PUBLICATIONS D'EQUIPE 3

Publications de Lequipe 3

MCHEBILA, INNAL F. Generalized analytical expressions for safety instrumented systems' performance measures: PFDavg and PFH”. Journal of Loss Prevention in the Process Industries [Internet]. 2015;34 (3) :167-176. Publisher's VersionAbstract
Safety Instrumented Systems (SIS) constitute an indispensable element in the process of risk reduction for almost all of nowadays' industrial facilities. The main purpose of this paper is to develop a set of generalized and simplified analytical expressions for two commonly employed metrics to assess the performance of SIS in terms of safety integrity, namely: the Average Probability of Failure on Demand (PFDavg) and the Probability of Dangerous Failure per Hour (PFH). In addition to the capability to treat any K-out-of-N architecture, the proposed formulas can smoothly take into account the contributions of Partial Stroke Testing (PST) and Common Cause Failures (CCF). The validity of the suggested analytical expressions is ensured through various comparisons that are carried out at different stages of their construction.
CHIREMSEL Z, NAIT-SAID R, CHIREMSEL R. Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network. J Fail. Anal. and Preven [Internet]. 2015;(16) :747–760. Publisher's VersionAbstract
Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.
CHIREMSEL Z, NAIT-SAID R, CHIREMSEL R. Probabilistic Fault Diagnosis of Safety Instrumented Systems based on Fault Tree Analysis and Bayesian Network. J Fail. Anal. and Preven [Internet]. 2016;16 :747–760. Publisher's VersionAbstract
Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.
MCHEBILA. Simultaneous evaluation of safety integrity’s performance indicators with a generalized implementation of common cause failures. Process Safety and Environmental Protection [Internet]. 2018;2018 (117(7) :214-222. Publisher's VersionAbstract
The average unavailability and the average unconditional failure intensity of safety-instrumented systems represent the main performance indicators of safety integrity. This paper employs an approach based on the exploitation of the availability expression to obtain both performance measures in a simultaneous and straightforward way for any KooN configuration. The implementation of such an approach is generalized to take into account the contribution of common cause failures using any parametric model. The validation of the obtained results is verified through their application using several architectures and using Beta Factor and Binomial Failure Rate models to handle such type of dependent events. Therefore, the contribution of this paper lies in proposing one single formula that can be used to estimate the two main safety integrity’s performance indicators for any KooN architecture using any kind of common cause failures parametric model.
SELLAMI I, NAIT-SAID R, CHETEHOUNA K, IZARRA C, Zidani F. Quantitative consequence analysis using Sedov-Taylor blast wave model. Part II: Case study in an Algerian gas industry. Process Safety and Environmental Protection [Internet]. 2018;2018 (116(5) :771-779. Publisher's VersionAbstract

In the oil and gas industry, it is common to use gas liquefaction that allows storage and transport of large quantities of LNG and LPG. One of the main disadvantages of this storage mode is the BLEVE risk, which remains a major concern for risk decision-makers. In order to prevent the occurrence of this risk and reduce its impact, risk analysts often use quantitative risk analysis (QRA), which is based on the understanding and quantification of the accidental phenomena and their consequences (overpressure, thermal radiation, toxicity dose). QRA is a rigorous and advanced approach that requires reliable data in order to obtain a good estimate and control of risks. The main objective of this paper (Part II) is to integrate the Sedov-Taylor model developed in Part I into the QRA approach in order to evaluate BLEVE blast effect, and illustrate it with a case study on a pressurized LPG accumulator located in the MPP3-plant of SONATRACH company in the Hassi R'Mel gas field (the largest gas field in Algeria). A parametric analysis of the fuel mass, temperature at failure and rupture pressure is carried out to study their influence on the evolution of BLEVE overpressure. In addition, the evaluation of BLEVE thermal effect is performed in order to better realize an exhaustive QRA. Through this application, the results show the great relevance of the Sedov-Taylor model in the consequence analysis and also in the development of process safety recommendations.