- Email: [email protected]
CFD modeling of large-scale flammable cloud dispersion using FLACS
Journal of Loss Prevention in the Process Industries xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Journal of Loss Prevention in the Process Industries journal homepage: www.elsevier.com/locate/jlp
CFD modeling of large-scale flammable cloud dispersion using FLACS Ankit Dasgotra, G.V.V. Varun Teja, Ankit Sharma, Kirti Bhushan Mishra∗ Technological Risk Research and Analysis Group TRAG, Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
A R T I C L E I N F O
A B S T R A C T
Keywords: CFD models FLACS Flammable cloud dispersion Explosion
The number of accidents in oil and gas refineries/storage terminals are increasing worldwide. Such events are disastrous to both human beings and infrastructure. It is therefore necessary to utilize the best methods to study worst-case scenarios associated with a process and/or plant. Computational Fluid Dynamics (CFD) models are appropriate to perform 3D modeling of major events with all necessary details. The present work reports the 3D CFD modeling of large-scale flammable cloud dispersion in a real configuration. The most widely approved CFD code for dispersion and explosion simulation FLACS (Flame Acceleration Simulator) is used to simulate the gases released with different flow rates in storage terminals. It was assumed that leak began near the pipes supplying fuel to the storage tank. The flow rate, surrounding condition and release duration were varied to study their influence on overall vapor cloud size i.e. diameter, height and explosive strength. Depending on the extent of LFL and UFL (Lower and Upper Flammability Limit) total flammable volumes of the clouds were predicted. It was found that such detailed modeling helped to understand the dispersion behavior much better than the phenomenological models. The strategic decisions on gas detectors layout can also be made for loss prevention and control. The simulation of worst-case scenario provided guidelines for pre- and post-incident mitigation measures.
1. Introduction Fuels obtained from refinement of crude oil continue to be the major sources of energy for transportation and power generation. These fuels constitute diesel, petrol, cleaner burning natural gas and petroleum gas which is now being used extensively in liquefied forms. To keep up with the growing needs of energy, many import, process and refinement facilities are proposed and are expected to be set up in India. With the growing number of facilities, there are increasing concerns about potential hazards these facilities pose (Hightower et al., 2004; Qi et al., 2010; Mishra et al., 2014; Woodward and Pitbaldo, 2010; Hansen, 2010). These hazards may vary from exposure to hazardous chemicals, fire and explosion. One of the major hazards from accidental leak of fuel is the formation flammable vapor cloud which drifts downwind direction (Qi et al., 2010). If any ignition source is present and the vapor cloud is within the flammable range, then it could ignite and lead to a fire or a vapor cloud explosion. The recent accidents occurred in Buncefield (2005), Puerto-Rico, USA (2009) and Jaipur, India (2009) have raised concerns for detailed scientific investigation to develop appropriate safety measures for future plants (Mishra et al., 2014). To ensure work place and public safety in surrounding areas, every facility has the need to use a validated consequence model to study and
∗
identify the potential hazards in case of an accidental release of fuel from any part of the facility. There are several consequence models developed which can be grouped under three categories, Gaussian models, Integral models and CFD models. Integral models such as HEGADIS (Heavy Gas Dispersion) and DRIFT models have been widely used because they do not require much computational time and are easy to use too (Woodward and Pitbaldo, 2010). But these models are limited to free-field dispersion with no obstructions and are generally not applicable to the geometries we encounter in real life situations. Today, the increased computational capacities have made it possible to utilize detailed 3D CFD models over phenomenological models. CFD models work by solving 3D Navier-Stokes equations without any scaling constraint. It allows simulation over real geometries including terrains with obstructions, transitions, varying boundary and atmospheric conditions. FLACS is a specialized CFD tool for safety applications. It is one of four CFD codes that published validations for LNG dispersion (Woodward and Pitbaldo, 2010; Hansen et al., 2007, 2010; Arntzen, 1998; Flacs, 2015). As a part of analysis in this work modeling of a large-scale flammable vapor cloud dispersion are performed using FLACS and the effects of obstructions, transitions (transition from subsonic combustion (deflagration) to supersonic combustion
Corresponding author. E-mail address: [email protected] (K.B. Mishra).
https://doi.org/10.1016/j.jlp.2018.01.001 Received 27 February 2017; Received in revised form 29 November 2017; Accepted 2 January 2018 0950-4230/ © 2018 Elsevier Ltd. All rights reserved.
Please cite this article as: Dasgotra, A., Journal of Loss Prevention in the Process Industries (2018), https://doi.org/10.1016/j.jlp.2018.01.001
Journal of Loss Prevention in the Process Industries xxx (xxxx) xxx–xxx
A. Dasgotra et al.
characteristics were carried out with CFD simulation in (Mishra, 2015; Pontiggia et al., 2011). The important findings are listed below.
(detonation)) and atmospheric conditions on dispersion of vapor cloud are studied. The three dimensional models of real plants are constructed and respective physics and boundary conditions are imposed to predict the diameter and height of cloud constituting within flammability limits. Such estimation finally help to establish realistic total volume of vapor cloud that actually contributes towards explosion overpressure.
1) The vapor density of released substance is crucial for the total vapor cloud characteristics. 2) The variable wind boundary conditions helped cloud to mix and spread much faster than the atmospheric boundary layer equations. 3) The presence of obstacles on the cloud path altered the overall dispersion extent and appearance. 4) The characteristics of cloud formed in cases of ground and elevated releases were different. 5) The reduction in gravitational acceleration also changed the cloud characteristics.
2. Objective The present work demonstrates the capability of CFD simulations to predict the characteristics of flammable vapor cloud dispersion in a large region (Mishra et al., 2014). Since experiments for such scenarios are not realizable 3D modeling and results on flammable volume above the ground level provide very useful information for assessing the risks to the people, nearby infrastructure and environment. Typical accidents involving dispersion and explosion that may occur in fuel storage terminals are reconstructed in this work. Due to several complexities e.g. atmospheric conditions and congestion due to plant items and vegetation present in a plant it is very difficult to assess the vapor cloud characteristics correctly with semi-empirical models. As a result of improper estimation of vapor cloud dimensions the equivalent explosive source is also not correctly calculated. Since correct estimation of this explosive potential is necessary to make decisions on land use planning for a plant it is necessary that all the best possible methods are used to develop an appropriate explosive mass. Prediction of this explosive mass correctly in worst-case incident by CFD models is the main aim of this article. The findings of this work can be used for the present and future plants for qualitative and quantitative risk assessment studies.
For modeling and simulation of the above cases FLACSv10.4 code (Flacs, 2015) has been used. It is an effective code to simulate high momentum jet leaks and subsequent gas dispersion in a model of an offshore module. Simulations of dispersion with high momentum jet leaks requires hours of CPU usage due to short time-steps and duration of long leak. In FLACSv10.4 the high momentum jet is modeled as conserving the flow of mass and momentum. By assuming isenthalpic expansion, it is possible to calculate the expansion of a sonic flow analytically. In summary, FLACS code has built-in facilities as handling realistic gas dispersion scenarios with external wind fields, various types of leak sources and wall-functions. A modified version of FLACS code has been used to simulate release of gas from high pressure pipelines, taking non-ideal gas effects into account. These results showed that the lower flammability limit of gas-air mixture reaches its most remote downstream position relatively early, before drawing in additional air somewhere. Due to the above features FLACS was chosen to simulate the considered scenarios in this work. Apart from the validation studies of various large-scale dispersion tests FLACS has also been used as an accidental scenario investigation tool by many authors in the past (Hansen et al., 2007, 2010; Arntzen, 1998; Flacs, 2015).
3. Background The rest of the paper has been divided into two parts. The first part referred to as case I describes the scenario of dense gas dispersion occurring in real-scale storage terminal (Fig. 1). All essential components are considered and 3D models for the same are created. The second part referred to as case II of the paper deals with the Jaipur oil terminal fire which broke out on 29 October 2009 at 7:30 p.m. (IST) at the Indian Oil Corporation (IOC) tank holding 8000 kL of oil, in Sitapura industrial area on the edges of Jaipur, Rajasthan, causing deaths of 12 individuals and harming more than 200 (Web1, 2017). A number of studies and reports are published on this incident (Mishra et al., 2013, 2014; IOC Fire Accident Investigation Report, 2011). However, CFD modeling and simulation work on this incident to study dispersion of fuel have not been performed yet. Thus, for the study of dispersion of vapor cloud at IOCL, Jaipur Terminal is also considered to reconstruct the incident. Fig. 2 shows the actual and modeled layouts of the facility. A comprehensive study on the parameters influencing vapor cloud
4. Modeling methodology FLACS mainly consists of three software parts: Computer Aided Scenario Design (CASD), Flacs Simulator, Flowvis (Flow Visualization). CASD is used to prepare the input data that defines a FLACS simulation, is basically a preprocessor. This comprises geometry model, computational grid, porosities, and scenarios. Flowvis, the postprocessor is a program for visualizing results from simulations of gas dispersion and gas explosion. In present simulations also in first part, all 3d model of the plant was built and boundary conditions were imposed on different parts. The mass and momentum equations were solved and results were visualized using Flowvis.
Fig. 1. The geometry used for modeling of typical oil storage/tankage facility.
2
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Fig. 2. 3D model of IOCL Jaipur facility showing the the possible leak origin.
Fig. 3. 2D cut plane of vapor cloud dispersion at height of 1 m from ground.
grid volumes were constructed. The finer the grid, the more computationally difficult it is to solve the simulation. Thus, the domain was divided uniformly into 200 control volumes along X, Y and Z direction. For case II i.e. Jaipur incident simulation the whole domain was descretized into 640000 control volumes. The selection of grid plays a great role in the solution of a CFD simulation. However, considering the large domains (∼ km) in present simulations the smaller size grids are not feasible to construct. Depending on the accuracy demanded from simulation results optimum grids were selected. It was found that further refinement than the selected grid did not improve the results by ±10%.
4.1. Geometry 4.1.1. Case 1: model for dense gas dispersion simulation The model is made of approximately same dimensions as the actual facility without any scaling. The objects of box and cylinder type are used for construction of different plant items. The heights of dykes were assumed to be of 5 m and boundary wall as 6 m. The tanks were approximated to be of proportion Height H = 1.25* Diameter(d) of tank. The relative positions and dimensions of dykes, walls, tanks and buildings are mapped from the data available through wikimapia (Web1, 2017). The built model is shown in Fig. 1. 4.1.2. Case 2: reconstruction of IOCL Jaipur accident 2009 The similar approach as above was followed here too. The variety of items e.g., building, control room, car parking, pump house and piping were created to replicate the actual plant. The leak origin was specified as shown in Fig. 2 where the fuel was being fed into the nearby tank.
4.3. Scenario settings FLACS allows to define various initial and boundary conditions for simulation. For this the wind speed is set to 2 m/s initially. The atmosphere is considered stable with relative turbulence set to 0. Setting relative turbulence to zero help achieving zero/calm wind conditions similar to that prevail in most of the accidental sites. The temperature and pressure are set to 20° C and 0.1 MPa. The roughness of ground was set to 0.0002 m. Propane was allowed to leak at various mass flow rates
4.2. Grid and porosities To study the grid dependency of predicted LFL distances different 3
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Fig. 4. 2D cut plane of vapor cloud dispersion at height of 3 m from ground.
Fig. 5. 2D cut plane of vapor cloud dispersion at height of 5 m.
through an area of 5 m2. The leak sizes were assumed based on the size of the pipe transferring fuel to the tank. The size of the leak was chosen according to the pipe diameter 2.5 m and orientation of leak was of Jet type in Y direction. The fuel leaks from t = 10 s to t = 3600 s at defined mass flow rates. Propane was used prior to octane as a dispersing fuel in order to study the difference in behavior between them. In case II, octane leaks occurring at various mass flow rates from an area of 1 m2 are simulated. Two cases as the fuel leaks from t = 20 s to t = 1800 s (tmax = 2000 s) at mass flow rate of 50 kg/s and fuel leaks from t = 10 s to t = 900 s (tmax = 1000 s) at mass flow rate of 25 kg/s are considered. The reasons for selecting octane as a fuel are to reproduce the leak of gasoline vapors and to simulate dense vapor cloud dispersion in a real-scale plant. As in the Jaipur and Buncefield incidents the leaked media was gasoline hence it has been selected as a fuel in this particular case.
5. Validation studies FLACS has already been well validated and approved as a CFD code for risk assessment studies for variety of gas dispersion cases. In (Hansen, 2010; Flacs, 2015) the large-scale experiments (China Lake, Burro, Coyote) conducted in the USA were reproduced with FLACS and good agreement between measured and predicted values was obtained for different atmospheric conditions. An extensive validation work on the applications of FLACS has already been done before and reported in (Hansen et al., 2007, 2010; Flacs, 2015) this is not repeated here.
6. Results and discussion 6.1. Case I: release of dense gas in a model oil and gas storage facility The results for the 50 kg/s case are shown in Figs. 3–5 for different heights i.e., 1 m, 3 m and 5 m, respectively, from ground. The blue and red color represent the lower and upper flammability limits for 4
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Fig. 6. Contour plot of vapor cloud at t = 77 s from the start of leak.
Fig. 7. Contour plot of vapor cloud at t = 1084 s from the start of leak.
Buncefield, 2005, Puerto-rico 2009 and IOCL, Jaipur, 2009 (Mishra et al., 2014, 2013). They provide useful information on the consideration of total loss of content for the determination of source term following which potential mitigation measures can be decided.
propane. The maximum height of the pancake shaped cloud was found to be 5 m. The fuel leak lasts for 1 h and forming a large thick vapor cloud which can disperse throughout the facility. It is important to mention that the height of cloud in case of more dense gas (octane vapors) was higher than in case of less dense one (propane) as will be shown in next section. The average diameter of vapor cloud in all cases were found to be between 590 and 755 m with an average height of about 2 m. Total estimated volume of pancake shaped cloud considering the time averaged diameters and heights for the considered cases were between 1.3*106 m3 to 3.9*106 m3. Such large vapor cloud sizes were realistic from the recent accidents perspective e.g.,
6.2. Case II: reconstruction of IOCL Jaipur accident 2009 For case II, two cases of 50 kg/s and 100 kg/s leaking from a 1 m2 origin were simulated for different times so that the total escaped mass remains similar. These results were obtained for calm weather conditions representing the worst-case. The calm weather helps cloud to 5
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Fig. 8. Contour plot of vapor cloud dispersion at t = 2000 s from the start of leak.
make strategic decisions on locating the gas detectors, control room, pump house etc. and on pre and post-incident mitigation measures. This work is being further extended to study the various scenarios of gas explosions and resulting overpressures from them in the above facilities.
settle on the ground and accumulate. It then drifts slowly in the direction of wind covering the wider area of the plant. In case of strong wind the cloud will generally be carried away posing less threat of accumulation. The dispersion scenarios with 50 kg/s at different times in IOCL Jaipur plant has been shown in Figs. 6–8. The blue and red colors show LFL and UFL, respectively for octane vapors. It is evident from Figs. 6–8 that the cloud covers the whole plant in 1084 s (depicted at 1 m above ground). In case of 100 kg/s the cloud crossed the boundary of the plant and reached outside. The vapor cloud diameters in both the investigated cases were predicted to be between 800 and 900 m. The large diameters of vapor cloud corresponds well to previously reported data on accidents e.g. Buncefield and others (Mishra et al., 2014, 2013). In case of a worst-case the typical size of the vapor cloud in a comparable facility should not be considered less than 500 m. Such information on overall explosion potential of flammable cloud are vital for safer plant and process design.
References Arntzen, B.J., 1998. Modelling of Turbulence and Combustion for Simulation of Gas Explosions in Complex Geometries. PhD Thesis. NTNU, Norway. Flacs v10, 2015. 4r2 Users Manual. Confid. report. Gexcon AS, Bergen, Norway. Hansen, O.R., 2010. Validation of FLACS against experimental data sets from the model evaluation dtabase for LNG vapor dispersion. J. Loss Prev. Process. Ind. 23, 857–877. Hansen, O., Melheim, J., Storvik, I., 2007. CFD-modeling of LNG dispersion experiments. AIChE Spring Natl. Meeting. https://aiche.confex.com/aiche/s07/techprogram/ P77795.HTM. Hightower, M., Gritzo, L., Luketa-Hanlin, A., Covan, S., Tieszen, S., Wellman, G., Irwin, M., Kaneshige, M., Melof, B., Morrow, C., Ragland, D., 2004. Guidance on Risk Analysis and Safety Implications of a Large Liquefied Natural Gas (LNG) Spill over Water. DTIC Document SAND2004–6258. IOC Fire Accident Investigation Report, 2011. Oil Industry Safety Directorate, India. Mishra, K.B., 2015. CFD model for large hazardous dense cloud spread predictions, with particular reference to Bhopal disaster. Atmos. Environ. 117, 74–91. Mishra, K.B., Wehrstedt, K.D., Krebs, H., 2013. Lessons learned from recent fuel storage fires. Fuel Process. Technol. 107, 166–172. Mishra, K.B., Wehrstedt, K.D., Krebs, H., 2014. Amuay refinery disaster: the aftermaths and challenges ahead. Fuel Process. Technol. 198, 198–203. Pontiggia, M., Landucci, G., Busini, V., Derudi, M., Alba, M., Scaioni, M., Bonvicini, S., Cozzani, V., Rota, R., 2011. CFD model simulation of LPG dispersion in urban areas. Atmos. Environ. 45, 3913–3923. Qi, R., Ng, D., Cormier, B.R., 2010. M. Sam Mannan, Numerical simulations of LNG vapor dispersion in brayton fire training field tests with ANSYS CFX. J. Hazard Mater. 183, 1–3 51-61. https.//www.wikimapia.org/. Woodward, J., Pitbaldo, R., 2010. LNG Risk Based Safety: Modeling and Consequence Analysis. John Wiley & Sons, Inc ISBN: 9780470317648.
7. Conclusions and future work Three-dimensional CFD simulations of a dense gas dispersion in a real oil and gas storage facility were performed to study the overall volume of the accumulated flammable cloud representing the worstcase scenarios that have been observed in the recent incidents. The simulation results revealed that in all cases the average cloud diameters was in the range of 500 m–1000 m, for relatively calm weather conditions. Furthermore, it was found that the heights of octane cloud was much higher than propane cloud leading to larger total volume. The presence of major obstacles (tanks, pipings, buildings etc.) alter the cloud shape and size significantly. Such detailed information on possible scenarios is crucial for the risk assessor and safety professionals to
6
Contents lists available at ScienceDirect
Journal of Loss Prevention in the Process Industries journal homepage: www.elsevier.com/locate/jlp
CFD modeling of large-scale flammable cloud dispersion using FLACS Ankit Dasgotra, G.V.V. Varun Teja, Ankit Sharma, Kirti Bhushan Mishra∗ Technological Risk Research and Analysis Group TRAG, Department of Mechanical and Industrial Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
A R T I C L E I N F O
A B S T R A C T
Keywords: CFD models FLACS Flammable cloud dispersion Explosion
The number of accidents in oil and gas refineries/storage terminals are increasing worldwide. Such events are disastrous to both human beings and infrastructure. It is therefore necessary to utilize the best methods to study worst-case scenarios associated with a process and/or plant. Computational Fluid Dynamics (CFD) models are appropriate to perform 3D modeling of major events with all necessary details. The present work reports the 3D CFD modeling of large-scale flammable cloud dispersion in a real configuration. The most widely approved CFD code for dispersion and explosion simulation FLACS (Flame Acceleration Simulator) is used to simulate the gases released with different flow rates in storage terminals. It was assumed that leak began near the pipes supplying fuel to the storage tank. The flow rate, surrounding condition and release duration were varied to study their influence on overall vapor cloud size i.e. diameter, height and explosive strength. Depending on the extent of LFL and UFL (Lower and Upper Flammability Limit) total flammable volumes of the clouds were predicted. It was found that such detailed modeling helped to understand the dispersion behavior much better than the phenomenological models. The strategic decisions on gas detectors layout can also be made for loss prevention and control. The simulation of worst-case scenario provided guidelines for pre- and post-incident mitigation measures.
1. Introduction Fuels obtained from refinement of crude oil continue to be the major sources of energy for transportation and power generation. These fuels constitute diesel, petrol, cleaner burning natural gas and petroleum gas which is now being used extensively in liquefied forms. To keep up with the growing needs of energy, many import, process and refinement facilities are proposed and are expected to be set up in India. With the growing number of facilities, there are increasing concerns about potential hazards these facilities pose (Hightower et al., 2004; Qi et al., 2010; Mishra et al., 2014; Woodward and Pitbaldo, 2010; Hansen, 2010). These hazards may vary from exposure to hazardous chemicals, fire and explosion. One of the major hazards from accidental leak of fuel is the formation flammable vapor cloud which drifts downwind direction (Qi et al., 2010). If any ignition source is present and the vapor cloud is within the flammable range, then it could ignite and lead to a fire or a vapor cloud explosion. The recent accidents occurred in Buncefield (2005), Puerto-Rico, USA (2009) and Jaipur, India (2009) have raised concerns for detailed scientific investigation to develop appropriate safety measures for future plants (Mishra et al., 2014). To ensure work place and public safety in surrounding areas, every facility has the need to use a validated consequence model to study and
∗
identify the potential hazards in case of an accidental release of fuel from any part of the facility. There are several consequence models developed which can be grouped under three categories, Gaussian models, Integral models and CFD models. Integral models such as HEGADIS (Heavy Gas Dispersion) and DRIFT models have been widely used because they do not require much computational time and are easy to use too (Woodward and Pitbaldo, 2010). But these models are limited to free-field dispersion with no obstructions and are generally not applicable to the geometries we encounter in real life situations. Today, the increased computational capacities have made it possible to utilize detailed 3D CFD models over phenomenological models. CFD models work by solving 3D Navier-Stokes equations without any scaling constraint. It allows simulation over real geometries including terrains with obstructions, transitions, varying boundary and atmospheric conditions. FLACS is a specialized CFD tool for safety applications. It is one of four CFD codes that published validations for LNG dispersion (Woodward and Pitbaldo, 2010; Hansen et al., 2007, 2010; Arntzen, 1998; Flacs, 2015). As a part of analysis in this work modeling of a large-scale flammable vapor cloud dispersion are performed using FLACS and the effects of obstructions, transitions (transition from subsonic combustion (deflagration) to supersonic combustion
Corresponding author. E-mail address: [email protected] (K.B. Mishra).
https://doi.org/10.1016/j.jlp.2018.01.001 Received 27 February 2017; Received in revised form 29 November 2017; Accepted 2 January 2018 0950-4230/ © 2018 Elsevier Ltd. All rights reserved.
Please cite this article as: Dasgotra, A., Journal of Loss Prevention in the Process Industries (2018), https://doi.org/10.1016/j.jlp.2018.01.001
Journal of Loss Prevention in the Process Industries xxx (xxxx) xxx–xxx
A. Dasgotra et al.
characteristics were carried out with CFD simulation in (Mishra, 2015; Pontiggia et al., 2011). The important findings are listed below.
(detonation)) and atmospheric conditions on dispersion of vapor cloud are studied. The three dimensional models of real plants are constructed and respective physics and boundary conditions are imposed to predict the diameter and height of cloud constituting within flammability limits. Such estimation finally help to establish realistic total volume of vapor cloud that actually contributes towards explosion overpressure.
1) The vapor density of released substance is crucial for the total vapor cloud characteristics. 2) The variable wind boundary conditions helped cloud to mix and spread much faster than the atmospheric boundary layer equations. 3) The presence of obstacles on the cloud path altered the overall dispersion extent and appearance. 4) The characteristics of cloud formed in cases of ground and elevated releases were different. 5) The reduction in gravitational acceleration also changed the cloud characteristics.
2. Objective The present work demonstrates the capability of CFD simulations to predict the characteristics of flammable vapor cloud dispersion in a large region (Mishra et al., 2014). Since experiments for such scenarios are not realizable 3D modeling and results on flammable volume above the ground level provide very useful information for assessing the risks to the people, nearby infrastructure and environment. Typical accidents involving dispersion and explosion that may occur in fuel storage terminals are reconstructed in this work. Due to several complexities e.g. atmospheric conditions and congestion due to plant items and vegetation present in a plant it is very difficult to assess the vapor cloud characteristics correctly with semi-empirical models. As a result of improper estimation of vapor cloud dimensions the equivalent explosive source is also not correctly calculated. Since correct estimation of this explosive potential is necessary to make decisions on land use planning for a plant it is necessary that all the best possible methods are used to develop an appropriate explosive mass. Prediction of this explosive mass correctly in worst-case incident by CFD models is the main aim of this article. The findings of this work can be used for the present and future plants for qualitative and quantitative risk assessment studies.
For modeling and simulation of the above cases FLACSv10.4 code (Flacs, 2015) has been used. It is an effective code to simulate high momentum jet leaks and subsequent gas dispersion in a model of an offshore module. Simulations of dispersion with high momentum jet leaks requires hours of CPU usage due to short time-steps and duration of long leak. In FLACSv10.4 the high momentum jet is modeled as conserving the flow of mass and momentum. By assuming isenthalpic expansion, it is possible to calculate the expansion of a sonic flow analytically. In summary, FLACS code has built-in facilities as handling realistic gas dispersion scenarios with external wind fields, various types of leak sources and wall-functions. A modified version of FLACS code has been used to simulate release of gas from high pressure pipelines, taking non-ideal gas effects into account. These results showed that the lower flammability limit of gas-air mixture reaches its most remote downstream position relatively early, before drawing in additional air somewhere. Due to the above features FLACS was chosen to simulate the considered scenarios in this work. Apart from the validation studies of various large-scale dispersion tests FLACS has also been used as an accidental scenario investigation tool by many authors in the past (Hansen et al., 2007, 2010; Arntzen, 1998; Flacs, 2015).
3. Background The rest of the paper has been divided into two parts. The first part referred to as case I describes the scenario of dense gas dispersion occurring in real-scale storage terminal (Fig. 1). All essential components are considered and 3D models for the same are created. The second part referred to as case II of the paper deals with the Jaipur oil terminal fire which broke out on 29 October 2009 at 7:30 p.m. (IST) at the Indian Oil Corporation (IOC) tank holding 8000 kL of oil, in Sitapura industrial area on the edges of Jaipur, Rajasthan, causing deaths of 12 individuals and harming more than 200 (Web1, 2017). A number of studies and reports are published on this incident (Mishra et al., 2013, 2014; IOC Fire Accident Investigation Report, 2011). However, CFD modeling and simulation work on this incident to study dispersion of fuel have not been performed yet. Thus, for the study of dispersion of vapor cloud at IOCL, Jaipur Terminal is also considered to reconstruct the incident. Fig. 2 shows the actual and modeled layouts of the facility. A comprehensive study on the parameters influencing vapor cloud
4. Modeling methodology FLACS mainly consists of three software parts: Computer Aided Scenario Design (CASD), Flacs Simulator, Flowvis (Flow Visualization). CASD is used to prepare the input data that defines a FLACS simulation, is basically a preprocessor. This comprises geometry model, computational grid, porosities, and scenarios. Flowvis, the postprocessor is a program for visualizing results from simulations of gas dispersion and gas explosion. In present simulations also in first part, all 3d model of the plant was built and boundary conditions were imposed on different parts. The mass and momentum equations were solved and results were visualized using Flowvis.
Fig. 1. The geometry used for modeling of typical oil storage/tankage facility.
2
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Fig. 2. 3D model of IOCL Jaipur facility showing the the possible leak origin.
Fig. 3. 2D cut plane of vapor cloud dispersion at height of 1 m from ground.
grid volumes were constructed. The finer the grid, the more computationally difficult it is to solve the simulation. Thus, the domain was divided uniformly into 200 control volumes along X, Y and Z direction. For case II i.e. Jaipur incident simulation the whole domain was descretized into 640000 control volumes. The selection of grid plays a great role in the solution of a CFD simulation. However, considering the large domains (∼ km) in present simulations the smaller size grids are not feasible to construct. Depending on the accuracy demanded from simulation results optimum grids were selected. It was found that further refinement than the selected grid did not improve the results by ±10%.
4.1. Geometry 4.1.1. Case 1: model for dense gas dispersion simulation The model is made of approximately same dimensions as the actual facility without any scaling. The objects of box and cylinder type are used for construction of different plant items. The heights of dykes were assumed to be of 5 m and boundary wall as 6 m. The tanks were approximated to be of proportion Height H = 1.25* Diameter(d) of tank. The relative positions and dimensions of dykes, walls, tanks and buildings are mapped from the data available through wikimapia (Web1, 2017). The built model is shown in Fig. 1. 4.1.2. Case 2: reconstruction of IOCL Jaipur accident 2009 The similar approach as above was followed here too. The variety of items e.g., building, control room, car parking, pump house and piping were created to replicate the actual plant. The leak origin was specified as shown in Fig. 2 where the fuel was being fed into the nearby tank.
4.3. Scenario settings FLACS allows to define various initial and boundary conditions for simulation. For this the wind speed is set to 2 m/s initially. The atmosphere is considered stable with relative turbulence set to 0. Setting relative turbulence to zero help achieving zero/calm wind conditions similar to that prevail in most of the accidental sites. The temperature and pressure are set to 20° C and 0.1 MPa. The roughness of ground was set to 0.0002 m. Propane was allowed to leak at various mass flow rates
4.2. Grid and porosities To study the grid dependency of predicted LFL distances different 3
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Fig. 4. 2D cut plane of vapor cloud dispersion at height of 3 m from ground.
Fig. 5. 2D cut plane of vapor cloud dispersion at height of 5 m.
through an area of 5 m2. The leak sizes were assumed based on the size of the pipe transferring fuel to the tank. The size of the leak was chosen according to the pipe diameter 2.5 m and orientation of leak was of Jet type in Y direction. The fuel leaks from t = 10 s to t = 3600 s at defined mass flow rates. Propane was used prior to octane as a dispersing fuel in order to study the difference in behavior between them. In case II, octane leaks occurring at various mass flow rates from an area of 1 m2 are simulated. Two cases as the fuel leaks from t = 20 s to t = 1800 s (tmax = 2000 s) at mass flow rate of 50 kg/s and fuel leaks from t = 10 s to t = 900 s (tmax = 1000 s) at mass flow rate of 25 kg/s are considered. The reasons for selecting octane as a fuel are to reproduce the leak of gasoline vapors and to simulate dense vapor cloud dispersion in a real-scale plant. As in the Jaipur and Buncefield incidents the leaked media was gasoline hence it has been selected as a fuel in this particular case.
5. Validation studies FLACS has already been well validated and approved as a CFD code for risk assessment studies for variety of gas dispersion cases. In (Hansen, 2010; Flacs, 2015) the large-scale experiments (China Lake, Burro, Coyote) conducted in the USA were reproduced with FLACS and good agreement between measured and predicted values was obtained for different atmospheric conditions. An extensive validation work on the applications of FLACS has already been done before and reported in (Hansen et al., 2007, 2010; Flacs, 2015) this is not repeated here.
6. Results and discussion 6.1. Case I: release of dense gas in a model oil and gas storage facility The results for the 50 kg/s case are shown in Figs. 3–5 for different heights i.e., 1 m, 3 m and 5 m, respectively, from ground. The blue and red color represent the lower and upper flammability limits for 4
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Fig. 6. Contour plot of vapor cloud at t = 77 s from the start of leak.
Fig. 7. Contour plot of vapor cloud at t = 1084 s from the start of leak.
Buncefield, 2005, Puerto-rico 2009 and IOCL, Jaipur, 2009 (Mishra et al., 2014, 2013). They provide useful information on the consideration of total loss of content for the determination of source term following which potential mitigation measures can be decided.
propane. The maximum height of the pancake shaped cloud was found to be 5 m. The fuel leak lasts for 1 h and forming a large thick vapor cloud which can disperse throughout the facility. It is important to mention that the height of cloud in case of more dense gas (octane vapors) was higher than in case of less dense one (propane) as will be shown in next section. The average diameter of vapor cloud in all cases were found to be between 590 and 755 m with an average height of about 2 m. Total estimated volume of pancake shaped cloud considering the time averaged diameters and heights for the considered cases were between 1.3*106 m3 to 3.9*106 m3. Such large vapor cloud sizes were realistic from the recent accidents perspective e.g.,
6.2. Case II: reconstruction of IOCL Jaipur accident 2009 For case II, two cases of 50 kg/s and 100 kg/s leaking from a 1 m2 origin were simulated for different times so that the total escaped mass remains similar. These results were obtained for calm weather conditions representing the worst-case. The calm weather helps cloud to 5
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Fig. 8. Contour plot of vapor cloud dispersion at t = 2000 s from the start of leak.
make strategic decisions on locating the gas detectors, control room, pump house etc. and on pre and post-incident mitigation measures. This work is being further extended to study the various scenarios of gas explosions and resulting overpressures from them in the above facilities.
settle on the ground and accumulate. It then drifts slowly in the direction of wind covering the wider area of the plant. In case of strong wind the cloud will generally be carried away posing less threat of accumulation. The dispersion scenarios with 50 kg/s at different times in IOCL Jaipur plant has been shown in Figs. 6–8. The blue and red colors show LFL and UFL, respectively for octane vapors. It is evident from Figs. 6–8 that the cloud covers the whole plant in 1084 s (depicted at 1 m above ground). In case of 100 kg/s the cloud crossed the boundary of the plant and reached outside. The vapor cloud diameters in both the investigated cases were predicted to be between 800 and 900 m. The large diameters of vapor cloud corresponds well to previously reported data on accidents e.g. Buncefield and others (Mishra et al., 2014, 2013). In case of a worst-case the typical size of the vapor cloud in a comparable facility should not be considered less than 500 m. Such information on overall explosion potential of flammable cloud are vital for safer plant and process design.
References Arntzen, B.J., 1998. Modelling of Turbulence and Combustion for Simulation of Gas Explosions in Complex Geometries. PhD Thesis. NTNU, Norway. Flacs v10, 2015. 4r2 Users Manual. Confid. report. Gexcon AS, Bergen, Norway. Hansen, O.R., 2010. Validation of FLACS against experimental data sets from the model evaluation dtabase for LNG vapor dispersion. J. Loss Prev. Process. Ind. 23, 857–877. Hansen, O., Melheim, J., Storvik, I., 2007. CFD-modeling of LNG dispersion experiments. AIChE Spring Natl. Meeting. https://aiche.confex.com/aiche/s07/techprogram/ P77795.HTM. Hightower, M., Gritzo, L., Luketa-Hanlin, A., Covan, S., Tieszen, S., Wellman, G., Irwin, M., Kaneshige, M., Melof, B., Morrow, C., Ragland, D., 2004. Guidance on Risk Analysis and Safety Implications of a Large Liquefied Natural Gas (LNG) Spill over Water. DTIC Document SAND2004–6258. IOC Fire Accident Investigation Report, 2011. Oil Industry Safety Directorate, India. Mishra, K.B., 2015. CFD model for large hazardous dense cloud spread predictions, with particular reference to Bhopal disaster. Atmos. Environ. 117, 74–91. Mishra, K.B., Wehrstedt, K.D., Krebs, H., 2013. Lessons learned from recent fuel storage fires. Fuel Process. Technol. 107, 166–172. Mishra, K.B., Wehrstedt, K.D., Krebs, H., 2014. Amuay refinery disaster: the aftermaths and challenges ahead. Fuel Process. Technol. 198, 198–203. Pontiggia, M., Landucci, G., Busini, V., Derudi, M., Alba, M., Scaioni, M., Bonvicini, S., Cozzani, V., Rota, R., 2011. CFD model simulation of LPG dispersion in urban areas. Atmos. Environ. 45, 3913–3923. Qi, R., Ng, D., Cormier, B.R., 2010. M. Sam Mannan, Numerical simulations of LNG vapor dispersion in brayton fire training field tests with ANSYS CFX. J. Hazard Mater. 183, 1–3 51-61. https.//www.wikimapia.org/. Woodward, J., Pitbaldo, R., 2010. LNG Risk Based Safety: Modeling and Consequence Analysis. John Wiley & Sons, Inc ISBN: 9780470317648.
7. Conclusions and future work Three-dimensional CFD simulations of a dense gas dispersion in a real oil and gas storage facility were performed to study the overall volume of the accumulated flammable cloud representing the worstcase scenarios that have been observed in the recent incidents. The simulation results revealed that in all cases the average cloud diameters was in the range of 500 m–1000 m, for relatively calm weather conditions. Furthermore, it was found that the heights of octane cloud was much higher than propane cloud leading to larger total volume. The presence of major obstacles (tanks, pipings, buildings etc.) alter the cloud shape and size significantly. Such detailed information on possible scenarios is crucial for the risk assessor and safety professionals to
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