Generalized analytical expressions for safety instrumented systems' performance measures: PFDavg and PFH

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 (PFD_avg) 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.     

An extension to Fuzzy Fault Tree Analysis (FFTA) application in petrochemical process industry

Fault Tree Analysis (FTA) is an established technique in risk management associated with identified hazards specific to focused fields. It is a comprehensive, structured and logical analysis method aimed at identifying and assessing hazards of complex systems. To conduct a quantitative FTA, it is essential to have sufficient data. By considering the fact that sufficient data is not always available, the FTA method can be adopted into the problems under fuzzy environment, so called as Fuzzy Fault Tree Analysis (FFTA). This research extends FFTA methodology to petrochemical process industry in which fire, explosion and toxic gas releases are recognized as potential hazards. Specifically, the case study focuses on Deethanizer failure in petrochemical plant operations to demonstrate the proposed methodology. Consequently, the study has provided theoretical and practical values to challenge with operational data shortage in risk assessment.     

Risk assessment of safety and health (RASH) for building construction

In this research Risk Assessment of Safety and Health RASH method for building construction has been developed with risks classified into Safety Risks and Health Risks. 11 factors representing safety risks and 8 factors representing health risks were identified based on field survey in Oman. 40 Safety and Health specialists were involved in carrying out risk assessment using the existing method of risk analysis RA and the proposed RASH method. It was found that RASH method resulted in superior accuracy for assessment of risk zones than the existing RA method. The accuracy by RASH was almost twice the accuracy by RA. The overall percentages of the correct answers for the four scenarios using the RASH method and the RA method were 72.5 percent and 40 percent respectively. The proposed RASH method gave fewer errors than the existing RA method for all scenarios. Two scenarios were found to be the most problematic ones with largest overestimation of risks occur when using the existing RA method. Wilcoxon Ranked Test showed that the two methods are significantly different (z = −3.357, p > 0.01). The new method RASH is statistically acceptable and it resulted in better response in terms of estimating the risk than the RA method.     

Advanced process control system with MPC as a new approach for layer of protection analysis

Layer of protection analysis (LOPA) is a widely used method to support process safety in the chemical industries. In the LOPA, the process is classified into many layers, one of such layers considers the basic process control system (BPCS) which commonly uses PID controllers. This kind of controllers cannot deal with constraints. For this reason, the main purpose of this work is to provide a framework to enhance the control layer in the LOPA, which consists of a model predictive control (MPC) with safety features. These features include: sublayers in the controller system (such as real time optimization, target calculation, and MPC), safety constraints, and guarantee of stability by adopting an Infinite Horizon MPC (IHMPC). Here, we propose an approach for control-inspired view to process safety, replacing the BPCS by an Advanced Process Control System (APCS). Moving forward with these concepts, first, a literature review emphasizes the content, showing two perspectives for the APCS. The APCS is designed for two varieties of controllers, a basic IHMPC and IHMPC with zone control to compare the performance. In this framework, the first sublayer consists of a real time optimization (RTO) structure, that calculates the optimal operating condition for the process controller, which computes the control action. Besides, RTO has an additional constraint called the safety index, based on the protection of process operational. RTO and basic IHMPC communicate directly, while for IHMPC with zone control there is an inner sublayer called Target Calculation, it computes a feasible target to the controller, working as another safety strategy in APCS. After that, we demonstrate both structures applied to a CSTR reactor. From the case study, we compared both controllers, and evaluated the effect that the safety index constraint causes in the setpoints, outputs, and control actions. The use of safety constraint in RTO proved to be a safe strategy for the control layer, as well as IHMPC with zone control presented a safer profile than basic IHMPC. Furthermore, the results show that safety constraint affect the economic goal, decreasing its value.     

Resilience assessment of chemical industrial areas during Natech-related cascading multi-hazards

In chemical industrial areas, technological accidents triggered by natural events (Natech events) may escalate. Complex cascading multi-hazard scenarios with high uncertainties may be caused. Resilience is an essential property of a system to withstand and recover from disruptive events. The present study focuses on the change of the resilience level due to (possible) interactions between cascading hazards, chemical installations and safety barriers during the dynamic evolution of fire escalations triggered by a natural hazard (certain cascading multi-hazard scenarios). A quantitative resilience assessment method is developed to this end. The state transition of a system facing accidents in the context of resilience is explored. Moreover, the uncertainties accompanying an accident evolution are quantified using a Dynamic Bayesian Network, allowing a detailed analysis of the system performance in different time steps. System resilience is measured as a time-dependent function with respect to the change of system performance. The applicability of the proposed methodology is demonstrated by a case study, and the effects of different configurations of safety barriers on improving resilience are discussed. The results are valuable to support disaster prevention within chemical industrial areas.     

On the effectiveness of mitigation strategies for cryogenic applications

The need for sustainable energy sources, as well as the current energetic crisis involving the majority of markets, has promoted the use of cryogenic liquefaction for the transportation and storage of natural gas (i.e., LNG). To guarantee the development of a robust and safe infrastructure, a complete understanding of the main phenomena occurring at low temperatures is paramount. In this sense, the largest grey areas are the characterization of the combustion at low-initial temperature and the interactions between water and cryogenic liquid. For these reasons, this work presents an experimental campaign on the possible mitigation strategies for the mitigation of consequences related to the accidental release of LNG. Particular emphasis was posed on the direct and indirect effects of water on cryogenic pool fire. The former resulted in a significant increase in the dimensions of fire (∼+50%) and burning rate (∼300%) with respect to the case with no direct contact between water and LNG, whereas the latter generated an abrupt decrease in the measured temperatures (<100 °C). The use of an emergency flare to empty an LNG tank was tested, as well. The spatial distribution of temperature was monitored along with the time to guarantee the safe operability of this equipment in the case of LNG combustion. The explanations for the observed phenomena and trends were provided, allowing for the development of safe procedures for the emergency response related to cryogenic fuels.     

A new multiple-risk map approach to solve process plant layout considering safety and economic aspects

Mathematical models used to optimize the process plant layout (PPL) with risk reduction have four primary objectives, which are related to the minimization of land, pumping (pipe system), protection system devices, and risk costs. Moreover, these models are of two types: continuous plane models (CPM) and grid-based models (GBM); however, the nonconvexity of the CPM models makes difficult to achieve the global optimum, because it is formulated as Mixed-Integer Nonlinear Programming (MINLP). Thus, the risk map approach has been implemented with the grid-based models to solve problems of process plant layout focused on finding the best possible solution. However, these risk map formulations present important limitations, mainly related with the use of protection devices and the occupied area. Therefore, a new GBM-MILP formulation is proposed to optimize the selection of protection devices and minimize the occupied area. The risk is reduced through the investment on safety devices instead of considering the increase of separation distances. The proposed model was used to solve the layout problem of an ethylene oxide process, and the results was compared with a process layout reported in the literature. The results show that the model can provide the best possible solution; however, the time spent in the calculation is considerably greater than that reported for continuous plane models. Finally, the model can be used by decision-makers to evaluate different layout options for several explosion scenarios, during the early stages of the plant design.     

Modeling using dynamic variables – An approach for the design of loss prevention programs

Records from The National Safety Council [National Safety Council, 2007. Safety Intervention Evaluation: A Systematic Approach. <http://www.acgih.org/events/ControlBand/Thomas_SafetyIntervention.pdf> (accessed 10.01.07)] have shown that in 2004 alone, on-the-job injuries to workers constituted 35% of total recorded injuries in the United States. This generated an associated cost of about $142.2 billion. Unfortunately, the safety intervention programs enforced at work places to mitigate such losses are driven mainly by intuition and experience of involved safety personnel. This paper details implementing a computer program to furnish safety personnel with an empirical basis for designing loss prevention programs based on historical safety data. The computer tool is driven by a dynamic mathematical model which adapts itself to variations in data patterns and explains the correlation between historical incident rates and corresponding resources committed to interventions. This study empowers the industry with a tool that is capable of forming the core of optimizing valuable human resource allocation in safety program designs.     

Predicting safety culture: the roles of employer, operations manager and safety professional

Introduction: This study explores predictive factors in safety culture. Method: In 2008, a sample 939 employees was drawn from 22 departments of a telecoms firm in five regions in central Taiwan. The sample completed a questionnaire containing four scales: the employer safety leadership scale, the operations manager safety leadership scale, the safety professional safety leadership scale, and the safety culture scale. The sample was then randomly split into two subsamples. One subsample was used for measures development, one for the empirical study. Results: A stepwise regression analysis found four factors with a significant impact on safety culture (R² = 0.337): safety informing by operations managers; safety caring by employers; and safety coordination and safety regulation by safety professionals. Safety informing by operations managers (ß = 0.213) was by far the most significant predictive factor. Impact on industry: The findings of this study provide a framework for promoting a positive safety culture at the group level.