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Comparison of Numerical Methods for Uncertainty Quantification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F13%3A00208309" target="_blank" >RIV/68407700:21110/13:00208309 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Comparison of Numerical Methods for Uncertainty Quantification

  • Original language description

    An extensive development of efficient methods for stochastic modelling enabled uncertainty propagation through complex models. In this contribution, we present a review and comparison of several approaches such as stochastic Galerkin method, stochastic collocation method or polynomial regression based on Latin Hypercube Sampling. The advantages and disadvantages of these methods are demonstrated within the comparison with the traditional Monte Carlo method on a simple illustrative example of a frame structure.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JM - Structural engineering

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2013

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Engineering Mechanics 2013

  • ISBN

    978-80-87012-47-5

  • ISSN

    1805-8256

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    235-246

  • Publisher name

    Ústav termomechaniky AV ČR

  • Place of publication

    Praha

  • Event location

    Svratka

  • Event date

    May 13, 2013

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article