Integration of MIMAH and Fuzzy Bayesian Networks for risk analysis in chemical tanker loading operations

Journal of Marine Engineering & Technology, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: Feb. 13, 2025

This study provides a systematic risk assessment approach for chemical tanker loading operations, focusing on high-risk scenario identified through operational data from model vessel. To address the complexities of transportation, hybrid methodology combining Methodology Identification Major Accident Hazards (MIMAH) and Fuzzy Bayesian Network (FBN) analysis was developed. MIMAH's structured framework systematically identifies critical events using Bow-Tie (BT) diagram, integrating Fault Tree (FT) Event (ET) providing thorough breakdown potential accident pathways. BT structure converted into (BN) to improve probability estimations by incorporating conditional dependencies expert-driven fuzzy logic, particularly where historical limited. The further employed dual-method sensitivity analysis, Fussell-Vesely (FV) importance measures Improvement Index (II), identify improvement-prone basic (BEs). Key findings highlight dominance human error in events, manifold connection failures incorrect valve alongside mechanical vulnerabilities with significant improvement potential. extends ARAMIS principles maritime contexts, reliability-based fuzzy-based estimation methods detailed adaptable that enhances safety resilience hazardous transport.

Language: Английский

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Advancements in Corrosion Prevention Techniques

Journal of Bio- and Tribo-Corrosion, Journal Year: 2024, Volume and Issue: 10(4)

Published: July 22, 2024

Language: Английский

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Incorporating human and organizational failures into the formation pattern for different Arctic maritime accidents using a data-driven Bayesian network

Ocean Engineering, Journal Year: 2024, Volume and Issue: 312, P. 119125 - 119125

Published: Aug. 30, 2024

Language: Английский

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Optimization approach for sustainable decommissioning of unpiggable subsea pipelines: Insights from the Arabian Gulf

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124180 - 124180

Published: Feb. 1, 2025

Unpiggable pipelines, often inaccessible for traditional pigging operations, pose significant risks due to residual hydrocarbons and limited inspection options. This paper presents an optimized methodology flushing, de-oiling, abandoning unpiggable subsea specifically designed address the unique environmental regulatory challenges in Arabian Gulf. The introduces innovative approach that integrates advanced modeling tools ‒ OLGA internal flow assurance CORMIX pollutant dispersion analysis manage oil-in-water (OIW) concentrations effectively, ensuring compliance with stringent 15-ppm discharge limit. proposed not only mitigates contamination but also enhances operational efficiency through adaptive measures. By addressing plateauing contaminant removal rates leveraging region-specific data, current study provides actionable guidance sustainable decommissioning of pipelines. findings hold broad applicability projects environmentally sensitive marine ecosystems, hence, supporting global efforts toward responsible practices.

Language: Английский

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Dynamic System Failure Assessment of Lifeboat Under Emergency Response Operations

Studies in systems, decision and control, Journal Year: 2025, Volume and Issue: unknown, P. 111 - 128

Published: Jan. 1, 2025

Language: Английский

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Reliability Analysis of Offshore Pipeline Under Stochastic Degradation

Studies in systems, decision and control, Journal Year: 2025, Volume and Issue: unknown, P. 169 - 181

Published: Jan. 1, 2025

Language: Английский

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A quantitative analysis method based on network evolution for risk factors of safety production in chemical enterprises

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 10, 2025

Language: Английский

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Potential hazard analysis of accidents in Indian underground mines using Bayesian network model

International Journal of Systems Assurance Engineering and Management, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

Language: Английский

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A multi‐perspective process safety risk assessment with hybrid risks

Risk Analysis, Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

Abstract In this paper, we assert that the process safety risks vary based on identity of stakeholders involved, for example, employees, management, regulators, community members, insurance companies, and environment. These differ in perceptions, magnitudes, ramifications across an array stakeholders. Hence, risk assessment taken from a single perspective, as is often case, inadequate perhaps misleading. Instead, more realistic approach multi‐perspective by considering interactions existing among different perspectives building concurrent compatible models explicitly. This marks first innovation current research work. The second centers hybrid nature analysis. We recognize distinction between impacting human well‐being affecting facilities, properties, capital assets, introduces safety‐facility to address types risks. Still, developing multiple represent complex, time‐consuming, tedious, very costly. addition, results may become incompatible, confusing To avoid such difficulties, comprehensive model developed initially, which, while impractical itself, allows extraction practical perspective‐based through reduction. methodology was illustrated validated examining city gas pressure reduction station 12 perspectives, illustrating highlighting necessity accurate However, widely applicable areas, not limited gate (CGS). Furthermore, twelve considered are specific context CGS case suburb Tehran other situations. By incorporating these practices, organizations can ensure comprehensive, inclusive, risks, ultimately leading better management decision‐making.

Language: Английский

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Risk assessment of gas pipeline using an integrated Bayesian belief network and GIS: Using Bayesian neural networks for external pitting corrosion modelling

The Canadian Journal of Chemical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: July 7, 2024

Abstract Corrosion poses a great risk to the integrity of oil and gas pipelines, leading substantial investments in corrosion control management. Several studies have been conducted on accurately estimating maximum pitting depth pipelines using available field data. Some frequently employed machine learning techniques include artificial neural networks, random forests, fuzzy logic, Bayesian belief support vector machines. Despite ability methods address variety problems, traditional evident limitations, such as overfitting, which can diminish model's generalization capabilities. Additionally, models that provide point estimations are incapable addressing uncertainties. In current study, network is proposed uncertainty defect pipeline exposed external corrosion. The results then incorporated into for evaluating probability failure its corresponding consequences terms social impact, thus forming comprehensive assessment framework. validated data achieved testing accuracy 90%. framework study offers powerful decision‐making tool management against

Language: Английский

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