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contributor authorJin Collins
contributor authorJeffrey Weidner
date accessioned2023-11-27T23:08:14Z
date available2023-11-27T23:08:14Z
date issued8/1/2023 12:00:00 AM
date issued2023-08-01
identifier otherJBENF2.BEENG-5920.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4293319
description abstractBridge management systems are a critical component in the toolbox of those who are responsible for maintaining a population of bridges. Deterioration models are generally incorporated in bridge management systems, but minimal consideration is paid to how those models work and how the assumptions inherent to the model might influence the prediction. This paper identifies, synthesizes, and assesses typical bridge deterioration model approaches from the stochastic family of models. Each model considered is applied to two data sets for bridges in Texas and compared. A novel modeling approach that considers all models together is described. The novel approach demonstrates the value of considering multiple models when attempting to predict a future condition or behavior. It was found that a simple multiple model approach inherently and transparently reduces the uncertainty of a single model approach.
publisherASCE
titleComparison of Markovian-Based Bridge Deterioration Model Approaches
typeJournal Article
journal volume28
journal issue8
journal titleJournal of Bridge Engineering
identifier doi10.1061/JBENF2.BEENG-5920
journal fristpage04023047-1
journal lastpage04023047-13
page13
treeJournal of Bridge Engineering:;2023:;Volume ( 028 ):;issue: 008
contenttypeFulltext


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