Normal view MARC view ISBD view

Bayesian implicit filters for the analysis of numerically stiff structural dynamic state space models

By:

Nisha, A S

Contributor(s):

Manohar, C S advised

Material type: Book

BookLanguage: en Publication details: Bangalore : IISc , 2023 .Description: xxxiii, 336p. col. ill. ; 29.1 cm * 20.5 cm e-Thesis 18.53MbDissertation: PhD; 2023; Civil engineeringSubject(s):

DDC classification:

624 NIS

Online resources:

Click here to access online

Dissertation note: PhD; 2023; Civil engineering Summary: This thesis reports on combined experimental and computational investigations conducted on problems of state and combined state and parameter estimation applied to vibrating engineering structures. The standard dynamic state space modeling framework is adopted for this purpose, and the analysis is carried out using the Kalman filter (and its variants), particle filters, and Markov chain Monte Carlo (MCMC) samplers. A review of the relevant literature has revealed that these tools have not been applied to situations where the system under study and its numerical representation via the discretized process equation displays numerical stiff behaviour. This numerical stiffness is characterized by the presence of response components with widely separated decay rates and (or) frequencies of oscillations.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Call number	Status	Date due	Barcode
E-BOOKS	JRD Tata Memorial Library	624 NIS (Browse shelf(Opens below))	Available		ET00167

include bibliographic reference and index

PhD; 2023; Civil engineering

This thesis reports on combined experimental and computational investigations conducted on problems of state and combined state and parameter estimation applied to vibrating engineering structures. The standard dynamic state space modeling framework is adopted for this purpose, and the analysis is carried out using the Kalman filter (and its variants), particle filters, and Markov chain Monte Carlo (MCMC) samplers. A review of the relevant literature has revealed that these tools have not been applied to situations where the system under study and its numerical representation via the discretized process equation displays numerical stiff behaviour. This numerical stiffness is characterized by the presence of response components with widely separated decay rates and (or) frequencies of oscillations.

There are no comments on this title.

to post a comment.