Probabilistic Finite Element Model Updating Using Bayesian Statistics

Applications to Aeronautical and Mechanical Engineering

Nonfiction, Science & Nature, Technology, Engineering, Mechanical
Cover of the book Probabilistic Finite Element Model Updating Using Bayesian Statistics by Tshilidzi Marwala, Ilyes Boulkaibet, Sondipon Adhikari, Wiley
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Author: Tshilidzi Marwala, Ilyes Boulkaibet, Sondipon Adhikari ISBN: 9781119153016
Publisher: Wiley Publication: September 23, 2016
Imprint: Wiley Language: English
Author: Tshilidzi Marwala, Ilyes Boulkaibet, Sondipon Adhikari
ISBN: 9781119153016
Publisher: Wiley
Publication: September 23, 2016
Imprint: Wiley
Language: English

Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering

Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa

Sondipon Adhikari, Swansea University, UK

Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering

Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering.

The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering.

Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering.

Key features:

  • Contains several contributions in the area of model updating using Bayesian techniques which are useful for graduate students.
  • Explains in detail the use of Bayesian techniques to quantify uncertainties in mechanical structures as well as the use of Markov Chain Monte Carlo techniques to evaluate the Bayesian formulations.

The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Probabilistic Finite Element Model Updating Using Bayesian Statistics: Applications to Aeronautical and Mechanical Engineering

Tshilidzi Marwala and Ilyes Boulkaibet, University of Johannesburg, South Africa

Sondipon Adhikari, Swansea University, UK

Covers the probabilistic finite element model based on Bayesian statistics with applications to aeronautical and mechanical engineering

Finite element models are used widely to model the dynamic behaviour of many systems including in electrical, aerospace and mechanical engineering.

The book covers probabilistic finite element model updating, achieved using Bayesian statistics. The Bayesian framework is employed to estimate the probabilistic finite element models which take into account of the uncertainties in the measurements and the modelling procedure. The Bayesian formulation achieves this by formulating the finite element model as the posterior distribution of the model given the measured data within the context of computational statistics and applies these in aeronautical and mechanical engineering.

Probabilistic Finite Element Model Updating Using Bayesian Statistics contains simple explanations of computational statistical techniques such as Metropolis-Hastings Algorithm, Slice sampling, Markov Chain Monte Carlo method, hybrid Monte Carlo as well as Shadow Hybrid Monte Carlo and their relevance in engineering.

Key features:

The book is essential reading for researchers, practitioners and students in mechanical and aerospace engineering.

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