A machine learning framework for the quantification of the uncertainties associated with ab-initio based modeling of non-equilibrium flows

Simone Venturi, Maitreyee Sharma, Marco Panesi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish (US)
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
DOIs
StatePublished - Jan 1 2019
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: Jan 7 2019Jan 11 2019

Publication series

NameAIAA Scitech 2019 Forum

Conference

ConferenceAIAA Scitech Forum, 2019
CountryUnited States
CitySan Diego
Period1/7/191/11/19

ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

Venturi, S., Sharma, M., & Panesi, M. (2019). A machine learning framework for the quantification of the uncertainties associated with ab-initio based modeling of non-equilibrium flows. In AIAA Scitech 2019 Forum (AIAA Scitech 2019 Forum). American Institute of Aeronautics and Astronautics Inc, AIAA. https://doi.org/10.2514/6.2019-0788