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UID:0-8339@eng.ufl.edu
DTSTART;TZID=America/New_York:20260323T100000
DTEND;TZID=America/New_York:20260323T110000
DTSTAMP:20260313T125105Z
URL:https://www.eng.ufl.edu/news-events/events/computational-design-of-int
 elligent-material-and-structural-systems-from-topology-optimization-to-ind
 ustriali/
SUMMARY:Computational Design of Intelligent Material and Structural Systems
 : From Topology Optimization to Industriali
DESCRIPTION:Computational Design of Intelligent Material and Structural Sys
 tems: From Topology Optimization to Industrialized Construction\nSpeaker: 
 Chao Wang\nPh.D. Candidate (ABD) in Civil Engineering\, University of Illi
 nois Urbana-Champaign\, Illinois\, USA\nIndustrialized construction is tra
 nsforming the building environment\, demanding structural design methodolo
 gies that integrate performance\,\nmanufacturability\, and automation for 
 prefabricated systems. This talk presents a unified computational design f
 ramework focusing\non topology optimization for intelligent material and s
 tructural systems. We present physics-based inverse design methods combine
 d with\nnonlinear mechanics modeling for designing materials with targeted
  mechanical responses. This method can be integrated with\nmanufacturing c
 onsideration\, including path-planning strategies for additive manufacturi
 ng\, providing a direct pipeline from computational\ndesign to fabrication
  for industrialized construction. The effectiveness of the optimized desig
 ns has been demonstrated in applications such as\nsoft robotics\, biomedic
 al devices\, and resilient structures. This design framework opens new opp
 ortunities for industrialized\nconstruction engineering. Topology optimiza
 tion combined with robotic additive manufacturing enables automated design
  of large-scale 3Dprinted\nstructures\, where structural performance and p
 rintability are considered simultaneously. Similar ideas extend to modular
  and\nprefabricated systems\, where structural design can be coupled with 
 transportation and assembly constraints. In addition\, integrating AI with
 \ntopology optimization\, through data-driven surrogate models or physics-
 informed neural networks\, offers new approaches to improve\nthe generalit
 y of designing complex structural systems.
CATEGORIES:Faculty Search,Seminars
LOCATION:Weil Hall Room 365\, 1949 Stadium Road\, Gainesville\, FL\, 32611\
 , United States
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 ille\, FL\, 32611\, United States;X-APPLE-RADIUS=100;X-TITLE=Weil Hall Roo
 m 365:geo:0,0
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