Weibull distribution optimization for piping risk calculation due to uniform corrosion using Monte Carlo method

Hartoyo, Fernanda; Irianti, Gabriella Pasya; Fatriansyah, Jaka Fajar; Ovelia, Hanna; Mas'ud, Imam Abdillah; Digita, Farhan Rama; Fauzi, Andrian; Anis, Muhammad Yunus

doi:10.1016/j.matpr.2023.02.312

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…Monte Carlo simulation is a statistical method that is used for modeling random processes and making decisions based on probabilistic calculations (Hartoyo et al, 2023;Tran, Robbe, and Lim, 2023;Clare, Piggott, and Cotter, 2022). It is based on the idea of generating random numbers that are then used to create a set of possible scenarios.…”

Section: Methodsmentioning

confidence: 99%

Risk Modeling in the Oil and Gas Industry

Rodionov,

Gataullin,

Smirnova

et al. 2023

IJTech

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The oil and gas industry is a sector that is prone to risks that can have severe consequences for both the environment and the economy. In this study. the aim is to develop an effective mathematical tool for risk modeling in the oil and gas industry. The research proposes a simulation modeling approach that focuses on two key risk parameters -frequency and severity. By using differentiated distributions. the unique properties of risk in the oil and gas industry can be effectively described, and an algorithm can be developed for practical applications. The findings of this study have significant implications for the oil and gas industry, policymakers, and investors. By using an effective mathematical tool for risk modeling. they can identify and manage risks more effectively, reduce the likelihood of accidents and other events that can have severe consequences. and minimize the potential impact of these events. Overall, this research provides valuable insights into the development of an effective mathematical tool for risk modeling in the oil and gas industry. By using simulation modeling and differentiated distributions. this study proposes an algorithm that can be practically applied to manage risks effectively in this important sector.

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Section: Methodsmentioning

confidence: 99%