Vapor Cloud Research Articles

Blast-Resistant Performance of Steel Petrochemical Control Room with 3D-Kagome Sandwich Wall

As the control brain of the petrochemical plant, blast-resistant performance requirements are important for the sustainability of the petrochemical control room and should be guaranteed when the vapor cloud explosion occurs in the petrochemical production process. The 3D-Kagome truss core sandwich structure is a kind of blast-resistant material with high energy absorption and recycling. Considering the influential factors of the radius of the truss core rod and thickness of the upper and lower panels, in this paper, the blast-resistant performance of a real steel petrochemical control room with a 3D-Kagome truss core sandwich wall was analyzed. With the optimization goal of plastic deformation energy and panel displacement, the optimal wall thickness and radius of the truss core rod were obtained. The optimized blast-resistant walls were assembled, and the dynamic response of the steel petrochemical control room with the 3D-Kagome truss core sandwich blast-resistant wall was analyzed. The simulation results indicate that the truss core layer is ineffective in dissipating blast energy when the radius ratio of the truss core rod exceeds 2.7% of the total wall thickness. Moreover, as the thickness of the upper and lower panels increases from 0.5 cm to 3 cm, the proportion of plastic deformation energy in the truss core layer gradually rises from 55% to 95%, stabilizing at around 90%. The optimal configuration for blast resistance is achieved when the panel thickness ratio is 6.7% of the total wall thickness; the truss core rod radius ratio is 2.7% of the total thickness. This study establishes the effectiveness of the optimized 3D-Kagome sandwich wall as a blast-resistant solution for steel petrochemical control rooms.

Experimental and numerical study on natural gas explosion evolution in open space under different initial conditions

The vapor cloud explosion in open space are greatly affected by the initial conditions of gas cloud and the surrounding environment, while in the gas compressor station, these factors are ubiquitous. While the researches of external influencing factors like the obstacle and initial turbulence effect on natural gas explosion in open space are rare. In this paper, a series of natural gas explosion experiments were conducted and a long-distance natural gas pipeline compressor station was taking as an example to simulate the natural gas leakage and explosion in the typical location. Results showed that the greater the initial turbulence, the greater the peak overpressure of gas explosion. When the initial wind speed is 5 m/s, the peak overpressure can promote 73.4 % higher than that without initial turbulence. However, the overpressure doesn't linearly increase with the increasing of initial wind speed. What's more, the flame speed showed the same law with the overpressure, and the effect of concentration on overpressure is lower than that of initial turbulence and obstacle density. The explosion damaging range in the condenser area is larger than that in the separator area, and the maximum overpressure can reach about 21 kPa and the temperature can reach above 2280K, which provides an important basis for the safety prevention and personnel protection in natural gas compressor station.

Табиғи және техногендік сипаттағы өрттердің зиянды шығарындыларын талдау

Over the past decade, the number of natural and man-made fires has increased, which lead to great casualties, serious environmental pollution and large economic losses. The paper presents the statistics of forest and steppe fires for 2022 in the Republic Kazakhstan, and the statistics of deaths in emergencies associated with a fire. During forest fires, the composition of combustion products depends on the composition of wood and the conditions of its combustion. Accordingly, the emissions are carbon dioxide, nitrogen, carbon monoxide and sulfur dioxide. Also, the calculation of the explosion radius in the diesel fuel warehouse was made. It has been established that the maximum explosion pressure and flame temperature for mixtures of limiting composition are practically constant at different initial pressures. For a mixture of constant composition, these characteristics change significantly with an increase in the initial pressure. The composition of combustion products is analyzed at various initial pressures. From the analysis of time scales, area, facilities and equipment, ignition sources, types of emergency substances and liability, statistical results show that the most dangerous area is the loading and unloading area and the most vulnerable facility and equipment are storage tanks. Meanwhile, the proportions of ignition sources are distributed so evenly that the prevention of fire and explosion must be equally focused on several factors of influence. A vapor cloud explosion may be the most common type of accident at oil depots, and management responsibility dominates all accident causes. A visual interpretation of the obtained results is presented.

Agent-based risk modeling of domino effects in urban LNG stations

As the transfer hub between natural gas and users, urban LNG stations (ULSs) are the important link of the whole LNG industry chain. Due to special geographical location and various process equipment, potential risks in ULSs, especially domino effect accidents, usually lead to catastrophic consequences and social impacts. In this study, a dynamic risk assessment model for analyzing domino effects in urban LNG stations (DRADL) based on agent modelling and simulation is proposed. Tanks and tank cars as well as vaporizers and boilers in ULSs are modeled. A set of physical process and effect models are employed as the simulation process in this paper. Considering the lightweight nature and narrow flammability limit of LNG vapor cloud, a cyclic process is applied to judge the consequences of vapor cloud dispersion, which could avoid overestimating the results. A real urban LNG station is taken as a case study for modeling its potential domino effect risk. The results demonstrate the effectiveness and the advantages of the proposed ABMS approach for LNG dynamic risk assessment. The proposed DRADL model takes into account the combined effects of explosion and fire and LNG characteristics, which can provide guidance for risk management and rescue operation of domino effect accidents in urban LNG stations.

Large scale experimental research of VCEs – A summary from one viewpoint

Vapor cloud explosions (VCEs) are rare but have severe consequences, both in terms of harm and damage. The cause of pressure generation in these explosions was poorly understood five decades ago and methods for estimating the hazard at any location took no account of the factors that might influence the severity of a VCE. The situation two decades into the 21st century is vastly different; we understand the importance of repeated obstacles such as process pipework within a vapor cloud and have validated tools for modelling VCEs. These tools are routinely used in the design of facilities handling large quantities of flammable fluid. This considerable advance was achieved through model development progressing alongside experimental research, ranging from laboratory studies up to full scale experiments. Acknowledging that many organizations were involved in this research; this paper presents one thread through the research, concentrating on large scale experimental research spanning the five decades. This experimental research was both prompted and influenced by three disasters in the UK, Flixborough (1974), Piper Alpha (1988) and Buncefield (2005) but continues to be relevant given the expanding role of hydrogen within the energy transition to net-zero greenhouse gas emissions.

Evaporation from a cylindrical cavity: effect of gravity on the vapour cloud

We examine the vapour cloud of a pure liquid evaporating from a millimetric cylindrical well/cavity/aperture. This is accomplished by injecting the liquid up a vertical pipe towards its outlet onto a horizontal substrate. The injection is halted before the liquid surpasses the substrate level. The resulting final state is a meniscus at or near the pipe's end. The analysis is realised by vapour interferometry (side view over the substrate) closely intertwined with simulations (including Stefan flow), which also help to fill up certain gaps in the measurements and provide computed evaporation rates. Comparison with experiment is facilitated by converting the computed vapour clouds into interferometric images, especially helpful when an inverse (Abel-type) conversion is difficult. Experiments are conducted in both microgravity (via parabolic flights) and ground conditions, thus enabling direct assessment of the role of gravity. The contrast is accentuated by a working liquid with heavy vapour (refrigerant HFE-7100), when instead of being flattened on ground the vapour cloud assumes a roughly hemispherical shape in microgravity. Furthermore, a non-trivial vapour-cloud response to the flight ${\rm g}$ -jitter (residual gravity oscillations) is unveiled, ${\rm g}$ -jitter vibrations posing a challenge for interferometry itself. A number of undesired but curious side issues are revealed. One concerns vapour formed deep inside the pipe during rapid injection and subsequently ejected into the field of view, which is detected experimentally and quantified in terms of vapour Taylor dispersion in the pipe. Others are an injection volume anomaly and parasitic postinjection specifically observed in microgravity conditions.

CFD Turbulence Models Assessment for the Cavitation Phenomenon in a Rectangular Profile Venturi Tube

This study investigates cavitation in a rectangular-profile Venturi tube using numerical simulations and four turbulence models. The unsteady Reynolds-averaged Navier–Stokes technique is employed to simulate vapor cloud formation and compared against experimental data. κ-ε realizable, κ-ε RNG, κ-ω SST, and κ-ω GEKO models are evaluated. The simulation results are analyzed for pressure, turbulence, and vapor cloud formation. Discrepancies in cavitation cloud formation among turbulence models are attributed to turbulence and vapor cloud interactions. RNG and SST models exhibit closer alignment with the experimental data, with RNG showing a superior performance. Key findings include significant vapor cloud shape differences across turbulence models. The RNG model best predicts velocity at the throat exit with an error of 4.145%. Static pressure predictions include an error of 4.47%. The vapor cloud length predictions show variation among models, with the RNG model having a 0.386% error for the minimum length and 4.9845% for the maximum length. The SST model exhibits 4.907% and 13.33% errors for minimum and maximum lengths, respectively. Analysis of the cavitation number reveals agreement with the experimental data and sensitivity to cavitation onset. Different turbulence models yield diverse cloud shapes and detachment points. Weber number contours illustrate the variation in the cavitation cloud behavior under different turbulence models.

Proactive Emergency Response Strategies for First Responders to Hydrogen Gas Leakages in Vehicles

The widespread use of fossil fuels in automobiles has become a concern, particularly in light of recent frequent natural disasters, prompting a shift towards eco-friendly vehicles to mitigate greenhouse gas emissions. This shift is evident in the rapidly increasing registration rates of hydrogen vehicles. However, with the growing presence of hydrogen vehicles on roads, a corresponding rise in related accidents is anticipated, posing new challenges for first responders. In this study, computational fluid dynamics analysis was performed to develop effective response strategies for first responders dealing with high-pressure hydrogen gas leaks in vehicle accidents. The analysis revealed that in the absence of blower intervention, a vapor cloud explosion from leaked hydrogen gas could generate overpressure exceeding 13.8 kPa, potentially causing direct harm to first responders. In the event of a hydrogen vehicle accident requiring urgent rescue activities, the appropriate response strategy must be selected. The use of blowers can aid in developing a variety of strategies by reducing the risk of a vapor cloud explosion. Consequently, this study offers a tailored response strategy for first responders in hydrogen vehicle leak scenarios, emphasizing the importance of situational assessment at the incident site.

Using Computer Vision to Detect E-cigarette Content in TikTok Videos.

Previous research has identified abundant e-cigarette content on social media using primarily text-based approaches. However, frequently used social media platforms among youth, such as TikTok, contain primarily visual content, requiring the ability to detect e-cigarette-related content across large sets of videos and images. This study aims to use a computer vision technique to detect e-cigarette-related objects in TikTok videos. We searched 13 hashtags related to vaping on TikTok (eg, #vape) in November 2022 and obtained 826 still images extracted from a random selection of 254 posts. We annotated images for the presence of vaping devices, hands, and/or vapor clouds. We developed a YOLOv7-based computer vision model to detect these objects using 85% of extracted images (N = 705) for training and 15% (N = 121) for testing. Our model's recall value was 0.77 for all three classes: vape devices, hands, and vapor. Our model correctly classified vape devices 92.9% of the time, with an average F1 score of 0.81. The findings highlight the importance of having accurate and efficient methods to identify e-cigarette content on popular video-based social media platforms like TikTok. Our findings indicate that automated computer vision methods can successfully detect a range of e-cigarette-related content, including devices and vapor clouds, across images from TikTok posts. These approaches can be used to guide research and regulatory efforts. Object detection, a computer vision machine learning model, can accurately and efficiently identify e-cigarette content on a primarily visual-based social media platform by identifying the presence of vaping devices and evidence of e-cigarette use (eg, hands and vapor clouds). The methods used in this study can inform computational surveillance systems for detecting e-cigarette content on video- and image-based social media platforms to inform and enforce regulations of e-cigarette content on social media.

A risk‐based evaluation of safe distance for a hydrogen refueling station

AbstractTo ensure the safety of hydrogen refueling stations (HRSs) and protective targets in the surrounding area, this paper has introduced a risk‐based safe distance assessment method for a 35MP HRSs, emphasizing the impact of the station's surrounding area. The findings indicate that the safe distance is determined by vapor cloud explosion (VCE) accident scenarios arising from pipeline leaks (compressor‐hydrogen storage tanks) at 125 m. Therefore, a crucial focus should be placed on safeguarding and maintaining hydrogen pipelines. Furthermore, based on societal risk, the requirement of a 358‐m safe distance specifies that the population gathering within this range should be <500 people, virtually eliminating the possibility of constructing hydrogen stations in urban residential areas. Only in scenarios where VCE risks are not considered, less‐populated surrounding environments might reduce the safe distance of hydrogen stations. Eliminating the risk scenarios of VCE is a crucial approach to lowering the safe distance of HRSs, making establishing such stations in urban centers feasible. Therefore, factors such as open spaces, well‐ventilated facilities, and blast walls become critical elements in reducing the safe distance of HRSs.

Interannual Variability of Zonal Mean Temperature, Water Vapor, and Clouds in the Tropical Tropopause Layer

AbstractWater vapor and cirrus clouds in the tropical tropopause layer (TTL) are important for the climate and are largely controlled by temperature in the TTL. On interannual timescales, both stratospheric and tropospheric modes of the large‐scale variability could affect temperatures in the TTL. Here multiple linear regression (MLR) is used to investigate explained variance in the cold point tropopause temperature (CPT), cold point tropopause height (CPZ), 83 hPa water vapor (WV83), 83 hPa ozone (O383), and total cirrus cloud fraction with cloud base (TTLCCF) and top (ALLCF) above 14.5 km, all averaged over 15°S‐15°N. Predictors of the MLR are a set of stratospheric and tropospheric large‐scale modes of variability. The MLR explains significant variance in CPT (76%), CPZ (78%), WV83 (65%), O383 (62%), TTLCCF (52%), and ALLCF (36%). The interannual variability of CPT and WV83 is dominated by stratospheric processes associated with the Quasi‐Biennial Oscillation (QBO) and Brewer‐Dobson Circulation (BDC), whereas the variability of CPZ, O383, TTLCCF and ALLCF is also controlled by 500 hPa temperature (T500). Residual variability in CPT and CPZ not captured by the MLR are further significantly correlated to stratospheric temperature. It is shown that the portion of the BDC's shallow branch missed by the eddy heat flux based BDC index contributes significant amounts of the explained variances.

Exposure assessment during paint spraying and drying using PTR-ToF-MS.

Spraying is a common way to distribute occupational products, but it puts worker's health at risk by exposing them to potentially harmful particles and gases. The objective of this study is to use time-resolved measurements to gain an understanding of spray applications at the process level and to compare them to predictions of exposure models. We used proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) at 1-s time resolution to monitor the gas phase concentration of the solvents acetone, ethanol, butyl acetate, xylene and 1-methoxy-2-propy acetate during outdoor spraying and indoor drying of metal plate under various conditions of outdoor air supply. We found that during spraying, gas-phase exposure was dominated by the more volatile solvents acetone and ethanol, which exhibited strong concentration variations due to the outdoor winds. During drying, exposure strongly depended on the strength of ventilation. Under conditions with high supply of outdoor air, our measurements show a near-exponential decay of the solvent concentrations during drying. Conversely, under conditions without outdoor air supply, the drying process required hours, during which the less volatile solvents passed through a concentration maximum in the gas phase, so that the exposure during drying exceeded the exposure during spraying. The concentrations measured during spraying were then compared for each of the substances individually with the predictions of the exposure models ECETOC TRA, Stoffenmanager, and ART using TREXMO. For these conditions, ECETOC TRA and Stoffenmanager predicted exposures in the measured concentration range, albeit not conservative for all solvents and each application. In contrast, ART largely overestimated the exposure for the more volatile solvents acetone and ethanol and slightly underestimated exposure to 1M2PA for one spraying. ECETOC TRA and ART do not have options to predict exposure during drying. Stoffenmanager has the option to predict drying together with spraying, but not to predict the drying phase independently. Our study demonstrates the importance of considering both the spray cloud and solvent evaporation during the drying process. To improve workplace safety, there is a critical need for enhanced exposure models and comprehensive datasets for calibration and validation covering a broader range of exposure situations.

Consequence Analysis of An Industrial Accident at a Fuel Station

Major industrial accident is a type of technological disaster that may require extraordinary intervention in areas outside the facility, in addition to those affected within the facility. It causes damage to the environment and loss of life at the time it occurs or afterward. Studies to be carried out to prevent these accidents Zor to reduce their effects are important. In this study, a case study for the consequences of an industrial accident that may occur in a fuel station was analyzed. Firstly, possible accident scenarios were created by obtaining chemical, atmospheric and source data. The LPG (Liquefied Petroleum Gas) storage tank (40m3) was considered in modeling a fuel station in the Korfez district of Kocaeli province, where the industry is dense in Turkey. The average atmospheric data of the province for the months of August and January were used to represent summer and winter conditions, respectively. Threat zones were produced with ALOHA (Areal Locations of Hazardous Atmospheres) software based on a release to atmosphere without burning, a jet fire as a result of a leak in the LPG tank and BLEVE scenarios. The two most dangerous scenarios were determined as a possible jet fire in August and a possible BLEVE (Boiling Liquid Expanding Vapor Explosion) in January. Overpressure effects were also obtained using the BST (Baker-Strehlow-Tang) method, thus ensuring the validation. With the software, the vapor cloud explosion distance as a result of the leak in August was obtained as 456m and 268m for the yellow (6.89kPa) and orange (24.13kPa) threat zones, respectively. Overpressure in an area of 500 meters was calculated as 5.06kPa with BST method. This calculated overpressure has the potential for damage that can lead to glass and window breakage in parallel with the ALOHA output. It has been determined that indirect injuries may occur to living beings.

(Invited) The Path to Vapour Cloud Explosions and Lithium-Ion Batteries

The lecture will cover the research that led to the realisation that vapour cloud explosion was and is the understated hazard of lithium-ion batteries, commencing with work in January and March 2020 and leading up to the present day. The research was initiated with an exploration of the effect of various abuse methods on 1.7 kWh Envision-AESC modules, followed by investigating the effect of State-of-Charge on the manifestation of thermal runaway, the latter leading to the realisation of the vapour cloud and its potential consequences. This was followed by experiments on the larger scale to analyse the vapour cloud composition and to trigger deflagration: these suggested the possibility that arc plasma may have a role in the production of the vapour cloud. Later, experiments on the suppression of thermal runaway clearly showed the risks associated with the suppression of fire without the suppression of thermal runaway, as the hazard flips from fire to explosion. This was a key finding, as was the large volume of vapour cloud produced by lithium-ion batteries (i.e. at least 500 L/kWh and up to 5500 L/kWh), causing the routinely observed rocket-like flames when the cloud ignites immediately, and the fact that even small lithium-ion batteries (e-bikes, e-scooters) are causing vapour cloud explosions.As well as academic research, the concepts and ideas discussed will be illustrated with information and videos from a wide range of sources including first responder reports from across the world.Finally, the possible risks and hazards of the use of electric vehicle batteries in 2nd life applications will be addressed

How the Hunga Tonga—Hunga Ha'apai Water Vapor Cloud Impacts Its Transport Through the Stratosphere: Dynamical and Radiative Effects

AbstractThe eruption of the Hunga Tonga—Hunga Ha'apai (HTHH) volcano on 15 January 2022 injected about 150 Tg of water vapor (H2O), roughly 10% of the background stratospheric H2O content, to altitudes above 50 km. Simulations of the spatial evolution of the H2O cloud with the ICON‐Seamless model are very close to observations from the Aura Microwave Limb Sounder. The vertical transport of the H2O cloud had three phases: an initial subsidence phase, a stable phase, and a rising phase. Radiative cooling of H2O clearly affects the transport of the H2O cloud, as demonstrated with passive tracers, and is the main driver within the subsidence phase. It also counteracts the large‐scale rising motion in the tropics, leading to the stable phase, and modulates the large‐scale transport of the H2O cloud for about 9 months. This holds for different QBO phases, where the H2O cloud differs mainly in its vertical extent.

A finite element analysis-based approach for blast-resistant design of LNG containment tanks

Inside Liquid Natural Gas (LNG) facilities, ignition of large vapor clouds in a congested region might result in Vapor Cloud Explosions (VCE) leading to high speed blast waves and compromising the structural integrity of equipment and structures. The escalation of an initial blast is referred to as ‘Cascading Effect’. In performing risk assessment of a facility, structural damage of LNG containment tanks due to blast scenarios needs to be considered. This article presents a numerical approach-based methodology to analyze containment structures using Finite Element Analysis (FEA). The objective of this study is to elucidate the critical parameters in blast resistant design of containment tanks. Four major types of containment tanks are studied under representative scenarios of deflagration and detonation. Containment tank geometries were created almost in its entirety and the structural response is modeled with appropriate constitutive relations for steel and concrete. Additionally, pertinent hard contact with friction interaction between the tank inner to outer shell surfaces are assigned. The results indicate that a single containment tank model experienced severe damage in its outer shell under deflagration compared to other types of containment tanks. In the case of double, full and membrane containment tanks cracking in the prestressed concrete wall was observed due tensile damage which is pronounced for detonation than for deflagration cases. It is concluded that single containment tanks are most vulnerable to Cascading Effect. Based on the results of FEA, recommendations are provided for safe practice of designing the structures and maintaining the structural integrity of tanks.

Consequences analysis of the LPG tank truck traffic accident: A case study of the Wenling explosion accident

Liquefied Petroleum Gas (LPG) is a vital energy source as well as a chemical feedstock, known for its flammable and explosive property. The demand for LPG has increased in recent years, leading to the frequent occurrence of leaks and explosion accidents, which pose a serious threat to public safety. This paper investigates the process of the consequences evolution of leakage of LPG and explosion accidents, using the Wenling, Zhejiang, China, LPG tanker explosion accident as an example. The main explosive processes that occurred after the leak, i.e., Boiling Liquid Expanding Vapor Explosion (BLEVE) and Vapor Cloud Explosion (VCE), were reconstructed through the collection and organization of data from the incident. The EFFECTS software was used for the simulation of container rupture, vapor dispersion and explosion pressure. The simulation results were consistent with the actual on-site effects. Multi-energy TNO method was used to measure the impact of VCE on overpressure hazards. This resulted in a blast energy of 3.1 × 105 MJ and a staff wound radius of 324 m. Based on the site's terrain and traffic route layout, measures were proposed to install protective walls around the turnaround area. Effective measures were taken to reduce the range and intensity of the explosion and thus to mitigate the consequences of the accident. This measure reduced the damage radius of the accident by 25.6%. This work will serve as a reference for investigation, analysis, scenario development and recommendations to prevent accidents.

Traces of the action of ball lightning as material for studying its structure

According to observations, at the site of the ball lightning disappearance there are no traces left except a cloud of vapor. This reduces the number of materials for its formation in nature to air and water molecules. It is shown that, using these materials, it is possible to create a model of ball lightning with an energy reserve with a density up to 1010 J/m3. Ball lightning has an electrical charge and mass. It is capable of heating water, tearing off bark from trees, jumping on the ground, cutting discs in glass, and melting holes in metal barriers. An explanation for this behavior of ball lightning is given.

A Computational Study of Hydrogen Dispersion and Explosion after Large-Scale Leakage of Liquid Hydrogen

This study employs the FLACS code to analyze hydrogen leakage, vapor dispersion, and subsequent explosions. Utilizing pseudo-source models, a liquid pool model, and a hybrid model combining both, we investigate dispersion processes for varying leak mass flow rates (0.225 kg/s and 0.73 kg/s) in a large open space. We also evaluate explosion hazards based on overpressure and impulse effects on humans. The computational results, compared with experimental data, demonstrated reasonable hydrogen vapor cloud concentration predictions, especially aligned with the wind direction. For higher mass flow rate of 0.73 kg/s, the pseudo-source model exhibited the most reasonable predictive performance for locations near the leak source despite the hybrid model yielded similar results to the pseudo-source model, while the liquid pool model was more suitable for lower mass flow rate of 0.225 kg/s. Regarding explosion analyses using overpressure-impulse diagram, higher mass flow rates leaded to potentially fatal overpressure and impulse effects on humans. However, lower mass flow rates may cause severe eardrum damage at the maximum overpressure point.

Modelling respiratory droplet cloud transport: Group evaporation effect

The transport of respiratory droplet cloud arising from human cough is investigated in the present work. A mathematical model based on particle mass, momentum and energy conservation in a Lagrangian framework is adopted to track individual respiratory droplets in a constant carrier flow. The objective here is to study the role of group evaporation of the droplet cloud on the suspension time and transport distance of the respiratory droplets. Two different models for the group effect are examined which are validated against in-house experiments using single-, dual- and triple-droplet suspension arrangements. The strength and limitations of the models are assessed. The results demonstrate that the Group evaporation number (G), which characterizes the collective vaporization of the droplet cloud, is of the order of ‘one’ which refers to reduced droplet evaporation rate within the cloud compared to an isolated droplet. In such cases, the droplet suspension time as well as the distance over which the cloud is transported are much longer in comparison to the case when an isolated droplet evaporation model is employed. Accordingly, even a gentle wind speed spreads the ejected droplets in the range of 10 m–50 m from the source (lower ambient temperature and higher humidity increase the spread). It is also found that the group evaporation is sensitive to the initial characteristic droplet size rather than the mass and duration of the injected liquid. Finally, the current results highlight the group evaporation effect as a potential contributor to enhancing the droplet suspension time in the air.