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    Advanced Dimension-Adaptive Sparse Grid Integration Method for Structural Reliability Analysis

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 003::page 04021031-1
    Author:
    Xiaohui Yu
    ,
    Zihan He
    ,
    Chao-Lie Ning
    DOI: 10.1061/AJRUA6.0001148
    Publisher: ASCE
    Abstract: The conventional sparse grid (SG) integration method treats all considered random variables equally for the numerical integration of performance functions. The dimension-equal treatment inevitably causes a considerable demand of computation devoted to unimportant variables. To overcome this shortcoming, an advanced dimension-adaptive sparse grid (ADASG) integration method is proposed by introducing a numerical indicator quantifying the importance levels of tensor products of difference quadrature formulas. By achieving a target number of function evaluations, only several important tensor products of difference quadrature formulas are retained while the unimportant ones are removed. The proposed ADASG integration method is firstly employed to estimate the first four moments of performance functions. The estimated moments are then applied to structural reliability analysis by generating the probability density function of performance functions using the maximum entropy method. The advantage of the proposed ADASG integration method is demonstrated over four examples. The reliability index calculated by the proposed ADASG integration method shows favorable consistency to that obtained by the direct Monte Carlo simulation. Compared with conventional SG integration methods, the proposed ADASG integration method exhibits a better performance in terms of both accuracy and efficiency.
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      Advanced Dimension-Adaptive Sparse Grid Integration Method for Structural Reliability Analysis

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4270713
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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering

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    contributor authorXiaohui Yu
    contributor authorZihan He
    contributor authorChao-Lie Ning
    date accessioned2022-01-31T23:59:50Z
    date available2022-01-31T23:59:50Z
    date issued9/1/2021
    identifier otherAJRUA6.0001148.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4270713
    description abstractThe conventional sparse grid (SG) integration method treats all considered random variables equally for the numerical integration of performance functions. The dimension-equal treatment inevitably causes a considerable demand of computation devoted to unimportant variables. To overcome this shortcoming, an advanced dimension-adaptive sparse grid (ADASG) integration method is proposed by introducing a numerical indicator quantifying the importance levels of tensor products of difference quadrature formulas. By achieving a target number of function evaluations, only several important tensor products of difference quadrature formulas are retained while the unimportant ones are removed. The proposed ADASG integration method is firstly employed to estimate the first four moments of performance functions. The estimated moments are then applied to structural reliability analysis by generating the probability density function of performance functions using the maximum entropy method. The advantage of the proposed ADASG integration method is demonstrated over four examples. The reliability index calculated by the proposed ADASG integration method shows favorable consistency to that obtained by the direct Monte Carlo simulation. Compared with conventional SG integration methods, the proposed ADASG integration method exhibits a better performance in terms of both accuracy and efficiency.
    publisherASCE
    titleAdvanced Dimension-Adaptive Sparse Grid Integration Method for Structural Reliability Analysis
    typeJournal Paper
    journal volume7
    journal issue3
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
    identifier doi10.1061/AJRUA6.0001148
    journal fristpage04021031-1
    journal lastpage04021031-16
    page16
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering:;2021:;Volume ( 007 ):;issue: 003
    contenttypeFulltext
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