Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation

Journal Article · 07 September 2017 · ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems. Part B. Mechanical Engineering

DOI: https://doi.org/10.1115/1.4037447 · OSTI ID:1399512

Wang, Yan ^[1]; Swiler, Laura ^[2]

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1. Woodruff School of Mechanical Engineering,Georgia Institute of Technology,Atlanta, GA 30332e-mail: [e-mail]
2. Optimization and Uncertainty Quantification Department,Sandia National Laboratories,Albuquerque, NM 87185e-mail: [e-mail]

The importance of uncertainty has been recognized in various modeling, simulation, and analysis applications, where inherent assumptions and simplifications affect the accuracy of model predictions for physical phenomena. As model predictions are now heavily relied upon for simulation-based system design, which includes new materials, vehicles, mechanical and civil structures, and even new drugs, wrong model predictions could potentially cause catastrophic consequences. Therefore, uncertainty and associated risks due to model errors should be quantified to support robust systems engineering.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• Grant/Contract Number: AC04-94AL85000
• OSTI ID: 1399512
• Report Number(s): SAND--2017-7361J; 655296
• Journal Information: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems. Part B. Mechanical Engineering, Journal Name: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems. Part B. Mechanical Engineering Journal Issue: 1 Vol. 4; ISSN 2332-9017
• Publisher: American Society of Mechanical EngineersCopyright Statement
• Country of Publication: United States
• Language: English