A Case Study on the Use of Bayesian Inference in Fracture Mechanics Models for Inspection Planning
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TECHNICAL ARTICLE—PEER-REVIEWED
A Case Study on the Use of Bayesian Inference in Fracture Mechanics Models for Inspection Planning Tiago Ribeiro
. Luı´s Borges . Constanc¸a Rigueiro
Submitted: 28 June 2019 / Accepted: 8 August 2019 ASM International 2019
Abstract Combining fracture mechanics models for bidirectional crack growth with a Bayesian inference approach for taking into account the information acquired with structural health monitoring techniques is proposed as an analysis method for remaining fatigue life evaluation and inspection planning for fixed ocean structures. After providing a background for the proposed probabilistic analysis, as well as discussing the fundamental hypotheses and options, this paper exemplifies the method application to real data, from a case study. The method steps encompass global spectral fatigue analyses, a simplified probabilistic fatigue analysis, a deterministic fatigue analysis and a probabilistic fatigue analysis, including numerical experimentation with the Monte Carlo method. Keywords Inspection planning Structural health monitoring Bayesian inference Fracture mechanics Crack growth
T. Ribeiro (&) Tal Projecto, Lda., Av. Infante Santo 70, 1350-252 Lisbon, Portugal e-mail: [email protected]; [email protected] L. Borges C. Rigueiro ISISE, Coimbra, Portugal URL: https://www.structurame.com/en/node/4 C. Rigueiro e-mail: [email protected] L. Borges Structurame, SARL, Lausanne, Switzerland C. Rigueiro Polytechnic Institute of Castelo Branco, Castelo Branco, Portugal
Introduction Assessing remaining fatigue life (RFL) has become a task of paramount importance for nearly all key steel structures, namely the ones whose collapse would impose unbearable impacts for the society, either due to its cost, environmental risk or life losses. Using fracture mechanics (FM) models for attaining such results has a long tradition within aeronautic, mechanical and naval industries [5] and more recently gained wide employment in fixed offshore structures [27]. Nonetheless, fixed offshore structures current obsolescence makes RFL assessment and inspections planning an urgent need. Unlike the common approaches for structural design that deal with uncertainties by imposing safety (or design) factors upon the actions and resistances expected values, assessing RFL is all about accuracy and dealing explicitly with the available information and its shortcomings. Therefore, instead of deterministic calculations, probabilistic methods shall be employed. Such difference has a deep outcome in almost every aspect of fatigue life computation. Indeed, the common and convenient damage sum approach (as provided by the Palmgren-Miner rule) has to be abandoned to endeavor another one that explicitly determines crack dimensions along the service life. Given Bayesian inference suitability for the purpose [26], this paper is deemed to illustrate its employment in FM models to continuously assess the RFL of an existing fixed offshore structure, therefore commanding its inspections pla
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