2011International Journal for Uncertainty QuantificationOpen access

POLYNOMIAL CHAOS FOR LINEAR DIFFERENTIAL ALGEBRAIC EQUATIONS WITH RANDOM PARAMETERS

Roland Pulch

Open full text 32 citations

Abstract

Technical applications are often modeled by systems of differential algebraic equations.The systems may include parameters that involve some uncertainties.We arrange a stochastic model for uncertainty quantification in the case of linear systems of differential algebraic equations.The generalized polynomial chaos yields a larger linear system of differential algebraic equations, whose solution represents an approximation of the corresponding random process.We prove sufficient conditions such that the larger system inherits the index of the original system.Furthermore, the choice of consistent initial values is discussed.Finally, we present numerical simulations of this stochastic model.

Open-access reader

About this research paper

What this paper is about

Technical applications are often modeled by systems of differential algebraic equations.The systems may include parameters that involve some uncertainties.We arrange a stochastic model for uncertainty quantification in the case of linear systems of differential algebraic equations.The generalized polynomial chaos yields a larger linear system of differential algebraic equations, whose solution represents an approximation of the corresponding random process.We prove sufficient conditions such that the larger system inherits the index of the original system.Furthermore, the choice of consistent initial values is discussed.Finally, we present numerical simulations of this stochastic model.

Why it matters

OpenAlex reports 32 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Technical applications are often modeled by systems of differential algebraic equations.The systems may include parameters that involve some uncertainties.We arrange a stochastic model for uncertainty quantification in the case of linear systems of differential algebraic equations.The generalized polynomial chaos yields a larger linear system of differential algebraic equations, whose solution represents an approximation of the corresponding random process.We prove sufficient conditions such that the larger system inherits the index of the original system.Furthermore, the choice of consistent initial values is discussed.Finally, we present numerical simulations of this stochastic model.

Key concepts: Polynomial chaos, Differential algebraic equation, Applied mathematics, Mathematics, Polynomial, Algebraic equation, Stochastic differential equation, Differential algebraic geometry

Related papers

Back to paper searchBrowse research topicsOriginal source
POLYNOMIAL CHAOS FOR LINEAR DIFFERENTIAL ALGEBRAIC EQUATIONS WITH RANDOM PARAMETERS — Research Paper | ScholarLens