Deriving the transition probability matrix using computational mechanics. Issue 2 (16th April 2018)

• Record Type: Journal Article
• Authors: Riveros, Guillermo A.; Rosario-Pérez, Manuel E.
• Is Part Of: Engineering computations. Volume 35:Issue 2(2018)
• Page Start: 692
• Page End: 709
• Publication Date: 2018-04-16
• Subjects: Corrosion -- Finite element modeling -- Markov chain -- Miter gates -- Multivariate samples of statistical distributions -- Navigation steel structures; Computer-aided engineering -- Periodicals; Computer graphics -- Periodicals; 620.00285
• DOI: 10.1108/EC-02-2017-0051
• Languages: English
• ISSNs: 0264-4401

Abstract

Abstract : Purpose: The combined effects of several complex phenomena cause the deterioration of elements in steel hydraulic structures (SHSs) within the US lock system: corrosion, cracking and fatigue, impact and overloads. Predicting the future condition state of these structures by the use of current condition state inspection data can be achieved through the probabilistic chain deterioration model. The purpose of this study is to derive the transition probability matrix using final elements modeling of a miter gate. Design/methodology/approach: If predicted accurately, this information would yield benefits in determining the need for rehabilitation or replacement of SHS. However, because of the complexity and difficulties on obtaining sufficient inspection data, there is a lack of available condition states needed to formulate proper transition probability matrices for each deterioration case. Findings: This study focuses on using a three-dimensional explicit finite element analysis (FEM) of a miter gate that has been fully validated with experimental data to derive the transition probability matrix when the loss of flexural capacity in a corroded member is simulated. Practical implications: New methodology using computational mechanics to derive the transition probability matrices of navigation steel structures has been presented. Originality/value: The difficulty of deriving the transition probability matrix to perform a Markovian analysis increases when limited amount of inspection data is available. The used state of practice FEM to derive the transition probability matrix is not just necessary but also essential when the need for proper maintenance is required but limited amount of the condition of the structural system is unknown.