Optimality of reinforced concrete coupled shear wall using machine learning

Optimality of reinforced concrete coupled shear wall using machine learning | 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 Research Article Optimality of reinforced concrete coupled shear wall using machine learning Nivedita Kumari, Prahlad Prasad, Seeram Madhuri This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4408410/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Jul, 2024 Read the published version in Asian Journal of Civil Engineering → Version 1 posted 9 You are reading this latest preprint version Abstract A coupled Shear Wall is a unified system consisting of the connection of two individual shear walls with a connecting beam (coupling beam). The coupling beam plays an important role in the lateral load resistance of the coupled shear wall structure. This paper addresses the innovative approach to optimizing coupling beam dimensions by introducing data in machine learning. The data are collected through ETABS modelling of encompassing buildings of varying heights, i.e., 15, 20, 25, 30 stories, with and without shear walls, and coupled shear walls with coupling beams of different lengths, i.e., 1 m, 1.5m, and 2m, and different depths, i.e., 1.5m, 1.25m, 1 m, 0.8m, and 0.75m which is analysed by keeping the end to end distance of both shear wall and shear wall with coupled beam in order to make it economical. The parameters considered include displacement, drift, reinforcement quantity, and concrete volume collected through ETABS. A total of 68 models were analyzed. Analysis made through that, in all of the storey except in 30 storey the shear wall with coupling beam dimension, length of 2 m and depth of 1.25 m is most optimum model and in the case of 30 storey optimized model changes, the coupling beam with a length of 1.5 m and depth of 1.25 m perform best. On increasing storey, it can be deduced that coupled shear wall performs much better. Furthermore, the machine learning-trained model will provide the optimum dimension of the coupling beam if storey height is provided. Coupled Shear Wall Machine Learning Reinforced concrete structures High rise ETABS Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 1 INTRODUCTION 1.1 Overview Coupled shear walls are structural systems utilised in high-rise buildings to improve lateral stiffness and resistance to horizontal stresses such as wind or earthquake. The reinforced concrete (RC) coupled shear wall is widely used in high-rise structures because it resists lateral and vertical loads through axial force, in-plane shear force, and bending moment countered by the coupling action in the connecting beam. It is a system made up of a coupling beam (Spandrel) and shear wall (Piers). Eurocode 8 (2004) defines coupling beams as the transfer of vertical forces between adjacent walls, creating a coupling action that introduces an extra moment that resists a portion of the total overturning moment induced by the seismic action. The Coupling beam connects the two adjacent shear walls and is provided at the floor level at the top of each storey. The coupling effect provides significant lateral stiffness and strength. Foundation restraint is more easily provided than comparable isolated walls because axial loads resist part of the base-overturning moment. Coupling beams provide an ideal energy dissipation mechanism, distributed along the structure's height and away from the base, without significantly affecting the stability of the walls. The length and depth of the coupling beam are the main elements for consideration. By optimizing the length and depth of coupling beams in coupled shear walls, the structure challenges such as enhanced load distribution, improved seismic resilience, efficient material utilization, architectural flexibility, cost-effectiveness, and meeting performance criteria can be rectified. The coupling beams can specify a tolerable level of damage to balance the construction and post-earthquake repair costs. The opening is created due to the coupled shear wall, which provides architectural flexibility and easier accessibility. Coupling beams are conventionally reinforced and diagonally reinforced, according to the demand of the coupling beam, its detailing is done. A diagonally reinforced beam is stronger and stiffer than a conventionally reinforced beam, so it is used at a place of less demand. According to ACI 318 code (2014) Coupling beams with an aspect ratio (Length of coupling beam (L cb )/Depth of coupling beam (H cb )) ≥ 4, then this type of beam will be designed by conventionally reinforced beam. While the aspect ratio (L cb /H cb ) < 4, that will be designed with diagonal reinforcement. The efficiency of reinforced confirmation depends mostly on the angle of inclination of the diagonal reinforcement with respect to the beam. Confining is only provided in the part of the diagonal element, not in the whole coupling beam. For aspect ratio (L cb /H cb ), we can also say that the larger the aspect ratio, the less efficient the coupling beam is. The depth of the coupling beam should be higher for the lower storey and lower for the higher storey to perform better. 1.2 Mechanics of coupled shear wall The moment M w at any level is then resisted by the sum of the bending moments M 1 and M₂ in the two walls at that level and the of the axial forces NL, where N is the axial force in each wall at that level, and L is the distance between their centroidal axes. The total base moment M w , a coupled wall structure, can be represented as M w $${M}_{w}=NL+{M}_{1}+{M}_{2}$$ The degree of coupling (DOC) of coupled shear walls (CSW) is defined by the axial bending moment at the base of the structure, expressed as a fraction of the total overturning moment. $$\text{D}\text{O}\text{C}=\frac{\text{N}\text{L}}{\text{N}\text{L}+{\text{M}}_{1}+{\text{M}}_{2}}$$ The relation between a peak shear force and an average shear force is called peak shear demand. $$PSD=\frac{{V}_{b.max}}{{V}_{b.avg}}$$ The degree of coupling DOC and the peak shear demand PSD are two important parameters in the design of coupled wall structures (Paulay, 1974 ). 2 METHODOLOGY 2.1 Modelling of Structure in ETABS In ETABS, the modelling of buildings was done at various heights, such as 15, 20, 25, and 30 stories, with each storey height of 3m. These models include configurations with and without shear walls and configurations with coupled shear walls featuring coupling beams of different lengths of 1 m, 1.5m, and 2m. The coupling beams of different lengths are also modelled in various depths, with dimensions including 1.5m, 1.25m, 1 m, 0.8m, and 0.75m (Lim, 2016). The end-to-end distance between both shear walls and shear walls with coupling beams is 5 m. These coupled shear walls are made by creating openings in the shear wall. The tables below show the building parameters. Table 1 Building parameters Building parameters Remarks Structure Moment resisting frame (MRFS), MR frame with shear wall, MR frame with coupled shear wall Number of stories 15,20,25,30 Type of building Regular and symmetrical in plan Plan area (X x Y) 25m x 25m Width of the bay in the x-direction 25m (5 bays) Width of the bay in the y-direction 25m (5 bays) Height of building 45m, 60 m, 75m, 90m Floor height 3m Support type Fixed Diaphragm type Rigid Table 2 Members parameter Number of stories Beam size Column size Grade 15 350×500 500×500 M30 20 325×500 550×550 M30 25 450×550 600×600 M30 30 575×500 700×700 M30 Table 3 Material Parameters Material Parameters Remarks Grade of concrete M30 Grade of steel Fe500- longitudinal reinforcement Fe500- confinement reinforcement Unit weight of reinforced concrete 25 kN/m3 Density of steel 7849.047 kg/m 3 Young’s modulus of M30 concrete, E c 27386.13 MPa Young’s modulus of steel, E s 200000 MPa Unit weight of Masonry wall 20 kN/m 3 Table 4 Load type Type of loads Intensities Type of load assigning Dead Load on Floors 1.5 kN/m 2 Shell type load (Distributed) Live load on floors 4 kN/m 2 Shell type load (Uniform) For infill walls – Wall load on floors 8 kN/m 2 Frame type load (Uniform) Table 5 Seismic parameter Seismic parameters Remarks Seismic zones and zone factor Zone Ⅴ(Z = 0.36) Importance factor 1.2 Response reduction factor 3 Soil Type II Damping ratio 5% 2.1.1 Load combination The load combination used here is 1.2DL + 1.2LL + 1.2RS x for Response Spectrum Analysis. 2.1.2 Nomenclature Due to increases in the number of models, every model is assigned a nomenclature here to foster clarity and ensure efficient communication. For different types of structures like reinforced concrete, Moment-resisting frame structure, Moment-resisting frame with shear wall and Moment-resisting frame with coupled shear wall denoted as MR, SW and CS, respectively. After that, we write the number of the building storey, like 15,20,25 and 30 storey. Table 6 Nomenclature of types of structure Types of Structure Nomenclature RC Moment-resisting Frame Structure MR Moment-resisting frame with shear wall SW Moment-resisting frame with coupled shear wall CS Table 7 List of the modelled building with nomenclature and description SL. No. Nomenclature Types of Structure Number of Storey Length of Coupling beam(m) Depth of Coupling beam(m) 1 MR15 MR 15 - - 2 SW15 SW 15 - - 3 CS15L1D1 CS 15 1 1.5 4 CS15L1D2 CS 15 1 1.25 5 CS15L1D3 CS 15 1 1 6 CS15L1D4 CS 15 1 0.8 7 CS15L1D5 CS 15 1 0.75 8 CS15L1.5D1 CS 15 1.5 1.5 9 CS15L1.5D2 CS 15 1.5 1.25 10 CS15L1.5D3 CS 15 1.5 1 11 CS15L1.5D4 CS 15 1.5 0.8 12 CS15L1.5D5 CS 15 1.5 0.75 13 CS15L2D1 CS 15 2 1.5 14 CS15L2D2 CS 15 2 1.25 15 CS15L2D3 CS 15 2 1 16 CS15L2D4 CS 15 2 0.8 17 CS15L2D5 CS 15 2 0.75 18 MR20 MR 20 - - 19 SW20 SW 20 - - 20 CS20L1D1 CS 20 1 1.5 21 CS20L1D2 CS 20 1 1.25 22 CS20L1D3 CS 20 1 1 23 CS20L1D4 CS 20 1 0.8 24 CS20L1D5 CS 20 1 0.75 25 CS20L1.5D1 CS 20 1.5 1.5 26 CS20L1.5D2 CS 20 1.5 1.25 27 CS20L1.5D3 CS 20 1.5 1 28 CS20L1.5D4 CS 20 1.5 0.8 29 CS20L1.5D5 CS 20 1.5 0.75 30 CS20L2D1 CS 20 2 1.5 31 CS20L2D2 CS 20 2 1.25 32 CS20L2D3 CS 20 2 1 33 CS20L2D4 CS 20 2 0.8 34 CS20L2D5 CS 20 2 0.75 35 MR25 MR 25 - - 36 SW25 SW 25 - - 37 CS25L1D1 CS 25 1 1.5 38 CS25L1D2 CS 25 1 1.25 39 CS25L1D3 CS 25 1 1 40 CS25L1D4 CS 25 1 0.8 41 CS25L1D5 CS 25 1 0.75 42 CS25L1.5D1 CS 25 1.5 1.5 43 CS25L1.5D2 CS 25 1.5 1.25 44 CS25L1.5D3 CS 25 1.5 1 45 CS25L1.5D4 CS 25 1.5 0.8 46 CS25L1.5D5 CS 25 1.5 0.75 47 CS25L2D1 CS 25 2 1.5 48 CS25L2D2 CS 25 2 1.25 49 CS25L2D3 CS 25 2 1 50 CS25L2D4 CS 25 2 0.8 51 CS25L2D5 CS 25 2 0.75 52 MR30 MR 30 - - 53 SW30 SW 30 - - 54 CS30L1D1 CS 30 1 1.5 55 CS30L1D2 CS 30 1 1.25 56 CS30L1D3 CS 30 1 1 57 CS30L1D4 CS 30 1 0.8 58 CS30L1D5 CS 30 1 0.75 59 CS30L1.5D1 CS 30 1.5 1.5 60 CS30L1.5D2 CS 30 1.5 1.3 61 CS30L1.5D3 CS 30 1.5 1 62 CS30L1.5D4 CS 30 1.5 0.8 63 CS30L1.5D5 CS 30 1.5 0.75 64 CS30L2D1 CS 30 2 1.5 65 CS30L2D2 CS 30 2 1.25 66 CS30L2D3 CS 30 2 1 67 CS30L2D4 CS 30 2 0.8 68 CS30L2D5 CS 30 2 0.75 2.2 Machine Learning In this study, the random forest model is adopted as the type of machine learning by analyzing the performance of the four machine learning models which are random forest, decision tree, KNN, XG boost. The random forest is a type of supervised learning algorithm. The program utilize several important libraries used in machine learning for prediction of data. The important libraries that are employed here are libraries like Tkinter for GUI (graphical user interface) development, pandas for data manipulation, and scikit-learning for machine learning tasks, particularly utilizing train_test_split and Random Forest Regressor. Initially, data is imported from files which are prepared by the outputs from the ETABS analysis into a panda data frame, where subsequently, the data is preprocessed by selecting specific columns for features (x) and target variables (y). The dataset is split into training and testing sets using train_test_split(). With a Random Forest Regressor, the program trains the regression model on the training data. Define functions like calculate_score() and predict_CBD() are defined for score predictions and predicting the depth of the coupling beam (CBD), respectively. The score is calculated on the basis of adopting suitable weightage for all the input variables in order to make it easier to find an optimum value. The weightage is primarily considered on the basis of the variable importance, and the initial data from the ETABS is modified, and the data taken here is the relative difference in the model of that height with respect to data from the shear wall model of that height. After that, the Thinter window is created for user interaction. User input is taken as building height, and CBL is optionally taken. Predictions of CBD are made based on user input, with or without CBL, and subsequently displayed. Upon completion of tasks, the Tkinter window closes. 3 RESULTS AND DISCUSSION Firstly, we compare the parameters such as Storey displacement, storey drift, reinforcement required and volume of concrete required of 15,20,25, and 30-storey buildings without a shear wall, with a shear wall and a shear wall with a coupling beam of different dimensions. The storey displacement and drift for all buildings are the same in both the X and Y directions. Therefore, only the variation in the X-direction is depicted in the graph. The storey displacement represents the results obtained from the analysis of the building in ETABS. The reinforcement obtained through detailing is carried out in ETABS after the structure analysis. In the detailing of the coupled shear wall, diagonal reinforcement is adopted where required, many researchers ((Barney,1976) to (Naish, 2010 )) have shown in their work that diagonal reinforcement is a lot better in energy dissipation as illustrated in Fig. 3 for a 15-storey coupled shear wall structure with a 1.5 m length and 1.25 m depth of the coupled shear wall and an overall 5 m length of shear wall. The concrete required is the volume of concrete utilized in the shear walls of the structure only. The volume of concrete in the beam, column, and slab was the same for all models, so we only compared the volume of concrete in the shear wall. Just for the sake of visualization a typical model view are shown in Fig. 4 similarly other storey are also modelled in the same way. 3.1 Results 3.1.1 The coupled shear wall has a length of coupling beam of 1 m for 15 storey building. 3.1.2 The coupled shear wall has a length of coupling beam of 1.5 m for 15 storey building. 3.1.3 The coupled shear wall has a length of coupling beam of 2 m for 15 storey building. 3.1.4 The coupled shear wall has a length of coupling beam of 1 m for 20 storey building. 3.1.5 The coupled shear wall has a length of coupling beam of 1.5 m for 20 storey building. 3.1.6 The coupled shear wall has a coupling beam length of 2 m for 20 storey building. 3.1.7 The coupled shear wall has a coupling beam length of 1 m for 25 storey building. 3.1.8 The coupled shear wall has a coupling beam length of 1.5m for 25 storey building. 3.1.9 The coupled shear wall has a coupling beam length of 2m for 25 storey building. 3.1.10 The coupled shear wall has a coupling beam length of 1m for 30 storey building. 3.1.11 The coupled shear wall has a coupling beam length of 1.5m for 30 storey building. 3.1.12 The coupled shear wall has a coupling beam length of 2m for 30 storey building. 3.2 Discussion 3.2.1 Discussion for 15-storey building The results show that the lateral displacement and storey drift of the MR15 model is maximum. When comparing buildings with shear wall, the maximum lateral displacement and storey drift occurs in the least depth coupling beam buildings in all three cases, i.e. CS15L1D5, CS15L1.5D5, and CS15L2D5 models. The lateral displacement and storey drift are minimum for the SW15 model. The storey drift is the same between 12 and 13 storey. The reinforcement required is maximum for model CS15L1D1 in comparison with all 15-storey models. The reinforcement required for the CS15L2D5 model is minimum and almost equal to the SW15 model. The volume of concrete is reduced by 10–15% in coupled shear wall structures in comparison with solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS15L2D5 model is minimum and reduced by 30% compared to the SW15 model. The volume of concrete is maximum for model SW15 compared with all 15-storey models. 3.2.2 Discussion for 20-storey building The results show that the MR20 model exhibits maximum lateral displacement (180.491 mm) and storey drift (0.00461). The lateral displacement and storey drift are minimum for the SW20 model. Notably, models SW20 and CS20L1D2 demonstrate exactly the same lateral displacement and storey drift. Among different coupling beam lengths (1m, 1.5m, and 2m), CS20L1D2, CS20L1.5D1, and CS20L2D2 exhibit the least lateral displacement and storey drift, respectively. When comparing buildings with shear walls, the maximum lateral displacement and storey drift occur in models with the shallowest coupling beams, namely CS20L1D5, CS20L1.5D5, and CS20L2D5. The storey drift remains consistent between 15 and 16 storey. The reinforcement required is maximum for model CS20L1D1 and minimum for model SW20 compared to all 20-storey models. The reinforcement required for the CS20L2D5 model is 1% more than model SW20 model. The volume of concrete is reduced by 10–30% in coupled shear wall structures compared to solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS20L2D5 model is minimum and reduced by 30% compared to the SW20 model. The volume of concrete is maximum for model SW20 compared to all 20-storey models. 3.2.3 Discussion for 25-storey building The results show that the MR25 model exhibits maximum lateral displacement (233.154 mm) and storey drift (0.00467). The lateral displacement is minimum for the SW25 model. Notably, models SW25 and CS25L1D3 demonstrate exactly the same lateral displacement. Among different coupling beam lengths (1m, 1.5m, and 2m), CS25L1D3, CS25L1.5D1, and CS25L2D1 exhibit the least lateral displacement and CS25L1D3, CS25L1.5D5, and CS25L2D1 exhibit the least storey drift respectively. When comparing buildings with shear walls, the maximum lateral displacement and storey drift occur in models with the 0.8m depth of the coupling beam, namely CS25L1D4, CS25L1.5D4, and CS25L2D4. The storey drift of the CS25L1D3 model is minimal compared to all 25-storey buildings and 0.6% less than the SW25 model. The storey drift remains consistent between 22 and 23 storey. The reinforcement required is maximum for model CS25L1D1 and minimum for SW25 compared to all 25-storey models. The reinforcement required for the CS25L1D4 and CS25L2D5 models is 0.13% more than the SW25 model. The volume of concrete is reduced by 10–30% in coupled shear wall structures compared to solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS25L2D5 model is minimal and reduced by 30% compared to the SW25 model. The volume of concrete is maximum for model SW25 compared to all 25-storey models. 3.2.4 Discussion for 30-storey building The results show that the MR30 model exhibits maximum lateral displacement (281.634 mm) and storey drift (0.004594). The lateral displacement is minimum for the SW30 model. Among all shear wall models, CS30L1D1 shows the least lateral displacement, which is 0.16% more than model SW30. Among different coupling beam lengths (1m, 1.5m, and 2m), CS30L1D1, CS30L1.5D1, and CS30L2D1 exhibit the least lateral displacement and least storey drift respectively. When comparing buildings with shear walls, the maximum lateral displacement and storey drift occur in CS30L1D5, CS30L1.5D4, and CS30L2D4 models for different lengths of coupling beam. The storey drift of the CS30L1D1 and CS30L1D2 models is the same and minimum compared to all 30-storey buildings and 0.21% less than the SW30 model. The storey drift remains consistent between 26 and 27 storeys. The reinforcement required is maximum for model CS30L1D1 and minimum for CS30L1.5D2 compared to all 30-storey models. The reinforcement required for the CS30L1D4 and CS30L1.5D2 models is 2.31% and 4.13%, respectively, less than the SW25 model. The volume of concrete is reduced by 10–30% in coupled shear wall structures compared to solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS30L2D5 model is minimal and reduced by 30% compared to the SW30 model. The volume of concrete is maximum for model SW30 compared to all 30-storey models. 3.3 Machine learning results The RF, DT, XGBoost and KNN models were implemented using the Scikit-Learn library using Machine learning toolsnox in Python. The train_test_size parameter determines the proportion of the dataset to include in the 80% of the data used for training ( x_train and y_train ) and 20% for testing ( x_test and y_test ). The scores of train and test of all models that we implemented are shown in the following Table 8 Table 8 Model RF DT XG Boost KNN R 2 Train 0.9624 1.0000 0.9996 0.5285 R 2 Test 0.9259 0.8820 0.8737 0.5888 MSE Train 3.22E-05 0 3.32E-07 0.0004 MSE Test 0.0001 0.0002 0.0002 0.0006 MAE Train 0.0036 0.0000 0.0004 0.0146 MAE Test 0.0081 0.0108 0.0120 0.0204 Figure 18 shows the performance of all models in predicting the score by training and testing. From Fig. 18 (c) & Fig. 18 (d), it is clear that the XG Boost & KNN is not a good model for this set of data on the other hand the random forest and decision tree are pretty good but the predicted value shows more deviation than the random forest (see Fig. 18 (a) & Fig. 18 (b)). Similar trends are analyzed from the R 2 , MSE and MAE for all these four models see Table 8 . Figure 19 shows the correlation matrix derived from the original dataset, 7 input variables and 1 output variable. This matrix illustrates the correlation coefficients between every pair of variables, where a coefficient of 1 signifies the highest positive correlation, -1 represents the highest negative correlation, and 0 indicates no correlation. Through this matrix, the interrelations among various variables show positive and negative correlations among them. Here, the score was majorly influenced by the drift − 0.78 and very little on steel. This is so because drift is the most important parameter of seismic design. However, steel has a lesser impact because the change in its quantity with respect to shear walls is very less. By following the steps shown in Fig. 20, we can predict the length and depth of the coupling beam. Firstly, the user inputs the storey height. If opting for the coupling beam length (CBL), they enter "yes"; otherwise, "no" for both length and depth prediction. If we enter yes, then we have to enter the length of the coupling beam (CBL), then it shows the predicted depth of the coupling beam (CBD). Here, providing basic input like the height of the building being 90 meters and CBL being 1.75 m, the algorithm is able to deduce the optimum CBD as 1 m. The result is validated from the available data set as the calculated score after the modelling of this building is -0.06612 which lies between the available points. 4 CONCLUSION Shear wall configurations generally exhibit lower lateral displacement and storey drift compared to those with coupling beams, especially with deeper coupling beams. Among models with similar configurations, those with shallower coupling beams tend to experience higher displacement and drift. The storey drift remains consistent at 1/5 of the height of the building from the top. For 25-storey buildings, CSW buildings with CB of length (1m) and depth (1m) drift give better results than shear walls. CSW building with CB of length (1m) and depth (1.5m,1.25m) shows minimum storey drift compared to all 30-storey buildings. For 15-storey models, CSW building with CB of length (1m) and depth (1.5m) requires the maximum reinforcement while building with CB of length (2m) and depth (0.75m) requires the minimum, almost equal to solid shear wall building. For 20,25, and 30-storey models, CSW building with CB of length (1m) and depth (1.5m) requires maximum reinforcement, and solid shear wall building requires minimum reinforcement. For 30-storey models, a CSW building with a CB of length (1m) and depth (1.5m) requires the maximum reinforcement, and a building with a CB of length (1.5m) and depth (1.25m) requires 4.13% less reinforcement than solid shear wall structure. The volume of concrete gradually decreases as the depth and length of the coupling beam decrease. The volume of concrete is minimum for buildings with coupled shear walls of length (2 m) and depth (1.5 m) of coupling beam for all cases and reduced by 30% compared to the building with shear wall. The volume of concrete is maximum for buildings with shear walls compared to all cases. As the height of the building increases, coupled shear wall building performs better than shear wall building. The Random Forest model achieved higher R2 (i.e., 0.9624), lower MSE (i.e., 3.22E-05) and MAE (i.e., 0.0036) within the developed four machine learning models, demonstrating the best effectiveness of the random forest algorithm in predicting the best score. Abbreviations CBD Coupling beam depth CBL Coupling beam length CSW Coupled shear wall DL Dead Load DOC Degree of coupling Fe500 Reinforcement steel bar of minimum yield strength equivalent to 500 MPa. GUI Graphical user interface kg kilogram kN kilo-Newton L Length between the centroidal axes LL Live Load m meter M 1 & M 2 Moment in walls 1 & 2 M30 Design mix for compressive strength of 30 MPa. MAE Mean absolute error MPa Megapascal MRFS Moment resisting frame MSE Mean squared error M w Moment at base N Axial force PSD Peak shear demand RC Reinforced concrete RS x Response spectrum load in the x direction V b,avg Average of shear force developed V b,max Maximum shear force developed Declarations Author Contribution Conceptualization, N.K. and P.P.; methodology, N.K.; software, N.K.; validation, N.K.; resources, P.P; data curation, N.K.; writing—original draft preparation, N.K.; writing—review and editing, N.K.; visualization, N.K.; supervision, P.P and S.M. References ACI Committee 318. (2005). Building code requirements for structural concrete (ACI 318-05) and commentary . American Concrete Institute. ACI Committee 318. (2008). 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Naish, D. A. B. (2010). Testing and modeling of reinforced concrete coupling beams . University of. Park, W. S., & Yun, H. D. (2011). Seismic performance of pseudo strain-hardening cementitious composite coupling beams with different reinforcement details. Composites Part B: Engineering , 42 (6), 1427–1445. Paulay, T., & Binney, J. R. (1974). Diagonally reinforced coupling beams of shear walls, shear in reinforced concrete, SP-42 (pp. 579–598). American Concrete Institute. Seo, S., Lee, L., & Hawkins, N. M. (1998). The limiting drift and energy dissipation ratio for shear walls based on structural testing. Journal of the Korea Concrete Institute , 10 (2), 335–343. Shin, H. O., Yoon, Y. S., Cook, W. D., & Mitchell, D. (2016). Enhancing the confinement of ultra-high-strength concrete columns using headed crossties. Engineering Structures , 127 , 86–100. Shin, M., Gwon, S. W., Lee, K., Han, S. W., & Jo, Y. W. (2014). Effectiveness of high performance fiber-reinforced cement composites in slender coupling beams. Construction and Building Materials , 68 , 476–490. Shiu, K. N., Barney, G. B., Fiorato, A. E., & Corely, W. G. (1978). Reversing load tests of reinforced concrete coupling beams. Proceedings of the Central American Conference on Earthquake Engineering, San Salvador. Simona, A. R., Hridoya, F. K., Siddiquea, M. F., & Ahmed, S. (2023). Orientation and location of shear walls in RC buildings to control deflection and drifts. Souhaibou, A., & Li, L. (2023). April 28). A comparative study on the lateral displacement of a multi-story RC building under wind and earthquake load actions using base shear method and ETABS software. Standardization. Tassios, T. P., Moretti, M., & Bezas, A. (1996). On the behavior and ductility of reinforced concrete coupling beams of shear walls. ACI Structural Journal , 93 (6), 711–720. TBI Guidelines Working Group. (2010). Guidelines for performance-based seismic design of tall buildings-version 1.0. Report No. 2010/05 . Pacific Earthquake Engineering Research Center. Tegos, I. A., & Penelis, G. G. (1988). Seismic resistance of short columns and coupling beams reinforced with inclined bars. ACI Structural Journal , 85 (1), 82–88. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 20 Jul, 2024 Read the published version in Asian Journal of Civil Engineering → Version 1 posted Editorial decision: Revision requested 19 May, 2024 Reviews received at journal 19 May, 2024 Reviewers agreed at journal 13 May, 2024 Reviews received at journal 13 May, 2024 Reviewers agreed at journal 13 May, 2024 Reviewers invited by journal 13 May, 2024 Editor assigned by journal 13 May, 2024 Submission checks completed at journal 12 May, 2024 First submitted to journal 12 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4408410","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":304178419,"identity":"62c53985-42d7-470f-86e4-03d55d167eb8","order_by":0,"name":"Nivedita Kumari","email":"data:image/png;base64,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","orcid":"","institution":"National Institute of Technology Jamshedpur","correspondingAuthor":true,"prefix":"","firstName":"Nivedita","middleName":"","lastName":"Kumari","suffix":""},{"id":304178420,"identity":"e8455376-61e9-4519-84e6-0a752fdbb94f","order_by":1,"name":"Prahlad Prasad","email":"","orcid":"","institution":"National Institute of Technology 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19","display":"","copyAsset":false,"role":"figure","size":218836,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"F19.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4408410/v1/0dacb23cc98152b1a5ce7e46.jpg"},{"id":60730672,"identity":"188424f7-c611-4162-99bb-6e68ea317d90","added_by":"auto","created_at":"2024-07-20 08:14:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":9086891,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4408410/v1/0e0bd858-e2b5-42e5-b0e3-7a1a9d2100cc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimality of reinforced concrete coupled shear wall using machine learning","fulltext":[{"header":"1 INTRODUCTION","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Overview\u003c/h2\u003e \u003cp\u003eCoupled shear walls are structural systems utilised in high-rise buildings to improve lateral stiffness and resistance to horizontal stresses such as wind or earthquake. The reinforced concrete (RC) coupled shear wall is widely used in high-rise structures because it resists lateral and vertical loads through axial force, in-plane shear force, and bending moment countered by the coupling action in the connecting beam. It is a system made up of a coupling beam (Spandrel) and shear wall (Piers). Eurocode 8 (2004) defines coupling beams as the transfer of vertical forces between adjacent walls, creating a coupling action that introduces an extra moment that resists a portion of the total overturning moment induced by the seismic action. The Coupling beam connects the two adjacent shear walls and is provided at the floor level at the top of each storey. The coupling effect provides significant lateral stiffness and strength. Foundation restraint is more easily provided than comparable isolated walls because axial loads resist part of the base-overturning moment. Coupling beams provide an ideal energy dissipation mechanism, distributed along the structure's height and away from the base, without significantly affecting the stability of the walls. The length and depth of the coupling beam are the main elements for consideration. By optimizing the length and depth of coupling beams in coupled shear walls, the structure challenges such as enhanced load distribution, improved seismic resilience, efficient material utilization, architectural flexibility, cost-effectiveness, and meeting performance criteria can be rectified. The coupling beams can specify a tolerable level of damage to balance the construction and post-earthquake repair costs. The opening is created due to the coupled shear wall, which provides architectural flexibility and easier accessibility. Coupling beams are conventionally reinforced and diagonally reinforced, according to the demand of the coupling beam, its detailing is done. A diagonally reinforced beam is stronger and stiffer than a conventionally reinforced beam, so it is used at a place of less demand. According to ACI 318 code (2014) Coupling beams with an aspect ratio (Length of coupling beam (L\u003csub\u003ecb\u003c/sub\u003e)/Depth of coupling beam (H\u003csub\u003ecb\u003c/sub\u003e))\u0026thinsp;\u0026ge;\u0026thinsp;4, then this type of beam will be designed by conventionally reinforced beam. While the aspect ratio (L\u003csub\u003ecb\u003c/sub\u003e/H\u003csub\u003ecb\u003c/sub\u003e)\u0026thinsp;\u0026lt;\u0026thinsp;4, that will be designed with diagonal reinforcement. The efficiency of reinforced confirmation depends mostly on the angle of inclination of the diagonal reinforcement with respect to the beam. Confining is only provided in the part of the diagonal element, not in the whole coupling beam. For aspect ratio (L\u003csub\u003ecb\u003c/sub\u003e/H\u003csub\u003ecb\u003c/sub\u003e), we can also say that the larger the aspect ratio, the less efficient the coupling beam is. The depth of the coupling beam should be higher for the lower storey and lower for the higher storey to perform better.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Mechanics of coupled shear wall\u003c/h2\u003e \u003cp\u003eThe moment M\u003csub\u003ew\u003c/sub\u003e at any level is then resisted by the sum of the bending moments M\u003csub\u003e1\u003c/sub\u003e and M₂ in the two walls at that level and the of the axial forces NL, where N is the axial force in each wall at that level, and L is the distance between their centroidal axes. The total base moment M\u003csub\u003ew\u003c/sub\u003e, a coupled wall structure, can be represented as M\u003csub\u003ew\u003c/sub\u003e\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$${M}_{w}=NL+{M}_{1}+{M}_{2}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe degree of coupling (DOC) of coupled shear walls (CSW) is defined by the axial bending moment at the base of the structure, expressed as a fraction of the total overturning moment.\u003cdiv id=\"Equb\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e\n$$\\text{D}\\text{O}\\text{C}=\\frac{\\text{N}\\text{L}}{\\text{N}\\text{L}+{\\text{M}}_{1}+{\\text{M}}_{2}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe relation between a peak shear force and an average shear force is called peak shear demand.\u003cdiv id=\"Equc\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e\n$$PSD=\\frac{{V}_{b.max}}{{V}_{b.avg}}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe degree of coupling DOC and the peak shear demand PSD are two important parameters in the design of coupled wall structures (Paulay, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1974\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"2 METHODOLOGY","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Modelling of Structure in ETABS\u003c/h2\u003e \u003cp\u003eIn ETABS, the modelling of buildings was done at various heights, such as 15, 20, 25, and 30 stories, with each storey height of 3m. These models include configurations with and without shear walls and configurations with coupled shear walls featuring coupling beams of different lengths of 1 m, 1.5m, and 2m. The coupling beams of different lengths are also modelled in various depths, with dimensions including 1.5m, 1.25m, 1 m, 0.8m, and 0.75m (Lim, 2016). The end-to-end distance between both shear walls and shear walls with coupling beams is 5 m. These coupled shear walls are made by creating openings in the shear wall. The tables below show the building parameters.\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\u003eBuilding parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuilding parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRemarks\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStructure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMoment resisting frame (MRFS), MR frame with shear wall, MR frame with coupled shear wall\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stories\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,20,25,30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of building\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRegular and symmetrical in plan\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlan area (X x Y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25m x 25m\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidth of the bay in the x-direction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25m (5 bays)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidth of the bay in the y-direction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25m (5 bays)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight of building\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45m, 60 m, 75m, 90m\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFloor height\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3m\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSupport type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFixed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiaphragm type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRigid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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\u003eMembers parameter\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026times;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026times;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of stories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeam size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eColumn size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGrade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c2\"\u003e \u003cp\u003e350\u0026times;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c3\"\u003e \u003cp\u003e500\u0026times;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c2\"\u003e \u003cp\u003e325\u0026times;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c3\"\u003e \u003cp\u003e550\u0026times;550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c2\"\u003e \u003cp\u003e450\u0026times;550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c3\"\u003e \u003cp\u003e600\u0026times;600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c2\"\u003e \u003cp\u003e575\u0026times;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026times;\" colname=\"c3\"\u003e \u003cp\u003e700\u0026times;700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\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\u003eMaterial Parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaterial Parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRemarks\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade of concrete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrade of steel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFe500- longitudinal reinforcement\u003c/p\u003e \u003cp\u003eFe500- confinement reinforcement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnit weight of reinforced concrete\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 kN/m3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDensity of steel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7849.047 kg/m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u0026rsquo;s modulus of M30 concrete, E\u003csub\u003ec\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27386.13 MPa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYoung\u0026rsquo;s modulus of steel, E\u003csub\u003es\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200000 MPa\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnit weight of Masonry wall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 kN/m\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLoad type\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of loads\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntensities\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eType of load assigning\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDead Load on Floors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5 kN/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShell type load (Distributed)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLive load on floors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 kN/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShell type load (Uniform)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFor infill walls \u0026ndash; Wall load on floors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 kN/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrame type load (Uniform)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSeismic parameter\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeismic parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRemarks\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeismic zones and zone factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZone Ⅴ(Z\u0026thinsp;=\u0026thinsp;0.36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImportance factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse reduction factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDamping ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Load combination\u003c/h2\u003e \u003cp\u003eThe load combination used here is 1.2DL\u0026thinsp;+\u0026thinsp;1.2LL\u0026thinsp;+\u0026thinsp;1.2RS\u003csub\u003ex\u003c/sub\u003e for Response Spectrum Analysis.\u003c/p\u003e \u003cp\u003e2.1.2 \u003cb\u003eNomenclature\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDue to increases in the number of models, every model is assigned a nomenclature here to foster clarity and ensure efficient communication. For different types of structures like reinforced concrete, Moment-resisting frame structure, Moment-resisting frame with shear wall and Moment-resisting frame with coupled shear wall denoted as MR, SW and CS, respectively. After that, we write the number of the building storey, like 15,20,25 and 30 storey.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNomenclature of types of structure\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTypes of Structure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNomenclature\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRC Moment-resisting Frame Structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoment-resisting frame with shear wall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoment-resisting frame with coupled shear wall\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of the modelled building with nomenclature and description\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSL. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNomenclature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTypes of Structure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of Storey\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLength of Coupling beam(m)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDepth of Coupling beam(m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1.5D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1.5D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1.5D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1.5D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L1.5D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L2D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L2D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L2D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L2D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS15L2D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e 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\u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L1D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e 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\u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L1.5D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L1.5D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L1.5D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L1.5D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L1.5D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L2D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L2D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L2D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L2D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS20L2D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1.5D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1.5D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1.5D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1.5D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L1.5D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L2D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L2D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L2D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L2D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS25L2D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1.5D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1.5D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1.5D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1.5D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L1.5D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L2D1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L2D2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L2D3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L2D4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCS30L2D5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.75\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=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Machine Learning\u003c/h2\u003e \u003cp\u003eIn this study, the random forest model is adopted as the type of machine learning by analyzing the performance of the four machine learning models which are random forest, decision tree, KNN, XG boost. The random forest is a type of supervised learning algorithm. The program utilize several important libraries used in machine learning for prediction of data. The important libraries that are employed here are libraries like Tkinter for GUI (graphical user interface) development, pandas for data manipulation, and scikit-learning for machine learning tasks, particularly utilizing train_test_split and Random Forest Regressor. Initially, data is imported from files which are prepared by the outputs from the ETABS analysis into a panda data frame, where subsequently, the data is preprocessed by selecting specific columns for features (x) and target variables (y). The dataset is split into training and testing sets using train_test_split(). With a Random Forest Regressor, the program trains the regression model on the training data. Define functions like calculate_score() and predict_CBD() are defined for score predictions and predicting the depth of the coupling beam (CBD), respectively. The score is calculated on the basis of adopting suitable weightage for all the input variables in order to make it easier to find an optimum value. The weightage is primarily considered on the basis of the variable importance, and the initial data from the ETABS is modified, and the data taken here is the relative difference in the model of that height with respect to data from the shear wall model of that height. After that, the Thinter window is created for user interaction. User input is taken as building height, and CBL is optionally taken. Predictions of CBD are made based on user input, with or without CBL, and subsequently displayed. Upon completion of tasks, the Tkinter window closes.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 RESULTS AND DISCUSSION","content":"\u003cp\u003eFirstly, we compare the parameters such as Storey displacement, storey drift, reinforcement required and volume of concrete required of 15,20,25, and 30-storey buildings without a shear wall, with a shear wall and a shear wall with a coupling beam of different dimensions. The storey displacement and drift for all buildings are the same in both the X and Y directions. Therefore, only the variation in the X-direction is depicted in the graph. The storey displacement represents the results obtained from the analysis of the building in ETABS. The reinforcement obtained through detailing is carried out in ETABS after the structure analysis. In the detailing of the coupled shear wall, diagonal reinforcement is adopted where required, many researchers ((Barney,1976) to (Naish, \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e)) have shown in their work that diagonal reinforcement is a lot better in energy dissipation as illustrated in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e for a 15-storey coupled shear wall structure with a 1.5 m length and 1.25 m depth of the coupled shear wall and an overall 5 m length of shear wall. The concrete required is the volume of concrete utilized in the shear walls of the structure only. The volume of concrete in the beam, column, and slab was the same for all models, so we only compared the volume of concrete in the shear wall. Just for the sake of visualization a typical model view are shown in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e similarly other storey are also modelled in the same way.\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Results\u003c/h2\u003e\n \u003cp\u003e3.1.1 \u003cstrong\u003eThe coupled shear wall has a length of coupling beam of 1 m for 15 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.1.2 \u003cstrong\u003eThe coupled shear wall has a length of coupling beam of 1.5 m for 15 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.1.3 \u003cstrong\u003eThe coupled shear wall has a length of coupling beam of 2 m for 15 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.1.4 \u003cstrong\u003eThe coupled shear wall has a length of coupling beam of 1 m for 20 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.1.5 \u003cstrong\u003eThe coupled shear wall has a length of coupling beam of 1.5 m for 20 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.1.6 \u003cstrong\u003eThe coupled shear wall has a coupling beam length of 2 m for 20 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e3.1.7 \u003cstrong\u003eThe coupled shear wall has a coupling beam length of 1 m for 25 storey building.\u003c/strong\u003e\u003c/p\u003e\n \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\n \u003cp\u003e3.1.8 The coupled shear wall has a coupling beam length of 1.5m for 25 storey building.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\n \u003cp\u003e3.1.9 The coupled shear wall has a coupling beam length of 2m for 25 storey building.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\n \u003cp\u003e3.1.10 The coupled shear wall has a coupling beam length of 1m for 30 storey building.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n \u003cp\u003e3.1.11 The coupled shear wall has a coupling beam length of 1.5m for 30 storey building.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003cp\u003e3.1.12 The coupled shear wall has a coupling beam length of 2m for 30 storey building.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Discussion\u003c/h2\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.1 Discussion for 15-storey building\u003c/h2\u003e\n \u003cp\u003eThe results show that the lateral displacement and storey drift of the MR15 model is maximum. When comparing buildings with shear wall, the maximum lateral displacement and storey drift occurs in the least depth coupling beam buildings in all three cases, i.e. CS15L1D5, CS15L1.5D5, and CS15L2D5 models. The lateral displacement and storey drift are minimum for the SW15 model. The storey drift is the same between 12 and 13 storey. The reinforcement required is maximum for model CS15L1D1 in comparison with all 15-storey models. The reinforcement required for the CS15L2D5 model is minimum and almost equal to the SW15 model. The volume of concrete is reduced by 10\u0026ndash;15% in coupled shear wall structures in comparison with solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS15L2D5 model is minimum and reduced by 30% compared to the SW15 model. The volume of concrete is maximum for model SW15 compared with all 15-storey models.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.2 Discussion for 20-storey building\u003c/h2\u003e\n \u003cp\u003eThe results show that the MR20 model exhibits maximum lateral displacement (180.491 mm) and storey drift (0.00461). The lateral displacement and storey drift are minimum for the SW20 model. Notably, models SW20 and CS20L1D2 demonstrate exactly the same lateral displacement and storey drift. Among different coupling beam lengths (1m, 1.5m, and 2m), CS20L1D2, CS20L1.5D1, and CS20L2D2 exhibit the least lateral displacement and storey drift, respectively. When comparing buildings with shear walls, the maximum lateral displacement and storey drift occur in models with the shallowest coupling beams, namely CS20L1D5, CS20L1.5D5, and CS20L2D5. The storey drift remains consistent between 15 and 16 storey. The reinforcement required is maximum for model CS20L1D1 and minimum for model SW20 compared to all 20-storey models. The reinforcement required for the CS20L2D5 model is 1% more than model SW20 model. The volume of concrete is reduced by 10\u0026ndash;30% in coupled shear wall structures compared to solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS20L2D5 model is minimum and reduced by 30% compared to the SW20 model. The volume of concrete is maximum for model SW20 compared to all 20-storey models.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.3 Discussion for 25-storey building\u003c/h2\u003e\n \u003cp\u003eThe results show that the MR25 model exhibits maximum lateral displacement (233.154 mm) and storey drift (0.00467). The lateral displacement is minimum for the SW25 model. Notably, models SW25 and CS25L1D3 demonstrate exactly the same lateral displacement. Among different coupling beam lengths (1m, 1.5m, and 2m), CS25L1D3, CS25L1.5D1, and CS25L2D1 exhibit the least lateral displacement and CS25L1D3, CS25L1.5D5, and CS25L2D1 exhibit the least storey drift respectively. When comparing buildings with shear walls, the maximum lateral displacement and storey drift occur in models with the 0.8m depth of the coupling beam, namely CS25L1D4, CS25L1.5D4, and CS25L2D4. The storey drift of the CS25L1D3 model is minimal compared to all 25-storey buildings and 0.6% less than the SW25 model. The storey drift remains consistent between 22 and 23 storey. The reinforcement required is maximum for model CS25L1D1 and minimum for SW25 compared to all 25-storey models. The reinforcement required for the CS25L1D4 and CS25L2D5 models is 0.13% more than the SW25 model. The volume of concrete is reduced by 10\u0026ndash;30% in coupled shear wall structures compared to solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS25L2D5 model is minimal and reduced by 30% compared to the SW25 model. The volume of concrete is maximum for model SW25 compared to all 25-storey models.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\n \u003ch2\u003e3.2.4 Discussion for 30-storey building\u003c/h2\u003e\n \u003cp\u003eThe results show that the MR30 model exhibits maximum lateral displacement (281.634 mm) and storey drift (0.004594). The lateral displacement is minimum for the SW30 model. Among all shear wall models, CS30L1D1 shows the least lateral displacement, which is 0.16% more than model SW30. Among different coupling beam lengths (1m, 1.5m, and 2m), CS30L1D1, CS30L1.5D1, and CS30L2D1 exhibit the least lateral displacement and least storey drift respectively. When comparing buildings with shear walls, the maximum lateral displacement and storey drift occur in CS30L1D5, CS30L1.5D4, and CS30L2D4 models for different lengths of coupling beam. The storey drift of the CS30L1D1 and CS30L1D2 models is the same and minimum compared to all 30-storey buildings and 0.21% less than the SW30 model. The storey drift remains consistent between 26 and 27 storeys. The reinforcement required is maximum for model CS30L1D1 and minimum for CS30L1.5D2 compared to all 30-storey models. The reinforcement required for the CS30L1D4 and CS30L1.5D2 models is 2.31% and 4.13%, respectively, less than the SW25 model. The volume of concrete is reduced by 10\u0026ndash;30% in coupled shear wall structures compared to solid shear wall structures. The volume of concrete gradually decreases as the depth of the coupling beam decreases. The volume of concrete for the CS30L2D5 model is minimal and reduced by 30% compared to the SW30 model. The volume of concrete is maximum for model SW30 compared to all 30-storey models.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Machine learning results\u003c/h2\u003e\n \u003cp\u003eThe RF, DT, XGBoost and KNN models were implemented using the Scikit-Learn library using Machine learning toolsnox in Python. The \u003cstrong\u003etrain_test_size\u003c/strong\u003e parameter determines the proportion of the dataset to include in the 80% of the data used for training (\u003cstrong\u003ex_train\u003c/strong\u003e and \u003cstrong\u003ey_train\u003c/strong\u003e) and 20% for testing (\u003cstrong\u003ex_test\u003c/strong\u003e and \u003cstrong\u003ey_test\u003c/strong\u003e). The scores of train and test of all models that we implemented are shown in the following Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\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\u003cbr\u003e\u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRF\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eXG Boost\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eKNN\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\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9996\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.5888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.22E-05\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\u003e3.32E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTest\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\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0000\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=\"char\"\u003e\n \u003cp\u003e0.0146\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMAE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e18\u003c/span\u003e shows the performance of all models in predicting the score by training and testing. From Fig. \u003cspan class=\"InternalRef\"\u003e18\u003c/span\u003e (c) \u0026amp; Fig. \u003cspan class=\"InternalRef\"\u003e18\u003c/span\u003e (d), it is clear that the XG Boost \u0026amp; KNN is not a good model for this set of data on the other hand the random forest and decision tree are pretty good but the predicted value shows more deviation than the random forest (see Fig. \u003cspan class=\"InternalRef\"\u003e18\u003c/span\u003e (a) \u0026amp; Fig. \u003cspan class=\"InternalRef\"\u003e18\u003c/span\u003e (b)). Similar trends are analyzed from the R\u003csup\u003e2\u003c/sup\u003e, MSE and MAE for all these four models see Table \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e. Figure \u003cspan class=\"InternalRef\"\u003e19\u003c/span\u003e shows the correlation matrix derived from the original dataset, 7 input variables and 1 output variable. This matrix illustrates the correlation coefficients between every pair of variables, where a coefficient of 1 signifies the highest positive correlation, -1 represents the highest negative correlation, and 0 indicates no correlation. Through this matrix, the interrelations among various variables show positive and negative correlations among them. Here, the score was majorly influenced by the drift \u0026minus;\u0026thinsp;0.78 and very little on steel. This is so because drift is the most important parameter of seismic design. However, steel has a lesser impact because the change in its quantity with respect to shear walls is very less.\u003c/p\u003e\n \u003cp\u003eBy following the steps shown in Fig. 20, we can predict the length and depth of the coupling beam. Firstly, the user inputs the storey height. If opting for the coupling beam length (CBL), they enter \u0026quot;yes\u0026quot;; otherwise, \u0026quot;no\u0026quot; for both length and depth prediction. If we enter yes, then we have to enter the length of the coupling beam (CBL), then it shows the predicted depth of the coupling beam (CBD). Here, providing basic input like the height of the building being 90 meters and CBL being 1.75 m, the algorithm is able to deduce the optimum CBD as 1 m. The result is validated from the available data set as the calculated score after the modelling of this building is -0.06612 which lies between the available points.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 CONCLUSION","content":"\u003cp\u003eShear wall configurations generally exhibit lower lateral displacement and storey drift compared to those with coupling beams, especially with deeper coupling beams. Among models with similar configurations, those with shallower coupling beams tend to experience higher displacement and drift. The storey drift remains consistent at 1/5 of the height of the building from the top. For 25-storey buildings, CSW buildings with CB of length (1m) and depth (1m) drift give better results than shear walls. CSW building with CB of length (1m) and depth (1.5m,1.25m) shows minimum storey drift compared to all 30-storey buildings. For 15-storey models, CSW building with CB of length (1m) and depth (1.5m) requires the maximum reinforcement while building with CB of length (2m) and depth (0.75m) requires the minimum, almost equal to solid shear wall building. For 20,25, and 30-storey models, CSW building with CB of length (1m) and depth (1.5m) requires maximum reinforcement, and solid shear wall building requires minimum reinforcement. For 30-storey models, a CSW building with a CB of length (1m) and depth (1.5m) requires the maximum reinforcement, and a building with a CB of length (1.5m) and depth (1.25m) requires 4.13% less reinforcement than solid shear wall structure. The volume of concrete gradually decreases as the depth and length of the coupling beam decrease. The volume of concrete is minimum for buildings with coupled shear walls of length (2 m) and depth (1.5 m) of coupling beam for all cases and reduced by 30% compared to the building with shear wall. The volume of concrete is maximum for buildings with shear walls compared to all cases. As the height of the building increases, coupled shear wall building performs better than shear wall building. The Random Forest model achieved higher R2 (i.e., 0.9624), lower MSE (i.e., 3.22E-05) and MAE (i.e., 0.0036) within the developed four machine learning models, demonstrating the best effectiveness of the random forest algorithm in predicting the best score.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCBD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Coupling beam depth\u003c/p\u003e\n\u003cp\u003eCBL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Coupling beam length\u003c/p\u003e\n\u003cp\u003eCSW \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Coupled shear wall\u003c/p\u003e\n\u003cp\u003eDL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Dead Load\u003c/p\u003e\n\u003cp\u003eDOC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Degree of coupling\u003c/p\u003e\n\u003cp\u003eFe500 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Reinforcement steel bar of minimum yield strength equivalent to 500 MPa.\u003c/p\u003e\n\u003cp\u003eGUI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Graphical user interface\u003c/p\u003e\n\u003cp\u003ekg \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;kilogram\u003c/p\u003e\n\u003cp\u003ekN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; kilo-Newton\u003c/p\u003e\n\u003cp\u003eL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Length between the centroidal axes\u003c/p\u003e\n\u003cp\u003eLL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Live Load\u003c/p\u003e\n\u003cp\u003em \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; meter\u003c/p\u003e\n\u003cp\u003eM\u003csub\u003e1\u0026nbsp;\u003c/sub\u003e\u0026amp; M\u003csub\u003e2\u003c/sub\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Moment in walls 1 \u0026amp; 2\u003c/p\u003e\n\u003cp\u003eM30 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Design mix for compressive strength of 30 MPa.\u003c/p\u003e\n\u003cp\u003eMAE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean absolute error\u003c/p\u003e\n\u003cp\u003eMPa \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Megapascal\u003c/p\u003e\n\u003cp\u003eMRFS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Moment resisting frame\u003c/p\u003e\n\u003cp\u003eMSE \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Mean squared error\u003c/p\u003e\n\u003cp\u003eM\u003csub\u003ew\u003c/sub\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Moment at base\u003c/p\u003e\n\u003cp\u003eN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Axial force\u003c/p\u003e\n\u003cp\u003ePSD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Peak shear demand\u003c/p\u003e\n\u003cp\u003eRC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Reinforced concrete\u003c/p\u003e\n\u003cp\u003eRS\u003csub\u003ex\u003c/sub\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Response spectrum load in the x direction\u003c/p\u003e\n\u003cp\u003eV\u003csub\u003eb,avg \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/sub\u003eAverage of shear force developed\u003c/p\u003e\n\u003cp\u003eV\u003csub\u003eb,max \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/sub\u003eMaximum shear force developed\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, N.K. and P.P.; methodology, N.K.; software, N.K.; validation, N.K.; resources, P.P; data curation, N.K.; writing\u0026mdash;original draft preparation, N.K.; writing\u0026mdash;review and editing, N.K.; visualization, N.K.; supervision, P.P and S.M.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eACI Committee 318. 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Orientation and location of shear walls in RC buildings to control deflection and drifts.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouhaibou, A., \u0026amp; Li, L. (2023). April 28). A comparative study on the lateral displacement of a multi-story RC building under wind and earthquake load actions using base shear method and ETABS software.\u003c/span\u003e \u003cspan\u003eStandardization.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTassios, T. P., Moretti, M., \u0026amp; Bezas, A. (1996). On the behavior and ductility of reinforced concrete coupling beams of shear walls. \u003cem\u003eACI Structural Journal\u003c/em\u003e, \u003cem\u003e93\u003c/em\u003e(6), 711\u0026ndash;720.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTBI Guidelines Working Group. (2010). \u003cem\u003eGuidelines for performance-based seismic design of tall buildings-version 1.0. Report No. 2010/05\u003c/em\u003e. Pacific Earthquake Engineering Research Center.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTegos, I. A., \u0026amp; Penelis, G. G. (1988). Seismic resistance of short columns and coupling beams reinforced with inclined bars. \u003cem\u003eACI Structural Journal\u003c/em\u003e, \u003cem\u003e85\u003c/em\u003e(1), 82\u0026ndash;88.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"asian-journal-of-civil-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Asian Journal of Civil Engineering](https://www.springer.com/journal/42107)","snPcode":"42107","submissionUrl":"https://submission.nature.com/new-submission/42107/3","title":"Asian Journal of Civil Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Coupled Shear Wall, Machine Learning, Reinforced concrete structures, High rise, ETABS","lastPublishedDoi":"10.21203/rs.3.rs-4408410/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4408410/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA coupled Shear Wall is a unified system consisting of the connection of two individual shear walls with a connecting beam (coupling beam). The coupling beam plays an important role in the lateral load resistance of the coupled shear wall structure. This paper addresses the innovative approach to optimizing coupling beam dimensions by introducing data in machine learning. The data are collected through ETABS modelling of encompassing buildings of varying heights, i.e., 15, 20, 25, 30 stories, with and without shear walls, and coupled shear walls with coupling beams of different lengths, i.e., 1 m, 1.5m, and 2m, and different depths, i.e., 1.5m, 1.25m, 1 m, 0.8m, and 0.75m which is analysed by keeping the end to end distance of both shear wall and shear wall with coupled beam in order to make it economical. The parameters considered include displacement, drift, reinforcement quantity, and concrete volume collected through ETABS. A total of 68 models were analyzed. Analysis made through that, in all of the storey except in 30 storey the shear wall with coupling beam dimension, length of 2 m and depth of 1.25 m is most optimum model and in the case of 30 storey optimized model changes, the coupling beam with a length of 1.5 m and depth of 1.25 m perform best. On increasing storey, it can be deduced that coupled shear wall performs much better. Furthermore, the machine learning-trained model will provide the optimum dimension of the coupling beam if storey height is provided.\u003c/p\u003e","manuscriptTitle":"Optimality of reinforced concrete coupled shear wall using machine learning","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-28 17:58:46","doi":"10.21203/rs.3.rs-4408410/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-19T12:03:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-19T10:56:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215734853289880038387312775818230429016","date":"2024-05-13T12:19:16+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-13T08:09:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199686641999039408051930811786387193829","date":"2024-05-13T08:02:41+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-13T08:00:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-13T04:40:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-13T01:13:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Asian Journal of Civil Engineering","date":"2024-05-12T12:13:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"asian-journal-of-civil-engineering","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Asian Journal of Civil Engineering](https://www.springer.com/journal/42107)","snPcode":"42107","submissionUrl":"https://submission.nature.com/new-submission/42107/3","title":"Asian Journal of Civil Engineering","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"a168cf34-139e-43ed-b94b-f80c73c113cd","owner":[],"postedDate":"May 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-07-20T08:13:55+00:00","versionOfRecord":{"articleIdentity":"rs-4408410","link":"https://doi.org/10.1007/s42107-024-01104-x","journal":{"identity":"asian-journal-of-civil-engineering","isVorOnly":false,"title":"Asian Journal of Civil Engineering"},"publishedOn":"2024-07-20 08:13:55","publishedOnDateReadable":"July 20th, 2024"},"versionCreatedAt":"2024-05-28 17:58:46","video":"","vorDoi":"10.1007/s42107-024-01104-x","vorDoiUrl":"https://doi.org/10.1007/s42107-024-01104-x","workflowStages":[]},"version":"v1","identity":"rs-4408410","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4408410","identity":"rs-4408410","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}