[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122966-en":3,"doc-seo-122966-105":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},122966,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","Machine Learning-Based Constitutive Modelling for Granular Materials","Granular materials play a central role in hydraulic structures, roads, and bridges, particularly in dam-building rockfill systems where pore structures and graded particles govern mechanical behavior. Accurate constitutive descriptions are required for safety analyses of ultra-high rockfill dams. This work targets the gap in unified constitutive theory by leveraging machine learning to learn deformation–response relationships, improve prediction accuracy, and support boundary value problem calculations. The thesis develops deep learning, active learning sampling, and an FEM–NN computational framework for boundary value use.","Machine Learning-Based Constitutive Modelling for Granular Materials  \nShaoheng Guan  \nSchool of Aerospace, Civil, Electrical, General and Mechanical Engineering  \nSwansea University  \nSubmitted in fulfilment of the requirements for the degree of  \nPhD  \nSep. 22, 2023  \nCopyright: The Author, Shaoheng Guan, 2023  \nDedication  \nDedicated to my dearest wife, Ma Yukun,  \nOur journey began in Swansea, UK, where we crossed paths. From those early days to the final stages of my doctoral thesis and our shared moments in Graz, Austria, each step has been illuminated by your presence. Together, we strolled along Swansea’s coastline, savoured the taste of fish and chips in Tenby, and listened to the enchanting tunes of Scottish bagpipes.  \nIn times of doubt, you’ve remained my constant and steadfast source of support. As I dedicate the accomplishment of my doctoral thesis, I’m also dedicating it to you. It symbolises not only my achievement but also the love and companionship we’ve shared on this incredible journey.  \nWith boundless love, Shaoheng Guan  \nAcknowledgements  \nI want to convey my deepest appreciation to Prof. Feng Y.T. , my supervisor, for his unwavering assistance, and endless patience throughout my doctoral voyage. He not only granted me considerable freedom in my research but also consistently provided me with useful and timely help whenever I encountered obstacles. Being a student of such a brilliant scholar and wise man was a true honour.  \nI would also like to express my gratitude to Prof. Zhou Wei and Prof. Ma Gang from Wuhan University, Dr Xiao Dunhui at Swansea Univeristy, and Dr Zhang Xue from Liverpool University for their valuable guidance and support.  \nMy time in Swansea allowed me to forge meaningful friendships. I am deeply appreciative of individuals like Qu Tongming, Fu Jinlong, Wang Mengqi, Fu Rui, Li Yang, Liu Biao, Chai Yanjiang, Sun Guangshuai, Peng Linzhi, Li Zhanfeng, Zou Xi, Chen Bingbing, Nathan Ellmer, Yash and Agustina Felipe.  \nHeartfelt thanks go to my parents and my wife for their consistent support. Their love acts as the driving force that propels me forward.  \nI also want to acknowledge the beauty of Swansea’s grassy landscapes, expansive sea, and captivating blue skies – elements that contributed to an enriching experience.  \nAbstract  \nAs a material second only to liquids in nature, granular materials are widely used in hydraulic structures, roads, bridges etc. Dam-building granular materials are complex systems of pore structures and continuously graded rock particles. An accurate description of their mechanical properties is essential for the safety analysis of ultra-high rockfill dams. At the microscopic scale, granular materials are discrete elementary systems aggregated by complex internal interactions, and their microscopic mechanical structure and statistical characteristics influence the macroscopic mechanical properties; at the macroscopic scale, especially in engineering-scale computational analysis, granular materials are often regarded as continuous media and their constitutive relationship are described using non-linear or elastic-plastic theories. Yet, there is no unified theory to characterise all their constitutive properties.  \nConstitutive modelling stands as a pivotal topic within mechanical calculations. Establishing an accurate description of the relationship between deformation and constitutive response serves as the foundation for Boundary Value Problem analysis. With the growing prominence of machine learning techniques in the data-driven realm, they are expected to enhance constitutive modelling and potentially surpass classical models based on simplifying assumptions. More and more endeavours have been dedicated to integrating machine learning into mechanical calculations and assessing its efficacy.  \nThis PhD thesis focuses on the use of machine learning techniques to investigate the feasibility of developing a constitutive model for granular materials and apply","cbCaibCiNaqSsYQX","https://ap.wps.com/l/cbCaibCiNaqSsYQX","pdf",53637954,1,233,"English","en",105,"# Abstract\n## Machine learning for constitutive modelling\n## Chapter 2: Deep learning from DEM data\n## Chapter 3: Active learning for loading paths\n## Chapter 4: FEM–NN computational framework","[{\"question\":\"Why is constitutive modelling important for granular materials in engineering?\",\"answer\":\"Constitutive modelling provides the relationship between deformation and mechanical response, which is essential for boundary value problem analysis and safety assessment in structures such as rockfill dams.\"},{\"question\":\"What does the thesis propose in Chapter 2?\",\"answer\":\"Chapter 2 introduces a deep learning model using LSTM networks to reproduce macroscopic stress–strain responses across different particle size distributions, initial states, and loading conditions, trained from DEM simulation data.\"},{\"question\":\"How does Chapter 3 reduce the number of DEM simulations while improving sampling?\",\"answer\":\"An active learning strategy selects strain paths with the largest predicted errors while avoiding redundant sampling by excluding points near already selected samples; the trained model is evaluated across loading cycles.\"}]","Machine Learning-Based Constitutive Modelling for Granular Materials | PDF",1785813936,587,{"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-based-constitutive-modelling-for-granular-materials","",{"@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-based-constitutive-modelling-for-granular-materials/122966/",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","2026-08-04",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 is constitutive modelling important for granular materials in engineering?","Question",{"text":75,"@type":76},"Constitutive modelling provides the relationship between deformation and mechanical response, which is essential for boundary value problem analysis and safety assessment in structures such as rockfill dams.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What does the thesis propose in Chapter 2?",{"text":80,"@type":76},"Chapter 2 introduces a deep learning model using LSTM networks to reproduce macroscopic stress–strain responses across different particle size distributions, initial states, and loading conditions, trained from DEM simulation data.",{"name":82,"@type":73,"acceptedAnswer":83},"How does Chapter 3 reduce the number of DEM simulations while improving sampling?",{"text":84,"@type":76},"An active learning strategy selects strain paths with the largest predicted errors while avoiding redundant sampling by excluding points near already selected samples; the trained model is evaluated across loading cycles.","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"]