Application of domino effect quantitative risk assessment to an extended industrial area

Escalation of primary accidental scenarios triggering a “domino effect” have caused extremely severe accidental events in the chemical and process industry. The identification of possible escalation events is required in the safety assessment of sites where relevant quantities of hazardous substances are stored or handled. In the European Union, “Seveso-II” Directive requires the assessment of on-site and off-site possible escalation scenarios in sites falling under the obligations of the Directive. In the present study, a methodology developed for the quantitative assessment of risk due to domino effect was applied to the analysis of an extended industrial area. Recently developed equipment damage probability models were applied for the identification of the final scenarios and for escalation probability assessment. The domino package of the Aripar-GIS software was used for risk recomposition. The results evidence that quantitative risk assessment of escalation hazard is of fundamental importance in order to identify critical equipment and to address prevention and protection actions.     

Application of dynamic risk analysis in offshore drilling processes

Process safety is the common global language used to communicate the strategies of hazard identification, risk assessment and safety management. Process safety is identified as an integral part of process development and focuses on preventing and mitigating major process accidents such as fires, explosions, and toxic releases in process industries. Accident probability estimation is the most vital step to all quantitative risk assessment methods. Drilling process for oil is a hazardous operation and hence safety is one of the major concerns and is often measured in terms of risk. Dynamic risk assessment method is meant to reassess risk in terms of updating initial failure probabilities of events and safety barriers, as new information are made available during a specific operation. In this study, a Bayesian network model is developed to represent a well kick scenario. The concept of dynamic environment is incorporated by feeding the real-time failure probability values (observed at different time intervals) of safety barriers to the Bayesian network in order to obtain the corresponding time-dependent variations in kick consequences. This study reveals the importance of real-time monitoring of safety barrier performances and quantitatively shows the effect of deterioration of barrier performance on kick consequence probabilities. The Macondo blowout incident is used to demonstrate how early warnings in barrier probability variations could have been observed and adequately managed to prevent escalation to severe consequences.     

A new approach for layout optimization in maintenance workshops with safety factors: The case of a gas transmission unit

In this study, an Integrated Simulation-Data Envelopment Analysis (DEA) approach is presented for optimum facility layout of maintenance workshop in a gas transmission unit. The process of repair of incoming parts includes various operations on different facilities. The layout problem in this system involves determining the optimum location of all maintenance shop facilities. Layout optimization plays a crucial role in this type of problems in terms of increasing the efficiency of main production line. Standard types of layouts including U, S, W, Z and straight lines are considered. First, the maintenance workshop is modeled with discrete-event-simulation. Time in system, average waiting time, average machine utilization, average availability of facilities, average queue length of facilities (AL) and average operator utilization are obtained from simulation as key performance indicators (KPIs) of DEA. Also, safety index and number of operators are considered as other KPIs. Finally, a unified non-radial Data Envelopment Analysis (DEA) is presented with respect to the stated KPIs to rank all layouts alternatives and to identify the best configuration. Principle Component Analysis (PCA) is used to validate and verify the results. Previous studies do not consider safety factor in layout design problems. This is the first study that presents an integrated approach for identification of optimum layout in a maintenance workshop of gas transmission unit by incorporating safety and conventional factors.     

A fuzzy set analysis to estimate loss intensity following blast wave interaction with process equipment

Blast waves are able to produce structural damage to process equipment even at great distances from the source point of an explosion. A loss of containment may follow and, if hazardous substances are released, relevant secondary scenarios may be triggered, resulting in domino effects.The present study was focused on the assessment of the expected structural damage and of the associated intensity of loss of containment of process vessels loaded by blast waves. Hence, a knowledge-based fuzzy set analysis was used to assess the expected overall probability of occurrence of different damage states defined for several categories of process equipment items. The fuzzy approach was also used to obtain specific threshold values for the escalation sequences (domino effects), taking into account the hazard due to the expected secondary scenarios caused by the loss of containment following blast wave impact.     

Assessment of football grounds for player safety

Professional football clubs have a duty under UK health and safety legislation to carry out risk assessments of their activities; one requirement under this duty is to assess the impact of ground layout on player safety. To assist clubs in meeting this requirement, a Ground Player-safety Score (GPS) has been developed that is defined by a base-factor, determined from the position of perimeter fencing in relation to the pitch, but which is degraded when other hazards, e.g. advertising hoardings, photographers and TV equipment, are present in the areas contiguous with the playing area. This approach has been used to assess the layouts of forty seven English and Scottish professional football clubs. The assessment showed that only 42% of the English and 71% of the Scottish clubs achieved an acceptable score. However, in all but a few cases the clubs could modify their ground layout to improve the GPS and reduce risks to players without capital expenditure. With these changes, acceptable GPS figures could be achieved by 92% of the English and by 100% of the Scottish clubs.     

Mechanism analysis and risk assessment of escalation scenario in chemical industry zones

Many major hazard installations (MHIs) are located in chemical industry zones and escalation effect may be triggered when the fire or explosion occurs on a MHI. To investigate the mechanism of the accident escalation, a systematic quantitative assessment methodology is proposed by the considering the feature and uncertainty of the escalation scenario. The main accident energy carriers of the escalation are heat radiation, overpressure of blast and fragments. The escalation probability, joint influence of the three energy carriers and risk characterization of the accident scenarios are carried out. By the new methodology, the escalation scenario in chemical industry zones can be analyzed and the risk escalation morphology is demonstrated by the simulation software. The visualized risk cloud figure gives a supplementary way to prevent the escalation scenario in chemical industry zones planning.     

Quantitative risk assessment of domino effect in Natech scenarios triggered by lightning

Lightning strike is the natural event more frequency causing Natech accidents involving atmospheric storage tanks. Despite the resulting fires have usually limited severity and only local effects, domino effect may cause the escalation of these primary events, possibly affecting nearby pressurized storages and process equipment, thus resulting in relevant increase in the potential area impacted. A methodology was developed for the quantitative assessment of risk due to domino effects caused by Natech accidents triggered by lightning. A comprehensive procedure was obtained, tailoring lightning risk assessment to include probabilistic models for domino escalation based on probit approach and combinatorial analysis. The methodology was applied to a case-study to evidence the shift in risk figures due to domino effect and the credibility of the secondary domino scenarios. The results of the case-study show that an increase up to two orders of magnitude with respect to risk calculated for conventional scenarios is possible when considering lightning-induced Natech primary scenarios and their escalation.     

Quantitative assessment of domino scenarios by a GIS-based software tool

A software procedure was developed for the quantitative assessment of domino effect. The procedure was based on a systematic methodology for the identification of domino scenarios and for the assessment of consequences and expected frequencies of the escalation events. A geographical information system (GIS) platform was interfaced to the domino assessment software. The implementation of plant lay-out data to the GIS allowed the automatic identification of the possible targets of escalation effects by the software procedure, and a straightforward calculation of the contribution to individual and societal risk indexes caused by the possible domino scenarios. The procedure was applied to the analysis of several case-studies based on actual plant lay-outs. The results evidenced that the approach allows the quantitative assessment of risk caused by escalation events with a limited additional effort with respect to that required by a conventional QRA. The use of a GIS-based software was a key element in the limitation of the effort required for the quantitative assessment of domino scenarios. Moreover, the results of the case-studies pointed out that the estimation of risk increase due to domino events is an important tool for an effective assessment and control of industrial risk in chemical and process plants.     

Development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant

Petrochemical facilities and plants require essential ongoing maintenance to ensure high levels of reliability and safety. A risk-based maintenance (RBM) strategy is a useful tool to design a cost-effective maintenance schedule; its objective is to reduce overall risk in the operating facility. In risk assessment of a failure scenario, consequences often have three key features: personnel safety effect, environmental threat and economic loss. In this paper, to quantify the severity of personnel injury and environmental pollution, a failure modes and effects analysis (FMEA) method is developed using subjective information derived from domain experts. On the basis of failure probability and consequence analysis, the risk is calculated and compared against the known acceptable risk criteria. To facilitate the comparison, a risk index is introduced, and weight factors are determined by an analytic hierarchy process. Finally, the appropriate maintenance tasks are scheduled under the risk constraints. A case study of a continuous catalytic reforming plant is used to illustrate the proposed approach. The results indicate that FMEA is helpful to identify critical facilities; the RBM strategy can increase the reliability of high-risk facilities, and corrective maintenance is the preferred approach for low-risk facilities to reduce maintenance expenditure.     

Combining FAP,MAP and correlation analysis for multivariate alarm thresholds optimization in industrial process

In the real industrial process, alarm threshold optimization is an important part of alarm system rationalization. If the design of alarm threshold is unreasonable, it would result in nuisance alarms, among which the critical alarms are overwhelmed. In order to alleviate this phenomenon, we propose a method of multivariate alarm thresholds optimization to reduce the nuisance alarms. Firstly, causal relationship between process variables is constructed based on the time delay estimation method, thus we can determine the alarms propagation path and then select the optimized variables. Secondly, in order to guarantee both the process safety and correlation consistency, three factors - false alarm probability (FAP), missed alarm probability (MAP), and the correlation between the alarm information and process information – are combined to establish the objective function of the optimization process for the first time. Then, the optimal thresholds are obtained by the genetic algorithm. Finally, the validity and effectiveness of the developed method are illustrated by the Tennessee Eastman process.     

An approach to solve the facility layout problem based on the worst-case scenario

A new approach to determine the optimal distribution of process facilities is presented in this paper. The formulation considers a set of facilities already installed in a given land and a new set of facilities to be accommodated within the same land. In addition, it is considered that a set of facilities either installed or to be laid out presents the possibility of toxic release. Based on previous analysis, the worst-case scenario implies calm wind and stable atmospheric condition. Since these conditions tend to exist during several days of the year, the proposed model is formulated assuming these deterministic values for wind and atmospheric conditions. The final model is formulated as a disjunctive model that is converted into a mixed-integer non-linear program (MINLP) via the convex-hull method. The model is then solved with local and global optimizers in the GAMS package. Using the current approach based on minimum distances for a particular case study results in a distribution with a very high risk whereas the optimal results using this proposed approach indicate large separations between releasing facilities and the inhabited facilities due to the high toxicity of the released material. More elaboration will be aggregated into the developed model to include prevention and mitigation systems to produce more compact but optimal and safe layouts.     

A stochastic approach for risk analysis in vapor cloud explosion

A stochastic approach for evaluating the risk of vapor cloud explosions is proposed in this work. The proposed methodology aims to incorporate the effect of uncertainty into the risk analysis to produce a better overall view for the risk. Some stochastic variables are used to estimate the probability of vapor cloud explosions: frequency of the release, the probability of not having an immediate ignition, the probability of delayed ignition and the probability of a vapor cloud explosion given a delayed ignition, as well as different possible meteorological conditions. These stochastic variables are represented with probability distribution curves. Different curves for the frequencies of releases from process equipment types (steel process pipes, flanges, manual valves, actuated valves, etc.), different equipment diameters and different leak sizes are also used in this analysis. Monte Carlo simulation is performed to obtain the risk as a probability distribution using the Analytic Solver Platform. Then the risk distribution curve obtained by Monte Carlo simulation is used to estimate the probability of satisfying the risk tolerance criterion.     

Approach enhancing inherent safety application in onshore LNG plant design

This study aims to provide the approach for inherent safety design of onshore LNG plants to be applied at the very early stages (concept definition phase) of the project development. Onshore LNG plant development project starts from the “Concept Definition” phase, where financial feasibility is estimated and major conditions, such as site location and plant foot print, are set.The inherent safety design basic criteria and design measures should be identified and selected when setting the basic conditions during the Concept Definition phase of the project development, such as the site location (relative location from populated areas), site condition (prevailing wind direction) and plant production capacity (number of process train, number of product tanks). The safety measures, which are usually not fully developed at the project early stages in the current design execution practices, are the emergency systems, which mitigate an accident escalation, the modularized plant and layout, and the tank selection.The inherent safety design measures discusses in this paper were identified based on the categories of plot plan, emergency system, and module plant application.The proposed approach will contribute to improve inherent safety design of onshore LNG plants and it will also yield schedule and cost benefits.     

Uncertainty reduction for improved mishap probability prediction: Application to level control of distillation unit

At all levels, the understanding of uncertainty associated with risk of major chemical industrial hazards should be enhanced. In this study, a quantitative risk assessment (QRA) was performed for a knockout drum in the distillation unit of a refinery process and then probabilistic uncertainty analysis was applied for this QRA. A fault tree was developed to analyze the probability distribution of flammable liquid released from the overfilling of a knockout drum. Bayesian theory was used to update failure rates of the equipment so that generic information from databases and plant equipment real life data are combined to gain all available knowledge on component reliability. Using Monte Carlo simulation, the distribution of top event probability was obtained to characterize the uncertainty of the result. It was found that the uncertainty of basic event probabilities has a significant impact on the top event probability distribution. The top event probability prediction uncertainty profile showed that the risk estimation is improved by reducing uncertainty through Bayesian updating on the basic event probability distributions. The whole distribution of top event probability replaces point value in a risk matrix to guide decisions employing all of the available information rather than only point mean values as in the conventional approach. The resulting uncertainty guides where more information or uncertainty reduction is needed to avoid overlap with intolerable risk levels.     

Optimization of gas detector placement considering scenario probability and detector reliability in oil refinery installation

Gas detection system is a critical layer of protection in process safety. Leak scenario probability and detector reliability are two key factors in the optimization of gas detector placement. However, they are easily neglected in previous studies, which may lead to an inaccurate evaluation of the optimization solutions. In this study, a stochastic programming (SP) optimization method is proposed considering these two factors. In order to quantitatively represent the probability of leak scenarios, a complete accident scenario set (CASS) is built combining leak sources and wind fields. Then, the computational fluid dynamics (CFD) method is adopted for consequence modeling of gas dispersion. The Markov model is developed to predict the detector reliability. With the objective of minimal cumulative detection time (MCDT), the SP formulation considering scenario probability and detector reliability (MCDT-SPR) is proposed. By introducing the particle swarm optimization (PSO) algorithm, the optimization formulations can be solved. A case study is investigated on a diesel hydrogenation refining unit. Results validate this approach is promising to improve the detection efficiency. This method is more practical and matching with the actual industrial environment, where the leak scenarios and the detector reliability can change dynamically in real process setting.     

Optimization of dilution ventilation layout design in confined environments using Computational Fluid Dynamics (CFD)

Dilution ventilation systems have been widely used to control the airborne toxic and explosive material in confined spaces. Layout design of dilution ventilation is critical to industrial hygiene control and ventilation efficiency. A properly designed dilution ventilation system can significantly improve the safety of confined workshops and maintain a comfortable work condition. In this work, Computational Fluid Dynamics (CFD) has been used to analyze the performance of dilution ventilation system in the confined workshop environment. Seven different ventilation layouts are proposed to evaluate ventilation performance of different installation layouts. Carbon monoxide (CO), which has the similar density as air, is selected as the sample contaminant to conduct steady-state CFD simulations. The simulation results of different layouts are examined and compared to get the optimal layout design for the best contaminant control. Results have shown that the layout with two opposite inlets has the highest ventilation efficiency among seven proposed layouts. This work can serve as a reference to increase dilution ventilation efficiency and minimize the energy cost in general confined areas.     

Quantitative assessment of domino and NaTech scenarios in complex industrial areas

Since the late 80s the application of quantitative risk assessment to the issue of land-use planning with respect to major accident hazards emerged as a topic to be addressed within the safety assessment of chemical and process plants. However, in the case of industrial clusters or complex industrial areas specific methodologies are needed to deal with high-impact low-probability (HILP) events. In the present study, innovative methodologies developed for the quantitative assessment of risk due to domino and NaTech scenarios are presented. In recent years a set of models for the calculation of equipment damage probability were developed. A specific effort was dedicated to the improvement of models for the calculation of equipment damage probability in these accident scenarios. In the present study, the application of these models to case-studies was analyzed. The results of the improved models obtained for NaTech quantitative assessment were compared to previous results in the literature. A specific innovative approach was developed to multi-level quantitative assessment of domino scenarios, and its potential was analyzed. The results were examined also evidencing the role and the progress with respect to the pioneering work started on these topics by Franco Foraboschi.     

Methodology for computer aided fuzzy fault tree analysis

Probabilistic risk assessment (PRA) is a comprehensive, structured and logical analysis method aimed at identifying and assessing risks of complex process systems. PRA uses fault tree analysis (FTA) as a tool to identify basic causes leading to an undesired event, to represent logical dependency of these basic causes in leading to the event, and finally to calculate the probability of occurrence of this event.To conduct a quantitative fault tree analysis, one needs a fault tree along with failure data of the basic events (components). Sometimes it is difficult to have an exact estimation of the failure rate of individual components or the probability of occurrence of undesired events due to a lack of sufficient data. Further, due to imprecision in basic failure data, the overall result may be questionable. To avoid such conditions, a fuzzy approach may be used with the FTA technique. This reduces the ambiguity and imprecision arising out of subjectivity of the data.This paper presents a methodology for a fuzzy based computer-aided fault tree analysis tool. The methodology is developed using a systematic approach of fault tree development, minimal cut sets determination and probability analysis. Further, it uses static and dynamic structuring and modeling, fuzzy based probability analysis and sensitivity analysis.This paper also illustrates with a case study the use of a fuzzy weighted index and cutsets importance measure in sensitivity analysis (for system probabilistic risk analysis) and design modification.