A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry

Khalil, Mohammad; Abdou, Mohamed A.; Mansour, M. A.; Farag, H.A.; Ossman, M.E.

doi:10.1016/j.jlp.2012.04.010

Cited by 37 publications

(18 citation statements)

References 8 publications

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“…It is obvious that these fuzzy results cannot reflect the efficiency quantitatively. Therefore, fuzzy set theory [21] is applied to calculate the fuzzy probability of failure on demand (PFD) of the emergency protection to complete the calculation of LOPA. In this paper the assessment results are turned into the corresponding trapezoidal fuzzy numbers with the converted function.…”

Section: -1 Fuzzy Set Theorymentioning

confidence: 99%

Study on risk assessment of chemical process based on an advanced layers of protection analysis method

Tong

Zong-zhi

Wang

et al. 2016

Korean J. Chem. Eng.

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This paper focuses on an advanced layers of protection analysis (LOPA) method to assess the risk of a chemical process. Based on the chemical accident statistics between 2001 and 2014 in China, an acceptable risk function was built for chemical processes to confirm the acceptable risk value for an accident scenario. The assessment index for an emergency system was developed to assess the protective function of emergency protection based on analytic hierarchy process (AHP), and the probability of failure on demand (PFD) of emergency protection was obtained by fuzzy comprehensive assessment method and fuzzy set theory. The proposed method was applied to a methanol distillation installation. The result showed that the protections, including emergency protection, were sufficient because the probability of mitigation protection (1×10 −8 ) was less than the acceptable risk value (3.04×10 −7 ). The advanced LOPA method was proven to be able to improve the integrity and accuracy of traditional LOPA.

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Section: -1 Fuzzy Set Theorymentioning

confidence: 99%

Study on risk assessment of chemical process based on an advanced layers of protection analysis method

Tong

Zong-zhi

Wang

et al. 2016

Korean J. Chem. Eng.

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“…This approach is best suited for those cases where availability of data is highly uncertain (MATLAB help;Ross, 2010;Tang et al, 2000;Huang et al, 2005;Mikhailov, 2004;An et al, 2007;An, Chen, & Baker, 2011;Mohammadi & Meech, 2013;Vahdani et al, 2011;Venkatrao, 2013, Buyukozkan & Cifci, 2012a, 2012b, Khalil, Abdou, Mansour, Farag & Ossman, 2012Rouhani, Ghazanfari & Jaari, 2012;Wang, Fan & Wang, 2010;Wang & Lee, 2007). Either data is over available or scanty.…”

Section: Fuzzy Reasoning Approach (Fra)mentioning

confidence: 99%

Integration of fuzzy reasoning approach (FRA) and fuzzy analytic hierarchy process (FAHP) for risk assessment in mining industry

Verma

Chaudhri

2014

JIEM

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Abstract:Purpose: Mining industry has always been known for its unsafe working environment. This industry is one of the most hazard prone industries. To maintain safety in workplace timely assessment of risk associated with different operations performed to extract ore from the ore body has become necessity. To serve the said purpose, present work demonstrates a robust hybrid risk assessment approach for mining industry.Design/Methodology: Accident data from 1995 to 2012 is reviewed to identify hazards contributed to negative outcomes. The FRA approach is implemented to evaluate the risk levels associated with identified hazard factors. Thereafter AHP pairwise comparison matrix is developed to obtain priority weights for the hazard factors. Final priority of hazards based on severity of level of risk associated with them is obtained considering the outcome of FRA approach in terms of risk score for the hazards, combined with the priority weights obtained from AHP technique.Findings: Defuzzified FAHP weight of hazard factors, this weight gives priority sequence of hazards to be considered for development of plan of mitigation.

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“…Currently, the fuzzy logic-based model has been applied to diverse fields of engineering sciences for multiple risk assessments [13][14][15][16]. Khalil et al [14] applied cascaded fuzzy logic-layer of protection analysis (CFL-LOPA) model for risk management in the natural gas industry, and they found the superior performance of CFL-LOPA model for maintaining the safety integrity level. Yan et al [15] proposed the set pair analysis-layer of protection (SPA-LOPA) model to assess the severity of gas leakage in the biomass gasification (BG) system.…”

Section: Introductionmentioning

confidence: 99%

Drought index prediction using advanced fuzzy logic model: Regional case study over Kumaon in India

et al. 2020

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A new version of the fuzzy logic model, called the co-active neuro fuzzy inference system (CANFIS), is introduced for predicting standardized precipitation index (SPI). Multiple scales of drought information at six meteorological stations located in Uttarakhand State, India, are used. Different lead times of SPI were computed for prediction, including 1, 3, 6, 9, 12, and 24 months, with inputs abstracted by autocorrelation function (ACF) and partial-ACF (PACF) analysis at 5% significance level. The proposed CANFIS model was validated against two models: classical artificial intelligence model (e.g., multilayer perceptron neural network (MLPNN)) and regression model (e.g., multiple linear regression (MLR)). Several performance evaluation metrices (root mean square error, Nash-Sutcliffe efficiency, coefficient of correlation, and Willmott index), and graphical visualizations (scatter plot and Taylor diagram) were computed for the evaluation of model performance. Results indicated that the CANFIS model predicted the SPI better than the other models and prediction results were different for different meteorological stations. The proposed model can build a reliable expert intelligent system for predicting meteorological drought at multi-time scales and decision making for remedial schemes to cope with meteorological drought at the study stations and can help to maintain sustainable water resources management.

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A cascaded fuzzy-LOPA risk assessment model applied in natural gas industry

Cited by 37 publications

References 8 publications

Study on risk assessment of chemical process based on an advanced layers of protection analysis method

Study on risk assessment of chemical process based on an advanced layers of protection analysis method

Integration of fuzzy reasoning approach (FRA) and fuzzy analytic hierarchy process (FAHP) for risk assessment in mining industry

Drought index prediction using advanced fuzzy logic model: Regional case study over Kumaon in India

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