{"647164":{"#nid":"647164","#data":{"type":"event","title":"PhD Proposal by Zhenyu Gao","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EZhenyu Gao\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Cem\u003E(Advisor: Prof. Dimitri N. Mavris)\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003Ewill propose a doctoral thesis entitled\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ERepresentative Data and Models for Complex Aerospace Systems Analysis\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cem\u003EOn\u003C\/em\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EFriday, May 14 at 10:00 a.m. (EDT)\u003Cbr \/\u003E\r\nOnline via Bluejeans\u003C\/strong\u003E\u003Cbr \/\u003E\r\n\u003Ca href=\u0022https:\/\/bluejeans.com\/696230282\u0022\u003Ehttps:\/\/bluejeans.com\/696230282\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003Cbr \/\u003E\r\nData-driven analysis of complex aerospace systems often involves two kernel elements: large amounts of real-world operations data, and a diverse ensemble of models. Nevertheless, in reality due to constraints in computational cost or resources, practitioners can face the inability to process the entire large data set or build a complete model portfolio when performing simulation and systems analysis. In this dissertation we propose the use of \u0026ldquo;representatives\u0026rdquo;, which is the opposite of the entire population, to conduct efficient and accurate systems analysis. The proposed methods utilize data mining and high-dimensional data analysis to select a small proportion of representative data and models from the population and apply them to tackle challenges in several application cases in aviation environmental impact modeling.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe first part of this dissertation addresses the challenge of representative data. Specifically, we consider the scenario of an extreme numerosity reduction on large data sets while still maintaining the same data distribution. We propose Probabilistic REpresentatives Mining (PREM), an efficient data mining approach to obtain probabilistically representative small data sets. PREM employs a balanced clustering set-up which avoids over-sampling and under-sampling phenomena produced by traditional clustering algorithms and a multi-stage computing strategy which enables the method to be scalable on massive data sets.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThe second part proposes the concept of representative models, which tackles the challenge of insufficient resources in building Aircraft Noise and Performance (ANP) models. In the first scenario, we consider the problem of selecting a representative model portfolio at each permitted size level to sufficiently cover the entire population space with the desirable maximum distortion guarantee. In the second scenario, we introduce the use of mixture models to represent and model ``unconventional groups\u0026#39;\u0026#39; in the population, where the model substitution is compromised by a lack of coverage. Mixture model relies on the identification of complementary candidate models and uses a multi-model approach to outperform any candidate model alone.\u003C\/p\u003E\r\n\r\n\u003Cp\u003EOverall the dissertation is expected to make contributions to both analytical methodologies for certain scenes and the solutions to specific challenges in aviation environmental impact modeling.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cul\u003E\r\n\t\u003Cli\u003EProf. Dimitri N. Mavris \u0026ndash; School of Aerospace Engineering (advisor)\u003C\/li\u003E\r\n\t\u003Cli\u003EProf. Koki Ho \u0026ndash; School of Aerospace Engineering\u003C\/li\u003E\r\n\t\u003Cli\u003EProf. Graeme J. Kennedy \u0026ndash; School of Aerospace Engineering\u003C\/li\u003E\r\n\t\u003Cli\u003EProf. Yao Xie \u0026ndash; School of Industrial and Systems Engineering\u003C\/li\u003E\r\n\t\u003Cli\u003EDr. Tejas G. Puranik \u0026ndash; School of Aerospace Engineering\u003C\/li\u003E\r\n\u003C\/ul\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Representative Data and Models for Complex Aerospace Systems Analysis"}],"uid":"27707","created_gmt":"2021-05-04 19:45:40","changed_gmt":"2021-05-04 19:45:40","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2021-05-14T11:00:00-04:00","event_time_end":"2021-05-14T13:00:00-04:00","event_time_end_last":"2021-05-14T13:00:00-04:00","gmt_time_start":"2021-05-14 15:00:00","gmt_time_end":"2021-05-14 17:00:00","gmt_time_end_last":"2021-05-14 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"102851","name":"Phd proposal"}],"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":""}}}