Hazardous Gas Dispersion Research Articles

Application of uncertainty quantification techniques in the framework of process safety studies: Advanced dispersion simulations

AbstractIn the framework of process safety studies, consequence assessment of accidental scenarios is a crucial step affecting the eventual risk profile associated with the facilities under analysis. Conventional models used for consequence assessment are based on integral models, and may not be adequate to cope with the dynamic evolution of accidental scenarios and their three‐dimensional features. On the other hand, consequence assessment models based on computational fluid dynamics (CFD) approaches are promising to cope with complex scenarios and environments, but setting the simulation introduces relevant uncertainties associated with both the input data, assumptions, and with the modelling of physical effects involved. In the present study, uncertainty quantification (UQ) techniques are applied to support advanced safety studies based on CFD simulations of hazardous gas dispersion. Firstly, the accidental scenarios are characterized by defining release scenarios and conditions and quantifying source terms using integral models. At the same time, input meteorological data are gathered. This enables the development of high‐fidelity CFD simulations of gas dispersion based on different input sets and eventually the implementation of UQ techniques. The generalized polynomial chaos (gPC) expansion is employed to obtain hazardous gas concentration based on the variation of wind direction and speed. The present method is applied for the analysis of a real plant featuring a complex layout. The results show the advantages of the present approach by quantifying the influence of meteorological conditions and providing indications for supporting the development of protection systems and emergency measures.

Modelling of hazardous chemical gas building ingress and consequence analysis during a leak accident

Leakage of hazardous chemical gases during storage or transport via roadways is a common type of accident that threatens human life. This study built a typical residential building model in rural areas of southern China based on Building Information Model technology. The model was then simplified and employed as a target building to simulate the hazardous gas dispersion around it after a leak accident by means of Computational Fluid Dynamic methods. A dose-response model was combined with a probit function analysis to quantitatively identify the exposure risks for different scenarios. The impacts of source location and ventilation path on the dispersion characteristics were analyzed through comparisons of indoor concentration distributions. In addition, the study also quantified the relationship between individual mortality risk and the source intensity by employing H2S as a source of toxic substances. If the source strength was increased by 2.5 times for the same ventilation path, the corresponding mortality rates can improve from 0.1 to 99%. The findings provide effective information about rapid consequence evaluation after accidental leakage of hazardous chemical gas and could be helpful in proposing effective emergency measures to minimize the exposure risk in roadside buildings.

Simulating Flow and Hazardous Gas Dispersion by Using WRF–CFD Coupled Model under Different Atmospheric Stability Conditions

In this paper, the Weather Research and Forecasting (WRF) model is coupled with the computational fluid dynamics (CFD) model to study the diffusion model of the accidental leakage of hazardous gas under different atmospheric stability conditions. First, the field test at Nanjing University was used to validate the different turbulence models of CFD. The experimental data confirm that the realizable k-ε model can describe the behavior of hazardous gas diffusion. On this basis, the diffusion process of the accidental release of tracer gas under different atmospheric stability conditions is simulated. The results show that atmospheric stability has a significant effect on the flow field distribution and the area of plume of hazardous substances. The ambient wind deflects under unstable conditions and vertical turbulence is slightly larger than that under neutral and stable conditions. Under stable conditions, the dilution of harmful gases is suppressed due to weak turbulent mixing. In addition, stable atmospheric conditions can increase near-surface gas concentrations.

Numerical simulation of accidental released hazardous gas dispersion at a methanation plant using GASFLOW-MPI

Power-to-Gas technologies could play an important role in future energy systems, since they make it possible to store surplus electric energy from fluctuating renewable energy sources such as solar and wind. In Power-to-Gas concepts, the first step towards storage is the production of H2 by electrolysis, a possible further step is methanation. The Engler-Bunte-Institute, Fuel Technology at Karlsruhe Institute of Technology is conducting research on catalytic methanation in slurry bubble column reactors, which represent a highly load flexible reactor technology. To obtain experimental data at a semi-industrial scale a methanation pilot plant was built and commissioned. The plant is equipped with various safety valves, which may release the hazardous gases H2, CO and CH4 in the chemical reactor into the environment in the unintended case of overpressure, which may lead to a flammable and/or toxic cloud, threatening the safety of the workers and other humans near the plant. In this work, the safety evaluation of the accidental release in the methanation plant is performed using the numerical tool GASFLOW-MPI. Both toxicity and flammability of the hazardous gas cloud are analyzed and discussed. A local-global two-step simulation strategy, including a local computational model and a global computational model, is employed to calculate the hazardous gas dispersion efficiently and accurately. In the first step, a local detailed computational model with fine mesh is used to calculate the release mass flow through the exhaust tube and the complicated shock waves directly without any further assumption model such as the notional nozzle model. In the second step, a large-scale model with the relatively coarse mesh is chosen to efficiently predict the hazardous gas dispersion around the entire methanation plant. Moreover, the performances of two different types of exhaust pipes are compared and discussed, and the recommended exhaust pipe design is provided. The simulation results show that version B of the exhaust tubes is more recommendable from the viewpoint of safety.

Numerical Investigation of Hazardous Gas Dispersion Over Obstacles and Residential Areas

In the present study, an attempt has been made to use Computational Fluid Dynamics (CFD) in the assessment of hazardous gas dispersion over obstacles. For this aim, the accidental dispersion of hazardous gas from the hole and the effect of different parameters such as changes in inlet wind velocity, the direction of the pollutant cloud and its movement, mass fraction of gas dispersion, and the pressure distribution were numerically analyzed. The flow was assumed as three-dimensional, unsteady, turbulent, and compressible. Different turbulent models were used in modeling the gas release and the most accurate one was suggested. The numerical simulation demonstrated that the gas mass fraction increased significantly due to the sudden dispersion of the gas. The amount of gas concentration gradually decreased after the formation of pollutant clouds by moving in the horizontal direction. Moreover, gas mass fraction had decreased by increasing the height. Comparing the results revealed that the pollutant cloud did not cover the surrounding area in the wind velocity of 1 m/s. Therefore, the pollutant clouds generated in this case could not impose a threat. In higher wind velocities (3 m/s and 5 m/s), the pollutant cloud approximately covered the surrounding areas, which caused a severe threat. The maximum overpressure at the hole is 5.7 Pa for a wind velocity of 5 m/s, while the maximum negative pressure was about -7.1 Pa. The influencing radius was obtained about 9.3 m. The overpressure did not cause obvious damage to buildings but led to a slight hurt to humans.

Modeling the effect of hypothetical chlorine leakage from Malay-Sino Chemical Industries using ALOHA software and development of an emergency evacuation route around Teluk Kalong industrial area

Malay-Sino Chemical Industries in Teluk Kalong is the largest chlor-alkali manufacturer in Malaysia, which may potentially affect the safety of plant workers and nearby residential area in the event accidental chlorine leakage. The dispersion of a hypothetical chlorine leakage from Malay-Sino Chemical Industries in Teluk Kalong industrial area was modelled using ALOHA. The effect of different wind direction, wind speed and time in the meteorological mesoscale area was evaluated. The wind speed ranging from 1.55 to 11.1 m/s obtained from a local weather station was considered. Heavy gas dispersion model was used to determine the concentration of chlorine plume within the area of concern. The leakage rate was set at 702 kg/h. The result showed that the residential area R5 (Kampung Bukit Kuang, and Kampung Sungai Terjun) is affected by the plume dispersed by northern wind at night. A greater hazard zone can be formed under the wind speed below 1.55 m/s. A suitable safety evacuation routes were proposed to reduce the risk of exposure to hazardous gas. Finding from this work is useful to understand the risk of hazardous gas dispersion around Teluk Kalong industrial area.

Turbulence Model Selection for Heavy Gases Dispersion Modeling in Topographically Complex Area

The dispersion of hazardous gas in the environment presents dangerous risks for people living close to chemical plants or storages. Since heavy gases tend to stay at lower levels and disperse at a slower pace in the atmosphere, they are potentially more dangerous. In this paper, various mathematical models for turbulence (including k-ε, RNG k-ε, EARSM, LES, DES) and their associated parameters have been assessed, compared and validated against the experimental data in various scenarios to find the most suitable one for atmospheric dispersion of dense-gases. This topic has been investigated and validated by a computational fluid dynamics (CFD) simulation of the Kit-Fox experiment. The precision of the CAD models, practicality, computational resource requirements, and some other factors have been considered and addressed in this paper to achieve a comprehensive solution for atmospheric dispersion. The results here suggest that the proper selection of the turbulence model and the turbulent Schmidt number is crucial. Our results indicate that the most promising combination in the case of atmospheric dense-gas dispersion is the RNG k-ε model with the Schmidt number of 0.4, considering the demand for accuracy and computational resource.

Fused CFD-interpolation model for real-time prediction of hazardous gas dispersion in emergency rescue

Accidental releases of hazardous gases in chemical industries can pose great threats to public security. The computational fluid dynamics (CFD) model is commonly applied to predict gas dispersion in complex structured areas. It can provide good accuracy but it is too time-consuming to be used in emergency response. To reduce computation time while keep acceptable accuracy, this paper proposes several fused CFD-interpolation models which combine CFD model with different interpolation methods. Spline, linear and nearest interpolation methods are used. A CFD simulations database is created ahead of time which can be quickly recalled for emergency usage and unknown situations can be predicted instantly by interpolation methods instead of time-consuming CFD model. Fused models were applied to a case study involving a hypothetical propane release with varying conditions and validated against CFD model. The validation shows that prediction accuracy of these fusion models is acceptable. Among these models, CFD-Spline interpolation model performs best. It is faster than CFD model by a factor of 75 and is potentially a good method to be applied to real-time prediction.

Numerical Modelling of Air Pollutant Dispersion in Complex Urban Areas: Investigation of City Parts from Downtowns Hanover and Frankfurt

Hazardous gas dispersion within a complex urban environment in 1:1 scaled geometry of German cities, Hanover and Frankfurt, is predicted using an advanced turbulence model. The investigation involves a large group of real buildings with a high level of details. For this purpose, Computer Aided Design (CAD) of two configurations are cleaned, then fine grids meshed in. Weather conditions are introduced using power law velocity profiles at inlets boundary. The investigation focused on the effects of release locations and material properties of the contaminants (e.g., densities) on the convection/diffusion of pollutants within complex urban area. Two geometries demonstrating different topologies and boundaries conditions are investigated. Pollutants are introduced into the computational domain through chimney and/or pipe leakages in various locations. Simulations are carried out using Large Eddy Simulation (LES) turbulence model and species transport for the pollutants. The weather conditions are accounted for using a logarithmic velocity profile at inlets. CH4 and CO2 distributions, as well as turbulence quantities and velocity profiles, show important influences on the dispersion behavior of the hazardous gas.

On possibilities to estimate local concentration variations with CFD-LES in real urban environments

Applied studies with Large Eddy Simulation (LES) of hazardous gas dispersion around buildings in cities have become increasingly feasible due to rapid advancements in computing technology. However, there is little extant literature investigating how each model’s results compare with others, as well as their ability to predict near-field dispersion in a real city. In this study, three typical LES sub-grid-scale models are used to simulate gas dispersion, utilizing alternatively constant values and synthetic turbulence at inflow boundaries. The results are compared with data from the Joint Urban 2003 Atmospheric Dispersion Study in Oklahoma City. Flow and turbulence statistics of the simulation is presented at two probe locations, one inside the city-core and one outside. In addition, comparisons with the measured mean concentration and maximum concentration values are conducted. It was found that in the core of the city, simulated turbulence is mainly determined by buildings and their configurations, and is only weakly affected by model type and assumed turbulence at the inflow boundaries. On the other hand, outside and upwind the city center the turbulence set at the inflow boundaries is very important if realistic turbulence statistics is to be achieved. Downstream of the source, all tested models produce similar predictions of maximum concentration values, which in turn are similar to the experimental data. Thus, the results indicate that it could be better to use the LES calculated maximum-concentration instead of the calculated mean-concentration when developing methods for hazard area estimation.

Optimization Scheme for Construction Ventilation in Large-Scale Underground Oil Storage Caverns

The ventilation effect has a direct influence on the efficiency and security of the construction of an underground cavern group. Traditional forced ventilation schemes may be ineffective and result in resource wastage. Based on the construction ventilation of the Jinzhou underground oil storage project, an axial flow gallery ventilation mode using shafts as the fresh air inlet was proposed. A 3D steady RANS (Reynolds Averaged Navier-Stokes) approach with the RNG (Renormalization-group) k-ε turbulence model was used to study airflow behavior and hazardous gas dispersion when different ventilation schemes were employed. Field test values of the air velocity and CO concentration in the main cavern and construction roadway were also adopted to validate the RNG k-ε turbulence model. The results showed that the axial flow gallery ventilation mode can ensure that the direction of air flow is the same as that of heavy trucks, fresh air is always near the excavation face, and the disturbance of the construction process is greatly reduced. The scheme is suitable for large-scale caverns with a ventilation distance less than 2 km, and an intermediate construction shaft is not needed. When the ventilation distance exceeds 2 km, it is possible to use jet fans to assist the axial flow gallery ventilation mode or to completely adopt jet-flow gallery ventilation.

Study of Dispersion Hazard Potential of The LPG Stations Around the RDE Site in Rainy and Dry Season

STUDY OF DISPERSION HAZARD POTENTIAL OF THE LPG STATIONS AROUND THE RDE SITE IN RAINY AND DRY SEASON. There are two LPG station (SPPBE) which are the depot of filling, storage and distribution of Liquid Petroleum Gas (LPG) namely PT. BM and PT. ISR which the distance each are 2,995 and 4,141 km from Experimental Power Reactor (RDE) site with capacity 15 and 30 tons. LPG station is a stationary source, which is one aspect of the external human induced events that need to be analyzed in the preparation of site evaluation reports to obtain site permits. Hazard potential that may occur from the depot LPG are fire, explosion and dispersion of hazardous and toxic gas. The release of LPG due to valve leakage which is then dispersed at a certain dose has potentially harmful to health, even death to the population around the RDE site. The purpose of the study was to know the effect of seasons (rainy and dry) to the potential hazard of LPG dispersion from LPG truck tank valve to the around RDE site. The method of study are collection the atmospheric data such as wind direction and speed, temperature and humidity, collection the station LPG characteristic, such as mass of gas, diameter and length of tank, and valve diameter, etc. The atmospheric data was obtained from Pondok Betung Climatology Station, in dry, transition, and rainy seasons, furthermore data was analyzed using ALOHA software version 5.4.5. The results show dispersion from LPG release due to valve leakage from PT. BM and PT. ISR around the RDE site, in the dry season (April), the transition (January and July) as well as the rainy season (October) does not hazardous to the RDE site. Maximum threat zone occurs in dry season at April (wind speed 1.54 m/s), which reaches radius 179 m with airborne LPG concentration 5500 ppm, radius 111 m with concentration 17000 ppm and radius 71 m with concentration 53000 ppm.

Data-Driven Hazardous Gas Dispersion Modeling Using the Integration of Particle Filtering and Error Propagation Detection.

The accurate prediction of hazardous gas dispersion process is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in a chemical cluster. Conventional Gaussian-based dispersion models can seldom give accurate predictions due to inaccurate input parameters and the computational errors. In order to improve the prediction accuracy of a dispersion model, a data-driven air dispersion modeling method based on data assimilation is proposed by applying particle filter to Gaussian-based dispersion model. The core of the method is continually updating dispersion coefficients by assimilating observed data into the model during the calculation process. Another contribution of this paper is that error propagation detection rules are proposed to evaluate their effects since the measured and computational errors are inevitable. So environmental protection authorities can be informed to what extent the model output is of high confidence. To test the feasibility of our method, a numerical experiment utilizing the SF6 concentration data sampled from an Indianapolis field study is conducted. Results of accuracy analysis and error inspection imply that Gaussian dispersion models based on particle filtering and error propagation detection have better performance than traditional dispersion models in practice though sacrificing some computational efficiency.

Comparison of Machine Learning Models for Hazardous Gas Dispersion Prediction in Field Cases.

Dispersion prediction plays a significant role in the management and emergency response to hazardous gas emissions and accidental leaks. Compared with conventional atmospheric dispersion models, machine leaning (ML) models have both high accuracy and efficiency in terms of prediction, especially in field cases. However, selection of model type and the inputs of the ML model are still essential problems. To address this issue, two ML models (i.e., the back propagation (BP) network and support vector regression (SVR) with different input selections (i.e., original monitoring parameters and integrated Gaussian parameters) are proposed in this paper. To compare the performances of presented ML models in field cases, these models are evaluated using the Prairie Grass and Indianapolis field data sets. The influence of the training set scale on the performances of ML models is analyzed as well. Results demonstrate that the integrated Gaussian parameters indeed improve the prediction accuracy in the Prairie Grass case. However, they do not make much difference in the Indianapolis case due to their inadaptability to the complex terrain conditions. In addition, it can be summarized that the SVR shows better generalization ability with relatively small training sets, but tends to under-fit the training data. In contrast, the BP network has a stronger fitting ability, but sometimes suffers from an over-fitting problem. As a result, the model and input selection presented in this paper will be of great help to environmental and public health protection in real applications.

An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries.

Chemical production activities in industrial districts pose great threats to the surrounding atmospheric environment and human health. Therefore, developing appropriate and intelligent pollution controlling strategies for the management team to monitor chemical production processes is significantly essential in a chemical industrial district. The literature shows that playing a chemical plant environmental protection (CPEP) game can force the chemical plants to be more compliant with environmental protection authorities and reduce the potential risks of hazardous gas dispersion accidents. However, results of the current literature strictly rely on several perfect assumptions which rarely hold in real-world domains, especially when dealing with human adversaries. To address bounded rationality and limited observability in human cognition, the CPEP game is extended to generate robust schedules of inspection resources for inspection agencies. The present paper is innovative on the following contributions: (i) The CPEP model is extended by taking observation frequency and observation cost of adversaries into account, and thus better reflects the industrial reality; (ii) Uncertainties such as attackers with bounded rationality, attackers with limited observation and incomplete information (i.e., the attacker’s parameters) are integrated into the extended CPEP model; (iii) Learning curve theory is employed to determine the attacker’s observability in the game solver. Results in the case study imply that this work improves the decision-making process for environmental protection authorities in practical fields by bringing more rewards to the inspection agencies and by acquiring more compliance from chemical plants.

Performance analysis of an air quality CFD model in complex environments: Numerical simulation and experimental validation with EMU observations

Assessment of air quality in complex industrial and urban regions is essential in setting effective policies for sustainable development of society and assisting to improve the environment and thereby support health and safety. In this study, a CFD model fluidyn-PANACHE, dedicated to the dispersion of hazardous gases in complex industrial and urban sites, is critically validated with tracer observations from EMU experiment for two distinct types of sources in two geometrically different environments: (i) Case-A1 (release from an open door in courtyard area of a simple L-shaped building), and (ii) Case-C1 (continuous release over the larger distances around an industrial site featuring numerous buildings and complex local topography). The steady RANS solution is used first to get quick results and comparison with the experimental data shows a good agreement between the modelled and measured concentrations. Nevertheless, in order to examine the performance of the solver, unsteady RANS simulations are performed. A detailed statistical analysis shows that the performance of fluidyn-PANACHE against both Cases of EMU observations is well within the acceptable bounds of statistical measures for air quality applications. It is observed that in a simple geometry with lesser complexity in Case-A1, steady and unsteady simulations give similar performance against the tracer observations and predicts ≈68% points within a factor of two. In a more complex industrial site in Case-C1, unsteady RANS is performing slightly better than the steady simulation and it predicts ≈80.0% points within factor of two, which is higher than ≈67.0% points from the steady simulation.

Air flow behavior and gas dispersion in the recirculation ventilation system of a twin-tunnel construction

Forced ventilation and recirculation systems are usually used in the construction of long twin tunnels as they offer large amounts of fresh air economically. However, because of the confluence near the cross-aisle, the fluid behavior and gas concentration are very different than in traditional forced ventilation for a single tunnel. A three-dimensional numerical model was built to study the air flow behavior and hazardous gas dispersion near the cross-aisle of a twin-tunnel construction. Field measurements were also carried out to validate the numerical model. The results show that there is a “dead zone” ahead of the cross-aisle which has a much lower air velocity than in other parts of the twin tunnels and where hazardous gases are more concentrated and uniformly distributed. In the cross-aisle and confluence zone of the air flow-out tunnel, methane tends to gather at the top and hydrogen sulfide tends to gather at the bottom. Increasing the recirculation velocity does not eliminate the “dead zone” near the cross-aisle although it consumes a huge amount of energy. Increasing the air velocity of the duct is an effective method to improve the air quality, but it is also expensive, especially when the air duct is long. When a jet fan was placed ahead of the cross-aisle in this study, the “dead zone” was eliminated completely. With respect to the recirculation ventilation system of twin tunnels, local jet fans offer an effective and economical way to eliminate the “dead zone”.

Experimental data and CFD performance for CO2 cloud dispersion analysis

Dispersion of hazardous gas releases represents a major threat to health and to the environment; therefore, the prediction of the dispersion features raises great interest. In recent years, with the increase in computational capacity, the interest in Computational Fluid Dynamics (CFD) tools to evaluate dispersion analysis has increased. With the growing use of CFD tools to perform dispersion analysis in different scenarios, it is imperative to amplify the availability of experimental data in order to allow validations studies to contribute to understanding the real capacity of CFD tools to properly represent real cases. The second stage of the field tests conducted by a joint venture between the University of São Paulo and the Universitat Politecnica de Catalunya was established to investigate the performance of CFD tools when analyzing cloud dispersion of hazardous substances by means of ad-hoc experimentation. The experiments consisted of CO2 clouds formation and dispersion tracking of releases of up to 0.85 kg s−1 of about 40 s of duration in a 600-m2discharge area. We provide a description of the tests and the main results of the simulation using the FLACS software; the peak concentrations for 51 sensors placed at the dispersion cloud path are provided here and compared with CFD simulations. In general terms, the CFD simulator presented good performance; all the statistical performance measures were well within the acceptable range. However, the simulator performance presented sensitivity to the wind profile, especially when cross wind occurs.

The real-time estimation of hazardous gas dispersion by the integration of gas detectors, neural network and gas dispersion models

Release of hazardous materials in chemical industries is a major threat to surrounding areas. Current gas dispersion models like PHAST and FLACS, use release velocity, release elevation, meteorological parameters, and other related information as model input. In general, such information is not always available during an on-going accident. In this paper, we develop a fast prediction approach which could bypass the input parameters that are difficult to obtain and predict the released gas concentration at certain off-site location using parameters that could be obtained easily. The new approach is an integration of gas detectors, artificial neural network (ANN) and one of the aforementioned gas dispersion models. PHAST is applied to simulate numbers of release scenarios and the results containing the spatial and temporal distributions of released gas concentration are prepared as input and target data samples for training the neural network. The approach was applied to a case study involving a hypothetical chlorine release with varying release rates and atmospheric conditions. The results of the approach that are concentration and dispersion time profiles in the environmental sensitive locations were validated against PHAST. The validation shows highly correlations with PHAST and convincingly demonstrates the effectiveness of the proposed approach.

Prediction and innovative control strategies for oxygen and hazardous gases from diesel emission in underground mines

Diesel engine is widely used in underground mining machines due to its efficiency, ease of maintenance, reliability and durability. However, it possesses significant danger to the miners and mining operations as it releases hazardous gases (CO, NO, CO2) and fine particles which can be easily inhaled by the miners. Moreover, the diesel engine consumes significant amount of oxygen which can lead to insufficient oxygen supply for miners. It is therefore critical to maintain sufficient oxygen supply while keeping hazardous gas concentrations from diesel emission below the maximum allowable level. The objective of this study is to propose and to examine various innovative ventilation strategies to control oxygen and hazardous gas concentrations in underground mine to ensure safety, productivity and cost related to energy consumption. Airflow distribution, oxygen and hazardous gas dispersion as well as ambient temperature within the mining area are evaluated by utilizing the well-established computational fluid dynamics (CFD) approach. The results suggest that our newly proposed ventilation design performs better as compared to the conventional design to handle hazardous gases from diesel emission.