[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125780-en":3,"doc-seo-125780-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},125780,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Machine learning-driven web-post buckling resistance prediction for high-strength steel beams with elliptically-based web openings","The use of periodical elliptically-based web (EBW) openings in high strength steel (HSS) beams is increasingly adopted to improve the strength-to-weight ratio and reduce floor height by enabling utility services through the web. These beams remain vulnerable to web-post buckling (WPB), requiring accurate capacity prediction tools. The paper implements multiple machine learning approaches to predict WPB capacity for HSS beams with EBW openings and evaluates the performance of existing analytical design models. A validated numerical framework generates 10,764 finite element web-post models for S460, S690 and S960 steel grades, training and validating ANN, SVR and GEP, and proposing new design models.","Results in Engineering 21 (2024) 101749  \nContents lists available at ScienceDirect  \nResults in Engineering  \njournal [homepage:](homepage: www.sciencedirect.com/journal/results-in-engineering)[ www.sciencedirect.com/journal/results-in-engineering](homepage: www.sciencedirect.com/journal/results-in-engineering)  \n| Machine learning-driven web-post buckling resistance prediction for high-strength steel beams with elliptically-based web openings\u003Cbr>Musab Rabia, Yazeed S. Jweihan b, Ikram Abarkanc, Felipe Piana Vendramell Ferreira d, Rabee Shamasse, Vireen Limbachiyaf, *, Konstantinos Daniel Tsavdaridisg,\u003Cbr>Luis Fernando Pinho Santos f\u003Cbr>a Dept of Civil Engineering, Jerash University, Jerash, 26150, Jordan\u003Cbr>b Civil and Environmental Engineering Department, College of Engineering, Mutah University, Mutah, P.O. BOX 7, Karak, 61710, Jordan c Department of Physics, Faculty of Sciences, Abdelmalek Essaˆadi University, 93002 Tetouan, Morocco\u003Cbr>d Faculty of Civil Engineering, Federal University of Uberlˆandia,– Campus Santa Mˆonica, Uberlˆandia, Minas Gerais, Brazil e Department of Civil and Environmental Engineering, Brunel University London, London, UK\u003Cbr>f Division of Civil and Building Services Engineering, School of Build Environment and Architecture, London South Bank University, UK g Department of Engineering, School of Science and Technology, City, University of London, Northampton Square, EC1V 0HB, London, UK |  |  |\n| --- | --- | --- |\n| A R T I C L E I N F O |  | A B S T R A C T |\n| Keywords:\u003Cbr>Finite element modelling\u003Cbr>Web-post buckling resistance Elliptically-based web openings High strength steel beams Artificial neural network\u003Cbr>Gene expression programming Support vector machine regression |  | The use of periodical elliptically-based web (EBW) openings in high strength steel (HSS) beams has been increasingly popular in recent years mainly because of the high strength-to-weight ratio and the reduction in the floor height as a result of allowing different utility services to pass through the web openings. However, these sections are susceptible to web-post buckling (WPB) failure mode and therefore it is imperative that an accurate design tool is made available for prediction of the web-post buckling capacity. Therefore, the present paper aims to implement the power of various machine learning (ML) methods for prediction of the WPB capacity in HSS beams with (EBW) openings and to assess the performance of existing analytical design model. For this purpose, a numerical model is developed and validated with the aim of conducting a total of 10,764 web-post finite element models, considering S460, S690 and S960 steel grades. This data is employed to train and validate different ML algorithms including Artificial Neural Networks (ANN), Support Vector Machine Regression (SVR) and Gene Expression Programming (GEP). Finally, the paper proposes new design models for WPB resistance prediction. The results are discussed in detail, and they are compared with the numerical models and the existing analytical design method. The proposed design models based on the machine learning predictions are shown tobe powerful, reliable and efficient design tools for capacity predictions of the WPB resistance of HSS beams with periodical (EBW) openings. |\n\n1. Introduction  \nSteel beams with periodical web openings (i.e., castellated, cellular and Angelinas) can be used in multi-story building designs, since they have many advantages such as the reduction in the structure’s selfweight and the floor height since as a result of allowing different utility services to pass through the web openings [1,2]. The present study focuses on S460, S690, S960 grade high strength steel beams (HSS) beams comprising periodical elliptically-based web (EBW) openings. The manufacturing and castellation process include three main steps: thermal cutting, shifting and welding [3]. These procedures result in an  \nincrease in inertia about the strong axis leading to","cbCaialY3RFnYJ4K","https://ap.wps.com/l/cbCaialY3RFnYJ4K","pdf",8383327,1,15,"English","en",105,"# Introduction\n## Background and problem definition\n## Buckling modes and focus on WPB\n## High-strength steel beams and motivation","[{\"question\":\"Why are elliptically-based web (EBW) openings used in high-strength steel beams?\",\"answer\":\"They improve the strength-to-weight ratio and reduce floor height by allowing utility services to pass through the openings.\"},{\"question\":\"What failure mode is the paper mainly concerned with?\",\"answer\":\"The study focuses on web-post buckling (WPB), a local failure mode driven by S-shaped double curvature caused by horizontal shear stresses.\"},{\"question\":\"Which machine learning methods are used to predict WPB capacity?\",\"answer\":\"The paper trains and validates Artificial Neural Networks (ANN), Support Vector Machine Regression (SVR), and Gene Expression Programming (GEP), based on a large validated finite element dataset.\"}]","Machine learning-driven web-post buckling resistance prediction for high-strength steel beams with elliptically-based web openings | PDF",1785901169,38,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-driven-web-post-buckling-resistance-prediction-for-high-strength-steel-beams-with-elliptically-based-web-openings","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-driven-web-post-buckling-resistance-prediction-for-high-strength-steel-beams-with-elliptically-based-web-openings/125780/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why are elliptically-based web (EBW) openings used in high-strength steel beams?","Question",{"text":75,"@type":76},"They improve the strength-to-weight ratio and reduce floor height by allowing utility services to pass through the openings.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What failure mode is the paper mainly concerned with?",{"text":80,"@type":76},"The study focuses on web-post buckling (WPB), a local failure mode driven by S-shaped double curvature caused by horizontal shear stresses.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning methods are used to predict WPB capacity?",{"text":84,"@type":76},"The paper trains and validates Artificial Neural Networks (ANN), Support Vector Machine Regression (SVR), and Gene Expression Programming (GEP), based on a large validated finite element dataset.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]