Rapid risk assessment of a fertilizer industry using recently developed computer-automated tool TORAP

Journal of Loss Prevention in the Process Industries 14 (2001) 413–427 www.elsevier.com/locate/jlp

Rapid risk assessment of a fertilizer industry using recently developed computer-automated tool TORAP Faisal I. Khan 1, Asad Iqbal 2, S.A. Abbasi

*

Centre for Pollution Control and Energy Technology, Pondicherry University, Pondicherry – 605014, India

Abstract 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.  2001 Elsevier Science Ltd. All rights reserved. Keywords: Risk assessment; Industrial hazards; Process safety; Computer-automated tool

1. Introduction In an ongoing programme of studies on risk assessment in chemical process industries, we have reported mathematical modelling of hazard and operability studies (HAZOP; Khan & Abbasi, 1997a,b,c), analysis and modelling of the domino effect (Khan & Abbasi, 1998a) and the development of new algorithms for fault tree analysis (Khan & Abbasi, 1999a, 2000a), and have presented computer-automated tools based on these methodologies (Khan & Abbasi, 1997c,d,e,f, 1998b,c,d,e,f,g, 1999b,c,d). We have also recently developed TORAP (TOol for Risk Assessment in Petrochemical industries) which is specific to petroleum refineries and downstream industries (Khan & Abbasi, 1998f). In this paper we present the application of TORAP in conducting rapid risk assessment in a typical

* Corresponding author. Tel.: +91-413-655363; fax: +91-41365227/65265. E-mail addresses: [email protected]; [email protected] (S.A. Abbasi). 1 Present address: Faculty of Engineering and Applied Sciences, The Memorial University of Newfoundland, St John’s, NF, Canada, A1B 3X5. 2 Present address: Chemical Engineering Group, Birla Institute of Technology and Science, Pilani 333 031, India.

fertilizer plant. It is hoped that this case study will be useful in the conducting of risk assessments in similar plants situated all over India. Although the study pertains to a real plant, ficticious names have been given to the plant and its location on the request of the plant managers who wish these identities not to be publicized.

2. The industry 2.1. Plant setting Bharat Fertilizers Limited (BFL) is one of the leading fertilizer producers in Western India. It produces raw ammonia, urea and nitrogen–phosphorous–potassium (NPK) fertilizers as its main products. The BFL plant is located at Chamoli, Guna district, 30 km north of downtown Mumbai, India. The topography of the land is generally flat with contours varying from 1.2 m to 1.8 m above mean sea level. The climate is semi arid, with mean daily temperatures ranging from 24°C to 40°C. The mean relative humidity is 71%, while the average annual rainfall in the area is 160 cm. As illustrated in Fig. 1, the plant is surrounded by a number of major industries, several of which process highly hazardous chemicals. Several well-populated villages are also located close to the plant.

0950-4230/01/$ - see front matter  2001 Elsevier Science Ltd. All rights reserved. PII: S 0 9 5 0 - 4 2 3 0 ( 0 0 ) 0 0 0 5 5 - 3

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Fig. 1.

Location of the BFL plant and its surroundings.

2.2. Process description At BFL, ammonia is produced through the naphtha– steam reformation process, urea through the total recycle process, and NPK through the Dorr Oliver NPK granulation process. The main plants and the corresponding sections in the plant are as follows. 2.2.1. Ammonia plant 앫 De-sulfurizer section 앫 Reformer section 앫 CO2 absorption section 앫 Compression section 앫 Ammonia synthesis unit

2.2.2. Urea plant 앫 Compressor section 앫 Urea reactor 앫 Decompressor unit 앫 Ammonia absorber unit 앫 Evaporation and drilling unit

2.2.3. NPK plant 앫 Neutralizing section 앫 Drying sections 앫 Screens and crushing section 앫 Cooling section 앫 Coating section Process flow diagrams of the different plants are given in Figs. 2–4.

3. Reconnaissance preceding the application of TORAP In order to optimize expert time and costs, a reconnaissance of all the units is recommended prior to the application of TORAP. The reconnaissance enables a rapid, semi-quantitative assessment of the hazards posed by the various units, and prioritization of the more hazardous units for greater attention. To accomplish this task with an adequate degree of accuracy and precision, we have developed the HIRA (hazard identification and ranking analysis) system (Khan & Abbasi, 1998c). HIRA has two constituent indices: FEDI (fire and explosion damage index) and TDI (toxic damage index). The distinguishing attributes of HIRA are: 1. it takes into consideration the impact of various process operations, and the associated parameters for hazard identification; 2. it provides quantitative results of good reliability; 3. most of the penalties used in computing FEDI and TDI (on which HIRA is based) are derived from welltried and tested models of thermodynamics, transport phenomena, heat transfer and fluid dynamics (Fire and Explosion Guidelines, 1994; Greenbook, 1992; Management of Process Hazards, 1990). A few penalties are quantified with the help of empirical models and hazard ranking procedures such as those given by the National Fire Protection Agency (NFPA) (Identification of the Hazardous of Material, 1989; Industrial Fire Hazards Handbook, 1990; Hazardous Materials Response Handbook, 1992) and for extremely hazardous substances (EHS database);

F.I. Khan et al. / Journal of Loss Prevention in the Process Industries 14 (2001) 413–427

Fig. 2.

Fig. 3.

Process flow diagram for ammonia plant.

Process flow diagram for urea plant.

4. it does not need case-to-case calibration as its magnitude directly signifies the level of hazard; and 5. it may be used for very rapid reconnaissance of risk. In the present case study, HIRA was applied to obtain

Fig. 4.

Process flow diagram for NPK plant.

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hazard index values as depicted in Tables 1–3. The units with scores above the threshold value of 100 were subjected to further detailed analysis by TORAP.

5. Application of TORAP to the BFL units shortlisted by HIRA 5.1. Application of the accident scenario generation step

4. The software TORAP TORAP enables accident simulation and damage potential estimation of petroleum and petrochemical industries. The software has been developed in an object-oriented architecture using Visual C++ as a coding tool. The software is compatible with the Windows operating environment. It is operable on computers with a minimum of 16 MB RAM and 1 GB ROM. The sequence of actions or main steps involved in TORAP, its object-oriented architecture, and information pathways are depicted in Figs. 5 and 6. Fig. 5 shows the object-oriented architecture of TORAP. Fig. 6 depicts five essential steps of TORAP; each is briefly described below along with the case study.

In this step accident scenarios are generated for the unit under study. It is a very important input for the subsequent steps. The more realistic the accident scenario, the more accurate is forecasting of the type of accident, its consequences and associated risks. This is essential for the development of more appropriate and effective strategies for crisis prevention and management. Each accident scenario is basically a combination of different likely accidental events that may occur in a plant. Such scenarios are generated based on the properties of chemicals handled by the plant, physical conditions under which reactions occur or reactants/products are stored, geometries and material strengths of vessel and conduits, in-built valves and safety arrangements, etc. External factors such as site characteristics (topography, the presence of trees, ponds or rivers in the

Table 1 Preliminary hazard assessment: hazard identification and ranking of BFL’s ammonia plant Serial Sub unit no 1.

HDS unit HDS-I

HDS-II

2.

HDS stripper Reformer unit Primary reformer

Secondary reformer 3.

Shift converter unit Primary CO converter Secondary CO converter

4.

Methanator

5.

Catacarb process Catacarb reboiler CO2 absorber

6.

Ammonia synthesis unit Ammonia converter/reactor Ammonia absorber

Hazardous chemicals

Fire and explosion damage index

Toxic damage index

Remark

Naphtha Hydrogen Hydrogen sulfide HDS naptha Naptha Hydrogen Naptha

226.31 34.41 1.27 11.14 190.69 20.17 112.23

12.41 25.43 37.43 3.75 1.37 28.45 25.37

Naptha Hydrogen Reformer gases Reformer gases (influent) Reformer gases (effluent)

226.45 144.76 294.52 241.53 323.86

13.43 59.73 78.67 85.46 100

Reformer Reformer Reformer Reformer Reformer Reformer

100.32 85.42 45.34 150.56 25.02 75.71

11.27 10.37 50.13 20.32 63.00 43.33

334.38 2.51 334.564 84.25

47.63 4.76 100.00 78.43

Highly hazardous

100.00 100.00 60.32

Extremely hazardous

gases gases gases gases gases gases

(influent) (effluent) (influent) (effluent) (influent) (effluent)

Reformer gases (influent) Reformer gases (effluent) Gas I (influent) Gas II (effluent) Gas I (influent) Gas II (effluent) Absorber gases

2911.23 3084.71 250.53

Moderately hazardous

Hazardous Hazardous Moderately hazardous Moderately hazardous

Highly hazardous Hazardous

Hazardous Less hazardous

Highly hazardous

Moderately hazardous

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Table 2 Preliminary hazard assessment: hazard identification and ranking of BFL’s urea plant S. no Sub unit 1.

2.

3.

4.

5.

Synthesis unit Urea reactor Absorber unit First absorber Second absorber Flash separator First flash separator Second flash separator Decomposer unit First decomposer Second decomposer Prill section evaporator

Hazardous chemicals

Fire and explosion damage index

Toxic damage index

Remark

Ammonia Carbon dioxide

1000.39 74.81

100.00 5.43

Extremely hazardous

100 100

Highly hazardous Highly hazardous

Ammonia Ammonia

415.7 343.2

Ammonia Ammonia

125.43 178.42

38.76 48.95

Hazardous

Ammonia Ammonia Ammonia

213.45 278.34 111.78

74.43 76.76 15.625

Moderately hazardous Hazardous

Table 3 Preliminary hazard assessment: hazard identification and ranking of BFL’s NPK plant Fire and explosion damage index

S. no Sub unit

Hazardous chemicals

1. 2. 3.

Pre-neutralizer Blunger Drier

4. 5.

Scrubber Cooler

Ammonia 345.43 Ammonia 228.73 Naptha 54.73 LPG 778.72 Fumes of H3PO4 and NPK 93.43 NPK 75.42

Toxic damage index

Remark

20.18 14.41 23.41 85.43 18.42 12.43

Highly hazardous Moderately hazardous Extremely hazardous Less hazardous Less hazardous

vicinity, proximity to other industries or neighbourhoods, etc.) and meteorological conditions are also considered. The following scenarios are generated for the BFL units (short-listed through HIRA).

and pressure, and there is a probability of side reactions occurring with release of heat. The accident scenario for this unit has been developed as CVCE followed by dispersion.

5.2. Ammonia plant

5.2.5. CO2 absorber: Scenario 5 The absorber unit is a mass transfer unit dealing with a mixture of gases. The purpose of this unit is to recover CO2 from the mixture of gases. As the unit operates at normal temperature and pressure, there is a low probability of the explosive release of chemicals. However, as the unit deals with hydrogen, which is highly flammable, there is a high probability of occurrence of flash fire. The accident scenario for this unit is envisaged as flash fire followed by release and dispersion of gases.

5.2.1. Primary hydro de-sulfurizer (HDS): Scenario 1 The primary hydro de-sulfurizer unit deals with hydrogen and naphtha. The accident scenario for this unit has been envisaged as boiling liquid vapour cloud explosion (BLEVE) followed by fire ball. 5.2.2. Primary reformer: Scenario 2 The accident scenario for the primary reformer unit is developed as BLEVE followed by fire ball. 5.2.3. Secondary reformer: Scenario 3 The accident scenario for the secondary reformer is perceived as confined vapour cloud explosion (CVCE) followed by pool fire. 5.2.4. Ammonia reactor: Scenario 4 The converter/reactor unit transforms synthesis gas into ammonia. This is operated under high temperature

5.3. Urea plant 5.3.1. Urea reactor: Scenario 6 Ammonia and carbon dioxide from the ammonia plant are processed in the urea reactor to form ammonium carbamate and urea. The accident scenario for the urea reactor is envisaged as CVCE followed by release and dispersion of toxic gases.

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Fig. 5.

Object-oriented architecture of TORAP.

5.3.2. Primary absorber: Scenario 7 Flashed and decomposed gases (ammonia and carbon dioxide) are mixed with a sufficient amount of ammonia to produce weak ammonium carbamate solution in the first absorber. The accident scenario for this equipment is envisaged as a BLEVE with release of gases. 5.3.3. Secondary absorber: Scenario 8 The probability of explosion in the secondary absorber is less, and hence only detailed calculation for the release and dispersion of toxic gases has been done. 5.4. NPK plant 5.4.1. Pre-neutralizer: Scenario 9 The accident scenario for this unit is envisaged as instantaneous release of BLEVE followed by dispersion. 5.4.2. Drier: Scenario 10 The accident scenario for the drier is forecast as BLEVE followed by fire ball.

6. The consequence analysis step and the ‘domino check’ step This step involves assessment of the likely consequences if an accident does materialize. The conse-

quences are quantified in terms of damage radii (the radius of the area in which damage would readily occur), damage to property (shattering of window panes, caving of buildings) and toxic effects (chronic/acute toxicity, mortality). The assessment of consequence involves a wide variety of mathematical models. For example, source models are used to predict the rate of release of hazardous material, the degree of flashing, and the rate of evaporation. Models for explosions and fires are used to predict the characteristics of explosions and fires. Impact intensity models are used to predict the damage zones due to fires, explosion and toxic load. Finally, toxic gas models are used to predict human response to different levels of exposure to toxic chemicals. A list of models included in TORAP for consequence estimation is given in Table 4. Several different types of explosion and fire models such as CVCE, partially confined vapour cloud explosion (PVCE), BLEVE, vented explosion, pool fire, flash fire, jet fire and fire ball are included. Likewise, models for liquid release and two-phase release have been incorporated. A special feature of TORAP is that it is able to handle dispersion of heavy (heavier-than-air) gases, as well as lighter-than-air and light-as-air gases. Further, an accident in a unit may cause another accident in another unit. This phenomenon is termed the ‘domino effect’ and is highly likely to occur in petroleum refineries petrochemical and chemical plants as

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for the scenarios developed in the previous step. The results are summarized below. 6.1. Ammonia plant

Fig. 6.

Essential steps involved in TORAP.

these industries handle a large variety of hazardous chemicals, that too in large quantities. Numerous past accidents (Khan & Abbasi, 1998e; Khan & Abbasi, 1999b; Lees, 1996), including the worst refinery accident of the 1990s — the HPCL refinery disaster which occurred at Vishakhapatnam, India, on November 14, 1997 (Khan & Abbasi, 1999c), have involved the ‘domino effect’. It is a speciality of TORAP that the package is capable of simulating second- and higher-order accidents. To do this, it uses models developed by Pietersen (1985, 1990), Clancey (1977), Eissenberg, Lynch, and Breeding (1975), Fowcett and Wood (1993), and Khan and Abbasi (1998a, 1998c, 1998e). If the probability of occurrence of a secondary accident is higher than a minimum value, the package will estimate the damage potential of the secondary accident and its likelihood of causing a third-degree accident, and so on. To estimate the probability of occurrence and damage characteristics, the package uses information related to the operating conditions of the secondary units, chemical properties and topographical/meteorological parameters (wind velocity, roughness, obstruction, etc.). Using TORAP, consequence analysis was conducted

The primary hydro de-sulfurizer unit deals with hydrogen and naphtha. The accident scenario for this unit, Scenario 1, has been generated as BLEVE followed by fire ball. Due to high temperature and pressure, there is a high probability that hydrogen may escape as BLEVE, while naphtha at elevated temperature and pressure on release and ignition may lead to a fire ball. The forecasts for this accident scenario are presented in Table 5. As the quantity of hydrogen is not very great, only a low-intensity BLEVE may occur yielding an overpressure of 217 kPa and a shock wave velocity of 335 m/s. These are not exactly catastrophic. The fire ball is also not likely to cause significant damage at the point of observation (苲500 m away from the site). Table 5 summarizes dispersion of hydrogen over the study area, which is not too worrisome. The accident scenario for the primary reformer unit is generated as BLEVE followed by fire ball (Table 6). The intensity of explosion in this case is observed to be slightly higher than in the previous case. Yet the impacts remain within moderately hazardous levels. The dimensions of the fire ball are similar to the one likely in the HDS unit. The dispersion of released gases was forecast with HAZDIG. It revealed the probability of a very high concentration build-up (100 mg/m3) of the reformed gases at the point of observation (Table 6). The concentration exceeds the threshold limit value (TLV) and may cause severe damage in terms of fatalities. In other words, the reformer unit poses moderately significant hazard due to fire and explosion, but would result in a lethal toxic load over an area of 200 m radius surrounding the reformer unit. The accident scenario for the secondary reformer is generated as CVCE followed by pool fire. As the unit deals with a high capacity of reformed gases (H2 and light hydrocarbons) under high pressure, the probability of CVCE is high. Further, the released hydrocarbons may burn as a pool fire. The forecasts for this scenario are presented in Table 7. An intense overpressure load (2175) along with a high-velocity shock wave (1151) is likely around the site of the accident. There would also be lethal heat load. The pool fire would not be as damaging as the explosion. Toxic load due to burned and unburned reformer gases may occur over the study area (Table 7). The damaging impact of severe heat load, peak overpressure and missiles would reach a distance of up to 800 m away from the epicentre of the explosion. The converter/reactor unit transforms synthesis gas into ammonia. This is operated under high temperature and pressure, and there is a probability of side reactions occurring with release of heat. The accident scenario for

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Table 4 List of different models used in TORAP Event Explosion BLEVE

VCE/PVCE CVCE Vented explosion

Fire Flash fire Pool fire Fire ball Jet fire

Toxic release Light gas dispersion Heavy gas dispersion

Models incorporated

References

Thermodynamic and heat transfer Baker, Cox, Westin, Kulesz, and Strelow (1983); Martinsen, Johnson, and model Terell (1986); Prugh (1991); Vernart, Rutledge, Sumathipala, and Sollows (1993) Condensed vapour cloud Kletz (1977); Lees (1996); Prugh (1987); Van den Berg (1985, 1989); explosion Van den Berg and Lennoy (1993) Vapour cloud explosion in Baker et al. (1983); Davenport (1986); Fire and Explosion Guidelines confinement (vessel or building) (1994); Greenbook (1992); Lees (1996) Release with momentum, Cates and Bimson (1991); Cates and Samuels (1991); Harrison and Keyre combustion flame propagation, (1987) and shock wave/overpressure impulse models Flare model, fire torch and spontaneous combustion Combustion of liquid pool Spontaneous combustion of vapour cloud Continuous release, combustion, flame propagation and heat transfer models

Fowcett and Wood (1993); Fire and Explosion Guidelines (1994); Greenberg and Crammer (1992); Kayes (1986) Greenbook (1992); Davies (1993); Kayes (1986) Baker et al. (1983); Davies (1993); Kayes (1986); Pietersen (1990); Roberts (1983) Cowley and Pritchard (1991); Crocker and Napier (1986); Johnson, Brightwell, & Carsley (1994)

Gaussian dispersion model with Erbink modification Box model, modified plume path theory for heavy gas

Erbink (1993); Gifford (1961); Pasquill and Smith (1983); Turner (1970, 1985) Deaves (1992); Erbink (1995); Khan and Abbasi (2000b); Van Ulden (1974, 1985) Greenbook (1992); Khan and Abbasi (1998a, 1998e); Lees (1996)

Domino effect (higher-order accident)

this unit has been developed as CVCE followed by dispersion. The forecasts based on detailed calculations for this scenario are presented in Table 8. It is evident that the intensity of explosion is very high as it would develop a peak overpressure of 1178 kPa, which is far above the threshold limit (30 kPa). Simultaneously, a shock wave of very high velocity (1112 m/s) would be observed over an area of more than 200 m radius. The damage potential of these events (shock waves and overpressure) would be severe enough to cause secondary accidents in the units placed within 500 m in all directions. The results for toxic dispersion are presented in Table 8. It is indicated that the lethal toxic load would persist over a small area 苲300 m radius. It is important to note that the damage potential of toxic release and dispersion is comparatively low compared with the damage potential of explosion. The absorber unit is a mass transfer unit dealing with a mixture of gases. The purpose of this unit is to recover CO2 from the mixture of gases. The unit operates at normal temperature and pressure. There is less likelihood of the explosive release of the chemicals; however, as the unit involves hydrogen, which is highly flammable, there is a high probability of flash fire. The accident

scenario for this unit is envisaged as flash fire followed by release and dispersion of gases. The forecasts of flash fire are illustrated in Table 9. Up to a radius of 200 m, intense heat load (sufficient to cause lethality at 50% probability) would persist. However, beyond 350 m radius the impact of this load would not be significant. The result for the toxic release of gases has been tabulated in Table 9. It is clear from the table that a high concentration of these gases would be observed up to a distance of 100 m. 6.2. Urea plant The units that are identified as hazardous in the previous step the by HIRA technique are studied here in detail. The forecasts based on detailed calculations for these scenarios are presented in Tables 10–12. Ammonia and carbon dioxide from the ammonia plant are processed in the urea reactor to form ammonium carbamate and urea. The accident scenario for the urea reactor is envisaged as CVCE followed by release and dispersion of toxic gases. The forecasts for this scenario are presented in Table 10. The peak overpressure generated by CVCE is more than 500 kPa, which is quite high. An

F.I. Khan et al. / Journal of Loss Prevention in the Process Industries 14 (2001) 413–427

Table 5 The output of TORAP for Scenario 1 Parameter

421

Table 6 The output of TORAP for Scenario 2 Value

Unit: Hydro de-sulfurization unit Scenario: BLEVE followed by fire ball and dispersion of toxic gas Explosion: BLEVE Total energy released (kJ) 1.82×105 Peak overpressure (kPa) 217.80 Variation of overpressure in air (kPa/s) 151.75 Shock wave velocity (m/s) 335.5 Duration of shock wave (ms) 24 Missile characteristics Initial velocity of fragment (m/s) 145.2 Kinetic energy of fragment (kJ) 6.51×104 Penetration ability at 50 m from the location of accident Concrete structure (m) 0.01 Brick structure (m) 0.06 Steel structure (m) 0.00 Fire ball Radius of fire ball (m) 66.5 Duration of fire ball (s) 27.1 Energy released by fire ball (kJ) 2.42×108 Radiation heat flux (kJ/m2) 965.4 Toxic release and dispersion Box instantaneous model: elevated source 3.452×10⫺4 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics 1.124×10⫺4 Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) 1.124×10⫺3 Cloud radius (m) 1.167×102 Maximum distance travelled by the cloud (m) 7.874×102 Maximum ground-level concentration (kg/m3) 1.765×10⫺1

area of more than 750 m radius may be damaged due to this accident. Such impacts would extend beyond the plant’s boundary. The forecasts for release and dispersion for toxic gas reveal that an area of 苲200 m radius would be under the influence of a lethal toxic load (Table 10). Flashed and decomposed gases (ammonia and carbon dioxide) are mixed with a sufficient amount of ammonia to produce weak ammonium carbamate solution in the first absorber. The accident scenario for this unit is envisaged as BLEVE with released gases. The results of detailed calculation for this scenario (Table 11) reveal that a lethal overpressure (greater than 0.3 atm) would persist over an area of 50 m radius. A shock wave of velocity sufficient to cause damage would be operative in the same region. The forecasts for dispersion of toxic gas (ammonia) are detailed in Table 11. Lethal concentrations of ammonia would encompass an area of 苲500 m radius. The probability of explosion in the secondary absorber is less and hence only detailed calculation for the release and dispersion of toxic gases has been done. The forecasts for this scenario are presented in Table 12. It is evident that a lethal concentration of ammonia would persist over an area of more than 200 m.

Parameter

Value

Unit: Primary reformer Scenario: BLEVE followed by fire ball and dispersion of toxic gas Explosion: BLEVE Total energy released (kJ) 3.65×105 Peak overpressure (kPa) 415.50 Variation of overpressure in air (kPa/s) 324.75 Shock wave velocity (m/s) 387.65 Duration of shock wave (ms) 41 Missile characteristics Initial velocity of fragment (m/s) 252.2 Kinetic energy of fragment (kJ) 1.12×105 Penetration ability at 50 m from the location of accident Concrete structure (m) 0.02 Brick structure (m) 0.09 Steel structure (m) 0.00 Fire ball Radius of fire ball (m) 75.4 Duration of fire ball (s) 32.4 Energy released by fire ball (kJ) 3.21×108 Radiation heat flux (kJ/m2) 1034.5 Toxic release and dispersion Box instantaneous model: elevated source 4.554×10⫺3 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics 1.765×10⫺4 Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) 1.765×10⫺3 Cloud radius (m) 5.511×103 Maximum distance travelled by the cloud (m) 6.567×102 Maximum ground-level concentration (kg/m3) 1.453×10⫺1

6.3. NPK plant The units that pose significant hazards in the NPK plant are the pre-neutralizer and drier. They have been analysed for detailed consequences and the results are illustrated in Tables 13 and 14. The accident scenario for the pre-neutralizer unit is envisaged as instantaneous release of BLEVE followed by dispersion. The forecasts of the accident are presented in Table 13. BLEVE would generate an overpressure of 苲884 kPa, which is several times higher than the lethal limit. A simultaneous shock wave of velocity 958 m/s would also be developed. The lethal damage potential of these effects (shock wave and overpressure) would be operative over an area of more than 苲500 m. The results of dispersion of the released gas indicate a comparatively low concentration of ammonia over the study zone of 200 m radius. It is so because the high turbulence in the atmosphere (due to overpressure and shock wave) would favour rapid dilution of the gas. The accident scenario for the drier has been forecast as BLEVE followed by fire ball and dispersion of ammonia. The hazardous chemicals processed in this unit are ammonia, fertilizer slurry, naphtha and liquefied

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Table 7 The output of TORAP for Scenario 3 Parameter

Table 9 The output of TORAP for Scenario 5 Value

Unit: Secondary reformer Scenario: CVCE followed by pool fire and dispersion of toxic gas Explosion: CVCE Total energy released (kJ) 6.45×107 Peak overpressure (kPa) 2175.80 Variation of overpressure in air (kPa/s) 1151.75 Shock wave velocity (m/s) 1051.81 Duration of shock wave (ms) 24 Missile characteristics Initial velocity of fragment (m/s) 763.2 Kinetic energy of fragment (kJ) 1.01×106 Penetration ability at 50 m from the location of primary accident Concrete structure (m) 0.40 Brick structure (m) 0.55 Steel structure (m) 0.14 Pool fire 91.67 Burning area (m2) Burning rate (kg/h) 37.46 9655.4 Radiation heat flux (kJ/m2) Toxic release and dispersion Box instantaneous model: elevated source 1.95×10⫺5 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics 0.854×10⫺5 Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) 0.854×10⫺4 Cloud radius (m) 2.958×102 Maximum distance travelled by the cloud (m) 1.345×102 Maximum ground-level concentration (kg/m3) 2.134×10⫺2

Table 8 The output of TORAP for Scenario 4 Parameter

Value

Unit: Ammonia reactor Scenario: CVCE followed by dispersion of toxic gas Explosion: CVCE Total energy released (kJ) 3.87×107 Peak overpressure (kPa) 1178.5 Variation of overpressure in air (kPa/s) 1451.2 Shock wave velocity (m/s) 1112.5 Duration of shock wave (ms) 41 Missile characteristics Initial velocity of fragment (m/s) 854.1 Kinetic energy of fragment (kJ) 1.35×106 Penetration ability at 50 m from the location of primary accident Concrete structure (m) 0.43 Brick structure (m) 0.58 Steel structure (m) 0.16 Toxic release and dispersion Box instantaneous model: elevated source 5.250×10⫺3 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics Ground-level concentration of puff (kg/m3) 1.732×10⫺4 Ground-level concentration on puff axis (kg/m3) 1.732×10⫺3 Cloud radius (m) 2.285×102 Maximum distance travelled by the cloud (m) 2.123×102 Maximum ground-level concentration (kg/m3) 4.085×10⫺1

Parameter PRIMARY EVENT Unit: CO2 absorber unit Scenario: Flash fire and dispersion of toxic gas Flash fire Volume of vapor cloud (m3) Area under fire effect (m2) Effective time of fire (s) Radiation heat flux (kJ/m2) Toxic release and dispersion Box instantaneous model: elevated source Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) Cloud radius (m) Maximum distance travelled by the cloud (m) Maximum ground-level concentration (kg/m3)

Value

437,277.4 508,282.4 54 2916.0 2.456×10⫺4 0.996×10⫺5 0.996×10⫺4 2.509×102 1.400×102 2.436×10⫺2

Table 10 The output of TORAP for Scenario 6 Parameter

Value

PRIMARY EVENT Unit: Urea reactor Scenario: CVCE followed by release and dispersion of toxic gas Explosion: CVCE Total energy released (kJ) 1.25×106 Peak overpressure (kPa) 875.5 Variation of overpressure in air (kPa/s) 675.2 Shock wave velocity (m/s) 787.2 Duration of shock wave (ms) 41 Missile characteristics Initial velocity of fragment (m/s) 315.4 Kinetic energy of fragment (kJ) 3.45×105 Penetration ability at 50 m from the location of primary accident Concrete structure (m) 0.15 Brick structure (m) 0.21 Steel structure (m) 0.09 Toxic release and dispersion Box instantaneous model: elevated source 2.974×10⫺5 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics 8.768×10⫺7 Ground-level concentration of puff (kg/m3) 3 Ground-level concentration on puff axis (kg/m ) 8.768×10⫺6 Cloud radius (m) 3.412×102 Maximum distance travelled by the cloud (m) 1.150×103 Maximum ground-level concentration (kg/m3) 7.395×10⫺3

petroleum gas (LPG). The last two chemicals are used as fuel for drying. The forecasts based on detailed calculations are presented in Table 14. The peak overpressure due to BLEVE would be 842 kPa, which is higher than the acceptable threshold by several orders of magnitude. Simultaneously shock waves of velocity 苲900 m/s would also be generated. The lethal impact of these events would reach an area of 苲500 m radius. Heat load due

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Table 11 The output of TORAP for Scenario 7 Parameter

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Table 13 The output of TORAP for Scenario 9 Value

PRIMARY EVENT Unit: Primary absorber unit Scenario: BLEVE followed by release and dispersion of toxic gas Explosion: BLEVE Total energy released (kJ) 6.65×104 Peak overpressure (kPa) 115.5 Variation of overpressure in air (kPa/s) 151.7 Shock wave velocity (m/s) 355.6 Duration of shock wave (ms) 21 Missile characteristics Initial velocity of fragment (m/s) 56.4 Kinetic energy of fragment (kJ) 1.21×104 Penetration ability at 50 m from the location of tertiary accident Concrete structure (m) 0.00 Brick structure (m) 0.00 Steel structure (m) 0.00 Toxic release and dispersion Box instantaneous model: elevated source 3.245×10⫺3 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics 1.675×10⫺4 Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) 1.675×10⫺3 Cloud radius (m) 2.509×102 Maximum distance travelled by the cloud (m) 1.470×102 Maximum ground-level concentration (kg/m3) 1.777×10⫺1

Parameter

Value

PRIMARY EVENT Unit: Pre-neutralizer unit Scenario: BLEVE followed by release and dispersion of toxic gas Explosion: BLEVE Total energy released (kJ) 7.45×105 Peak overpressure (kPa) 884.9 Variation of overpressure in air (kPa/s) 452.5 Shock wave velocity (m/s) 958.7 Duration of shock wave (ms) 41 Missile characteristics Initial velocity of fragment (m/s) 256.4 Kinetic energy of fragment (kJ) 1.16×105 Penetration ability at 50 m from the location of tertiary accident Concrete structure (m) 0.02 Brick structure (m) 0.09 Steel structure (m) 0.00 Toxic release and dispersion Box instantaneous model: elevated source 7.869×10⫺6 Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics 4.554×10⫺7 Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) 4.554×10⫺6 Cloud radius (m) 2.285×102 Maximum distance travelled by the cloud (m) 1.152×103 Maximum ground-level concentration (kg/m3) 1.882×10⫺3

Table 12 The output of MAXCRED for Scenario 8 Parameter PRIMARY EVENT Unit: Secondary absorber unit Scenario: Release and dispersion of toxic gas Toxic release and dispersion Box instantaneous model: elevated source Concentration at distance of 200 m (kg/m3) Heavy gas puff characteristics Ground-level concentration of puff (kg/m3) Ground-level concentration on puff axis (kg/m3) Cloud radius (m) Maximum distance travelled by the cloud (m) Maximum ground-level concentration (kg/m3)

Value Table 14 The output of TORAP for Scenario 10 Parameter 4.354×10⫺2 2.004×10⫺3 2.004×10⫺2 3.903×102 7.850×102 2.455×10⫺1

to fire would also be lethal over an area of more than 苲400 m radius. 7. Risk estimation On the basis of the results presented above, and the probabilities of occurrence of the various accident scenarios, risk factors have been computed. In order to enable visualization of the accidents, risk contours have been drawn over the plant layout (Figs. 7–11). The risk con-

Value

PRIMARY EVENT Unit: Drier unit Scenario: BLEVE followed by fire ball and dispersion of toxic gas Explosion: BLEVE Total energy released (kJ) 5.56×106 Peak overpressure (kPa) 842.5 Variation of overpressure in air (kPa/s) 415.5 Shock wave velocity (m/s) 902.5 Duration of shock wave (ms) 41 Missile characteristics Initial velocity of fragment (m/s) 201.5 Kinetic energy of fragment (kJ) 9.75×104 Penetration ability at 50 m from the location of tertiary accident Concrete structure (m) 0.02 Brick structure (m) 0.08 Steel structure (m) 0.00 Fire ball Radius of fire ball (m) 137.2 Duration of fire ball (s) 56.07 Energy released by fire ball (kJ) 1.60×1010 Radiation heat flux (kJ/m2) 2103.8

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Fig. 7. Risk contours for an accident scenario in primary hydrodesulfuriser showing impact area due to severe (A), high (B), and moderate (C) risk.

Fig. 8. Risk contours for an accident scenario in primary reformer showing impact area due to severe (A), high (B), and moderate (C) risk.

Fig. 9. Risk contours for an accident scenario in secondary reformer showing impact area due to severe (A), high (B), and moderate (C) risk.

Fig. 10. Risk contours for an accident scenario in ammonia reactor showing impact area due to severe (A), high (B), and moderate (C) risk.

tours for the urea plant are plotted in Figs. 12–14. The risk contours for the hazardous units of NPK plant are plotted in Figs. 15 and 16.

8. The worst-disaster scenario identification step Arriving at worst accident scenario is the last step in the TORAP algorithm. The step determines the worst accident scenario based on the results of consequence analysis. This step holds the key to the final objective of the risk analysis: devising strategies to avert a crisis or to minimize its adverse impact if the crisis does take place. It is possible that more than one ‘worst accident scenario’ emerges from the TORAP analysis because more than one sequence of events can lead to identical magnitudes of ‘worst’ damage. In such situations the control strategies would be developed by keeping all of

Fig. 11. Risk contours for an accident scenario in absorber unit showing impact area due to severe (A), high (B), and moderate (C) risk.

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Fig. 12. Risk contours for an accident scenario in urea reactor showing impact area due to severe (A), high (B), and moderate (C) risk.

Fig. 13. Risk contours for an accident scenario in primary absorber showing impact area due to severe (A), high (B), and moderate (C) risk.

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Fig. 15. Risk contours for an accident scenario in pre-neuteralizer showing impact area due to severe (A), high (B), and moderate (C) risk.

Fig. 16. Risk contours for an accident scenario in drier showing impact area due to severe (A), high (B), and moderate (C) risk.

the ‘worst’ scenarios in view. Application of this step of TORAP to BFL reveals that accident scenarios of the secondary reformer and ammonia reactor are the worst scenarios.

9. Conclusions

Fig. 14. Risk contours for an accident scenario in secondary absorber showing impact area due to severe (A), high (B), and moderate (C) risk.

Application of the computer-automated tool TORAP for the risk assessment of a fertilizer plant reveals that the tool is user-friendly and enables detailed forecasting and impact assessment of the likely accidents — with speed, accuracy and precision. Even though the case study focuses on a particular plant, the findings are applicable to all other fertilizer plants which have units and processes similar to the ones used by BFL. The study also highlights the fact that major hazards exist in these plants which do not seem to have been given the atten-

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tion they deserve. More often than not, these industries are situated in close vicinity of well-populated villages and towns, so that accidents occurring in them can cause serious damage to life and property as happened at the Hindustan Petroleum Corporation’s refinery at Vishakhapatnam, India, in November 1997 (Khan & Abbasi, 1999c). Application of TORAP to BFL reveals that accidents in the ammonia synthesis unit and secondary reformer have the potential of causing maximum damage in a primary accident and also have the maximum probability of causing the domino effect. The intensities of blast waves, missiles, heat and toxic load would be lethal over an area of more than 苲500 m radius due to accidents in these units. There are many vulnerable units close by, which may get damaged. This may propagate a long chain of accidents. On the other hand, the CO2 absorber has the least damage potential and also the least probability of causing secondary accidents. The study has also generated numerous other accident scenarios and has forecast their impacts. References Baker, W. E., Cox, P. A., Westin, P. S., Kulesz, J. J., & Strelow, R. A. (1983). Explosion hazard and evaluation. Amsterdam: Elsevier. Cates, A. T., & Bimson, S. J. (1991). Fuel and obstacle dependency in pre-mixed transient deflagration. In Proceedings of 13th ICODERS, Nagoya, Japan. Cates, A. T., & Samuels, B. (1991). A simple assessment methodology for vented explosions. Journal of Loss Prevention in the Process Industries, 4, 287. Clancey, V. J. (1977). Dangerous clouds, their growth and explosive properties. Chemical Process Hazards, 6, 111–123. Cowley, L. T., & Pritchard, M. J. (1991). Large-scale natural gas and LPG jet fires and thermal impact on structures. Gastech, 90, 3–6. Crocker, W. P., & Napier, D. H. (1986). Thermal radiation hazards of liquid pool fires. Hazards, IX, 159. Davenport, J. A. (1986). Hazards and protection of pressure storage of liquefied petroleum gases. Loss Prevention and Safety Promotion, 5, 221. Davies, P. A. (1993). A guide to the evaluation of condensed phase explosion. Journal of Hazardous Materials, 33, 1–33. Deaves, D. M. (1992). Dense gas dispersion modelling (HEAVGPLUME). Journal of Loss Prevention in the Process Industries, 5 (4), 219–222. Eissenberg, N. A., Lynch, C. J., & Breeding, R. J. (1975). Vulnerability model: a simulation system for assessing damage resulting from marine spills. Report CG-D-136-75 (Enviro control). US Coast Guard NTIS, Rockville, MD. Erbink, J. J. (1993). The advanced Gaussian model STACKS. In Proceedings of ERCOFTAC Workshop on Intercomparison of Advanced Practical Short Range Atmospheric Dispersion Modelling, ERCOFTAC, Manno, Switzerland. Erbink, J. J. (1995). Turbulent diffusion model from tall stacks. Ph.D. thesis submitted to VRIJ University, The Netherlands. Fire and explosion guidelines (1994). New York: Center for Chemical Process Safety (CCPS), AIChE. Fowcett, H. H., & Wood, W. S. (1993). Safety and accident prevention in chemical operation. (3rd ed.). New York: John Wiley. Gifford, F. A. (1961). Use of routine meteorological observation for estimate atmospheric diffusion. Nuclear Safety, 24, 67.

Greenberg, H. R., & Crammer, J. J. (1992). Risk assessment and risk management in chemical process industries. New York: Van Nostrand Reinhold. Greenbook (1992). Methods for determining of possible damage to people and objects resulting from release of hazardous materials. Report CPR-16E. Warrington, UK: Voorburg. Harrison, A. J., & Keyre, J. A. (1987). ‘External explosions’ as a result of combustion venting. Combustion Science and Technology, 52, 91. Hazardous materials response handbook (1992). USA: National Fire Protection Association (NFPA). Identification of the hazardous of material (1989). NFPA code 704. Quincy, MA: National Fire Protection Agency (NFPA). Industrial fire hazards book (1990). New Jersey: National Fire Protection Association (NFPA). Johnson, A. D., Brightwell, H. M., & Carsley, A. J. (1994). A model for predicting the thermal radiation hazards from large-scale horizontally released natural gas jet fires. Hazards, XII, 123. Kayes, P. J. (1986). Manual of industrial hazard assessment technique. London: Technica Ltd. Khan, F. I., & Abbasi, S. A. (1997a). optHAZOP: an effective and optimal HAZOP study. Journal of Loss Prevention in the Process Industries, 10 (3), 191–204. Khan, F. I., & Abbasi, S. A. (1997b). Mathematical model for HAZOP study time estimation. Journal of Loss Prevention in the Process Industries, 10 (4), 249–257. Khan, F. I., & Abbasi, S. A. (1997c). Accident hazard index: a multiattribute method for process industry hazard rating. Transactions of IChEM of UK (Environmental Protection and Safety, Part B), 75B, 217–224. Khan, F. I., & Abbasi, S. A. (1997d). Rapid risk analysis of a typical chemical industry using MAXCRED-I. Indian Journal of Chemical Technology, 4, 167–179. Khan, F. I., & Abbasi, S. A. (1997e). Risk analysis of epichlorohydrin manufacturing industry using new computer automated tool MAXCRED. Journal of Loss Prevention in the Process Industries, 10 (2), 91. Khan, F. I., & Abbasi, S. A. (1997f). Risk analysis of a cloralkali industry situated in densely populated area. Process Safety Progress, 16 (3), 172. Khan, F. I., & Abbasi, S. A. (1998a). Models for domino effect analysis in chemical process industries. Process Safety Progress, 17 (2), 107–113. Khan, F. I., & Abbasi, S. A. (1998b). Accident simulation as a tool for assessing and calculation environmental risk in CPI: a case study. Korean Journal of Chemical Engineering, 11 (2), 12–19. Khan, F. I., & Abbasi, S. A. (1998c). Multivariate hazard identification and ranking system. Process Safety Progress, 17 (3), 157–165. Khan, F. I., & Abbasi, S. A. (1998d). DOMIFFECT (DOMino eFFECT): a new software for domino effect analysis in chemical process industries. Environment Modelling and Software, 13, 163–177. Khan, F. I., & Abbasi, S. A. (1998e). Risk assessment in chemical process industries: Advance techniques. New Delhi: Discovery Publishing House. Khan, F. I., & Abbasi, S. A. (1998f). TORAP: tool for rapid risk assessment in petroleum refinery and petrochemical industries. Journal of Loss Prevention in the Process Industries, 12, 299–313. Khan, F. I., & Abbasi, S. A. (1998g). Techniques and methodologies for risk analysis in chemical process industries. Journal of Loss Prevention in the Process Industries, 11, 261–277. Khan, F. I., & Abbasi, S. A. (1999a). PROFAT: a new tool for probabilistic fault tree analysis in chemical process industries. Process Safety Progress, 18 (1), 21–34. Khan, F. I., & Abbasi, S. A. (1999b). Major accidents in process industries and analysis of their causes and consequences. Journal of Loss Prevention in the Process Industries, 12, 361–378.

F.I. Khan et al. / Journal of Loss Prevention in the Process Industries 14 (2001) 413–427

Khan, F. I., & Abbasi, S. A. (1999c). The worst chemical industry accident of 1990s — what happened and what might have been: a quantitative study. Process Safety Progress, 18, 135–145. Khan, F. I., & Abbasi, S. A. (1999d). MAXCRED — a new software package for rapid risk assessment in chemical process industries. Environment Modeling and Software, 14, 11–25. Khan, F. I., & Abbasi, S. A. (2000a). Analytical simulation and PROFAT II: a new methodology and a computer automated tool for fault tree analysis in chemical process industries. Journal of Hazardous Materials, A75, 1–27. Khan, F. I., & Abbasi, S. A. (2000b). Modeling and simulation of heavy gas dispersion on the basis of modification in plume path theory. Journal of Hazardous Materials, 80 (1–3), 15–30. Kletz, T. A. (1977). Unconfined vapor cloud explosions. AIChE Loss Prevention, 11, 50. Lees, F. P. (1996). Loss prevention in CPI. London: Butterworths. Management of process hazards, (1990). API recommended practice 750. (1st ed.). Washington, DC: American Petroleum Institute (API). Martinsen, W. E., Johnson, D. W., & Terell, W. F. (1986). BLEVE: their causes effects and prevention. Hydrocarbon Processing, 65 (11), 141. Pasquill, F., & Smith, F. B. (1983). Atmospheric diffusion. New York: John Wiley. Pietersen, C. M. (1985). Analysis of the LPG-incident in San Juan Ixhuasapec — Mexico city. TNO report. The Netherlands: TNO. Pietersen, C. M. (1990). Consequence of accidental release of hazardous material. Journal of Loss Prevention in the Process Industries, 3, 136–141.

427

Prugh, R. W. (1987). Evaluation of unconfined vapor cloud explosions. In Proceedings of International Conference of Vapor Cloud Modeling, AlChE, Boston, MA. Prugh, R. W. (1991). Quantitative evaluation of BLEVE hazards. Journal of Fire Protection Engineers, 3 (1), 9–24. Roberts, A. P. (1983). Thermal radiation hazard from release of LPG from pressurized storage. Fire and Safety Journal, 4, 197–212. Turner, D. B. (1970). Workbook on atmospheric dispersion estimates. Report Ap-26. Reseach Triangle Park, NC: US Environmental Protection Agency. Turner, D. B. (1985). Pragmatic method for the estimating boundary layer parameter for diffusion calculation. Boundary Layer Metrology, 8, 93–100. Van den Berg, A. C. (1985). The multi-energy method. A framework for vapor cloud explosion blast prediction. Journal of Hazardous Materials, 12 (1), 1. Van den Berg, A. C. (1989). REAGAS — a code for numerical simulation of 2-D reactive gas dynamics. In Report PML-1989-in-48. Rijswijk, The Netherlands: TNO Prins Maurits Laboratory. Van den Berg, A. C., & Lennoy, A. (1993). Methods for vapor cloud explosion blast modelling. Journal of Hazardous Materials, 34, 171. Van Ulden, A. P. (1974). On spreading of a heavy gas cloud released near ground. Loss Prevention and Safety Promotion, 1, 221. Van Ulden, A. P. (1985). Estimate of atmospheric boundary layer parameters for diffusion application. Journal of Climatology and Applied Meteorology, 25, 1609. Vernart, J. E. S., Rutledge, G. A., Sumathipala, K., & Sollows, K. (1993). To BLEVE or not to BLEVE; anatomy of boiling liquid expanding vapor explosion. Process Safety Progress, 2, 112–123.