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    Treating Epistemic Uncertainty Using Bootstrapping Selection of Input Distribution Model for Confidence-Based Reliability Assessment 

    Source: Journal of Mechanical Design:;2019:;volume( 141 ):;issue: 003:;page 31402
    Author(s): Moon, Min-Yeong; Choi, K. K.; Gaul, Nicholas; Lamb, David
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Accurately predicting the reliability of a physical system under aleatory uncertainty requires a very large number of physical output testing. Alternatively, a simulation-based method can be used, but it would involve ...
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    Reliability-Based Design Optimization Using Confidence-Based Model Validation for Insufficient Experimental Data 

    Source: Journal of Mechanical Design:;2017:;volume( 139 ):;issue: 003:;page 31404
    Author(s): Moon, Min-Yeong; Choi, K. K.; Cho, Hyunkyoo; Gaul, Nicholas; Lamb, David; Gorsich, David
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The conventional reliability-based design optimization (RBDO) methods assume that a simulation model is able to represent the real physics accurately. However, this assumption may not always hold as the simulation model ...
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    Framework of Reliability-Based Stochastic Mobility Map for Next Generation NATO Reference Mobility Model 

    Source: Journal of Computational and Nonlinear Dynamics:;2019:;volume( 014 ):;issue: 002:;page 21012
    Author(s): Choi, K. K.; Jayakumar, Paramsothy; Funk, Matthew; Gaul, Nicholas; Wasfy, Tamer M.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: A framework for generation of reliability-based stochastic off-road mobility maps is developed to support the next generation NATO reference mobility model (NG-NRMM) using full stochastic knowledge of terrain properties ...
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    Confidence-Based Uncertainty Quantification and Model Validation for Simulations of High-Speed Impact Problems 

    Source: Journal of Verification, Validation and Uncertainty Quantification:;2020:;volume( 005 ):;issue: 002:;page 021005-1
    Author(s): Moon, Min-Yeong; Sen, Oishik; Rai, Nirmal Kumar; Gaul, Nicholas J.; Choi, Kyung K.; Udaykumar, H. S.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Validation exercises for computational models of materials under impact must contend with sparse experimental data as well as with uncertainties due to microstructural stochasticity and variabilities in thermomechanical ...
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