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UID:0-6347@eng.ufl.edu
DTSTART;TZID=America/New_York:20240118T124500
DTEND;TZID=America/New_York:20240118T134500
DTSTAMP:20251201T210348Z
URL:https://www.eng.ufl.edu/news-events/events/mae-seminar-engineering-des
 ign-innovation-in-the-data-era/
SUMMARY:MAE Seminar - Engineering Design Innovation in the Data Era
DESCRIPTION:MAE Seminar\nCo-Sponsor\nUF Space Mission Institute\nTitle\nEng
 ineering Design Innovation in the Data Era\nSpeaker\nVigor Yang\, Regents 
 Professor of Aerospace Engineering and Industrial and Systems Engineering\
 , Georgia Institute of Technology\nAbstract\nDesign is a strategic approac
 h with an executable plan for achieving specific objectives. Design innova
 tion empowers leaders to develop new solutions\, add values\, and envision
  new possibilities. At the highest level\, design drives and inspires the 
 advance of science and technology.\nThis lecture addresses data-enabled de
 sign of complex systems. Integration of data science with engineering scie
 nce will allow architectures in which fully integrated modeling and simula
 tions\, data analytics\, systems engineering\, and design methodology can 
 be exploited for the purposes of scientific discovery and the advancement 
 of technology in complex systems. As a specific example\, a new approach t
 o the combustion dynamics in propulsion engines is discussed. The effort i
 nvolves design of experiments\, high-fidelity simulation and experiment\, 
 reduced-order modeling\, uncertainty quantification\, machine learning\, a
 nd testing and certification. The developed paradigm enables efficient sur
 veys of the design space and identification of the key design attributes t
 hat dictate the system behavior. The unified approach starts with high fid
 elity modeling and simulations of combustion dynamics in engines using lar
 ge-eddy-simulation techniques. Reduced-basis models and emulation then lev
 erage the established database for physics-based data assimilation. Stocha
 stic-based extraction of physics from complex flowfields provides faithful
  and interpretable representations of the underlying mechanisms. Feature e
 xtraction techniques are incorporated into a spatio-temporal surrogate mod
 el built on machine-learning techniques such as Gaussian process (GP) regr
 ession. Combined with statistical methodologies and control theories\, the
 se techniques are integrated to allow for efficient design optimization an
 d uncertainty quantification. Finally\, a system-level model is developed 
 for effective assessment of system behaviors.\nThis example is specific to
  a propulsion engine problem\, but the general approach can be taken as a 
 model. Other complex systems\, such as aero vehicles\, could be addressed 
 following a similar paradigm. A big obstacle is the relative insularity of
  academic and research fields\, as well as the divide between engineers/sc
 ientists with domain expertise and data science. Looking forward\, a huge 
 opportunity exists for the community in bringing together researchers in t
 he engineering\, data science\, and computer modeling areas to collaborati
 vely develop large-scale design systems\nBiography\nVigor Yang is Professo
 r of Aerospace Engineering and Industrial and Systems Engineering at the G
 eorgia Institute of Technology. He was the William R. T. Oakes Professor a
 nd Chair of Georgia Tech’s School of Aerospace Engineering for a decade 
 (2009-2018). He has published 10 comprehensive volumes and numerous techni
 cal papers on combustion\, propulsion\, energetics\, and data science. He 
 was the recipient of the American Institute of Aeronautics and Astronautic
 s (AIAA) Air-Breathing Propulsion Award (2005)\, the Pendray Aerospace Lit
 erature Award (2008)\, the Propellants and Combustion Award (2009)\, and t
 he von Kármán Lectureship in Astronautics Award (2016). He was awarded t
 he Worcester Reed Warner Medal (2014) by the American Society of Mechanica
 l Engineers (ASME)\, and the Lifetime Achievement Award (2014) by the Join
 t U.S. Army\, Navy\, NASA\, and Air Force (JANNAF) Interagency Propulsion 
 Committee. He also received the Statistics in Physical Engineering Science
 s Award (2019) from the American Statistical Association (JSA).\nDr. Yang 
 was the editor-in-chief of the AIAA Journal of Propulsion and Power (2001-
 2009) and the JANNAF Journal of Propulsion and Energetics (2009-2012). He 
 is currently an editor of the Aerospace Book Series of the Cambridge Unive
 rsity Press (2010-). A member of the U.S. National Academy of Engineering\
 , an Academician of Academia Sinica\, and a foreign member of the Chinese 
 Academy of Engineering and the Indian National Academy of Engineering\, Dr
 . Yang is a fellow of the AIAA\, ASME\, Royal Aeronautical Society\, and C
 ombustion Institute. He was a vice president and a member of the executive
  committee of the AIAA (2012-2015).\nMAE Faculty Host\nJacob Chung
CATEGORIES:Seminars
LOCATION:Malachowsky Hall\, NVIDIA Auditorium\, 1889 Museum Road\, Gainesvi
 lle\, FL\, 32611\, United States
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1889 Museum Road\, Gainesvi
 lle\, FL\, 32611\, United States;X-APPLE-RADIUS=100;X-TITLE=Malachowsky Ha
 ll\, NVIDIA Auditorium:geo:0,0
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