[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-116964-en":3,"doc-seo-116964-105":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},116964,34359740700684,"Finn","https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487",8,"Research & Report","Multiscale Machine Learning and Numerical Investigation of Ageing in Infrastructures - Doctor of Philosophy Thesis","Infrastructure forms a critical foundation for economic growth and reliable societal service. Ageing is inevitable and can reduce serviceability over time, especially when infrastructures face extreme service environments that accelerate degradation and weaken long-term performance. Rehabilitation strategies help extend service life, but their effectiveness is limited when ageing effects at smaller scales are ignored in rehabilitation design, forcing higher safety factors and increasing cost. This thesis uses machine learning with empirical datasets and numerical modelling to quantify ageing impacts across multiple scales, improving the efficiency and effectiveness of long-term performance prediction.","Multiscale Machine Learning and Numerical Investigation of  \nAgeing in Infrastructures  \nBy  \nKeyvan Aghabalaei Baghaei  \nA thesis submitted in fulfilment of the requirements for the degree of  \nDoctor of Philosophy  \nSchool of Civil Engineering  \nFaculty of Engineering  \nThe University of Sydney  \nSeptember 2023  \nStatement of originality  \nThis is to certify that to the best of my knowledge, the content of this thesis is my own work. This thesis has not been submitted for any degree or other purposes. I certify that the intellectual content of this thesis is the product of my own work and that all the assistance received in preparing this thesis and sources have been acknowledged.  \nKeyvan Aghabalaei Baghaei  \nAuthorship attribution statement and list of publications  \nChapters 3 and 4 in this thesis contains materials that are published in:  \n• Aghabalaei Baghaei, K. and Hadigheh, S.A. Durability assessment of FRP-to-concrete bonded connections under moisture condition using data-driven machine learning-based approaches, Composite Structures, 2021, 114576, DOI: [https://doi.org/10.1016/j.compstruct.2021.114576](https://doi.org/10.1016/j.compstruct.2021.114576)  \n• Aghabalaei Baghaei, K. and Hadigheh, S.A. A machine learning approach to modelling the bond strength of adhesively bonded joints under water immersion condition, 10th International Conference on FRP Composites in Civil Engineering (CICE 2021), 2022, Istanbul, Turkey.  \nThis includes Sections 3.4, 3.5 in Chapter 3 and Sections 4.1, 4.2.1, 4.3, 4.4.1, and 4.5 in Chapter 4 .  \nK. Aghabalaei Baghaei: Data curation, Formal analysis, Investigation, Software, Validation, Visualization, Writing - original draft. S.A. Hadigheh: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing-review & editing.  \nChapter 5 in this thesis contains materials that are published in:  \n• Aghabalaei Baghaei, K. and Hadigheh, S.A. Artificial neural network-based characterisation of the bond between FRP bar and concrete under environmental conditions, The 20th European Conference on Composite Materials (ECCM 20), 2022, Lausanne, Switzerland.  \nThis includes Section 5.9.  \nK. Aghabalaei Baghaei: Data curation, Formal analysis, Investigation, Software, Validation, Visualization, Writing - original draft. S.A. Hadigheh: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing-review & editing.  \nIn addition to the statement above, in cases where I am not the corresponding author of the published item, permission to include the published material has been granted by the corresponding author.  \nKeyvan Aghabalaei Baghaei, 30 September 2023  \nAs supervisor for the candidature upon which this thesis is based, I can confirm that the authorship attribution statements above are correct.  \nAli Hadigheh  \nAcknowledgements  \nI would like to express my sincere gratitude to my supervisor, Dr Ali Hadigheh, for his support, guidance, and encouragement throughout my doctoral studies. His expertise and advice were invaluable to me, and I am grateful for the opportunity to have worked with him.  \nI would also like to thank the members of the examining committee for their time and for reviewing my dissertation.  \nI also extend my thanks to Dr Slaven Marusic. His experience and knowledge were a great source of help for me to gain invaluable industrial experience.  \nI deeply appreciate the University of Sydney for providing financial support through the Engineering and IT Research Scholarship (EITRS) and the Postgraduate Research Support Scheme (PRSS) during my candidature, that helped me advance my research. I also appreciate the Australian Postgraduate Research Intern (APR.Intern) Program Scholarship that supported my research during my internship at Aurecon.  \nI would also like to thank my dear colleagues and friends, Dr Sina ","cbCainRc2GZpoBOj","https://ap.wps.com/l/cbCainRc2GZpoBOj","pdf",10788421,1,225,"English","en",105,"# Abstract\n## Infrastructure ageing and rehabilitation challenges\n## Multiscale machine learning framework\n# Authorship attribution and publications\n## Published materials in Chapters 3 and 4\n## Published materials in Chapter 5\n# Acknowledgements","[{\"question\":\"What problem does the thesis address regarding infrastructure ageing?\",\"answer\":\"Ageing inevitably reduces infrastructure serviceability, and extreme service environments accelerate long-term performance deterioration. Rehabilitation can be less efficient when ageing at smaller scales is overlooked in design.\"},{\"question\":\"How does the thesis use machine learning in its research approach?\",\"answer\":\"Machine learning is integrated with a series of empirical datasets and numerical modelling to analyse ageing impacts at multiple scales, improving efficiency and predictive capability under uncertainty.\"},{\"question\":\"What is the main contribution claimed by the developed frameworks?\",\"answer\":\"The results indicate that the proposed frameworks effectively contribute to modelling the long-term performance of infrastructure by addressing multi-scale ageing impacts.\"}]","Multiscale Machine Learning and Numerical Investigation of Ageing in Infrastructures - Doctor of Philosophy Thesis | PDF",1785672877,567,{"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},"multiscale-machine-learning-and-numerical-investigation-of-ageing-in-infrastructures-doctor-of-philosophy-thesis","",{"@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/multiscale-machine-learning-and-numerical-investigation-of-ageing-in-infrastructures-doctor-of-philosophy-thesis/116964/",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","2026-08-02",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},"What problem does the thesis address regarding infrastructure ageing?","Question",{"text":75,"@type":76},"Ageing inevitably reduces infrastructure serviceability, and extreme service environments accelerate long-term performance deterioration. Rehabilitation can be less efficient when ageing at smaller scales is overlooked in design.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the thesis use machine learning in its research approach?",{"text":80,"@type":76},"Machine learning is integrated with a series of empirical datasets and numerical modelling to analyse ageing impacts at multiple scales, improving efficiency and predictive capability under uncertainty.",{"name":82,"@type":73,"acceptedAnswer":83},"What is the main contribution claimed by the developed frameworks?",{"text":84,"@type":76},"The results indicate that the proposed frameworks effectively contribute to modelling the long-term performance of infrastructure by addressing multi-scale ageing impacts.","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"]