Physics-Informed Optimization of Dross Formation inFiber-Laser Cutting: From Multi-Variable Design to aSingle Decision Rule

Physics-Informed Optimization of Dross Formation inFiber-Laser Cutting: From Multi-Variable Design to aSingle Decision Rule | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Physics-Informed Optimization of Dross Formation inFiber-Laser Cutting: From Multi-Variable Design to aSingle Decision Rule Tahseen Fadhil Abbas, Riyadh Algburi, Ahmed Abdullah Ebraheem, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8144440/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Laser cutting has the ability to produce detailed parts at small tolerances with minimal areas of heat impact, although theformation of dross still hinders the ability to produce repeatable and quality results. We experimented with stainless steel 201(SS201) having a five-factor design-laser power (Pu), cutting speed (V), assist-gas pressure (P), pulse frequency (F) as wellas the focus position (FP) in a 32-run Central Composite Design. On top of classical Response Surface Methodology, wepropose a physics-driven model, which consists of a dimensionless Dross Ejection Index (DEI) that balances melt-expulsionforces (assist-gas shear, recoil pressure) and retention (viscous drag, gravity, capillarity). Mapping of DEI to dross area(DA) using monotone sigmoidal law is a technique of collapsing scattered results onto one interpretable curve and providesa way of providing a practical threshold of clean cutting. Gaussian Process regression had the highest level of numericalaccuracy in cross-validated benchmarks (R2 ≈ 0.28, RMSE ≈ 22.8 mm2), but the De-sigmoid model was more interpretableand extrapolated more safely. Factor effects are in line with first principles: power and focus are leading (≈ 45% and 39%),then speed (7%), frequency (6.4%), and pressure (2.7%). The combined method transforms a tuning exercise involving fivevariables into a single-number decision rule—operate at DEI ≥ DEI∗—to provide definitive parameter indications to eliminatedross and enhance industrial quality in laser cutting. Physical sciences/Engineering Physical sciences/Mathematics and computing Laser cutting dross formation stainless steel 201 response surface methodology Gaussian Process mechanistic modeling multi-factor optimization Full Text Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstract.png DataSet.xlsx Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8144440","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":555492605,"identity":"822c3faa-84a4-4ab4-8b0d-62716981be1a","order_by":0,"name":"Tahseen Fadhil Abbas","email":"","orcid":"","institution":"Al-Farahidi University","correspondingAuthor":false,"prefix":"","firstName":"Tahseen","middleName":"Fadhil","lastName":"Abbas","suffix":""},{"id":555492606,"identity":"26d4cf94-4c1b-46ae-bd56-c4cbc963c4f5","order_by":1,"name":"Riyadh Algburi","email":"","orcid":"","institution":"Al-Farahidi University","correspondingAuthor":false,"prefix":"","firstName":"Riyadh","middleName":"","lastName":"Algburi","suffix":""},{"id":555492607,"identity":"d2843178-2d1e-442a-afd2-c1a0735a5dc6","order_by":2,"name":"Ahmed Abdullah Ebraheem","email":"","orcid":"","institution":"Al-Farahidi University","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"Abdullah","lastName":"Ebraheem","suffix":""},{"id":555492608,"identity":"5b1e76bc-f8b6-4039-9ef6-768a42ea7b76","order_by":3,"name":"Yeong Hyeon Gu","email":"","orcid":"","institution":"Sejong University","correspondingAuthor":false,"prefix":"","firstName":"Yeong","middleName":"Hyeon","lastName":"Gu","suffix":""},{"id":555492612,"identity":"8b5e87d1-cfab-4525-a0fd-c6a966a7d06d","order_by":4,"name":"Mugahed A. 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We experimented with stainless steel 201(SS201) having a five-factor design-laser power (Pu), cutting speed (V), assist-gas pressure (P), pulse frequency (F) as wellas the focus position (FP) in a 32-run Central Composite Design. On top of classical Response Surface Methodology, wepropose a physics-driven model, which consists of a dimensionless Dross Ejection Index (DEI) that balances melt-expulsionforces (assist-gas shear, recoil pressure) and retention (viscous drag, gravity, capillarity). Mapping of DEI to dross area(DA) using monotone sigmoidal law is a technique of collapsing scattered results onto one interpretable curve and providesa way of providing a practical threshold of clean cutting. Gaussian Process regression had the highest level of numericalaccuracy in cross-validated benchmarks (R2 ≈ 0.28, RMSE ≈ 22.8 mm2), but the De-sigmoid model was more interpretableand extrapolated more safely. Factor effects are in line with first principles: power and focus are leading (≈ 45% and 39%),then speed (7%), frequency (6.4%), and pressure (2.7%). 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