A Bayesian Network framework for probabilistic identification

Language: English

Published by LAP LAMBERT Academic Publishing Dez 2022, 2022

6205526794 / 9786205526798

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This item is printed on demand - Print on Demand Titel. Neuware -Chloride ingress into concrete is one of the major causes leading to the degradation of reinforced concrete structures with important damages after 10 to 20 years. Consequently, they should be periodically inspected and repaired to ensure an optimal level of serviceability and safety. Chloride ingress involves a large number of uncertainties related to material properties and exposure conditions. However, it is difficult to obtain sufficient inspection data to characterise the mid- and long-term behaviour of this phenomenon. The main objective of this thesis is to develop a framework based on Bayesian Network updating for improving the identification of uncertainties related to material and environmental model parameters. Based on results coming from in-lab normal and accelerated tests that simulate tidal conditions, several procedures are proposed to: (1) identify input random variables from normal or natural tests; (2) determine a scale factor for accelerated tests; and (3) characterise time-dependent parameters. The results indicate that the proposed framework could be a useful tool to identify model parameters even from limited data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 196 pp. Englisch. …

Seller Inventory # 9786205526798

Title
A Bayesian Network framework for probabilistic identification
Author
Thanh Binh Tran
Publisher
LAP LAMBERT Academic Publishing Dez 2022
Publication year
2022
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6205526794
ISBN 13
9786205526798
Item weight
310 grams
Dimensions
220x150x12 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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AbeBooks seller since January 23, 2017

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