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    A New Uncertainty Analysis-Based Framework for Data-Driven Computational Mechanics 

    Source: Journal of Applied Mechanics:;2021:;volume( 088 ):;issue: 011:;page 0111003-1
    Author(s): Guo, Xu; Du, Zongliang; Liu, Chang; Tang, Shan
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In this article, a new uncertainty analysis-based framework for data-driven computational mechanics (DDCM) is established. Compared with its practical classical counterpart, the distinctive feature of this framework is ...
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    Tensile Stress Driven Surface Wrinkles on Cylindrical Core–Shell Soft Solids 

    Source: Journal of Applied Mechanics:;2015:;volume( 082 ):;issue: 012:;page 121002
    Author(s): Tang, Shan; Li, Ying; Kam Liu, Wing; Hu, Ning; He Peng, Xiang; Guo, Zaoyang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: It has been experimentally observed that wrinkles formed on the surface of electrospun polymer nanofibers when they are under uniaxial tension (Appl. Phys. Lett., 91, p. 151901 (2007)). Molecular dynamics (MD) simulations, ...
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    Variable Chain Confinement in Polymers With Nanosized Pores and Its Impact on Instability 

    Source: Journal of Applied Mechanics:;2015:;volume( 082 ):;issue: 010:;page 101001
    Author(s): Tang, Shan; Greene, Steven M.; Liu, Wing Kam; Peng, Xiang He; Guo, Zaoyang
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Recent experiments and molecular dynamics simulations have proven that polymer chains are less confined in layers near the free surfaces of submicronnanosized pores. A recent model has incorporated this observed variable ...
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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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