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    An Efficient First-Principles Saddle Point Searching Method Based on Distributed Kriging Metamodels

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2018:;volume( 004 ):;issue:001::page 11006
    Author:
    Tran, Anh
    ,
    He, Lijuan
    ,
    Wang, Yan
    DOI: 10.1115/1.4037459
    Publisher: The American Society of Mechanical Engineers (ASME)
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      An Efficient First-Principles Saddle Point Searching Method Based on Distributed Kriging Metamodels

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4252642
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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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    contributor authorTran, Anh
    contributor authorHe, Lijuan
    contributor authorWang, Yan
    date accessioned2019-02-28T11:05:52Z
    date available2019-02-28T11:05:52Z
    date copyright9/7/2017 12:00:00 AM
    date issued2018
    identifier issn2332-9017
    identifier otherrisk_004_01_011006.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4252642
    publisherThe American Society of Mechanical Engineers (ASME)
    titleAn Efficient First-Principles Saddle Point Searching Method Based on Distributed Kriging Metamodels
    typeJournal Paper
    journal volume4
    journal issue1
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
    identifier doi10.1115/1.4037459
    journal fristpage11006
    journal lastpage011006-8;Searching for local minima, saddle points, and minimum energy paths (MEPs) on the potential energy surface (PES) is challenging in computational materials science because of the complexity of PES in high-dimensional space and the numerical approx
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2018:;volume( 004 ):;issue:001
    contenttypeFulltext
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