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    A Polynomial-Chaos-Based Multifidelity Approach to the Efficient Uncertainty Quantification of Online Simulations of Automotive Propulsion Systems 

    Source: Journal of Computational and Nonlinear Dynamics:;2022:;volume( 017 ):;issue: 005:;page 51012-1
    Author(s): Yang, Hang; Gorodetsky, Alex; Fujii, Yuji; Wang, K. W.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: As a result of the increasing system complexity and more strict performance requirements, intelligent and robust decision-making and control capabilities are of great importance for future automotive propulsion systems. ...
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    Bounds on the Poisson’s Ratios of Diamond-Like Structures 

    Source: Journal of Applied Mechanics:;2023:;volume( 090 ):;issue: 010:;page 101009-1
    Author(s): Liu, Yi; Zhang, Chunbo; Yang, Hang; Gao, Enlai
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Poisson’s ratios of diamond-like structures, such as cubic C, Si, and Ge, have been widely explored because of their potential applications in solid-state devices. However, the theoretical bounds on the Poisson’s ratios ...
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    Exploring Elastoplastic Constitutive Law of Microstructured Materials Through Artificial Neural Network—A Mechanistic-Based Data-Driven Approach 

    Source: Journal of Applied Mechanics:;2020:;volume( 087 ):;issue: 009:;page 091005-1
    Author(s): Yang, Hang; Qiu, Hai; Xiang, Qian; Tang, Shan; Guo, Xu
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this paper, a data-driven approach for constructing elastoplastic constitutive law of microstructured materials is proposed by combining the insights from plasticity theory and the tools of artificial intelligence (i.e., ...
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