Worst-case identification of gas dispersion for gas detector mapping using dispersion modeling

doi:10.1016/j.jlp.2013.08.019

Journal of Loss Prevention in the Process Industries

Volume 26, Issue 6, November 2013, Pages 1407-1414

https://doi.org/10.1016/j.jlp.2013.08.019 Get rights and content

Highlights

•
Gas dispersion was modeled for different cases of weather condition, release height and release location on plot plan.
•
The appropriate case of weather condition for dispersion modeling in order to place gas detector was the cold half-year.
•
The appropriate case of release height for dispersion modeling in order to place gas detector was the bottom of vessel.
•
The appropriate case of release location for dispersion modeling in order to place gas detector was the north of vessel.
•
Gas detectors were placed for an adsorber tower using modeling gas dispersion based on the selected appropriate cases.

Abstract

To quickly and accurately quantify the material release in process units, gas detectors may be placed according to the results of gas dispersion modeling. DNV's PHAST software is one of the most useful and reliable tools for material dispersion modeling. In this software, fluid dispersion is modeled based on the process conditions, the weather conditions and the specifications of the material release point. However, varying weather conditions throughout the year and the exact determination of the release point on the plot plan and the release elevation are problematic; these issues cause the results to be non-exact and non-integrated. Choosing the most appropriate conditions is challenging. In this paper, a scheme was provided to select the most appropriate conditions for gas dispersion modeling. This scheme approaches modeling based on the worst-case scenario (the situation in which the dispersed gas reaches the detector later in comparison to the other cases). Therefore, different weather conditions, release elevations and release points on the plot plan were modeled for an absorber tower of the Gonbadli Dehydration Unit of the Khangiran Refinery. The worst case of each release condition was then chosen. Finally, gas detectors were placed using the gas dispersion modeling results based on the worst-case scenario.

Introduction

Vessel leakage and rupture are the main sources of catastrophic events in the process industries, causing material dispersion, fire and explosion. Flixborough of England in 1974 (Report of the Court of Inquiry, 1975) and toxic gas release in Seveso (Italy) in 1978 (Assael & Kakosimos, 2010) are examples of events that occurred as a result of material release from vessels. The consequences of these events, in contrast to those that occurred before 1960, extended beyond the factory. Additionally, in Bhopal (India), one of the worst catastrophes in the process industries occurred for the same reason as a catastrophe in 1984 (Assael & Kakosimos, 2010). These events make material release awareness more necessary than ever. Therefore, gas detectors as tools to monitor alarming gas leakage are used in the process industries. One of the gas detector properties that affects its performance is its installation location. Thus, the most appropriate location must be chosen. In this study, a scheme for gas detector placement has been presented to optimize detector installation and increase the performance of gas detectors.

Currently, a high volume of chemicals with specific properties exists in the process industries. Thus, it is necessary to be able to predict the behavior of a released fluid to estimate potential injuries, make a rapid reaction plan and mitigate the consequences.

PHAST Software is a tool used for behavior prediction and dispersion modeling, presented by DNV in 1999. PHAST not only includes different event models but also makes the study of material release consequences possible, from leakage to explosion (Ruiz-Sánchez, Nelson, François, Cruz-Gómez, & Mendoza, 2012). PHAST is useful because it does not require large amounts of input data and its calculation time is very short. Additionally, it provides required data for the risk assessment of equipment and processes (Witlox, Stene, Harper, & Nilsen, 2011). Using this software, events are modeled based on process conditions such as pressure, temperature, material composition, material flow rate, atmospheric conditions and the properties of the material release point (Witlox, Harper, & Oke, 2009). By modeling the release consequences using PHAST software, the manner of dispersion and the amount of released material versus time can be determined. PHAST software graphs are presented as concentration versus distance and time. By looking at the results of the gas dispersion modeling at a specific time after release, optimized gas detector placement will be possible. The specific time is determined based on the Emergency Shutdown System of the unit and personnel ability during emergency response. This study discusses gas detector placement by dispersion modeling using PHAST 6.54 software based on the appropriate conditions.

Section snippets

Process conditions

Gas extracted from the earth must be properly treated for industrial and domestic use. One of the treatment steps is to separate extra water and hydrocarbons. The Gonbadli Dehydration Unit of the Khangiran Gas Refinery was designed to control the dew point of gas. The gas first passes through a loop. After the heavy hydrocarbons are separated, water and the remaining hydrocarbons enter the Gonbadli unit. 99.8% of the feed gas is methane (based on the process description of the Gonbadli

The worst-case selection

In PHAST, events are modeled based on the process conditions, atmospheric conditions and release point properties. To increase the accuracy, dispersion should be modeled based on the appropriate input data. However, it is difficult to examine the most appropriate weather conditions, release elevation and release point on the plot plan. The most appropriate conditions are represented by the situation where the release detection will be definite at a desirable time in the other conditions as

Gas detector placement

The worst-case scenario for gas dispersion was determined in the previous section. The selected conditions are appropriate for dispersion modeling of the other vessels. In this paper, the detectors were located for the absorber tower V-1600 as an example. With this in mind, gas dispersion versus time graphs were used to determine the optimal detector location. Based on the worst-case studies, dispersion was modeled for gas release from the bottom of the vessel with a height of 1.65 m in the

Conclusions and recommendations

Release in vessels can cause material dispersion, fire and explosion in the process industries (Fig. 11). Modeling of this dispersion is useful to predict the behavior of the released material and to properly place gas detectors. However, weather conditions, release elevation and release location on the plot plan, which are required for modeling, are variable. Thus, dispersion should be modeled based on the most appropriate cases (the worst-case scenario for gas dispersion). In this paper, gas

References (7)

T. Ruiz-Sánchez et al.
Application of the accident consequence analysis in the emergency system design of an SI cycle hydrogen production plant
International Journal of Hydrogen Energy
(2012)
H.W.M. Witlox et al.
Modeling of discharge and atmospheric dispersion for carbon dioxide releases
Journal of Loss Prevention in the Process Industries
(2009)
H.W.M. Witlox et al.
Modeling of discharge and atmospheric dispersion for carbon dioxide releases including sensitivity analysis for wide range of scenarios
Energy Procedia
(2011)

There are more references available in the full text version of this article.

Cited by (19)

Optimization of gas detector placement considering scenario probability and detector reliability in oil refinery installation
2020, Journal of Loss Prevention in the Process Industries
Citation Excerpt :
These accidents demonstrate besides good management of process safety and safety culture,in-time detection of hazardous gas release is a key element to prevent major accidents in process plants. However, one of the challenges to ensure efficient detection is the proper placement of gas detectors (Legg et al., 2012; Meysami et al., 2013; Rad and Rashtchian, 2016). Traditional methods applied for gas detector placement are experiential, typically based on standards, regulations and recommended practices, such as API (API, 2001), ISA (ISA, 2003), and so forth (IEC, 2007; ISA, 2010; NFPA, 2007).
Gas detection system is a critical layer of protection in process safety. Leak scenario probability and detector reliability are two key factors in the optimization of gas detector placement. However, they are easily neglected in previous studies, which may lead to an inaccurate evaluation of the optimization solutions. In this study, a stochastic programming (SP) optimization method is proposed considering these two factors. In order to quantitatively represent the probability of leak scenarios, a complete accident scenario set (CASS) is built combining leak sources and wind fields. Then, the computational fluid dynamics (CFD) method is adopted for consequence modeling of gas dispersion. The Markov model is developed to predict the detector reliability. With the objective of minimal cumulative detection time (MCDT), the SP formulation considering scenario probability and detector reliability (MCDT-SPR) is proposed. By introducing the particle swarm optimization (PSO) algorithm, the optimization formulations can be solved. A case study is investigated on a diesel hydrogenation refining unit. Results validate this approach is promising to improve the detection efficiency. This method is more practical and matching with the actual industrial environment, where the leak scenarios and the detector reliability can change dynamically in real process setting.
Risk hotspot of chemical accidents based on spatial analysis in Ulsan, South Korea
2020, Safety Science
The chemical industry is one of the major industries driving the Korean economy. However, increased chemical use accompanied by obsolete equipment and careless management has promoted the occurrence of chemical accidents. Therefore, to develop a preventive planning that can minimize human injury and economic losses caused by possible accidents, chemical risk hotspots should be identified. This study proposed a methodology based on geographical information system (GIS) and remote sensing (RS) to map risk hotspots in Ulsan, South Korea. Considering causes and effects of accidents, four categories were analyzed from a physical and social perspective: source of pollution (chemical plants and accidents), catalyst of pollution (wind speed and land surface temperature), receptor (population and residential area), and coping ability (distance to the nearest hospital, fire station, and main road). The results showed that the chemical risk hotspot covers at least 16 dongs of Ulsan and involves approximately 400,000 citizens, which represent 38% of the city's population. In addition, issues such as aging factories, contaminated environments, and lack of safety education further increase the chemical risk. Therefore, regular safety monitoring of chemical plants and their surroundings is essential to reduce future risks in this area.
Designing an effective mitigation system based on the physical barrier for hazardous chemical leakage accidents
2019, Journal of Industrial and Engineering Chemistry
An evaluation module based on the liquid discharge trajectory equation was developed to improve the safety as a result of chemical leakage accidents. An evaluation was performed on leakage based on changes in the vessel pressure and discharge height during a leakage accident involving a vertical storage tank containing 35% hydrochloric acid (HCl). In addition, areal locations of hazardous atmospheres (ALOHA) and the Phast program were used to evaluate the impact and dispersion range of the discharged hazardous chemicals. The evaluation results showed that installing the mitigation system resulted in a maximum 72.8% reduction in the damage impact range in the emergency response planning guideline (ERPG)-2 distance. It was also confirmed by the Phast analysis that the dispersion range and pattern were changed according to the presence of a dike. The dispersion range decreased by up to 40% depending on the presence of the dike. It was concluded that the dispersion range is related to the physical and chemical characteristics of hazardous chemicals.
Leakage risk quantitative calculation model and its application for anaerobic reactor
2017, Journal of the Taiwan Institute of Chemical Engineers
Citation Excerpt :
According to the above-mentioned three meteorological groups, as well as the combustion limit (UFL, LFL and LFL Frac), the radiation intensity of jet fire (4 kw/m2, 12.5 kw/m2 and 37.5 kw/m2), explosion overpressure range (0.02 bar, 0.13 bar and 0.2 bar) and other five target parameters in the calculation results, we are able to obtain the fitting formulas of all dependent variables respectively, and then take these formulas as the mathematical model used for later analysis and forecast. According to the above results gained from the orthogonal experiment, we can know that the working condition of the worst case scenario (WCS) is the leakage of ground broken pipe, namely, the leakage caliber is 150 mm and the leakage position is on the ground [18]. According to the size and position of typical leakage hole of API 581 [19], some potential leakage scenarios are classified based on actual situation in Table 5.
Anaerobic reactor is one of the most important reaction devices for biogas engineering. Fire, explosion and toxic incidents will be triggered if the biogas leaks, and severe serial explosion accidents will be easily caused if the leakage cannot be identified, monitored and warned early in the process of production and operation. Therefore, this paper aims to establish a leakage risk monitoring and early-warning model for anaerobic reactor. First of all, this paper collects the data from the simulation results of biogas leakage and diffusion, fire, explosion and other accidents, analyses the mechanism correlation that causes accidents of such multi-factor coupling as leakage calibers, elevation of leakage source, weather conditions and environments based on accident information, and finds major reasons that cause the anaerobic reactor accidents and their coupling relationships; second, a multi-parameter coupled model is established in this paper, which can be used to calculate the risk of all kinds of common leakage situations and obtain the information of accident consequences under various scenarios according to parametric variation; finally, this paper develops a quantitative calculation software aiming at the leakage hazards of anaerobic reactor in accordance with this monitoring early-warning model. This software can be employed to evaluate the safety distance and operation area by importing the data of actual production and operation. It can be calculated by the developed software that there shall be at least 9.5 m between anaerobic reactors, and the recommendation on the point location of the gas leakage detector is that the ground leakage source is from0.864 m (LFL) to 2.432 m (1/2 LFL). Besides, the distance of thermal radiation area in the emergency plan is planned.
Long-term consequence and vulnerability assessment of thermal radiation hazard from LNG explosive fireball in open space based on full-scale experiment and PHAST
2017, Journal of Loss Prevention in the Process Industries
Citation Excerpt :
The fatalities, which are the degree of harm to humans and surroundings, were applied based on the following criteria (Witlox et al., 2012; Woodward and Worthington, 1999; Crowl and Louvar, 2002b). According to the research results of thermal radiant flux criterion by China Academy of Safety Science and Technology (Witlox and Oke, 2008; Witlox, 2010b; Meysami et al., 2013), as presented in Table 2, these thermal radiant values vary from 1.6 to 37.5 kW/m2 and it is classified with five harmful level. As for the fatal zone, there is a 1% probability of death that if the person stays within the area for 10 s, comparatively, the people will not suffer from any harmful effects even if they have no protection in safe zone.
This study is related to consequence analyses of accidental LNG explosions are often carried out to assess the long-term consequence and vulnerability of the gas transportation pipeline system. In these consequence analyses, it's indispensable to adequately predict the thermal radiation intensity of LNG explosive fireball process in open space. In this study, a new empirical theoretical method for explosive fireball in open space was developed and a full-scale experiment involving LNG explosion in transmission pipeline was carried out. Significant theoretical prediction, experimental testing and quantitative analysis with numerical simulation commenced leading to a better understanding of the thermal radiation hazard from LNG explosive fireball. The parameters of LNG explosive fireball were compared and verified with the full-scale experimental data, and it found that the theoretical predictions agreed well with experimental data. To demonstrate and verify the probability and potential hazard range to humans and surroundings, hazard analysis of this case was performed on the PHAST simulator. Based on the corresponding thermal radiation harm criterion, it is concluded that a near 100% fatality is expected in the range of within 190 m and there is no any harm when people stay beyond the scope with the ellipse diameter of 720 m.
Utilization of regression technique to develop a predictive model for hazard radius from release of typical methane-rich natural gas
2016, Journal of Loss Prevention in the Process Industries
Citation Excerpt :
The resultant data formed a complete database (Table 3) which provides a regression-based model over it. Effective factors on hazard radius are in two categories: meteorological parameters and process parameters (Meysami et al., 2013). The area classification process is NOT a full hazard assessment which takes account of the range of meteorological and process conditions and release events (Roberts, 2001).
The aim of hazardous area classification around equipment handling or storing of flammable fluids is to avoid the ignition of those releases that may occur from time to time in the operation of these equipment. There is a point source approach for the classification of hazardous areas which can estimate hazard radius by using hole size and release pressure. Methane-rich natural gas is widely used or produced in the process industries. Till date, there exist no reference that represents hazard radii for the wide range of possible hole sizes and release pressures of this fluid. The aim of the present study was to propose a predictive model for estimation of hazard radii due to releases of typical methane-rich natural gas based on hole size and release pressure. In this study, a complete database of hazard radii due to a broad range of hole sizes and release pressures was provided using available discharge and dispersion models. A regression-based model for estimation of hazard radii was developed based on the provided database. Performance investigation of the proposed model and a case study showed that the results are reliable with an acceptable standard error.

View all citing articles on Scopus

View full text