2024A-OS2-2 Bayesian Estimation of Roll Damping Based on Onboard Measurements

Tomoki Takami; Masaru Kitahara; Atsuo Maki; Leo Dostal

doi:10.14856/conf.39.0_65

DOI https://doi.org/10.14856/conf.39.0_65

Conference information

Host: The Japan Society of Naval Architects and Ocean Engineers

Name : 2024 Annual Autumn Meeting

Number : 39

Location : Yokohama City Port Opening Memorial Hall

Date : November 21, 2024 - November 22, 2024

2024A-OS2-2 Bayesian Estimation of Roll Damping Based on Onboard Measurements

Tomoki Takami, Masaru Kitahara, Atsuo Maki, Leo Dostal

Author information

Keywords: Transitional Markov chain Monte Carlo, Nonlinear Roll Motion, One Degree-offreedom Model, Nonlinear Damping

CONFERENCE PROCEEDINGS FREE ACCESS

Pages 65-70

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Abstract

This paper numerically demonstrates the Bayesian estimation of damping terms. In the Bayesian estimation framework, the posterior distributions are to be derived via a sampling-based approach. This study employes the Markov chain Monte Carlo (MCMC) based on the Metropolis-Hastings algorithm and the Transitional Markov chain Monte Carlo (TMCMC). A simple mass-spring-damper model is first utilized to compare the effectiveness of MCMC and TMCMC, followed by a numerical demonstration using a one degree-of-freedom (DOF) roll motion model for roll damping estimation.

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