{"686513":{"#nid":"686513","#data":{"type":"event","title":"PhD Defense by Tzu-Jung Lee","body":[{"value":"\u003Cp\u003ETitle:\u003C\/p\u003E\u003Cp\u003EPhysics-Guided Airfoil Optimization Using Neural Network with Locally Converging Input (NNLCI)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDate:\u003C\/p\u003E\u003Cp\u003ETuesday, November 25, 2025\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ETime:\u003C\/p\u003E\u003Cp\u003E10:00 a.m. \u2013 12:00 p.m. ET\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ELocation:\u003C\/p\u003E\u003Cp\u003EMK 325, Guggenheim Building, and Microsoft Teams (\u003Ca href=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_NzNiNjlmZDMtYTA2Zi00NzcwLThhY2YtNjUzZWU5ZDEzMGUy%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%227575b221-afee-4070-8506-4cf2cd68f2cd%22%7d\u0022 target=\u0022_blank\u0022 title=\u0022https:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_NzNiNjlmZDMtYTA2Zi00NzcwLThhY2YtNjUzZWU5ZDEzMGUy%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%227575b221-afee-4070-8506-4cf2cd68f2cd%22%7d\u0022\u003Ehttps:\/\/teams.microsoft.com\/l\/meetup-join\/19%3ameeting_NzNiNjlmZDMtYTA2Zi00NzcwLThhY2YtNjUzZWU5ZDEzMGUy%40thread.v2\/0?context=%7b%22Tid%22%3a%22482198bb-ae7b-4b25-8b7a-6d7f32faa083%22%2c%22Oid%22%3a%227575b221-afee-4070-8506-4cf2cd68f2cd%22%7d\u003C\/a\u003E)\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ETzu-Jung Lee\u003C\/p\u003E\u003Cp\u003EMachine Learning Ph.D. Candidate\u003C\/p\u003E\u003Cp\u003EDaniel Guggenheim School of Aerospace Engineering\u003C\/p\u003E\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003ECommittee\u003C\/p\u003E\u003Cp\u003EDr. Vigor Yang (Advisor) - Daniel Guggenheim\u0026nbsp;School of Aerospace Engineering, Georgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Yingjie Liu - School of Mathematics, Georgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Yongxin Chen - Daniel Guggenheim\u0026nbsp;School of Aerospace Engineering, Georgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Lakshmi Sankar - Daniel Guggenheim\u0026nbsp;School of Aerospace Engineering, Georgia Institute of Technology\u003C\/p\u003E\u003Cp\u003EDr. Robert Funk - Principal Research Engineer, Aerospace, Transportation and Advanced Systems Laboratory (ATAS), Georgia Tech Research Institute\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EAbstract\u003C\/p\u003E\u003Cp\u003EThis dissertation develops a physics-guided framework for airfoil optimization using a Neural Network with Locally Converging Input (NNLCI) in a PARSEC parameter space. The NNLCI surrogate reconstructs high-fidelity flow fields from local multi-fidelity patches, while preserving shock structures and near-wall behavior that are critical for accurate lift and drag prediction. From the reconstructed fields, we recover surface pressure and viscous traction, and integrate them to obtain lift and drag, which are validated against high-fidelity CFD force integrals. The framework then performs constrained drag minimization at fixed lift using Differential Evolution, enforcing geometric feasibility and a lift constraint while relying mainly on low-fidelity evaluations with periodic high-fidelity checks.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPhysics-Guided Airfoil Optimization Using Neural Network with Locally Converging Input (NNLCI)\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Physics-Guided Airfoil Optimization Using Neural Network with Locally Converging Input (NNLCI)"}],"uid":"27707","created_gmt":"2025-11-18 17:01:23","changed_gmt":"2025-11-18 17:01:23","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-11-25T10:00:00-05:00","event_time_end":"2025-11-25T12:00:00-05:00","event_time_end_last":"2025-11-25T12:00:00-05:00","gmt_time_start":"2025-11-25 15:00:00","gmt_time_end":"2025-11-25 17:00:00","gmt_time_end_last":"2025-11-25 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"MK 325, Guggenheim Building, and Microsoft Teams ","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":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}