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    Iterative Most Probable Point Search Method for Problems With a Mixture of Random and Interval Variables 

    Source: Journal of Mechanical Design:;2020:;volume( 142 ):;issue: 007:;page 071703-1
    Author(s): Cho, Hyunkyoo; Choi, Kyung K.; Shin, Jaekwan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: To represent input variability accurately, an input distribution model for random variables should be constructed using many data. However, for certain input variables, engineers may have only their intervals, which represent ...
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    Special Issue on Sensitivity Analysis and Uncertainty Quantification 

    Source: Journal of Computational and Nonlinear Dynamics:;2018:;volume( 013 ):;issue: 003:;page 38001
    Author(s): Serban, Radu; Wang, Yan; Jayakumar, Paramsothy; Choi, Kyung K.
    Publisher: The American Society of Mechanical Engineers (ASME)
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    Special Issue: Sensitivity Analysis and Uncertainty Quantification 

    Source: Journal of Computational and Nonlinear Dynamics:;2019:;volume( 014 ):;issue: 002:;page 20301
    Author(s): Serban, Radu; Wang, Yan; Choi, Kyung K.; Jayakumar, Paramsothy
    Publisher: The American Society of Mechanical Engineers (ASME)
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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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