[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125791-en":3,"doc-seo-125791-105":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},125791,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Trustworthy Machine Learning for Experimental Characterization of Ceramic Matrix Composites - Dissertation","Trustworthy machine learning techniques are developed for experimental characterization of ceramic matrix composites, focusing on damage-related insights derived from measurable signals. The work formalizes how machine learning can identify damage mechanisms and quantify performance through benchmarking across alternative modeling frameworks. Emphasis is placed on reliable, reproducible workflows grounded in acoustic emission experiments and in situ characterization, enabling robust interpretation of material behavior. The dissertation outlines methods, evaluations, and scientific context supported by publications and academic committee oversight.","UC Santa Barbara  \nUC Santa Barbara Electronic Theses and Dissertations  \nTitle  \nTrustworthy Machine Learning for Experimental Characterization of Ceramic Matrix Composites  \nPermalink  \n[https://escholarship.org/uc/item/5796x7mb](https://escholarship.org/uc/item/5796x7mb)  \nAuthor  \nMuir, Caelin  \nPublication Date  \n2023  \nPeer reviewed|Thesis/dissertation  \n[eScholarship.org](eScholarship.org) Powered by the California Digital Library  \nUniversity of California  \nUniversity of California  \nSanta Barbara  \nTrustworthy Machine Learning for Experimental Characterization of Ceramic Matrix Composites  \nA dissertation submitted in partial satisfaction  \nof the requirements for the degree  \nDoctor of Philosophy  \nin  \nMaterials  \nby  \nCaelin Muir  \nCommittee in charge:  \nProfessor Tresa M. Pollock, Committee Co-Chair  \nProfessor Samantha H. Daly, Committee Co-Chair  \nProfessor Matthew Begley  \nProfessor Ram Seshadri  \nProfessor Enoch Yeung  \nDecember 2023  \nThe Dissertation of Caelin Muir is approved.  \n\n| Professor Matthew Begley |\n| --- |\n| Professor Ram Seshadri |\n| Professor Enoch Yeung |\n| Professor Samantha H. Daly, Committee Co-Chair |\n\nProfessor Tresa M. Pollock, Committee Co-Chair  \nNovember 2023  \nTrustworthy Machine Learning for Experimental Characterization of Ceramic Matrix  \nComposites  \nCopyright © 2023  \nby  \nCaelin Muir  \nAcknowledgements  \nAlthough acknowledgements are traditionally limited to one page, I firmly believe the work contained in here would not have been possible without the personal and professional support of a large number of people. Because of this, limiting my acknowledgements to one page seems disingenuous. So, in the spirit of Lesley Gore, ”It’s my dissertation and I can acknowledge as many people as I want to”.  \nFirst are my advisors at UCSB: Professor Samantha Daly, Professor Tresa Pollock. Sam, your careful attention to detail, endless curiosity, and optimism in the face of setbacks is inspiring. I cannot overstate how important your mentorship is, and how grateful I am to have your advice to guide me through my scientific and personal challenges. Tresa, working with you and your group has been instrumental in maintaining broader perspectives and becoming a well-rounded investigator. Every time I talk with you I learn something valuable.  \nNext is the NASA Space Technology Research Fellowship program, for funding my studies and providing me access to research opportunities that would have otherwise been inaccessible. Moreover, I want to thank my NASA and Michigan advising team: Dr. Craig Smith, Doug Kiser, Dr. Amjad Almansour, and Dr. Kathy Sevener. Your weekly guidance and insight with respect to AE and CMCs has been invaluable for conducting my research. I always look forward to our weekly meetings and trivia questions.  \nTo my colleagues both past and present, your friendship and scientific support has shaped me for the better. In no particular order Bhavana Swaminathan, Jeff Rosin, Neal Brodnik, Jayden Plumb, Andrew Christison, Nick Tulshibagwale, Andrew Furst, and Abed Musaffar. Talking about science with you all is so much fun and always seems to lead to new ideas. Long days in the office, conferences, trivia nights, and weekends at campus point have been some of the best experiences in grad school because of you.  \nTo my dear friends both in and out of graduate school: John Garcia, Phillip Griffith, Austin Hardy, Aaron Engel, Mary Franitza, Michael Chin, Matthew Clawson, and everyone else un-named who if written down would truly make this section egregiously long, you all have been a constant source of joy for me. Between board games and raid nights, oceanside and mountainside adventures, I am better for having you in my life.  \nFinally to my parents, family, and the cat that won’t read this. Mom and Dad, none of this would be possible without your love and support. I don’t think I’ll ever be able to truly express how grateful I am for the opportunities you gave me. Christine and Chr","cbCaikvG5Ud4N6R3","https://ap.wps.com/l/cbCaikvG5Ud4N6R3","pdf",14971888,1,175,"English","en",105,"# Acknowledgements\n## Education\n## Publications","[{\"question\":\"What is the dissertation’s main research focus?\",\"answer\":\"It develops trustworthy machine learning methods for experimental characterization of ceramic matrix composites, especially for understanding damage mechanisms from experimental signals.\"},{\"question\":\"Which experimental data source is emphasized?\",\"answer\":\"The dissertation highlights acoustic emission as a key measurement used with machine learning to identify damage mechanisms.\"},{\"question\":\"How does the work evaluate machine learning approaches?\",\"answer\":\"It includes quantitative benchmarking of acoustic emission machine learning frameworks to compare performance for damage mechanism identification.\"}]","Trustworthy Machine Learning for Experimental Characterization of Ceramic Matrix Composites - Dissertation | PDF",1785901222,441,{"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},"trustworthy-machine-learning-for-experimental-characterization-of-ceramic-matrix-composites-dissertation","",{"@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/trustworthy-machine-learning-for-experimental-characterization-of-ceramic-matrix-composites-dissertation/125791/",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},"What is the dissertation’s main research focus?","Question",{"text":75,"@type":76},"It develops trustworthy machine learning methods for experimental characterization of ceramic matrix composites, especially for understanding damage mechanisms from experimental signals.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which experimental data source is emphasized?",{"text":80,"@type":76},"The dissertation highlights acoustic emission as a key measurement used with machine learning to identify damage mechanisms.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the work evaluate machine learning approaches?",{"text":84,"@type":76},"It includes quantitative benchmarking of acoustic emission machine learning frameworks to compare performance for damage mechanism identification.","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"]