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Convergence and error analysis of compressible fluid flows with random data: Monte Carlo method

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985840%3A_____%2F22%3A00569928" target="_blank" >RIV/67985840:_____/22:00569928 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1142/S0218202522500671" target="_blank" >https://doi.org/10.1142/S0218202522500671</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1142/S0218202522500671" target="_blank" >10.1142/S0218202522500671</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Convergence and error analysis of compressible fluid flows with random data: Monte Carlo method

  • Original language description

    The goal of this paper is to study convergence and error estimates of the Monte Carlo method for the Navier-Stokes equations with random data. To discretize in space and time, the Monte Carlo method is combined with a suitable deterministic discretization scheme, such as a finite volume (FV) method. We assume that the initial data, force and the viscosity coefficients are random variables and study both the statistical convergence rates as well as the approximation errors. Since the compressible Navier-Stokes equations are not known to be uniquely solvable in the class of global weak solutions, we cannot apply pathwise arguments to analyze the random Navier-Stokes equations. Instead, we have to apply intrinsic stochastic compactness arguments via the Skorokhod representation theorem and the Gyöngy-Krylov method. Assuming that the numerical solutions are bounded in probability, we prove that the Monte Carlo FV method converges to a statistical strong solution. The convergence rates are discussed as well. Numerical experiments illustrate theoretical results.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10101 - Pure mathematics

Result continuities

  • Project

    <a href="/en/project/GA21-02411S" target="_blank" >GA21-02411S: Solving ill posed problems in the dynamics of compressible fluids</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Mathematical Models and Methods in Applied Sciences

  • ISSN

    0218-2025

  • e-ISSN

    1793-6314

  • Volume of the periodical

    32

  • Issue of the periodical within the volume

    14

  • Country of publishing house

    SG - SINGAPORE

  • Number of pages

    39

  • Pages from-to

    2887-2925

  • UT code for WoS article

    000900774200002

  • EID of the result in the Scopus database

    2-s2.0-85144563178