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The existing methods for calculating overpressure resulting from a vapour cloud explosion (VCE) were tested for their ability to predict overpressures from unconfined hydrogen explosions. For it, data collated from five reported experimental investigations on open air hydrogen explosions covering 1.4–300 m3 volume of hydrogen-air mixtures and concentrations ranging 20–57% were employed. It was found that the existing VCE models are grossly inadequate for predicting the overpressure generated by unconfined hydrogen explosions. A new method was then developed for assessing overpressures from hydrogen explosions for a given concentration and volume of release based on Sach's scaling laws. The new model has much greater ability to fit the experimental data, hence much stronger ability to forecast the severity and consequences of hydrogen-based VCEs compared to the existing models.

When two or more pool fires burn in close enough proximity to influence one another, the resultant combination is termed ‘multiple pool fire’ (MPF). Even though MPFs occur fairly often in chemical process industries, with highly destructive consequences, much lesser work has been done towards simulation, modeling, and control of MPFs than on stand-alone pool fires. Among the factors which strongly influence the interaction among the MPFs, and the consequent damage MPFs may cause, the most important is the type of fuel contained in the individual pools. This aspect affects the temperatures of the interacting flames, their soot production, and the resultant radiation load. However, studies to dynamically model this aspect have not been carried out so far. In this paper an attempt has been made, arguably the first of its kind, to explore the efficacy of computational fluid dynamics (CFD) in simulating the effect of fuel types on MPF clusters. A fair agreement has been found between the CFD simulation and the experimental findings reported by Vincent and Gollahalli (1995). The agreement between the experimental data and CFD simulation results is good considering the fact that the soot production has not been accounted by us.

Multiple pool fires (MPFs) is the term used to denote pool fires which occur close enough of each other to influence each other. Even though much lesser attention has been paid to the understanding and control of MPFs, in comparison to stand-alone pool fires (SPFs), MPFs are by no means uncommon in chemical process industries. Worse, most of the MPFs–such as the ones that occurred at Buncesfield (UK) in 2005, and Jaipur (India) in 2009–are so powerful that they defy all attempts of quenching them and continue to rage till the fuel that was feeding them gets exhausted. Such fires cause enormous damage to property, besides loss of lives as occurred at Jaipur. Of the several factors that influence the destruction potential of the MPFs, pool size and separation distance between pools (S) to diameter (D) ratio (S/D) were expected to be the key factors. But no study has been done so far to analyse the effect of pool size and S/D ratio on MPFs and the present paper attempts to bridge this knowledge gap. Computational fluid dynamics (CFD) was used to model the effect of pool sizes on MPFs. The model was validated with the experimental data generated earlier by Fukuda et al. (2005). The validated code was then used to simulate the burning rate of MPFs involving pools of diameters larger than the ones used by Fukuda et al. (2005). It was observed that flame temperature, flame height, and the burning rate, all increase with an increase in the pool diameter of the participating pools in the MPFs. It was also observed that of the four S/D ratios — 0.25, 0.45, 0.66 and 1.08 — for which we have done the simulations, maximum flame height and burning rates accrues with the S/D ratio of 0.45.

When two or more pool fires burn in such close proximity of one another that they can influence each other, they are termed ‘multiple pool fires’ (MPF). The characteristics and the structure of MPFs are significantly different from that of stand-alone pool fires. Even though MPFs have known to occur fairly often in chemical process industries, much lesser work has been done towards simulation, modeling and control of MPFs as compared to stand-alone pool fires. This paper is perhaps the first-ever attempt at surveying the MPF state-of-the-art. It recounts MPF accidents and catalogs the controlled experiments that have been done to understand the mechanism and impact of MPFs. Attempts to model MPFs have been assessed and possible ways to manage MPFs have been touched upon.

Pool fires are the most common of all process industry accidents. Pool fires often trigger explosions which may result in more fires, causing huge losses of life and property. Since both the risk and the frequency of occurrence of pool fires are high, it is necessary to model the risks associated with pool fires so as to correctly predict the behavior of such fires. Among the parameters which determine the overall structure of a pool fire, the most important is turbulence. It determines the extent of interaction of various parameters, including combustion, wind velocity, and entrainment of the ambient air. Of the various approaches capable of modeling the turbulence associated with pool fires, computational fluid dynamics (CFD) has emerged as the most preferred due to its ability to enable closer approximation of the underlying physical phenomena. A review of the state of the art reveals that although various turbulence models exist for the simulation of pool fire no single study has compared the performance of various turbulence models in modeling pool fires. To cover this knowledge-gap an attempt has been made to employ CFD in the assessment of pool fires and find the turbulence model which is able to simulate pool fires most faithfully. The performance of the standard k – ɛ model, renormalization group (RNG) k – ɛ model, realizable k – ɛ model and standard k – ω model were studied for simulating the experiments conducted earlier by Chatris et al. (2001) and Casal (2013) . The results reveal that the standard k – ɛ model enabled the closest CFD simulation of the experimental results.

Quantification of spatial and temporal concentration profiles of vapor clouds resulting from accidental loss of containment of toxic and/or flammable substances is of great importance as correct prediction of spatial and temporal profiles can not only help in designing mitigation/prevention equipment such as gas detection alarms and shutdown procedures but also help decide on modifications that may help prevent any escalation of the event. The most commonly used models – SLAB ( Ermak, 1990 ), HEGADAS ( Colenbrander, 1980 ), DEGADIS ( Spicer & Havens, 1989 ), HGSYSTEM ( Witlox & McFarlane, 1994 ), PHAST ( DNV, 2007 ), ALOHA ( EPA & NOAA, 2007 ), SCIPUFF ( Sykes, Parker, Henn, & Chowdhury, 2007 ), TRACE ( SAFER Systems, 2009 ), etc. – for simulation of dense gas dispersion consider the dispersion over a flat featureless plain and are unable to consider the effect of presence of obstacles in the path of dispersing medium. In this context, computational fluid dynamics (CFD) has been recognized as a potent tool for realistic estimation of consequence of accidental loss of containment because of its ability to take into account the effect of complex terrain and obstacles present in the path of dispersing fluid. The key to a successful application of CFD in dispersion simulation lies in the accuracy with which the effect of turbulence generated due to the presence of obstacles is assessed. Hence a correct choice of the most appropriate turbulence model is crucial to a successful implementation of CFD in the modeling and simulation of dispersion of toxic and/or flammable substances. In this paper an attempt has been made to employ CFD in the assessment of heavy gas dispersion in presence of obstacles. For this purpose several turbulence models were studied for simulating the experiments conducted earlier by Health and Safety Executive, (HSE) U.K. at Thorney Island, USA ( Lees, 2005 ). From the various experiments done at that time, the findings of Trial 26 have been used by us to see which turbulence model enables the best fit of the CFD simulation with the actual findings. It is found that the realizable k – ɛ model was the most apt and enabled the closest prediction of the actual findings in terms of spatial and temporal concentration profiles. It was also able to capture the phenomenon of gravity slumping associated with dense gas dispersion.

The phenomenon of superheating of liquids has fostered the development of several beneficial technologies and has the potential of revolutionizing the design and application of thermal micro-machines. But liquid superheat is also behind some of the most common and destructive accidents in the process industry. These include boiling liquid expanding vapor explosion (BLEVE), which occurs when a vessel storing pressure liquefied gas such as propane, chlorine, or ammonia is accidentally depressurized. Superheating was also responsible for the catastrophic release of methyl isocyanate in Bhopal. Besides great losses of life and inanimate assets, such accidents often cause severe environmental contamination. In nuclear industry superheated liquids pose an ever-present threat of thermo-hydraulic explosion if a leak or a break occurs in a pipeline carrying a superheated coolant. In metallurgical industries accidental contact of molten metal with another substance of much lower boiling point—such as water—can superheat the latter, causing explosion of great severity and destructive potential. Accidental dropping of water in hot oil and the resulting explosive vaporization of superheated water has been identified as the cause the largest number of household kitchen accidents. Even as knowledge of superheat limit temperature (SLT)—which is the temperature above which a liquid cannot exist at a given pressure—is central to the safe design and control of several industrial operations, reliable experimental or theoretical methods do not exist with which SLT can be determined accurately or quickly. In this paper we describe an attempt to develop a framework with which SLT of new substances can be theoretically determined with fair degree of confidence. Seven cubic equation of state (EOS) have been transformed by the application of the Maxwell's and the SLT criteria to eliminate those parameters of which correct values cannot be determined with certainty. The transformed equations have then been solved to generate SLT values. A comparison between the calculated and the observed values has been done for 75 industrial chemicals. It reveals that for a large number of chemicals the transformed Redlich–Kwong (RK) EOS is able to predict the SLT within less then 1% deviation from its experimental value. In case of the SLT of noble gases the transformed van der Waals (vdW) EOS has the best predictive ability. Only in a very few cases other EOS give a closer fit than the RK-EOS and the vdW-EOS. The ‘second best fit’ is almost always achieved with either the RK-EOS or the Twu–Redlich–Kwong (TRK) EOS.

Maximum credible accident analysis is one of the most widely used concepts in risk assessment of chemical process industries. Central to this concept is the aspect of ‘credibility’ of envisaged accident scenarios. However, thus far the term credibility is mostly treated qualitatively, based on the subjective judgement of the concerned analysts. This causes wide variation in the results of the studies conducted on the same industrial unit by different analysts. This paper presents an attempt to develop a criterion using which credible accident scenarios may be identified from among a large number of possibilities . The credible scenarios thus identified may then be processed for detailed consequence analysis. This would help in reducing the cost of the analysis and prevent undue emphasis on less credible scenarios at the expense of more credible ones.

An increase in the number of accidents in the process industries and the concomitant damage potential is a cause of concern in many countries. In order to control the alarming risk posed by these industries, the United States government has asked each manufacturing facility to carry out a worst-case disaster study and to develop alternatives to control this high risk. Other developed and developing countries such as Canada and India have taken similar measures. Recently Khan and Abbasi (J. Loss Prevent. Process Ind. (2001a) in press) have proposed a maximum credible accident analysis with a maximum credible accident scenario approach, which scores over a worst-case scenario approach for being realistic and reliable. In another effort, Khan and Abbasi (J. Hazard. Mater. (2001b) in press) have developed an efficient and effective algorithm for probabilistic fault tree analysis. These two approaches have been combined to yield a new methodology for a more realistic, reliable, and efficient safety evaluation and the design of risk control measures. The methodology is named SCAP: Safety, Credible Accident, Probabilistic fault tree analysis. The methodology is comprised of four steps of which the last step is a feedback loop. This paper recapitulates this methodology and demonstrates its application to ethylene oxide (EO) plants. The application of SCAP to EO plants identifies five units as risky and needing more safety measures. Further, this study recommends safety measures and demonstrates through SCAP that their implementation lower the risk to an acceptable level.

A computer-automated tool TORAP, developed recently by us, has been applied to conduct an illustrative risk assessment of a typical fertilizer plant. Hazardous units have been identified and elaborate scenarios have been generated of the accidents likely in these units. The consequences of the accidents, in terms of the damage to life and property that they may cause directly as well as the likelihood of causing secondary and higher-order accidents (domino effect), have also been studied. Apart from demonstrating the applicability of TORAP, these studies reveal the nature and size of several major hazards existing in a typical fertilizer plant. The studies also, indirectly, highlight the lack of seriousness with which such hazards are normally perceived, and emphasize the need for a thorough reassessment of the risk posed by such industries.

In the context of risk assessment and loss prevention in chemical process industries, the term domino effect denotes ‘chain of accidents’, or situations when a fire/explosion/missile/toxic load generated by an accident in one unit in an industry causes secondary and higher order accidents in other units. Most of the past risk assessment studies deal with accident in a single industry, more so in one of the units of an industry. But, often, accident in one unit can cause a secondary accident in a nearby unit, which in turn may trigger a tertiary accident, and so on. The probability of occurrence and adverse impacts of such ‘domino’ or ‘cascading’ effects are increasing due to increasing congestion in industrial complexes and increasing density of human population around such complexes. The multi-accident catastrophe which occurred in a refinery at Vishakhapatnam, India, on 14 September 1997, claiming 60 lives and causing loss of property worth over Rs 600 million, is the most recent example of the damage potential of domino effect [Lees F.P. Loss prevention in process industries, 2nd ed. Butterworths, 1-3, London; Khan, F.I., & Abbasi, S.A. (1999a). Major accidents in process industries and an analysis of their causes and consequences. Journal of Loss Prevention in Process Industries, 12, 361–378; Khan, F.I., & Abbasi, S.A. (1999b). The worst chemical industry accident of 1990's–what happened and what might have been: A quantitative study. Process Safety Progress, 18, 135–145]. Recently, we have proposed a systematic methodology called ‘domino effect analysis’ (DEA). A computer automated tool DOMIFFECT has also been developed by us based on DEA [Khan, F.I., & Abbasi, S.A. (1998a). Models for domino effect analysis in chemical process industries. Process Safety Progress — AIChE, 17 (2), 107–113; Khan, F.I., & Abbasi, S.A. (1998b). DOMIFFECT (DOMIno eFFECT): a new software for domino effect analysis in chemical process industries. Environmental Modelling and Software, 13, 163–177.]. The methodology is based on deterministic models used in conjunction with probabilistic analysis. This paper illustrates the application of DEA and DOMIFFECT to an industrial complex. Out of 16 credible accident scenarios envisaged in four closely situated industries namely Madras Fertilisers Limited (MFL), SPIC–Heavy Chemical Division (SPIC–HCD). Manali Petrochemical Limited (MPL), and Tamilnadu Petroproducts Limited (TPL), ten scenarios forecast domino effect. Further analysis reveals that accidents in the ammonia synthesis unit, secondary reformer, and urea reactor of MFL may cause domino effect. Similarly, accidents in the storage units of propylene oxide, ethylene oxide and mono propylene glycol at MPL, hydrogen storage units at SPIC–HCD, and the propylene oxide and fuel oil storage units of TPL are likely to cause a domino effect. The consequences of all these credible accidents have also been forecast. The paper makes a strong case for making DEA an integral part of all risk assessment initiatives.

This paper presents a risk assessment study of a typical chemical process (sulfolane manufacturing) industry using optimum risk analysis (ORA) methodology recently proposed by these authors ( Khan, F. I., & Abbasi, S. A. (1995) . Risk analysis; a systematic method for harzard identification and assessment. Journal of Industrial Pollution Control, 9(2), 66; Khan, F. I., & Abbasi, S. A. (1998a). Techniques for risk analysis of chemical process industries. Journal of Loss Prevention in Process Industries, 11(2), 91.) The paper also describes briefly the different steps of ORA methodology and the available techniques and tools to conduct each step of the ORA. The study suggests that the reactor and the storage units of the industry are highly vulnerable to accidents and need elaborate safety arrangements. The damage potential of these units is such that its impact would permeate far beyond the plant boundaries and would cause damage to nearby areas. A few recommendations have been made to reduce the existing risk potential. However, the industry still needs to have high level safety arrangements and emergency procedures in position to counter any unwanted situation in the industry.

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.

The paper describes the application of a new computer automated tool, developed by us, in the risk analysis of a typical chemical industry engaged in the manufacture of linear alkyl benzene. Using the tool—a comprehensive software package maxcred-III (MAXimum CREDible accident analysis)—nine different scenarios, one for each storage unit, have been studied. It is observed that the accident scenario for chlorine (instantaneous release followed by dispersion) leads to the largest area-under-lethal-impact, while the accident scenario for propylene (CVCE followed by fireball) forecasts the most intense damage per unit area. The accidents involving propylene, benzene, and fuel oil have a high possibility of causing domino/secondary accidents as their destructive impacts (shock waves, heat load) would envelope other storage and process units. Besides demonstrating the utilizability of maxcred-III, this study also focuses attention on the need to bestow greater effort towards risk assessment/crisis management. The authors hope that the study will highlight the severity of the risk posed by the industry and thus generate safety consciousness among plant managers. The study may also help in developing accident-prevention strategies and the installation of damage control devices.

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.

The use of a new computer-automated tool TORAP (TOol for Rapid risk Assessment in Petroleum refinery and petrochemical industries) is demonstrated through a rapid and quantitative risk assessment of a typical petroleum refinery. The package has been applied for an appraisal of the risks of accidents (fires, explosions, toxic release) posed by different units of the refinery, and to identify steps to prevent/manage accidents. The studies reveal that TORAP enables a user to quickly focus on the accidents likely to occur, and enables forecasting the nature and impacts of such accidents. This information is directly utilisable in identifying “soft” spots and in taking appropriate remedial measures to prevent or control accidents. The special attributes of TORAP are: (a) a wide range of applications—achieved by incorporating models capable of handling all types of industrial fires and explosions, (b) sophistication—brought about by including state-of-the-art models developed by these authors and others, (c) user-friendliness—achieved by incorporating on-line help, graphics, carefully formatted output, and, above all, an automatic module with which even a lay user can conduct risk assessment. The entire package, especially its automatic module, is supported by an extensive knowledge-base built into the software.

Dispersion of several common `heavy' gases (ethylene, propylene, ammonia, and chlorine) has been modelled on the basis of modifications in plume path theory. The model takes into account, among other things, the variations in temperature, density, and specific heat during the movement of the heavy gas plume. The effects of wind speed, density of the gas, and venting speed on the plume dispersion have been simulated. Based on the simulations a set of empirical equations has been developed. The equations have been validated by theoretical as well as experimental studies. Studies have also been carried out to simulate the effect of venting speed (manipulated by injecting hot air with the released gas) on the plume dispersion. The study reveals that the effect of venting speed on dispersion is very pronounced and can be used to reduce the risk posed by the accidental luxurious release of toxic/flammable gases. For example an increase of 20% in venting speed of chlorine (54.1 m/s) can reduce the distance up to which toxic concentration would occur by about 1100 meters.

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.

This paper presents a state-of-art-review of the available techniques and methodologies for carrying out risk analysis in chemical process industries. It also presents a set of methodologies developed by the authors to conduct risk analysis effectively and optimally.

Hazard and operability (HAZOP) studies constitute an essential step in the risk analysis of any chemical process industry and involve systematic identification of every conceivable abnormal process deviation, its causes and abnormal consequences. These authors have recently proposed optHAZOP as an alternative procedure for conducting HAZOP studies in a shorter span of time than taken by conventional HAZOP procedure, with greater accuracy and effectiveness [Khan, F. I. and Abassi, S. A., optHAZOP. An effective and efficient technique for hazard identification and assessment Journal of Loss Prevention in the Process Industries, 1997, 10, 191–204]. optHAZOP consists of several steps, the most crucial one requires use of a knowledge-based software tool which would significantly reduce the requirement of expert man-hours and speed up the work of the study team. TOPHAZOP (Tool for OPTmizing HAZOP) has been developed to fulfil this need. The TOPHAZOP knowledge-base consists of two main branches: process-specific and general. The TOPHAZOP framework allows these two branches to interact during the analysis to address the process-specific aspects of HAZOP analysis while maintaining the generality of the system. The system is open-ended and modular in structure to make easy implementation and/or expansion of knowledge. The important features of TOPHAZOP and its performance on an industrial case study are described.

To conduct effective and efficient HAZOP (Hazard and Operability) study it is essential that the study should be planned and managed well. The planning and management can be done effectively only when the various steps of the study, scope of each step, and duration of each step are well defined. Significant work has been done over the identification of various applications of HAZOP, but not much work has been done over HAZOP study duration estimation, which is a key parameter for proper planning and management of HAZOP study. Freeman et al. (1992) [6] have proposed a model for HAZOP study time (duration) estimation, however, it still needs modification in terms of easy application and more reliable estimation. The present work is an effort in the same direction, a mathematical model being proposed to forecast (estimate) the HAZOP study duration for varying capacity and complexity of the problem. The accuracy of the results has been checked with some of the past case studies carried out by various agencies. It has been observed that the authors' model predicts result with accuracy of about 90–95%, while Freeman's model is restricted to 85–90%. Moreover, the proposed model is simple, easy to implement, and can be automated to software.

Qualitative hazard assessment is part of the detailed risk analysis of chemical process industries and a hazard and operability (HAZOP) study is the best technique to carry out this step. It is a systematic study conducted by a team of experts of different disciplines to identify and assess hazards using brainstorming discussion of deviation in operational parameters from normal/standard conditions. This study needs high levels of expertise and substantial time commitments. The various steps involved in any typical HAZOP (application of deviation, cause-finding, and consequence analysis of each and every line and equipment) need a sustained high level of mental performance and alertness for a long span of time, but the repetitious nature of these steps inevitably generates a feeling of drudgery and mental fatigue, even exhaustion. This may not only reduce the effectiveness of HAZOP, but even render it incomplete or erroneous. This paper is devoted to a discussion about the factors that have direct influence on the efficiency, effectiveness and reliability of such studies. It also suggests an optimal approach to HAZOP study procedures (optHAZOP) based on the utilization of an already developed information base. The optHAZOP technique reduces the mental execution load of experts by a half, and thus provides more time to study typical hazardous units and conceptualize better control strategies. This technique takes around 45% less time than that of the conventional HAZOP study procedure (estimated using CPM networking and time analysis of different steps of study) with better efficiency and effectiveness.

Studies pertaining to risk analysis, conducted on the storage units of a typical chemical industry engaged in the manufacture of epichlorohydrin, are described. A comprehensive software package MAXCRED (MAXimum CREDible accident analysis) recently developed by us has been utilized for the purpose. Eight different scenarios, one for each storage unit, have been studied. It is observed that the accident scenario for chlorine (BLEVE followed by dipersion) leads to the largest area-under-lethal-impact while the accident scenario for propylene (CVCE followed by fire ball) forecasts the most intense damage per unit area. The accidents involving propylene, epichlorohydrin and fuel oil have high possibility of causing domino/secondary accidents as their destructive impacts (shock waves, heat load) would envelope other storage and process units. Besides demonstrating the utilizability of MAXCRED, this study also focuses attention on the need to bestow greater effort towards risk assessment/crisis management. The authors hope that these studies would highlight the severity of risk posed by the industry and would thus generate safety consciousness among plant managers. The studies may also help in developing accident-prevention strategies and installation of damage control devices.