis, paper writing, paper revision, documentation;\u003c/p\u003e\n\u003cp\u003eAuthor 2（corresponding author：Mingyang Jiang）: proposal of research ideas and research plan, data organization, paper writing, paper review and editing.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eThe authors have no competing interests to declare that are relevant to the content of this article.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article，or data sets used or analyzed in the current study may be made available upon reasonable request by the corresponding author or author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHai Ran, Liu Junxia, Li Jianwei.Current status of research on alumina red mud radioactivity and its shielding mechanism[J].Inorganic Chemicals Industry,2016,48(09):10\u0026ndash;12\u0026thinsp;+\u0026thinsp;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Bin, Zhang Baohua, Ning Ping, He Liwei, Zuo Xiaolin.Status and Prospect of Resource Utilization and Safe Disposal of Red Mud[J].Chemical Industry and Engineering Progress,2018,37(02):714\u0026ndash;723.DOI:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.16085/j.issn.1000-6613.2017-0843\u003c/span\u003e\u003cspan address=\"10.16085/j.issn.1000-6613.2017-0843\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLIUJia-qing, TAN Qian-wen, HEYan-quan, et al.Application of semi-flexible pavements(SFP) with red mud-based cementitious materials[J].Journal of Chang'an University(Natural Science Edition),2022,42(05):21\u0026ndash;32.DOI:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.19721/j.cnki.1671-8879.2022.05.003\u003c/span\u003e\u003cspan address=\"10.19721/j.cnki.1671-8879.2022.05.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDo, Tan Manh, Gyeong-O. 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Materials, 2022, 15(6): 2199.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXUE F, WANG T, ZHOU M, et al.Self-solidification / stabilisation of electrolytic manganese residue: mechanistic insights [J].Construction and Building Materials, 2020, 255: 118971.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"waste incineration ash, CLSM, response surface methodology, reaction mechanism","lastPublishedDoi":"10.21203/rs.3.rs-3800561/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3800561/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAiming at the environmental problems caused by waste incineration ash, a reuse solution was proposed to use waste incineration ash and red mud for the preparation of Controlled Low Strength Material (CLSM), to determine the effect of each parameter on the performance of the material by using a one-way test and to determine the reasonable interval of each parameter, and to design the test by using the Box-Behnken Response Surface Method. Three factors, namely, red mud percentage, water-gum ratio, and glue-sand ratio, were used as test variables, and 14d unconfined compressive strength, mobility, and cost were used as response values to optimize the objectives. The heavy metal toxicity and micro-morphology of CLSM were investigated by using microscopic means such as heavy metal leaching concentration, XRD, and FTIR. The results of the study showed that the optimal mixing ratio of CLSM was 0.5 for red mud percentage, 0.667 for water-gum ratio, and 0.45 for gum-sand ratio, which can effectively utilize the waste incineration ash and reduce environmental pollution. It was found that under alkali activation, the red mud-refuse incineration ash cementation system would change and produce new substances, with crystals as the framework and gel as the filling, forming a dense structure.\u003c/p\u003e","manuscriptTitle":"Study of the properties of red mud-waste incineration ash composites","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-01 09:46:12","doi":"10.21203/rs.3.rs-3800561/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2267b41a-b948-4b59-ac97-f108ae91ef66","owner":[],"postedDate":"January 1st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":27875694,"name":"Earth and environmental sciences/Environmental sciences"},{"id":27875695,"name":"Physical sciences/Engineering"}],"tags":[],"updatedAt":"2024-04-25T03:38:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-01 09:46:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3800561","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3800561","identity":"rs-3800561","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}