Titlebook: Bayesian Network Modeling of Corrosion; Narasi Sridhar Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license

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Corrosion Models,nd the cause-effect relationships, models are needed for any probabilistic assessment of the time evolution of failure. The models may be empirical or mechanistic, but all models are simplifications of actual phenomena—hence the basis for regarding all models as “wrong”. However, useful models enabl

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Statistical Models: Propagation of Uncertainty and Monte Carlo Modeling, numerical propagation of uncertainty, covering basic concepts such as random sampling and correlated sampling. Examples are presented to examine propagation of uncertainties in water chemistry, the corrosion potential, and the repasivation potential, to quantify the probability of initiation of loc

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Oil and Gas Production Systems,tems encompass various sub-systems, production conditions, and?materials corrosion modes. Although probabilistic assessments have been performed in a risk-based framework in Europe, in the U.S. and elsewhere, materials are designed within a prescriptive regulatory framework, governed by standards an

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BN for Reinforced Concrete Structures,fety and economic development. As a relatively new technique to assess risks, Bayesian Network (BN) has been applied in many fields, such as reliability of pipelines, software safety, etc. This chapter summarizes the state of the art for the application of BN in the risk assessment of aging RC struc

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