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    Special Section on Nonprobabilistic Approaches for Handling Uncertainty in Engineering

    Source: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2015:;volume( 001 ):;issue: 003::page 30201
    Author:
    Sofi, Alba
    ,
    Muscolino, Giuseppe
    ,
    Elishakoff, Isaac
    DOI: 10.1115/1.4030822
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Design processes involve several sources of uncertainties in loads and/or parameters that may seriously affect the estimates of performance and reliability of engineering systems. The selection of an appropriate mathematical representation of uncertainty that is based on available information is crucial to obtain realistic results. It is widely recognized that the credibility of traditional probabilistic methods is unquestionable when large data sets are available; when only limited data are available to define the probabilistic distribution of nondeterministic quantities, one may want to supplement probabilistic analysis by some other techniques. This consideration has aroused the evergrowing interest of researchers toward alternative uncertainty models based on nonprobabilistic concepts.
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      Special Section on Nonprobabilistic Approaches for Handling Uncertainty in Engineering

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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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    contributor authorSofi, Alba
    contributor authorMuscolino, Giuseppe
    contributor authorElishakoff, Isaac
    date accessioned2017-05-09T01:14:26Z
    date available2017-05-09T01:14:26Z
    date issued2015
    identifier issn2332-9017
    identifier otherRISK_1_3_030201.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/156874
    description abstractDesign processes involve several sources of uncertainties in loads and/or parameters that may seriously affect the estimates of performance and reliability of engineering systems. The selection of an appropriate mathematical representation of uncertainty that is based on available information is crucial to obtain realistic results. It is widely recognized that the credibility of traditional probabilistic methods is unquestionable when large data sets are available; when only limited data are available to define the probabilistic distribution of nondeterministic quantities, one may want to supplement probabilistic analysis by some other techniques. This consideration has aroused the evergrowing interest of researchers toward alternative uncertainty models based on nonprobabilistic concepts.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleSpecial Section on Nonprobabilistic Approaches for Handling Uncertainty in Engineering
    typeJournal Paper
    journal volume1
    journal issue3
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
    identifier doi10.1115/1.4030822
    journal fristpage30201
    journal lastpage30201
    treeASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering:;2015:;volume( 001 ):;issue: 003
    contenttypeFulltext
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