Efficient solution of the first passage problem by Path Integration for normal and Poissonian white noise

Mario Di Paola, Christian Bucher, Mario Di Paola

    Risultato della ricerca: Article

    11 Citazioni (Scopus)

    Abstract

    In this paper the first passage problem is examined for linear and nonlinear systems driven by Poissonian and normal white noise input. The problem is handled step-by-step accounting for the Markov properties of the response process and then by Chapman-Kolmogorov equation. The final formulation consists just of a sequence of matrix-vector multiplications giving the reliability density function at any time instant. Comparison with Monte Carlo simulation reveals the excellent accuracy of the proposed method.
    Lingua originaleEnglish
    pagine (da-a)121-128
    Numero di pagine8
    RivistaProbabilistic Engineering Mechanics
    Volume41
    Stato di pubblicazionePublished - 2015

    Fingerprint

    White noise
    white noise
    Probability density function
    Linear systems
    Nonlinear systems
    linear systems
    nonlinear systems
    multiplication
    formulations
    simulation
    Monte Carlo simulation

    All Science Journal Classification (ASJC) codes

    • Statistical and Nonlinear Physics
    • Mechanical Engineering
    • Ocean Engineering
    • Aerospace Engineering
    • Condensed Matter Physics
    • Nuclear Energy and Engineering
    • Civil and Structural Engineering

    Cita questo

    Efficient solution of the first passage problem by Path Integration for normal and Poissonian white noise. / Di Paola, Mario; Bucher, Christian; Di Paola, Mario.

    In: Probabilistic Engineering Mechanics, Vol. 41, 2015, pag. 121-128.

    Risultato della ricerca: Article

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    AU - Bucher, Christian

    AU - Di Paola, Mario

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    AB - In this paper the first passage problem is examined for linear and nonlinear systems driven by Poissonian and normal white noise input. The problem is handled step-by-step accounting for the Markov properties of the response process and then by Chapman-Kolmogorov equation. The final formulation consists just of a sequence of matrix-vector multiplications giving the reliability density function at any time instant. Comparison with Monte Carlo simulation reveals the excellent accuracy of the proposed method.

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