Using machine learning to understand and mitigate model form uncertainty in turbulence models

Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015

Volumn , Issue , 2016, Pages 813-818

  Ling, Julia ^a  

^a SANDIA NATIONAL LABORATORIES   (United States)

Author keywords

Machine learning; Rule extraction; Turbulence modeling

Indexed keywords

ARTIFICIAL INTELLIGENCE; COST ENGINEERING; DIELECTRIC PROPERTIES; EXTRACTION; TURBULENCE MODELS; UNCERTAINTY ANALYSIS;

COMPUTATIONAL COSTS; CRITICAL CHALLENGES; HIGH PERFORMANCE COMPUTING; LINEAR CORRECTIONS; MODEL CORRECTIONS; MODEL FORM UNCERTAINTIES; RULE EXTRACTION; TURBULENT TRANSPORTS;

LEARNING SYSTEMS;

EID: 84969626057     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2015.38     Document Type: Conference Paper

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