{"652032":{"#nid":"652032","#data":{"type":"event","title":"PhD Defense by Nimisha Roy","body":[{"value":"\u003Cp\u003EPh.D. Thesis Defense Announcement\u003Cbr \/\u003E\r\nPore Space Architecture of Particulate Materials: Characterization and Applications\u003Cbr \/\u003E\r\nby\u003Cbr \/\u003E\r\nNimisha Roy\u003Cbr \/\u003E\r\nAdvisor:\u003Cbr \/\u003E\r\nDr. J. David Frost (CEE)\u003Cbr \/\u003E\r\nCommittee \u0026nbsp;Members:\u003Cbr \/\u003E\r\nDr. Umit Catalyurek (CSE), Dr. Elizabeth Cherry (CSE), Dr. Mahdi Roozbahani (CSE), Dr. Giaocchino\u0026nbsp;\u003Cbr \/\u003E\r\nViggiani (Univ. Grenoble Alpes)\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDate \u0026amp; Time: Monday, November 08, 2021, at 12:00 PM\u003Cbr \/\u003E\r\nLocation: \u0026nbsp;Sustainable Education Building (SEB), Room 122\/ Virtual via Zoom:\u003Cbr \/\u003E\r\nhttps:\/\/us02web.zoom.us\/j\/89856743663?pwd=dFR6UzVVWlRiMDBkZHhzWWdybXZBUT09\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cbr \/\u003E\r\nABSTRACT\u003Cbr \/\u003E\r\nThe \u0026nbsp; behavior \u0026nbsp; of \u0026nbsp; particulate \u0026nbsp; materials \u0026nbsp; is \u0026nbsp; of \u0026nbsp; overarching \u0026nbsp; importance \u0026nbsp; across \u0026nbsp;\u0026nbsp;\u003Cbr \/\u003E\r\nmultiple \u0026nbsp; science \u0026nbsp; and engineering \u0026nbsp;fields, \u0026nbsp;given \u0026nbsp;its \u0026nbsp;ubiquitous \u0026nbsp;presence \u0026nbsp;in \u0026nbsp;nature. \u0026nbsp;These\u0026nbsp;\u003Cbr \/\u003E\r\nmaterials \u0026nbsp;are \u0026nbsp;typically \u0026nbsp;composed of two phases, solids and voids, and are therefore described as\u0026nbsp;\u003Cbr \/\u003E\r\ncomplex multi-phase materials that exhibit non-linear responses when subjected to varying boundary\u0026nbsp;\u003Cbr \/\u003E\r\nconditions. While the attributes of the solid phase of particulate materials have been extensively\u0026nbsp;\u003Cbr \/\u003E\r\ncharacterized both experimentally and numerically, there \u0026nbsp;is \u0026nbsp;much \u0026nbsp;less \u0026nbsp;understanding \u0026nbsp;of \u0026nbsp;the \u0026nbsp;\u003Cbr \/\u003E\r\nattributes \u0026nbsp;and \u0026nbsp;behavior \u0026nbsp;of \u0026nbsp;the \u0026nbsp;pore \u0026nbsp;phase. \u0026nbsp;Furthermore, classical pore models incorporate\u0026nbsp;\u003Cbr \/\u003E\r\nidealized assumptions of feature geometries, limiting the accuracy of the \u0026nbsp; information \u0026nbsp; that \u0026nbsp;\u0026nbsp;\u003Cbr \/\u003E\r\ncan \u0026nbsp; be \u0026nbsp; obtained \u0026nbsp; from \u0026nbsp; these \u0026nbsp; features. \u0026nbsp; This \u0026nbsp; study \u0026nbsp; aims \u0026nbsp; to \u0026nbsp; advance \u0026nbsp; digital\u0026nbsp;\u003Cbr \/\u003E\r\ncharacterization \u0026nbsp;capabilities \u0026nbsp;for \u0026nbsp;particulate \u0026nbsp;microstructures, \u0026nbsp;focusing \u0026nbsp;on \u0026nbsp;characterizing \u0026nbsp;\u003Cbr \/\u003E\r\nthe \u0026nbsp;geometry and \u0026nbsp;topology \u0026nbsp;of \u0026nbsp;the \u0026nbsp;highly \u0026nbsp;complex \u0026nbsp;pore \u0026nbsp;space \u0026nbsp;within \u0026nbsp;packed \u0026nbsp;particle \u0026nbsp;\u003Cbr \/\u003E\r\nsystems. \u0026nbsp;A \u0026nbsp;new \u0026nbsp;and \u0026nbsp;robust computational \u0026nbsp;algorithm \u0026nbsp;is \u0026nbsp;proposed \u0026nbsp;that \u0026nbsp;quantifies \u0026nbsp;various \u0026nbsp;\u003Cbr \/\u003E\r\ncharacteristics \u0026nbsp;of \u0026nbsp;the \u0026nbsp;three-dimensional pore space of a given particulate media, which is\u0026nbsp;\u003Cbr \/\u003E\r\nunimpeded by assumptions of feature shapes or user dependency. The method is validated against\u0026nbsp;\u003Cbr \/\u003E\r\npackings of known pore geometries and implemented on real, \u0026nbsp;simulated, \u0026nbsp;and \u0026nbsp;fabricated \u0026nbsp;\u003Cbr \/\u003E\r\nmicrostructures \u0026nbsp;of \u0026nbsp;different \u0026nbsp;packing \u0026nbsp;densities, \u0026nbsp;particle \u0026nbsp;sizes, \u0026nbsp;shapes, gradation, and\u0026nbsp;\u003Cbr \/\u003E\r\nfollowing different specimen preparation techniques to measure its ability in capturing multi-scale\u0026nbsp;\u003Cbr \/\u003E\r\nresponses of microstructures.\u003Cbr \/\u003E\r\nThe study also leverages the emergence of machine learning techniques to scale up the findings to\u0026nbsp;\u003Cbr \/\u003E\r\nreal- world field-scale applications comprising particle-pore systems with 10\u0026#39;s of millions of\u0026nbsp;\u003Cbr \/\u003E\r\nparticles. In this regard, \u0026nbsp;the \u0026nbsp;use \u0026nbsp;of \u0026nbsp;deep \u0026nbsp;learning \u0026nbsp;tools \u0026nbsp;for \u0026nbsp;the \u0026nbsp;rapid \u0026nbsp;estimation \u0026nbsp;of \u0026nbsp;\u003Cbr \/\u003E\r\npore \u0026nbsp;space \u0026nbsp;properties \u0026nbsp;from \u0026nbsp;three- dimensional \u0026nbsp;images \u0026nbsp;is \u0026nbsp;sought. \u0026nbsp;Finally, \u0026nbsp; the \u0026nbsp;developed \u0026nbsp;\u003Cbr \/\u003E\r\ntechniques \u0026nbsp;and \u0026nbsp;tools \u0026nbsp;are \u0026nbsp;implemented \u0026nbsp;on \u0026nbsp;real granular \u0026nbsp;soils \u0026nbsp;to \u0026nbsp;strengthen \u0026nbsp;the \u0026nbsp;\u003Cbr \/\u003E\r\nunderstanding \u0026nbsp;of \u0026nbsp;macro-geomechanical \u0026nbsp;phenomena. \u0026nbsp;The \u0026nbsp;findings highlight \u0026nbsp;the \u0026nbsp;importance \u0026nbsp;of \u0026nbsp;\u003Cbr \/\u003E\r\naccounting \u0026nbsp;for \u0026nbsp;pore \u0026nbsp;space \u0026nbsp;properties \u0026nbsp;when \u0026nbsp;interpreting \u0026nbsp;the \u0026nbsp;macroscopic\u003Cbr \/\u003E\r\nresponse of granular assemblies subjected to external mechanical and precipitational loading.\u003Cbr \/\u003E\r\n\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Pore Space Architecture of Particulate Materials: Characterization and Applications"}],"uid":"27707","created_gmt":"2021-10-25 20:24:31","changed_gmt":"2021-10-25 20:24:31","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-11-08T12:00:00-05:00","event_time_end":"2021-11-08T14:00:00-05:00","event_time_end_last":"2021-11-08T14:00:00-05:00","gmt_time_start":"2021-11-08 17:00:00","gmt_time_end":"2021-11-08 19:00:00","gmt_time_end_last":"2021-11-08 19:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}