Accidents In Chemical Process Industry Research Articles

Dynamic-risk-informed safety barrier management: An application to cost-effective barrier optimization based on data from multiple sources

An integrated approach for performance assessment and management of safety barriers in a systemic manner is needed concerning the prevention and mitigation of major accidents in chemical process industries. Particularly, the effects of safety barriers on system risk reduction should be assessed in a dynamic manner to support the decision-making on safety barrier establishments and improvements. A simulation approach, named Simulink-based Safety Barrier Modeling (SSBM), is proposed in this paper to conduct dynamic risk assessment of chemical facilities with the consideration of the degradation of safety barriers. The main functional features of the SSBM include i) the basic model structures of SSBM can be determined based on bow-tie diagrams, ii) multiple data (periodic proof test data, continuous condition-monitoring data, and accident precursor data) may be combined to update barrier failure probabilities and initiating event probabilities, iii) SSBM is able to handle uncertainty propagation in probabilistic risk assessment by using Monte Carlo simulations, and iv) cost-effectiveness analysis (CEA) and optimization algorithms are integrated to support the decision-making on safety barrier establishments and improvements. An illustrative case study is demonstrated to show the procedures of applying the SSBM on dynamic risk-informed safety barrier management and validate the feasibility of implementing the SSBM for cost-effective safety barrier optimization.

Determining performance shaping factors to assess human error in the emergency response team in chemical process industries: a case study

Objectives. Human error (HE) plays a crucial role in the occurrence of accidents in chemical process industries (CPIs). Emergency response team (ERT) members are predisposed to HEs due to the nature of their work. The HE potential is influenced by the performance shaping factors (PSFs). Managing PSFs can diminish the human error probability (HEP) and consequently increase the emergency response success chance. This article aimed to determine the PSFs for ERT members in CPIs. Methods. First, an initial list of PSFs was searched and classified within human reliability analysis methods and studies. Then, an expert panel of the emergency management system was utilized to identify, classify and weight the initial PSFs. The fuzzy Delphi method and content analysis technique were applied to summarize and categorize the PSFs. Results. The results of the study showed that 11 PSFs had greater impacts on the ERT members’ error potential. Findings revealed that stress and physiological stressors, competency, and team and organization were the three most important PSFs. Conclusion. The most important and relevant PSFs can be effectively used in accurate HE assessment of ERT members in CPIs.

Incidence investigation of accidents in chemical industries: A comprehensive study based on factor analysis

AbstractThis study aimed to identify factors affecting the incidence of chemical accidents in chemical process industries. The present study investigated 840 accidents in 42 chemical process industries over 11 years (2008–2018). Data analysis was conducted using exploratory and confirmatory factor analysis (EFA and CFA) and structural equation modeling (SEM). Data analysis was done using IBM SPSS AMOS v. 22. Moreover, χ2/df, RMSEA, CFI, NFI, and NNFA (TLI) indices were used as model fit indices. The descriptive results showed that 45.3% and 32.14% of the accidents were related to transportation and the release of chemicals, respectively. Factor analysis showed that 6 latent factors and 37 indicator variables affected the accidents. SEM findings showed that latent factors, including individual and occupational training, risk management, and their indicator variables, had indirect effects on the chemical accidents (P < 0.05). In contrast, unsafe conditions and unsafe acts latent factors with their indicator variables had a direct impact on the incidence of chemical accidents (P < 0.05). The findings confirmed that chemical accidents are affected by different causal layers. Using different methods of accident analysis and combining them with scientific and updated techniques of other sciences, that is, mathematics, as well as statistics, can improve accident analysis and controlling methodologies.

Methodologies for Assessing Risks of Accidents in Chemical Process Industries

Chemical process industries often handle, store and transport chemicals which are flammable and/or toxic. Also, often, processes are employed which are carried out at high temperatures of pressures. These happenings constitute major hazards which carry the risk of serious accidents. The bigger the hazard, the greater is the risk associated with its existence. Despite the best intentions of the industries not to allow any accident to occur, major accidents keep occurring all over the world. This makes it necessary to develop newer methods with which the likelihood of accidents can be forecast and steps taken to prevent those accidents from occurring. This paper presents an overview of the already developed, and still evolving, methods for assessing risk of accidents in chemical process industries.

Risk of Fuel Spills and the Transient Models of Spill Area Forecasting

Most accidents in chemical process industry, as well as a large number of fires in general, are triggered by accidental spilling of flammable liquids. Such spills either get auto-ignited or are set on fire by one or the other ignition source. If other flammable material happens to catch fire before the initial fire is extinguished, the accident gets escalated. In many situations, the escalation is catastrophic, resulting in very large fires, with or without explosions. This paper assesses the transient models developed so far to predict the areas covered by accidental fuel spills.

Chemical Accident Simulation Tool (CAST): A System for Assessing Consequences of Accidents in Chemical Process Industry

The development and validation of a new software named chemical accident simulation tool (CAST) is presented. CAST enables development of scenarios of different types of accidental fires and explosions that can occur in chemical process industry (CPI). CAST is also capable of assessing the likely consequences of such accidents in terms of the area impacted and the types of impacts. The distinguishing features of CAST are (a) it incorporates a larger set of established models than handled by existing packages to simulate a wider variety of accidents in CPI; (b) it is developed with an integrated mapping tool to display damage zones around accident center; this makes the application useful in decision making; and (c) it calculates the results in a fast and reliable manner. Due to these attributes, CAST has increased efficiency, better understanding of the accident scenarios, and better communication of results. Validation of the software has been done with published results which shows that the codes for calculating the impacts from accidents are correct.

Domino Effect Analysis, Assessment and Prevention in Process Industries

AbstractDomino effect is a fairly common phenomenon in process industry accidents, which makes many process industry accidents serious and the consequent losses enhanced. Domino effect of the major accidents in chemical cluster is emphasized. Many researchers have studied domino effect in chemical clusters from different perspectives. In the review, we summarize the research from three aspects: The statistical analysis of domino accidents in chemical process industry, the evaluation of domino accidents and the prevention of domino accidents in chemical clusters by game theory. From the analysis, we can find the characteristic of domino accidents such as the time and the location, the origin and causes of domino accidents. The methods of assessing domino effects such as quantitative risk assessment (QRA), Bayesian networks (BN) and Monte Carlo simulation (MCS) are analyzed. The prevention of domino accidents in chemical clusters using game theory is seldom, and there is still much space for improvement in enterprises’ efforts to prevent risk of domino accidents.

Development of a new chemical process-industry accident database to assist in past accident analysis

Past accident analysis (PAA) is one of the most potent and oft-used exercises for gaining insights into the reasons why accidents occur in chemical process industry (CPI) and the damage they cause. PAA provides invaluable ‘wisdom of hindsight’ with which strategies to prevent accidents or cushion the impact of inevitable accidents can be developed. A number of databases maintain record of past accidents in CPI. The most comprehensive of the existing databases include Major Hazard Incident Data Service (MHIDAS), Major Accident Reporting System (MARS), and Failure and Accidents Technical Information Systems (FACTS). But each of these databases have some limitations. For example MHIDAS can be accessed only after paying a substantial fee. Moreover, as detailed in the paper, it is not infallible and has some inaccuracies. Other databases, besides having similar problems, are seldom confined to accidents in chemical process industries but also cover accidents from other domains such as nuclear power plants, construction industry, and natural disasters. This makes them difficult to use for PAA relating to CPI. Operational injuries not related to loss of containment, are also often included. Moreover, the detailing of events doesn’t follow a consistent pattern or classification; a good deal of relevant information is either missing or is misclassified. The present work is an attempt to develop a comprehensive open-source database to assist PAA. To this end, information on about 8000 accidents, available in different open-source clearing houses has been brought into a new database named by us PUPAD (Pondicherry University Process-industry Accident Database). Multiple and overlapping accident records have been carefully eliminated and a search engine has been developed for retrieval of the records on the basis of appropriate classification. PUPAD doesn’t aim to replace or substitute the well established databases such as MHIDAS and MARS but, rather, aims to compliment them.

Enhancing the Accuracy of Forecasting Impact of Accidents in Chemical Process Industry by the Application of Cellular Automata Technique

Nearly all the techniques, tools and strategies for preventing accidents in chemical process industry revolve round the question: what would happen if a vessel, a conduit, a controller, or a process suddenly fails leading to an accident?’ To answer this question accidental scenarios are developed and, based on the wisdom of hindsight derived from the post-mortem of past accidents, the damage likely in each scenario is assessed. This information provides the key feedback for quantifying and ‘scaling’ hazards: higher the probability-cum-severity of the likely accident, higher the risk posed by the unit whose failure may cause the accident. In other words, assessment of the likely consequences of a likely accident is one of most common and important steps associated with loss prevention and safety promotion in process industry. In the hitherto used approach it is assumed that the blast wave and heat load generated by an explosion or explosion-cum-fire would travel radically outward with equal intensity in all directions from the accident epicentre. It is also assumed that the intensity of the impact felt by a receptor would only be a function of the receptor's distance from the epicentre but shall be independent of the receptor's direction. In real-life situations, however, the flux of energy, mass and momentum ensuing from an accident would not travel with equal intensity in all directions but would be absorbed or attenuated by different objects lying in its path in different directions. In order to foresee a more plausible picture of the ‘risk contours’ of a likely accident it is necessary to develop a methodology which takes cognizance of the site characteristics likely to influence the accident's impact zone. In this paper the technique of cellular automata (CA) has been used, in all probability for the first time ever, as a basis to develop a new methodology for assessing the consequences of an accident occurring in a chemical process industry. CA was originally developed by von Neumann to model life-like processes but until recently its use was very limited due to its need for expensive computer time. The technique is now experiencing a resurgence as the falling cost-capability ratio of computers has made CA increasingly affordable. In the CA-based methodology presented here, we have treated an industrial accident as an event occurring in a hypothetical square-shaped ‘cell’, surrounded on all sides by other square ‘cells’ of identical area. The grid simulates the accidental site and the model correlates all the cells of the grid with each other on the basis of ‘influencing’ or ‘transition’ functions; these functions, in turn, are governed by the cell characteristics—in other words the composition of the fragment of the site represented by that cell. The accident is modeled to proceed in small but discrete time-steps; in each step the impact of the ‘seed cell’ (the one in which the accident occurs) causes the state of the other cells to change in accordance with the appropriate transition function. It is, therefore, possible to take into account the nature of space that lies between the accident epicentre and the receptor in each direction. As a consequence ‘the impact zone’ of any accident can be forecasted much more accurately than possible hitherto. The applicability of the methodology has been demonstrated with the help of an illustrative case study.

Cushioning the impact of toxic release from runaway industrial accidents with greenbelts

Abstract The three aspects of accidents in chemical process industries which cause most serious damage—explosions, fires, and toxic releases—can all be controlled to some extent if greenbelts are present around the affected industry. We have recently developed and validated a system of methodologies for greenbelt design. In this paper we present the application of these models in designing greenbelts and forecasting their role in cushioning the impact of accidental release of toxic gases. With properly located and designed greenbelts as much as 33% of the accidental release of SO2, 43% of H2S, and 51% of NH3 under stable atmospheric conditions (in which the dispersion is very slow and the release thus has maximum toxic impact) can be absorbed.

Major accidents in process industries and an analysis of causes and consequences

Abstract This paper briefly recapitulates some of the major accidents in chemical process industries which occurred during 1926–1997. These case studies have been analysed with a view to understand the damage potential of various types of accidents, and the common causes or errors which have led to disasters. An analysis of different types of accidental events such as fire, explosion and toxic release has also been done to assess the damage potential of such events. It is revealed that vapour cloud explosion (VCE) poses the greatest risk of damage. The study highlights the need for risk assessment in chemical process industries.

Inherently safer design based on rapid risk analysis

Abstract The importance of inherently safer design (ISD) as a strategy to minimize risk of accidents in chemical process industries is being repeatedly stressed in recent years. The increasing number, frequency, and extents of damage caused by such accidents across the world have contributed to this thinking. However even as the need for ISD is being underscored, there are very few reports on precise methods to implement this concept. Significant recent reports are by Berge (1993 Berge, 1995) who has suggested a scenariobased design procedure in which construction of accident scenarios in a structured manner is made the basis of ISD. We have been developing and applying the concept of rapid risk analysis ( Khan & Abbasi, 1995 , Khan & Abbasi, 1996 , Khan & Abbasi, 1997a , Khan & Abbasi, 1997b , Khan & Abbasi, 1998a , Khan & Abbasi, 1998b ). In this paper we present an approach to ISD utilizing this concept. We believe, as detailed in this paper, that this approach is a significant improvement upon Berge's procedure in terms of ease, speed, and effectiveness.