Technical Papers
Mar 24, 2022

Change of Measure Enhanced Near-Exact Euler–Maruyama Scheme for the Solution to Nonlinear Stochastic Dynamical Systems

Publication: Journal of Engineering Mechanics
Volume 148, Issue 6

Abstract

The present study utilizes the Girsanov transformation-based framework for solving a nonlinear stochastic dynamical system in an efficient way in comparison with other available approximate methods. In this approach, rejection sampling is formulated to evaluate the Radon–Nikodym derivative arising from the change of measure due to Girsanov transformation. Rejection sampling is applied on the Euler–Maruyama approximated sample paths, which draw exact paths independent of the diffusion dynamics of the underlying dynamical system. The efficacy of the proposed framework was ensured using more accurate numerical as well as exact nonlinear methods. Finally, nonlinear applied test problems were considered to confirm the theoretical results. The test problems demonstrated that the proposed exact formulation of the Euler–Maruyama provides an almost exact approximation to both the displacement and velocity states of a second-order nonlinear dynamical system.

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Data Availability Statement

All data, models, or source code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

T. Tripura acknowledges the financial support received from the Ministry of Human Resource Development (MHRD), India, in form of the Prime Minister’s Research Fellows (PMRF) scholarship. S. Chakraborty acknowledges the financial support received from IIT Delhi in the form of a seed grant.

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Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 148Issue 6June 2022

History

Received: Nov 8, 2021
Accepted: Jan 17, 2022
Published online: Mar 24, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 24, 2022

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Ph.D. Scholar, Dept. of Applied Mechanics, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India. ORCID: https://orcid.org/0000-0003-0363-2663
Mohammad Imran
M.Tech Scholar, Dept. of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam 781039, India.
Budhaditya Hazra
Associate Professor, Dept. of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, Assam 781039, India.
Assistant Professor, Dept. of Applied Mechanics, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India; Assistant Professor (Joint Appointment), School of Artificial Intelligence, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India (corresponding author). ORCID: https://orcid.org/0000-0003-2383-2603. Email: [email protected]

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  • Simulating systems of Itô SDEs with split-step $ (\alpha, \beta) $-Milstein scheme, AIMS Mathematics, 10.3934/math.2023133, 8, 2, (2576-2590), (2023).

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