Review
Consequence Analysis of LPG-Related Hazards: Ensuring Safe
Transitions to Cleaner Energy
Carolina Ardila-Suarez *, Jean-Paul Lacoursière, Gervais Soucy
and Bruna Rego de Vasconcelos *
Department of Chemical and Biotechnological Engineering, Université de Sherbrooke, Sherbrooke,
QC J1K 2R1, Canada; jean-paul.lacoursiere@usherbrooke.ca (J.-P.L.); gervais.soucy@usherbrooke.ca (G.S.)
* Correspondence: carolina.ardila.suarez@usherbrooke.ca (C.A.-S.);
bruna.rego.de.vasconcelos@usherbrooke.ca (B.R.d.V.)
Abstract: Countries worldwide are focused on the objective of zero emissions by 2050.
However, the accelerated implementation of clean technologies has had some drawbacks,
remarkably those related to safety issues. Liquefied petroleum gas (LPG) emerges as a
transition fuel in this context, considering the following two aspects. First, LPG is a fuel
that has environmental advantages compared to other fossil fuels, so the extension of
coverage as a replacement fuel is a key factor. Second, LPG has a well-developed storage
and transportation infrastructure that can be used, sometimes without modifications, for
clean fuels, helping their implementation. Therefore, the safety analysis and the study of
the consequences related to the hazards of LPG is a current subject that contributes, through
all the tools reviewed in this article, to not only reduce the risks of this fuel but also to
connect with the safety issues of clean fuels. This review article provides a comprehensive
overview through consequence modeling tools, highlighting computational fluid dynamics
(CFD) and machine learning to pave the way for the full implementation of clean fuels that
will power the future of humanity.
Keywords: propane; LPG; hazards; consequence analysis; transition fuel
1. Introduction
Academic Editor: Javier Ereña
licenses/by/4.0/).
Global economic and political strategies focus on carbon neutrality objectives. Under
the Paris Agreement, Canada committed to reducing its greenhouse gas (GHG) emissions
by 30% below 2005 levels by 2030 and a driving target of net-zero emissions by 2050 [1].
At the provincial level, Quebec has committed to reducing its GHG emissions by 37.5%
compared to 1990 levels by 2030, to decreasing by 40% its consumption of petroleum-based
products, and to meeting carbon neutrality by 2050 [2]. In this context, it is necessary
to gradually transition to cleaner energy sources in which LPG plays a defining role as
a transition fuel toward the complete implementation of renewable energies [3]. Hence,
despite the increasing demand for electric and fuel-cell electric vehicles, replacing the existing internal combustion engine fleet demands significant investments for all the required
infrastructure [4,5]. From this perspective, LPG, as a low-carbon fuel, can be applied to the
existing spark ignition type of internal combustion engine vehicles with no substantial part
changes [6,7]. The relevance of this fuel is more than just transport [8,9] but also in applications such as domestic cooking [10,11] and the agricultural and industrial sectors [12,13].
While LPG offers numerous benefits, its usage is not without its safety considerations,
particularly regarding its flammability. Hence, LPG-related incidents will be discussed in
this review. Bariha et al. [14] accordingly reviewed the studies until 2016 related to failure
and other LPG and natural gas vessel hazards during handling, storage, and transport.
Fuels 2025, 6, 45
https://doi.org/10.3390/fuels6020045
Received: 31 January 2025
Revised: 7 April 2025
Accepted: 16 May 2025
Published: 5 June 2025
Citation: Ardila-Suarez, C.;
Lacoursière, J.-P.; Soucy, G.; Rego de
Vasconcelos, B. Consequence Analysis
of LPG-Related Hazards: Ensuring
Safe Transitions to Cleaner Energy.
Fuels 2025, 6, 45. https://doi.org/
10.3390/fuels6020045
Copyright: © 2025 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license
(https://creativecommons.org/
Fuels 2025, 6, 45
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In this review, the authors focused on propane and LPG due to their relevance in the
energy transition. They discussed the improvements to date in the existing models for
the various hazardous scenarios, seeking to identify the most critical gaps and research
priorities that could enhance the LPG and liquefied natural gas (LNG) risk assessment.
Nevertheless, the consequences of LPG-related accidents are enormous despite their low
likelihood [15]. Moreover, city expansion worldwide also increases the energy demand
and could lead to high risks during the storage and transportation of fuels. Consequently,
a secure energy supply will contribute to the city’s sustainable development and ensure
the safety of its inhabitants [16]. Furthermore, investigations on LPG continue as tools
and software advance, improving the accuracy of predictions for LPG-related incidents
to prevent accidents, facilitate rapid emergency responses, and minimize casualties. As
highlighted by Huffman et al. [17] in their bibliometric study of the transport risk of LPG
and LNG, there is a significant amount of safety-related experience with LPG compared
to LNG, especially in consequence analysis. Thus, within the framework of the current
energy transition, utilizing the existing LPG safety-related experience, infrastructure for
storage [18], transportation [19], and final applications [20,21] emerges as a viable option for
implementing and entering the market for renewable fuels. Accordingly, this study aims to
provide a comprehensive review of the recent progress in the studies on the consequences
of LPG-related incidents. The article also discusses the current LPG-trending applications
and the emergence of biopropane as a promising alternative as a direct drop-in fuel toward
a replacement of liquified petroleum gases. It notably focuses on the CFD advancement
works and addresses the rise of machine learning-coupled calculations to generate reliable
data to manage and predict LPG accidents but also to benefit the new and clean fuel
technologies that will fuel humanity.
2. Characteristics and Properties of Liquified Petroleum Gas
LPG is a gas product of petroleum refining or natural gas extraction, mainly consisting
of propane, butane, and other light hydrocarbons. Thus, natural gas or other gases are
purified to remove water and sulfur impurities. Further, it is converted to syngas via steam
methane reforming [22]. In Canada, 85% of the propane comes from natural gas and is
produced in plants located in Alberta, British Columbia, and Saskatchewan. The remaining
15% is derived from refining petroleum in refineries in all provinces except Manitoba, Nova
Scotia, and Prince Edward Island [23]. The LPG composition can vary in a wide range from
pure propane passing through different propane/butane ratios to pure butane, depending
on the location [23]. However, in the United States and Canada, LPG consists primarily of
propane [24–26]. Therefore, Grade 1 fuel in Canada must contain at least 90% propane for
use in internal combustion engines and general industrial/commercial applications [27].
Whether at the refinery or from natural gas processing, LPG contains contaminants,
primarily water and sulfur compounds, including hydrogen sulfide, carbonyl sulfide, and
elemental sulfur. According to the type and concentration of contaminants within LPG, one
or more purification processes, including adsorptive [28,29] and absorptive purification [30],
are employed to meet LPG quality specifications. Herein, the international trade of LPG
is governed by two primary standards established by the International Organization
for Standardization (ISO). ISO 8216-3 [31] is crucial in classifying petroleum products,
including light distillates. At the same time, ISO 9162:2013 [32] specifies the characteristics
of propane and butane. Additionally, several national standards regulate LPG trade
and usage across different regions. For instance, in Germany, the DIN 51622:2020-09
standard [33] sets guidelines for LPG, while the United Kingdom follows the BS 4250:2014
standard [32]. In the United States, the ASTM D 1835-22 outlines the characteristics of
liquified petroleum gases intended for various purposes, including heating and engine
Fuels 2025, 6, 45
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fuel in domestic, commercial, and industrial settings [34]; the EN 589:2024 specifies the
requirements and test methods tailored explicitly for LPG automotive fuels in Europe [35].
Meanwhile, the CAN/CGSB-3.14-2023 standard governs the specifications and usage
in Canada [27]. Table 1 compares the properties and requirements of some of the LPG
standards mentioned.
Table 1. Comparison of the key properties and requirements for LPG fuel as specified in ISO 9162:2013 [32],
ASTM D 1835-Special-Duty propane [34], and CAN/CGSB-3.14-2023 Grade 1 [27].
Component
Propane
Butane
C4 hydrocarbons
Sulfur
Evaporation residue
Vapor pressure
ISO 9162:2013 Commercial
Propane
ISO-F-LP
ASTM D
1835-Special-Duty
Propane (USA)
CAN/CGSB-3.14-2023
Grade 1 (Canada)
-
-
90% min. by volume
7.5% max. %(molar)
2.5% max. by volume
2.5% max. by volume
50 mg/kg max
60 mg/kg max
1550 kPa max at 40 ◦ C
123 mg/kg max
0.05 mL max per 100 ml
1435 kPa max at 37.8 ◦ C
123 mg/kg max
0.05 mL max per 100 mL
1435 kPa max at 37.8 ◦ C
Regarding its storage, LPG can be kept either above or below ground. For the first
storage type, the LPG could be held in pressure, refrigerated, and semi-refrigerated storage
tanks, considering that the boiling point of LPG approximately varies from −44 ◦ C to
−0.5 ◦ C [36] and that the vapor pressure (ps ) of its main components, propane and butane,
at 25 ◦ C is 951 kPa and 243 kPa, respectively [37]. Regarding underground storage, LPG
can be stored in salt caverns or caverns that withstand its vapor pressure [38]. As for
transportation, it is possible to move LPG through pipelines, waterways, roads, and
railways [39–41]. Figure 1 illustrates the LPG production process and its final applications,
which are discussed in the following section.
Figure 1. LPG: from production to final applications.
Regarding its properties, LPG is an odorless and colorless gas that is flammable
and heavier than air. Under room conditions, LPG is gaseous, but it can be liquified
and maintained under pressure to facilitate its storage and transportation [42]. The main
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properties of LPG are presented in Table 2, along with a comparative assessment of LPG,
gasoline, and diesel, which highlights the cleaner combustion characteristics of LPG.
Table 2. Physicochemical and combustion-related properties of the main components of LPG compared to gasoline and diesel fuels [43–46].
Component
Propane
Propene
n-Butane
Gasoline
Diesel
Boiling point @ 101.3 kPa (◦ C)
−42.1
1310
506.0 *
50,014
2.3
9.5
−47.7
1561
520.4 *
48,954
2.2
9.6
−0.5
356
583.0 *
49,155
1.9
8.5
30–220
~64
~730
~44,300
1.4
7.6
160–380
~2
~840
~45,500
0.7
5.0
Vapor pressure @ 37.8 ◦ C (kPa)
Density @ 15 ◦ C (kg/m3 )
Gross calorific value @ 25 ◦ C (kJ/kg)
Lower Flammability Limit, LFL (% vol. in air)
Upper Flammability Limit, UFL (% vol. in air)
* Liquid density (@saturated pressure).
3. Applications
LPG has a lower environmental impact than other fossil-based fuels and is similar
to LNG [47]. For instance, Bicer and Dincer [48] conducted a comparative environmental
impact assessment of alternative and conventional fueled vehicles, using a cradle-to-grave
approach and considering global warming and other environmental impact categories.
The study found that in terms of global warming potential 500a, vehicles fueled by LPG
produced 0.225 500a kg CO2 eq, which is lower than gasoline vehicles and comparable to
Compressed Natural Gas (CNG) vehicles with 0.27 and 0.205 kg CO2 eq, respectively. The
current and emerging LPG applications are disclosed below.
3.1. Transportation
Within the framework of global carbon neutrality targets, the adoption of electric
and hydrogen vehicles is lower than expected [49]. Accordingly, governments are driving policies to employ LPG instead of gasoline or diesel fuels in vehicles with internal
combustion engines [50,51]. As shown in Figure 2, motor gasoline is expected to remain
the primary transportation fuel in 2040. In countries belonging to the Organization for
Economic Co-operation and Development (OECD), the primary alternative-fueled vehicles
are electric and plug-in hybrid electric vehicles, followed by those fueled by LPG. In contrast, natural gas is the main alternative in non-OECD countries [52]. Therefore, the LPG
conversion technology has been adjusted to accommodate the development of gasoline
engines from the first to the sixth generation. This adjustment has led to improvements
in thermal efficiency, fuel consumption, and emission control, enabling the conversion
of conventional gasoline engines for LPG use [53]. Recent studies on modern internal
combustion engine designs—such as enhanced spray behavior, better combustion control,
and optimized fuel injection—suggest that LPG remains compatible with these ongoing
innovations. Its clean-burning characteristics and adaptability to direct injection systems
allow it to benefit from many of the same improvements applied to traditional fuels [54,55].
Furthermore, LPG-fueled vehicles can utilize the cooling potential from the phase
change in the vaporizer, thereby improving the air conditioning system [56]. LPG could
also be blended with standard liquid fuels to improve performance and decrease emissions
in spark ignition [57] and compression ignition engines [58,59]. Moreover, advanced LPG
blends with clean alternative fuels, such as dimethyl ether (DME) [60], methanol [61], and
hydrogen [62,63], aim to contribute to these fuel industries to establish alternatives towards
carbon neutrality.
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Figure 2. 2015–2040 projection of vehicle sales for OECD and non-OECD countries [52].
LPG is also a feasible fuel for facilitating the transition to zero-carbon ships [8,47]. In
line with this, Kim et al. [64] conducted a study on the use of LPG in small marine vessels
in South Korea. The study found that in a simulation-based comparison, exhaust emissions
from LPG engines were significantly lower, with reductions of 11.35% and 4.59% in CO2
emissions and substantial decreases of 92.55% and 98.58% in soot emissions, compared to
gasoline and diesel engines, respectively.
3.2. Heating and Cooking
LPG supports the clean energy transition by contributing to reduced pollutant emissions. The LPG has particle pollution from fine particulates (PM2.5 ) of 5.4 mg/MJ, whereas
wood, kerosene, and charcoal exhibit PM2.5 values of 116.6, 25.3, and 84.4, respectively [65].
Furthermore, LPG is widely utilized, particularly in regions near the equator, across key
energy end-use sectors such as residential [66,67], agriculture [68], commercial sector [69],
and industry [70,71].
3.3. Fuel Cells
Solid oxide fuel cells (SOFCs) are attractive energy conversion systems that can employ
hydrocarbons as fuels due to their high operating temperature. Among the hydrocarbon
fuels, LPG is a promising option due to its availability, high energy density, low cost,
and ease of storage [72]. When hydrocarbons serve as the energy source for SOFCs, an
expensive and external reformer is typically employed to break down larger molecules into
smaller ones, such as H2 , H2 O, CO, and CO2 . Alternatively, using an internal reformer or
directly using hydrocarbons as a SOFC fuel are compelling alternatives. Furthermore, the
direct use of propane as the SOFC fuel is a trending alternative [73,74].
3.4. Refrigeration
In addition to the well-known applications of LPG, this fuel has increased its relevance
as a natural refrigerant since it has a very low saturation temperature and low global
warming potential and absorbs latent heat from surroundings, thus lowering the temperature [75,76]. Notably, researchers are focused on improving LPG-based refrigeration
systems by using graphene, among other nanoparticles, to improve the coefficient of performance (COP) [77]. Furthermore, the carbon dioxide and propane mixture is a promising
replacement for refrigerants in systems requiring low and ultra-low temperatures [78].
Other applications include LPG utilization as feedstock in the petrochemical industry for
light olefins [79,80], aromatics [81], and hydrogen [82] production.
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4. Biopropane Perspectives
Despite the advantages of LPG over other fossil fuels, there is a critical need to
develop sustainable and renewable biofuels to address the depletion of petroleum-derived
products and their impact on climate change. The eventual commercialization of biopropane will reduce demand for natural gas and oil while maintaining the use of this cleanburning fuel [83]. Biopropane has a long-term potential to reduce air pollution and mitigate
carbon emissions from challenging-to-decarbonize industries, such as transportation and
rural heating [84].
Biopropane can be produced through various processes, with one notable example
being the hydrotreating of vegetable oils. The hydrogenated vegetable oil (HVO) process allows the obtainment of renewable diesel as the main product and biopropane as a
byproduct [85,86]. The Finland-headquartered Neste has patented the NEXBTL™ process
to produce HVO, which is a mature and already commercial-scale manufacturing process [87]. The production of bio-propane through the gasification and synthesis of cellulosic
organic wastes is in a demonstration state. Other pathways for biopropane production are
glycerine dehydrogenation [88], bio-derived n-butanol hydrothermal conversion [89], sugar
fermentation [90], waste digestion [91], and microbial biorefinery using amino acids such as
fatty acid photo decarboxylase [92]. Furthermore, the authors highlight using Power-to-X
as an emerging technology to produce renewable propane by hydrogenating captured
carbon dioxide with green hydrogen [93]. In closing, despite the bio-LPG production
(200 thousand tons/year) being far from those of LPG produced (300 million tons/year), it
presents to the propane industry a route to decarbonization, giving a bio-alternative for
consumers and as a potential competitor for governmental tax credits [86].
5. Highlighted Accidents Involving LPG Storage and Transportation
As mentioned earlier, accidents involving LPG have a low frequency but high consequences for life, the environment, and property. Those events have various contributing
factors, ranging from design conception to technical issues and human errors [94]. Part of
the accident-prevention approach involves learning from previous accidents, which entails
identifying the cause and sequence of events, aiming to avoid similar accidents and limit
damages to enhance process safety [95]. In this regard, implementing standards [96,97] and
best practices [98] guide process safety management and accident prevention. Depending
on the specific process requirements, best practices related to this article discussion are
found in several documents such as the API 2510, Design and Construction of LPG Installations [99], the Risk Management Program Guidance for Propane Storage Facilities (40 CFR
Part 68) [100], and the Process Safety Management for Storage Facilities [101]. Regarding
Canada, propane storage and handling are governed by the CSA B149.2:20 code [102].
Furthermore, CSA Z-767:24 Standard [103] aims to identify the performance requirements
for industries handling hazardous materials that plan to implement or have already implemented a process safety management (PSM) system [104]. Table 3 highlights some of the
LPG-related accidents with high consequences, many of which have been used as input
data or reference scenarios for validating consequence modeling approaches. For example,
the Wenling LPG explosion has been studied using modeling tools to evaluate dispersion
and the consequences of the explosion, as discussed in the following sections. Likewise,
industrial accident databases such as the Major Accident Reporting System (MARS, later
renamed eMARS after going online) [105], the Major Hazard Incident Data Service (MHIDAS) [106], and Analysis, Research, and Information on Accidents (ARIA) [107], among
others, are available and focused on the lessons learned from accidents involving hazardous
materials such as LPG. In addition to informing regulations and operational practices, these
documented cases reveal recurring patterns of failure that reinforce the need for advanced
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predictive methodologies—such as consequence analysis—to enable rigorous assessment
of accident scenarios and support evidence-based risk management strategies.
6. Risk Analysis
As mentioned earlier, the low pollution and price, among other properties of LPG,
have increased interest in and the consequent use of this fuel. However, like other fuels,
LPG is highly dangerous if not handled, stored, and transported correctly. Figure 3 shows
a qualitative comparison of hydrogen, ammonia, methane, and propane in terms of the
Risk Index of Explosion (ERI), Lower Flammability Limit (LFL), Upper Flammability
Limit (UFL), Minimum Ignition Energy (MIE), and Recommended Exposure Limit (REL).
Accordingly, hydrogen’s high risks are related to ERI, UFL, and MIE, which means that
hydrogen has a high probability and severity of combustion and explosion compared to
the other discussed fuels. On the other hand, ammonia exhibits a higher risk of toxic
damage to the human body caused by leakage during an accident [108]. In this context, the
safety-related experience related to LPG storage and handling [17,109–112] will contribute
to the safe production, storage, and distribution of new fuels on a large scale [113]. In this
context, the risks associated with LPG have been extensively studied through accident
investigations, experimental research, and validated consequence modeling, all of which
are supported by mature safety codes and regulatory frameworks. These well-established
elements, examined in the following sections, provide a reference framework to inform risk
analysis and guide the safe deployment of emerging fuels such as hydrogen and ammonia.
Figure 3. Qualitative comparison of ammonia, hydrogen, methane, and propane risks. Adapted from [108].
The flammable nature of propane is its main hazard. Thus, it can cause injuries due to
burns and thermal radiation, and suffocation may occur if LPG displaces air, resulting in
a decrease in oxygen concentration [44]. Propane in storage could leak and lead to vapor
cloud explosions (VCE) or boiling liquid expanding vapor explosions (BLEVEs). These
explosions cause massive damage to humans, the environment, and infrastructures due to
the accompanying fires and blasts [114], see Table 4. A BLEVE is the worst-case scenario
for an LPG-related accident. This physical explosion may occur when a container with
a pressure-liquified gas ruptures and its content is suddenly released. This results in an
explosive mixture of vapor and boiling liquid. If the BLEVE involves a flammable substance,
such as LPG, four main dangers can arise: Fire, thermal radiation from the fireball, pressure
due to the blast, and flying projectiles hazards. Among them, the projectiles could cause the
Fuels 2025, 6, 45
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most significant consequences. It is worth noting that the container size has a significant
impact on the likelihood of a BLEVE occurring. Thus, small tanks could BLEVE faster since
they have thinner walls than larger ones, leading to faster heating [115]. Comparatively, a
400 L tank could rupture in 5 to 7 min, a larger 4000 L one may fail in 5 to 7 min, while a
40,000-L tank on a truck would take 8 to 12 min to rupture. In an ignited vapor cloud event,
a fireball could be immediately formed. Accordingly, for a 400-L tank, the radius of the
fireball is around 18 m, and for a 4000-L tank, that radius doubles to about 36 m. Moreover,
for a 40,000 L tank, the fireball radius could achieve 81 m. Notably, the heat is radiated in
all directions, and the minimum observation distance is 90, 150, and 320 m for 400, 4000,
and 40,000 L tanks, respectively. On the other hand, if the released vapor cloud is not
ignited immediately, an explosion can occur due to delayed ignition. The resulting blast is
unpredictable, with highly probable catastrophic effects, thus highlighting the importance
of thorough safety measures [116,117].
To accurately assess all the major hazards and associated risks, specialized software
is available to assist governments and industries in complying with safety regulations
and corporate best practices. Software such as PHAST, EFFECTS, ALOHA, SAFETI, and
RISKCURVES, among others, play pivotal roles in these attempts. These consequence
modelling tools employ various computational approaches, each offering benefits and
limitations that depend on the complexity of the scenario and the level of detail required.
PHAST from DNV [118] and EFFECTS from Gexcon AS [119] display superior accuracy
with robust and validated models for complex scenarios involving hazardous materials
such as LPG release and dispersion. ALOHA [120,121], from the US EPA, is also a valuable
tool for consequence analysis and emergency planning; however, it is less accurate than the
software mentioned above due to its simplified assumptions.
On the other hand, SAFETI (DNV) [122] and RISKCURVES (Gexcon AS) [123] significantly contribute to risk assessment practices by providing systematic methodologies
for Quantitative Risk Analysis (QRA) in compelling hazard management. These tools
integrate statistical accident frequencies with consequence modeling outputs, enabling
structured risk quantification and prioritization of mitigation measures. Furthermore, the
CFD technique allows the improvement of existing models and the assessment of new
hazardous scenarios [124]. CFD methods provide high-resolution spatial and temporal
simulation capabilities, which are particularly valuable in urban or complex environments,
although they typically require extensive input data and significant computational effort. Thus, consequence prediction is a critical stage in risk assessment for estimating
the effects of fire, explosion, and dispersion scenarios on surrounding communities (see
Figure 4). Accordingly, it also brings a baseline for mitigation planning and process design improvement. As discussed in the following sections, one of the primary challenges
for both CFD and emerging data-driven tools, such as machine learning, is the limited
availability of large-scale experimental data for validation, particularly in rare or extreme
scenarios. Nevertheless, recent studies have addressed these limitations through hybrid
modeling approaches and validation against real-world accidents. Machine learning, in
particular, has emerged as a complementary strategy to traditional simulations, enabling
faster predictions by learning from available data, reducing computational demands, and
supporting rapid risk estimation in emergency scenarios involving hazardous materials
such as LPG [125,126].
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Figure 4. Study of LPG consequences scenarios.
6.1. Experimental Research and Consequence Prediction Methods
6.1.1. Experimental Assessment
Different studies have focused on the experimental investigation of LPG-related fires
and explosions, aiming to understand their mechanism for establishing prevention measures. Some previous experimental studies on LPG safety are reviewed in Table 5.
Table 3. Highlighted accidents involving LPG storage and transportation.
Place
Year
Feyzin, France
1966
Mexico City, Mexico
1984
Rio de Janeiro, Brazil
1972
Sainte-Élizabeth-deWarwick, QC, Canada
1993
Visakhapatnam, India
1997
Bucheon, Korea
1998
Cause
The operational failure of the plant
operator caused an LPG (propane) leak.
LPG (propane/butane mixture) leakage
followed by ignition caused several
explosions—domino effect.
The operator lost control in a draining
operation on an LPG sphere,
leading to a BLEVE.
An LPG (propane) tank near a barn was
involved in a violent fire
and ruptured by BLEVE.
LPG leakage in a storage vessel caused a
flammable vapor cloud followed by
ignition and explosion.
LPG (propane/butane mixture) leakage
during the discharge process from the
tank into subterranean storage.
Fatalities
Reference
18
[127]
>500
[128]
38
[129]
4
[130]
>60
[131]
1
[132]
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Table 3. Cont.
Place
Year
Toronto, Canada
2008
Viareggio, Italy
2009
Chiba, Japan
2011
Kannur, India
2012
Linyi, China
2017
Wenling, China
2020
Cause
Propane release at a transfer facility. An
unknown ignition source led to a VCE
and BLEVEs.
The derailment of a train carrying LPG
(propane) caused a release. The gas cloud
formed led to a flash fire.
Earthquakes led to LPG (propane)
vessels collapsing, resulting in a BLEVE.
A truck tanker overturned, producing an
LPG leak and a large vapor cloud that
ignited, leading to a BLEVE.
An LPG tanker leaked during unloading,
leading to a significant explosion
and fire.
An LPG (propane/butane mixture) tank
truck overturned while transiting at high
speed on an expressway ramp. The tank
collided with a concrete guardrail
and exploded.
Fatalities
Reference
2
[133]
31
[134]
[135]
20
[136]
10
[137]
20
[138]
Table 4. LPG-derived consequence scenarios.
Fires/Explosions
Definition
Pool fire
Combustion of a substance that evaporates from
a layer formed by a liquid fuel pool. A pool fire
exhibits high flame temperature and heat flux to
its surroundings.
Graphical Description
References
[139]
Jet fire
Results from a liquid, vapor, or gas discharge
into a free space from an orifice. The momentum
of the discharge induces the mixture of the
discharged material with the atmosphere.
[140]
Fireball
It is a fire that burns sufficiently rapidly for the
burning mass to rise into the air as a cloud or a
ball. It occurs if a flammable liquid, gas, or dust
cloud abruptly releases and has limited mixing
with air before ignition.
[141]
Flash fire
The combustion of the flammable vapor or gas is
mixed with air, and the flame propagates
through that mixture with no
overpressure generation.
[142]
Vapor cloud explosion (VCE)
Results from igniting a cloud of flammable vapor
or gas in which flame velocities are sufficiently
high to produce a pressure wave.
[143]
Boiling liquid expanding
vapor explosion (BLEVE)
A BLEVE could be described as the explosive
release of expanding vapor and boiling liquid
when a catastrophic failure occurs in a pressure
vessel holding a pressure-liquified gas.
[144]
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6.1.2. Empirical Modeling
Theoretically based empirical correlations, such as those from the Netherlands Organization (TNO), Baker-Strehlow-Tang (BST), and the TNT equivalent methods, are the
most commonly used for predicting the consequences of explosions. These approaches
are sometimes inaccurate, as they often include experimentally adjusted factors that can
lead to overestimating the calculated values. However, these methods have an easy
implementation and do not require specialized software, high computational consumption, or deep programming knowledge compared to the integral methods, which will be
discussed later [145,146].
Lv et al. [147] experimentally studied the evolution of propane jet flame geometrical
profiles and air entrainment characteristics. The authors quantified the air entrainment
coefficients using an integral model derived from conservation equations. Furthermore,
they proposed a characteristic-length scale that represents the competition between the jet
momentum component in the horizontal direction and thermal buoyancy in the vertical
direction, thereby normalizing the flame geometrical profile parameters. This opens the
door to using the developed models in simulators such as Fire Dynamics Simulator (FDS)
or FireFoam.
Birk [133] presented a theoretical method for calculating the required overpressure
for condensation cloud formation due to a BLEVE or VCE explosion. Air temperature and
relative humidity are required as input parameters for the model. The Sunrise explosion
accident is used as a validation example, utilizing video records from the incident. Accordingly, the explosion energy and expected damages at other distances can be calculated
using the overpressure and distance data, which can be helpful for accident analysis.
Kraft et al. [148] developed simple and dimensionless equations for directly estimating
distances considering the occurrence of a BLEVE event. The model correlated design
or operation variables with safety distances as output. The input variables included the
substance (i.e., propane), vessel volume, target vulnerability, explosion temperature, and
the Jakob Number. This number could be designed as a hazard index related to BLEVE
events. The aim of the work is also to facilitate the quantitative risk analysis of complex
events. Furthermore, Elizaryev et al. [149] performed a comparative analysis of three
mathematical models for assessing thermal radiation at BLEVE at a propane storage tank.
The compared models, designated as MM1, MM2, and MM3, are those proposed by M.W.
Roberts, the project GOST 12.3.047-2012 of the National Standard of the Russian Federation,
and Dhurandher et al., respectively [150,151]. Unlike the other models, MM1 considers
the time-dependent nature of a fireball’s thermal radiation. On the other hand, the surface
radiant heat flux employed by MM2 is 350 kW/m2 , whereas that calculated from MM3 is
387 kW/m2 . Therefore, the models were compared at different times of fireball existence,
according to MM1, in which the surface radiant heat flux corresponded to those of the MM2
and MM3 models (t = 4.16 s and t = 3.15 s, respectively). The results showed that the height
of the center of the fireball resulting from MM1 is significantly lower, at 59.22 m and 68.33 m,
compared to MM2 and MM3, respectively, at the corresponding times. Accordingly, the
authors concluded that the energy potential with the BLEVE effect on the tank estimated
by MM1 is incommensurable compared to MM2 and MM3.
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Table 5. Previous experimental studies on LPG safety.
Incident
Objective
Experiment Details
Jet fire
Study on the horizontal jet flame
that impinges a vertical plate.
Plate (Q235 low-carbon steel)
dimensions: 1 m × 1 m × 5 mm,
thermal conductivity:
53.6 W/(mK). Nozzle (stainless
steel): inner diameters of 2.0 mm,
3.0 mm, and 4.2 mm. Spacings
between nozzle exit and plate:
0.20, 0.25, 0.30, 0.35 and 0.40 m.
Effect of nozzle exit velocity, exit
diameter, and exit-plate spacing
on the horizontally impinging
jet fire.
LPG tank under fire
Study the consequences of an
LPG vehicle tank failure under
fire conditions.
Ten fire tests on toroidal LPG
vehicle tanks with no safety
devices were conducted.
Tank filling level, fragmentation
distance, and the radius of the
danger zone.
A small-scale apparatus was
constructed to record detailed
images of the failure process and
measure overpressures near the
vessel. The apparatus is an
aluminum tube with D = 50 mm
and L = 300 mm.
A small-scale apparatus was
constructed to record detailed
images of the failure process and
measure overpressures
near the vessel
(R/Dtube = 0.175/0.050 = 3.5):
Aluminum tube with D = 50 mm
and L = 300 mm.
A small-scale apparatus was
constructed to record detailed
images of the failure process and
measure overpressures
near the vessel
(R/Dtube = 0.175/0.050 = 3.5):
Aluminum tube with
D = 50.8 mm and L = 300 mm.
Different tests on DDTs using
propane in a test rig of 50,000 ft3
(1500 m3 ) gross volume were
performed by SRI International
and Gexcon.
Failure pressures: from 10 to
33 bar. Measurement of
(i) properties: temperature and
pressure and (ii) consequences:
blast overpressure, loud imaging,
and shock around the vessel,
among others.
The observation revealed the presence of a Mach
shock at the vessel at the early stage of the opening.
The results also demonstrated that the lead shock is
generated before and gone before the liquid starts
boiling, which indicates that the vapor expansion is
primarily responsible for the first shock overpressure.
[144]
Overpressure in the near-field
(distance from the BLEVE center
to the target, measured in the
range within ten times the
diameter of the BLEVE vessel);
high-speed images.
Using shock tube overpressure prediction and
spherical shock propagation model, a model based on
the vapor phase properties at failure and a spherical
shock propagation model was developed to predict
BLEVEs overpressures in the near-field.
[154]
The failure pressure Pfail (from
11.7 bar to 32.7 bar); liquid fill
level φliq (from 0 to 87%); the
weakened length through
machining at the top of the tube,
Lc (from 50 mm to 150 mm).
The liquid fill ratio and the length of the debilitated
vessel govern the magnitude of the ground force,
which, jointly with the impulse, were linearly related
to the rupture pressure and liquid fill ratio.
[155]
Variables: levels of congestion,
confinement, and gas
concentrations. The flame speed
and overpressure measurements
were used for validation.
The congested area plays a significant role in the
occurrence probability of DDTs. Also, the effects of
detonating clouds are more critical than previously
thought, which should be considered in future plant
layout assessments.
[156]
BLEVE
Study the first moments (early
milliseconds) of small-scale
BLEVE in propane vessels
BLEVE
Analysis of the peak
overpressure from the lead shock
produced by a BLEVE using a
new method: spherical
shock theory.
BLEVE
Study the ground force effect of
BLEVEs: their impact on bridges
and other infrastructure.
Deflagration-to-detonation
transitions (DDTs)
Prediction of DDTs at large scales
in congested areas.
Studied Variables
Main Conclusions
A new correlation coupling the turbulent Karlovitz
stretch factor and the ratio of nozzle exit diameter to
exit-plate spacing was developed for the flame
extension area of both horizontally and vertically
impinging jet fire. It is noted that the temperature
profile holds a big difference in the upward and
downward directions along the vertical plate.
All the tested tanks failed with a BLEVE within a
t < 5 min after ignition, accompanied by a fireball, a
near-field blast wave, and enormous fragmentation,
leading to a high risk to rescue services when an LPG
tank is affected by a fire.
Reference
[152]
[153]
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Reinders et al. [157] developed a lumped equilibrium tank model to study the
pressure and temperature of LPG increase in a thermally coated pressure vessel exposed to a surrounding fire outbreak from a BLEVE. The results were validated
against experimental tests in which three m3 tanks were filled to 50% capacity. The
tests were carried out by the TNO research organization in the Netherlands and the
Bundesanstalt für Materialforschung und-prüfung https://www.euro-mic.org/partner/
bundesanstalt-fur-materialforschung-und-prufung-bam/ (accessed on 3 May 2025) (BAM)
in Berlin. A good correlation was obtained between the modeled and experimental
pressure and temperature evolutions over time, using a constant value for the thermal conductivity of the insulation layer of the tank. The developed model could
be helpful for emergency response units acting to repress an LPG tank fire safely.
Hemmatian et al. [158] proposed a methodology for the BLEVE mechanical energy release calculation based on the thermodynamic assumption of actual gas behavior and
adiabatic irreversible expansion for different gases, including propane. The model only
required the vessel filling percentage and temperature at failure as input data. This methodology enabled the achievement of good results in a straightforward manner. Hemmatian
et al. [159] also proposed a new, theoretically based empirical method for predicting overpressure easily and simply, considering the liquid fill ratio and failure temperature. This
latest method was developed to accurately reflect the behavior of real gases and adiabatic
irreversible expansion. The model was validated with experimental data.
Furthermore, Hemmatian et al. [159] comprehensively compared BLEVE overpressure
predictions. The authors compared the empirically calculated data based on theory with
experimental data. They concluded that the overpressures predicted using theoreticalbased empirical models (i.e., TNO [160] and Roberts [150]) were conservative due to
assumptions regarding isentropic expansion, isothermal expansion, ideal gas behavior,
and constant volume energy. In contrast, the predicted overpressures closely aligned with
experimental data when real gas behavior and adiabatic irreversible expansion (RAIE) were
considered (i.e., Casal & Salla [161] and Planas-Chuchi et al. [162]). Recently, Laamarti
et al. [163] developed a predictive correlation that estimated the ground loading from
small-scale propane BLEVEs. The correlation had the vessel size, burst pressure, fill level,
and weakened length as inputs, and the outputs were peak ground force, force duration,
and impulse. The results revealed a significant influence of the liquid phase on the ground
load force and its duration. Thus, vessels close to 95% full of liquid led to BLEVE incidents
with the highest ground loads. The authors emphasized that correlation validation should
be conducted on larger scales.
Sellami et al. [164] studied the validation of the Sedov–Taylor blast wave model for a
BLEVE. The proposed model allowed the estimation of the overpressure effect of a BLEVE
phenomenon by determining physical quantities characterizing the blast wave evolution,
such as radius and velocity. The results were validated with BLEVE experiments, and
they are more suitable for large-scale (5.6 m3 cylindrical tanks containing 2 tons of LPG,
heated until a pressure of 15.2 bar) than medium-scale explosions (2000 L tanks, containing
between 109.5 and 538 kg of LPG, with failure pressures between 15 to 19 bar). Afterward,
the authors embedded the proposed model within the quantitative risk analysis (QRA)
of a gas-processing unit. The authors used conventional tools such as the Hazard and
Operability Analysis (HAZOP) and the Failure Modes and Effects Analysis (FMEA), which
disclosed that the LPG accumulator is a critical system. Thus, it is essential to enhance
its safety by optimizing existing safety barriers and implementing new ones to prevent
BLEVE catastrophic consequences. Furthermore, incorporating the QRA–Sedov–Taylor
approach enabled the derivation of realistic predictions for these BLEVE consequences (i.e.,
overpressure and thermal radiation) [165].
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6.1.3. Integral Methods
Researchers have been working on developing more accurate mathematical models for
consequence analysis, which is crucial for improved risk assessment and decision-making
in safety management. In this context, integral models such as those employed in software
such as ALOHA, EFFECTS, and PHAST are lumped-parameter ones developed typically
for one- or two-dimensional consequence predictions [166].
In that direction, Bariha et al. [167] studied the risks of LPG transfer operation in a
bottling plant. The effects of flammable vapor dispersion, jet fire, pool fire, and fireballs
were investigated using ALOHA and PHAST (unspecified versions and models). Using
the same input data, the authors found differences in results, such as the maximum
damage distance for a thermal intensity of 37.5 kW/m2 , resulting in 24.16 and 10 m
for PHAST and ALOHA, respectively. The results revealed that the thermal radiation,
estimated between 4–40 kW/m2 for the studied bottling plant, could affect the nearby
population. Furthermore, using ALOHA, Beheshti et al. [168] conducted a study on the
impact of LPG leakage from domestic cylinders. The study involved leaking LPG from a
valve with a 1-inch hole in cylinders of varying sizes (26, 60, 78, and 107 L). In a BLEVE
scenario, it was observed that the thermal radiation at distances of 39, 48, and 53 m reached
about 10 kW/m2 , posing a risk of causing fatalities to individuals within that range. At
greater distances of 55, 68, and 74 m, the resulting thermal radiation was measured at
5 kW/m2 , which could potentially lead to second-degree burns. This study emphasizes
the importance of developing an emergency response plan in the event of catastrophic
scenarios involving domestic LPG cylinders. Another study employing ALOHA [169] was
devoted to modeling the consequences of a gas leakage and explosion fire from an LPG
(100% propane) tank within a filling station. Thus, the thermal radiation from a BLEVE
is approximately 10 kW/m2 up to 184 m from the explosion and 5 kW/m2 at distances
of 260 m from the tank. On the other hand, comparable results were obtained using the
same software by Kukfisz et al. [170]. They investigated the potential safe distance between
public buildings and LPG (100% propane) filling stations, which consist of two gas storage
tanks and a dispenser. Three different BLEVE scenarios were studied, with a tank filled
at 20%, 42.5%, and 85% capacity. According to the results, for BLEVE scenarios with
short-term radiation emission, the limit value of 12.6 kW/m2 is reached for distances of up
to 149 m if the LPG storage tank is filled with 85% at the time of the explosion.
Witlox et al. [118] performed an overview of the verification and validation of consequence modeling for accidental releases of toxic or flammable chemicals, including propane.
This verification of different models, such as flammable effect, dispersion, pool spreading/evaporation, and discharge models, provided an extensive experimental database to
validate the consequence models in the hazard assessment package PHAST and the risk
analysis package Safeti (V.8.1). Malviya and Rushaid [171] performed the consequence
analysis of a BLEVE scenario of an LPG sphere tank using the PHAST software (V.6.5,
unspecified model) and compared it to numerical calculations. According to the PHAST
results, the exposure duration to a fireball is 27.57 s. It decreased to 24.41 s using numerical
calculations. Furthermore, the thermal radiation PHAST results differed significantly as the
receptor distance increased. Thus, for a receptor distance of 100.12 m, the calculated thermal
radiation is 58.36 kW/m2 and 62.33 kW/m2 for PHAST and mathematical calculations,
respectively. However, for 330.36 m, the calculated thermal radiation is 43.56 kW/m2 and
50.37 kW/m2 for past and mathematical calculations, respectively. On the other hand,
Alfatesh and Biak [172] analyzed the BLEVE caused by a loss of containment of an LPG road
tanker using PHAST software (V.8.11) and compared the results with those from a mathematical model. The results evidenced that the analysis performed with PHAST resulted
in a larger radius covered, except for the worst thermal radiation value, >37.5 kW/m2 ,
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with a receptor distance of <170 m and <175 m, for PHAST and the mathematical model,
respectively. Meanwhile, for thermal radiation of 12.5 kW/m2 , the distances are 295 m and
273 m for PHAST and the mathematical model, respectively. Moreover, Lyu et al. [138]
studied and simulated the LPG tank truck accident in Wenling, China, using EFFECTS and
ALOHA software (unspecified versions). EFFECTS was employed to simulate the probable
distribution of the tank debris after the BLEVE and the evaporation and spreading of the
LPG. In contrast, ALOHA software and the TNO multi-energy method were employed to
simulate the VCE. The results showed that the values given by the software for the distance
of the tank residues are significantly lower than the actual distance (400 m). Furthermore,
the authors noted the difficulty in predicting explosions in confined environments using
simple leakage-dispersion models.
Additionally, MacNguyen [112] employed PHAST software (V.8.71) to compare the
hazards of hydrogen with those of standard hydrocarbon fuels, including LPG. Among
other results, the authors showed that the thermal reach distance for a pool fire from a 6-in.
bounded release at storage conditions is lower for hydrogen than for LPG and LNG. For
example, for a thermal radiation level of 12 kW/m2 , the downwind distance for LPG and
LNG is 42 m, and for hydrogen, it is 20 m. The authors stated that the study will provide
the industry risk stakeholders with helpful guidance toward transitioning from LPG and
LNG to hydrogen fuels.
6.1.4. Computational Fluid Dynamics (CFD)
An advantage of CFD-based consequence analysis, which involves conducting numerical simulations of dispersion, explosion, and fire, is that this method can thoroughly
consider obstacles and terrain, leading to more accurate results than the previously mentioned methods. The mainstream software packages for CFD simulations in safety processes
are ANSYS Fluent and CFX, GEXCON FLACS, and open-sourced OpenFOAM, among
others [124]. It is essential to note that the reliability and accuracy of CFD models depend
heavily on the validation of experimental data. In this respect, the modeling capabilities
of CFD remain limited, though substantial progress has been made recently [173]. Table 6
highlights selected CFD studies on LPG consequences analysis.
LPG has a high risk of pool fires during transportation, storage, and applications.
Therefore, Yi et al. [174] analyzed the hazards of LPG in large-scale pool fires using the
CFD ANSYS Fluent software (V.19.2). After comparison with benchmark experimental
data, the authors demonstrated that the employed CFD model accurately predicted the
radiation of large LPG pool fires, and safe separation distances between LPG facilities
and surroundings were estimated. Afterward, Yi et al. [139] also analyzed how pool
diameter and wind velocity could influence the configuration of LPG pool fires using
an experimentally validated CFD model developed in the same software (ANSYS Fluent
2019 R2). The authors proposed more accurate correlations that provide more accurate
predictions of flame height and tilt angle compared to the reported empirical models.
Scarponi et al. [175] used a CFD modeling approach to simulate and predict the behavior
of an LPG pressurized tank exposed to a partially engulfing pool fire using ANSYS Fluent
software (V.18.2). The comparison of the pressure build-up, wall temperature predictions,
and lading temperature with the results of experimental fire tests verified the model as a
reliable tool for analyzing pressure tanks under complex fire conditions.
Mashhadimoslem et al. [176] studied and simulated vertical propane jet fire through
the k-epsilon (k-ε), realizable k-epsilon (RNG k-ε), baseline (BSL), baseline Raynolds Stress
(BSL RS), and Shear Stress Transport (SST) models using the ANSYS CFX software (V.15.0).
The results showed that the SST turbulence model is the most suitable, with an average
error of 4.7% for a jet fire simulation. Vijayan et al. [177] studied the main geometrical
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features of jet flames using the CFD code FDS for regular and reduced ambient pressure
conditions, and it was validated using results from previous works. The authors found that
low-pressure conditions could lead to higher jet flame areas, and the flame length mainly
depends on the exit momentum.
A VCE, followed by a fire, represents one of the most dangerous and high-consequence
events in chemical facilities involving flammable materials. Hu et al. [178] investigated the
LPG vapor cloud explosion hazards using CFD models through the FLACS software (V.10.7).
Accordingly, in an ignition event, a nonuniform LPG cloud can result in a turbulent flame
impacting the diluted explosive cloud at high speed, resulting in more severe consequences.
Should LPG leakage exceed 300 s and the aperture widen beyond 10 mm, the hazard
zone (Pc > 2 kPa) experiences a sharp escalation, thereby emerging as the pivotal factor in
controlling explosion hazards. The LPG safe reserve demonstrates minimal variation at low
protection distances (Rp) and critical overpressures (Pc). However, it shows an exponential
increase when Rp and Pc surpass 200 m and 20 kPa, respectively.
Furthermore, Wang et al. [179] studied the dynamic process and damage evaluation of
the Wenling, China, accident in 2020 (see Table 3) through scene reconstruction in FLACS
(unspecified version). The authors found that the expansion of the LPG explosion around
the expressway moved along the spaces between the obstacles. The overpressure was
sufficient to cause considerable damage to the surrounding structures. Additionally, a
detailed damage analysis of coupling characteristics resulting from an LPG tank trailer
explosion is proposed, which will be useful for future blast-resistant structure design. Wang
et al. [180] employed FLACS software (unspecified version) to simulate the 2018 LPG tank
truck accident in Bologna, Italy. The authors found that the continuous dispersion from
the LPG tank trailer triggered the vapor cloud explosion. The proposed work involved a
failure analysis and classification of accidents involving LPG tank trailers, focusing on the
explosive destruction and damage mechanisms that contributed to hazard identification
and emergency response. Recently, Dhiman et al. [181] evaluated the performance of the
PDRFoam tool (unspecified version- an open-source variant of OpenFOAM) on the vapor
cloud explosions of propane. The evaluation of results was evaluated against a database of
medium-scale experiments. The results showed that the flame propagation is well-modeled.
However, over-predictions for peak pressure were found. The authors noted that PDRFoam
is a computationally cost-effective solver for CFD explosion modeling, and its open-source
nature opens up possibilities for further modeling.
On the other hand, Wang et al. [182] performed a hazard analysis on a characteristic
fireball of an LPG riad tanker BLEVE using the FDS code from NIST (unspecified version).
The authors found that the bigger the fuel mass, the larger the longitudinal diameter of the
fireball, as well as the fireball’s diameter and aspect ratio. Accordingly, the fireball gradually
changes from momentum-driven to buoyancy-driven as the mass of fuel increases. The
results showed that the simulation data agrees well with the experimental data and could
help us understand the evolution and hazards of BLEVE accidents. On the other hand,
Sellami et al. [183] also proposed a CFD approach to evaluate the thermal effects of a
BLEVE in the gas processing plant using the FDS CFD code FDS from NIST (V.6.5.3).
The approach considered a sensitivity analysis for choosing appropriate models to fire
reactive flows. The procedure was validated through empirical correlations and large-scale
data from the literature, demonstrating good agreement. However, the authors noted the
importance of the liquid-gas transition and the container disintegration to model a BLEVE
process entirely.
Weerheijm et al. [184] performed a quantitative risk analysis of tunnel LPG explosions.
The authors simplified 3D-CFD codes to a 1-dimensional numerical gas explosion model
developed specifically for tunnel conditions. The results showed that in the case of an
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instantaneous LPG release, the cloud is initially above the upper flammability limit (UFL).
Depending on the initial amount of LPG released, the cloud will be mainly fuel-rich by
the time it reaches the end of the tunnel or may fall within the flammability limits before
the tunnel ends. Li [185] also studied the hazards of alternative fuel vehicles, including
those working with LPG, using a one-dimensional CFD program that was verified with
previous tests. An analysis of the peak overpressure in case of an explosion in a tunnel
showed that for gas tank rupture and BLEVE, the peak overpressure decreases rapidly
along the tunnel and is reliable for users more than 100 m away from the tank. On the
contrary, a cloud explosion would be most severe and intolerable for tunnel users. These
studies contribute to the safety design of vehicles and tunnels. Moreover, Cheng et al. [186]
investigated the ground vibrations caused by an LPG BLEVE inside a road tunnel using
FLACS and LS-DYNA software (unspecified versions) to simulate the BLEVE process and
the response of arched tunnel and surroundings, respectively. The authors found that the
cover depth of the tunnel, the rock type, and the porosity are significantly more influential
than the tunnel lining concrete grade in the LPG BLEVE-induced ground vibrations.
Shelke et al. [187] performed CFD analysis for two hydrocarbon BLEVE fireballs using
the FireFOAM CFD code (unspecified version). The authors estimated the FireFOAM
capabilities to simulate the fireball diameter, lifetime, flame dynamics, and structure and
compared the results with BAM experiments and an aircraft. The authors concluded that the
calculated fireball diameter and lifting height are in good agreement with available video
records. Abdel-Jawad [188] proposed a hybrid method (analytical-numerical) using Prugh’s
method as a feasible alternative for rapid solution times for BLEVEs modeling without
accuracy loss, using the exploCFD code (V.7.0). The explosion source was first calculated
analytically regarding pressure and temperature, then fed into the exploCFD code to
estimate the blast wave propagation in a 2D domain. The initial rupture, catastrophic failure,
and subsequent ignition were modeled as occurring instantaneously at the beginning of
the simulation. Compared to the experiments [189], the simulation results showed that for
a sensor location 10 m away from the side of the tank, an overpressure overestimation by
exploCFD was about 20%. Consequently, in further work [190] the same author improved
the method by coupling it with the confinement-specific correlation (CSC) gas explosion
model, demonstrating exceptional agreement with previous experiments for peak pressure,
impulse, and the time history of the first peak parameters. Compared to prior work,
for a sensor location 10 m away from the side of the tank, the exploCFD prediction for
the maximum overpressure closely matches the experimental results [189]. Based on the
author’s findings, there is a variation of a few hundred Pascals. Davidy [191], on the
other hand, proposed an algorithm using large eddy simulation (LES), calculation of the
convective and radiative heat fluxes, thermochemical and heat transfer analysis of the
vessel coating, and the calculation of the time required to evaporate the liquefied propane
using FDS simulator (V.5.0) and COMSOL Multiphysics (V.4.3b). The author proposed a
new and flexible tool for analyzing pressure vessels exposed to jet fire. Future work with
other hydrocarbon fuels, as well as BLEVEs caused by pool fires, is also possible.
Scarponi et al. [192] developed a two-dimensional CFD-based model using ANSYS
Fluent (V.18.2.0) to observe the pressure build-up of LPG tanks exposed to fire until BLEVE
occurrence. The model enabled the study of the effects of free convection and thermal
boundary phenomena, thermal stratification in both the liquid and vapor phases, and
liquid thermal expansion. The authors noted that the development model could support
studies predicting vessel failure under fire explosion. Subsequently, Scarponi et al. [193]
extended the work by developing a 3D model in ANSYS Fluent (V.18.2.0) to simulate the
pressure build-up in equipment with saturated liquids exposed to fire. The comparison
between 2D and 3D model results showed that the 2D models are reliable in modeling
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fluid behavior when homogeneous heat exposure conditions exist. However, 3D models
overcome limitations such as temperature profiles and recirculation patterns. The same
authors [194] recently performed a parametric analysis to investigate the behavior of a
1.9m3 bullet LPG tank in partial engulfment fire scenarios using ANSYS Fluent (V.18.2.0).
Different cases were studied by varying the position of the zone exposed to fire and the
filling degree of the tank. It was demonstrated that the engulfment mode and the filling
degree strongly influence the tank’s pressurization rate, energy accumulation, and hightemperature mechanical wakening.
Furthermore, Li and Hao [195,196] employed the CFD-based software FLACS (V.10.7)
to predict the BLEVE blast wave in open space and hindered environments. Accordingly,
the authors found that the liquid flashing from the LPG tanks is slower than vapor expansion in generating shock waves. The maximum peak pressures from the models were
mainly attributed to vapor expansion. Regarding shock waves in obstructed environments,
obtaining simulation-based correlations for pressure predictions that can predict explosion
loads is feasible. A good agreement was achieved between the CFD results and medium- to
large-scale experimental data. In addition, Ma et al. [197] performed numerical simulations
using the k-ε and eddy-dissipation models of FLUENT (unspecified version) to analyze the
mass and heat transfer in an LPG leak from a vessel. The simulation results agreed well
with the experimental observations, validating the phase transition during the LPG boiling
process. This provided information on the temperature, pressure, and thermal radiation
distribution of the explosion flow field.
Wang et al. [198] also studied the BLEVE loading on rigid structures using FLACS
(V.22.LR2). Previous large-scale experiments were used to calibrate the numerical model.
The authors analyzed the diffraction and clearing effects on the reflected waves concerning
the dimensions of the structure. Consequently, reflection coefficient charts were developed
to predict the reflected BLEVE overpressure on rigid structures. In their subsequent
work, the authors [199] investigated the influence of structural stiffness and BLEVE wave
duration on the reflected BLEVE pressure on the structure. The interaction of BLEVE waves
with flexible structures was simulated using ANSYS Fluent (V.16.0) for the blast wave
propagation coupled with ANSYS Mechanical (V.APDL.16.0) for structural analysis. The
results showed that during the action of a BLEVE wave, the more flexible the structure,
the smaller the peak reflected pressure and the longer the duration of the action on the
structure. The results can be used to predict explosion loads when designing structures
against BLEVEs.
On the other hand, Yuan et al. [200] studied, through numerical simulation using
FLACS (V.10.7), the LPG gas explosion accident in Beijing on 15 March 2022 (an example
of an accident in a high blockage environment). The results showed that the explosion
of 4.0–4.1 m3 of LPG can destroy several walls, with a maximum indoor overpressure
of 1.130 bar. Additionally, the explosion resulted in a high-pressure injury area of 10 m
and a high-temperature injury area of 14 m outdoors. Also, if structures have the same
spatial direction as the propagation direction of the initial wave, they will suffer less
damage. Doors and windows constrain the normal venting process of the explosion
reaction fluid in civil buildings, leading to severe outdoor consequences. Accordingly,
reasonable pressure relief areas will contribute to preventing and mitigating disasters
from explosion accidents. Furthermore, Kang et al. [41] proposed a CFD-based simulation
methodology using satellite maps along the FLACS software (V.10.7) to visualize the
consequences of the failure of an LPG tanker leak explosion, aiming to provide support
for LPG accident prevention. Recently, Lyu et al. [201] studied the predictive ability of the
model for LPG gas dispersion using the data from the LPG tank truck accident in Wenling,
China, and using the commercial CFD code ANSYS Fluent (V.14.0). The geometric model
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and grid were established using geographic information system (GIS) data from Google
Maps of the accident site. The authors discussed the multicomponent liquid flash and
liquid pool evaporation and spreading. The authors found that one of their simulations
was consistent with the distribution of accident damage. The proposed methodology
could guide accident consequence assessment and emergency response measurement
development. Furthermore, the authors encourage studying and validating the discussed
model for other liquid gasses, such as liquefied natural gas, chlorine, and ammonia. These
recent case-based studies reaffirm the relevance of CFD as a valuable tool for simulating
real-world LPG incidents, thereby enhancing the accuracy of consequence prediction and
supporting the development of emergency response strategies in complex environments.
Table 6. Highlighted CFD studies on LPG-related consequences modeling.
Incident
Pool fire
Objective
Heat radiation from
large LPG pool fires
CFD Code
ANSYS Fluent
Models
k-ε model; radiation:
P-1 model;
non-premixed
combustion model;
surface emissive
power (SEP) model;
Pool fire
Flame height and
flame tilt as
functions of pool
diameter and
wind velocity.
ANSYS Fluent
k-ε model; radiation:
P-1 model;
non-premixed
combustion model;
Jet fire
Compare different
turbulence models
for vertical propane
jet fire simulation.
Home code coupled
with ANSYS CFX
Turbulence models:
k-ε, SST, BSL, BSL
RS, and RNG k-ε;
EDC combustion
model; Monte Carlo
radiation model.
Jet fire
Flame geometry of
horizontal turbulent
jet fires in
reduced pressures
FDS
LES turbulence
model; EDC
combustion model.
Vapor Cloud
Esplosion
Study the hazard
evolution of
considerable LPG
leakage and vapor
cloud explosion
FLACS
RANS turbulence
model
Scenario
Main Conclusions
Reference
Three different pool
diameters of 12.9, 14.9,
and 16.9 m with
atmosphere temperatures
of 309, 306, and 312 K,
mass burning rates of
29.087, 47.328,
44.426 kg/s, and wind
velocity of 3, 2.5, 0 m/s,
respectively.
Air velocities of 0, 0.5, 2.5,
and 3 m/s were selected
for each of the following
pool fires with diameter,
ambient temperature,
and average mass
burning rate of (i): 10.4 m,
306 K, and 8.406 kg/s
(ii): 12.9 m, 309 K,
12.932 kg/s, (iii): 14.9 m,
306 K, and 17.254 kg/s,
and (iv) 16.9 m, 312 K,
and 22.196 kg/s.
Computational domain:
Cylinder with L = 10 m
and D = 2 m. Fuel inlet to
simulate the vertical jet
fire: Nozzle with
D = 12.75 mm.
Temperature range:
1500–1700 K. Fuel rates:
148.41 m/s (0.03 kg/s)
and 252.75 m/s
(0.19 kg/s).
The domain size is
8 m × 8 m × 7 m. The
release square nozzle
(20 mm × 20 mm) is
provided in the Y-Z plane,
1.3 m above the ground.
Five ambient pressure
conditions, ranging
between 0.6 and 1 atm,
and eight jet fuel exit
velocities, between 27.5
and 125 m/s,
were studied.
The model size of the
LPG plant was
450 × 300 m, including
six oil tanks, six
refrigerated tanks, and
four pressure tanks. The
LPG vapor cloud with
stoichiometric
concentration was
ignited at the top of the
refrigerated tank; the
initial temperature
was 301 K.
The employed CFD
model (compared to
experimental data)
accurately predicted the
radiation of large LPG
pool fires. Safe separation
distances between LPG
facilities and
surroundings
were estimated.
[174]
Higher horizontal wind
velocity → stronger
convection effect in the
horizontal direction,
reducing the flame height
and increasing the flame
tilt angle.
Larger diameters are less
sensitive to the
wind velocity.
[139]
The SST turbulence
model is the most
suitable, with an average
error of 4.7% for a jet
fire simulation
[176]
Low-pressure conditions
could lead to higher jet
flame areas, and the flame
length mainly depends
on the exit momentum
[177]
LPG expansion about the
ground occurs along the
gaps between structural
congestion. Continuous
large-scale congestions,
such as walls,
significantly enhance the
LPG expansion and
concentration accumulation.
[178]
Fuels 2025, 6, 45
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Table 6. Cont.
Incident
Vapor cloud
Explosion
BLEVE fireball
BLEVE fireball
Objective
CFD Code
Evaluate the
PDR approach
(PDRFoam) to
model the effect of
small-scale obstacles:
pipes on flame
propagation and
explosion overpressure.
Analyze the
consequences of the
fireball from an
LPG tanker
BLEVE accident.
Evaluate the BLEVE
thermal effects on a
gas processing plant.
LPG BLEVE in a
tunnel
Investigate the rock
vibrations induced
by an LPG BLEVE
inside a tunnel.
BLEVE
Blast wave
prediction of
large-scale BLEVE in
the open space.
BLEVE
BLEVE-VCE
Wenling accident
Blast wave
prediction of
medium to
large-scale BLEVE in
an obstructed
environment.
Simulation of gas
dispersion resulting
from the accidental
instantaneous
release of LPG and
reconstructing
actual accident
processes.
OpenFOAM
FDS
Models
κ-ϵ—PDR-based
modifications for
turbulence;
laminar flamelet
combustion model
LES
Scenario
Pipe geometry: 3 m in
length, 1 m in breadth,
and 1 m in height. The
pitch is 0.33 m vertically
and horizontally, and the
obstacle diameter (D) is
0.01 m. The fuel-air
mixture was filled in the
domain with an
equivalence ratio of unity.
A 200 m3 cube was
selected as the domain.
The sides and top of the
domain behaved as an
open atmosphere. Initial
pressure: atmospheric
pressure; initial oxygen
mass fraction: 0.232;
initial temperature:
20 ◦ C.
LES turbulence
model; EDC
combustion model;
thermal radiation
model
Plant: open calculation
domain of
300 m × 300 m × 360 m.
Relative humidity: 40%,
ambient temperature:
20 ◦ C. Accumulator:
Temperature 40 ◦ C;
Pressure: 14.5 barg;
Volume: 50 m3 .
FLACS and ANSYS
LS-DYNA
κ-ϵ model; ALE
algorithm
Model domain: 30 m
length, 30 m width, 60 m
height. LPG tank:
volume 20 m3 ; diameter
2.4 m. The tank center is
located at the center of
the upper arc of the
curved-wall-arched
tunnel.
FLACS
RANS turbulence
model
A 2000 L propane tank is
modeled as a 2.6 m long
cuboid. Stretched grids
start at 4 m from the edge
of the core grid domain.
RANS turbulence
model
Two domains were
simulated with
dimensions of
65 × 40 × 30 m3 and
230 × 60 × 40 m3 . The
obstacles in the following
parametric study are
located on the ground
and at least 5 m away
from the BLEVE source.
RANS turbulence
model; SIMPLE
algorithm
CFD simulation domain:
A high-resolution terrain
geometric model of the
region around the
accident site with an area
of 3.83 km2 and height of
300 m (ICEM software),
containing buildings,
viaducts, ramps, and
trees. GIS data from
Google Maps at a
horizontal resolution of
10 m.
FDS
FLACS
Ansys Fluent
Main Conclusions
Reference
The flame propagation is
well modeled
considering the database
of vapor cloud explosion
experiments. However,
over-predictions for peak
pressure were found.
[181]
The bigger the fuel mass,
the larger the
longitudinal diameter of
the fireball, as well as the
fireball’s diameter and
aspect ratio. Fireball
gradually changes from
momentum-driven to
buoyancy-driven as the
mass of fuel increases.
The procedure showed
good agreement with
experimental data.
However, the authors
noted the importance of
the liquid-gas transition
and the container
disintegration in
modeling a
BLEVE process.
The cover depth of the
tunnel, the rock type, and
the porosity are
significantly more
influential than the
tunnel lining concrete
grade in the LPG
BLEVE-induced ground
vibrations.
The liquid flashing from
the LPG tanks is slower
than vapor expansion
when generating shock
waves. The maximum
peak pressures from
models were mainly
attributed to
vapor expansion.
Only the vapor
expansion from BLEVE
was considered to
simulate the shock waves
in an obstructed
environment. Good
agreement was obtained
between the CFD results
and medium-large-scale
experimental data.
Simulation-based
correlations for pressure
predictions that could
predict explosion loads
were proposed.
The LPG
instantaneous-release
model was constructed
considering the
multicomponent liquid
flash and liquid pool
evaporation and
spreading. The droplets
in the release source,
terrains, and obstacles
significantly affected the
vapor cloud’s dispersion
behavior and
extension distance.
[182]
[183]
[186]
[195]
[196]
[201]
6.1.5. Application of Machine Learning
Machine learning is increasingly important for analyzing consequences and assessing
risks. It provides advanced predictive capabilities and improved accuracy in identifying potential hazards and their consequences by analyzing large datasets, facilitating assessment,
Fuels 2025, 6, 45
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and saving time for rapid emergency response [202–204]. Therefore, machine learning
has been proposed to enhance the accuracy and efficiency of BLEVE pressure prediction.
Thus, Hemmatian et al. [205] estimated the mechanical energy of propane and butane
BLEVEs. The dataset, derived from real gas behavior and the adiabatic irreversible expansion method, was used to train the Artificial Neural Networks (ANN). A Bayesian
regularization was the three-layer backpropagation training algorithm. Temperature and
vessel filling degree at failure have been considered input parameters (plus vessel volume),
and the ANN model estimated the BLEVE blast energy as output data, validated with
experimental values.
In this context, Gabhane and Kanidarapu [206] analyzed worse-case scenarios for
an LPG terminal. Firstly, the authors performed a Hazard Identification (HAZID) study
to obtain the worst-case failure scenario data. They used them in the ALOHA software
to generate safety distance measures, considering the effects of flammable vapor clouds,
thermal radiation, and overpressure blast waves. The resulting dataset was divided for
training, validation, and testing of the ANN. The results from the ANN demonstrated
high accuracy in safety distance prediction, providing valuable insights for informed risk
management decisions.
On the other hand, accurately simulating CFD model simulations of BLEVE events,
including their wave propagation and effects on the surroundings, is time- and resourceconsuming. Machine learning arises as a promising option for relieving those CFD drawbacks. In machine learning approaches, training data are required to train the model to map
from input variables to selected target outputs [166]. Accordingly, Li et al. [207] developed
CFD techniques that utilized an ANN model to predict the impact of blast-loading generated from BLEVEs. The authors found that the application of the ANN model significantly
decreased processing times from hours to seconds. Furthermore, the results from the
trained ANN showed an error of only 1.3% compared to CFD simulations based on actual
experiments. Similarly, Li et al. [208] improved the BLEVE pressure predictions from CFD
models through the ANN model. Despite the reliable estimation of BLEVE consequences
inside a tunnel, this work lacked rigorous validation compared to previous work. Although
ANNs enable expedited calculations related to the consequences of BLEVEs, their use could
be made more straightforward. In this regard, Wang et al. [209] employed a surrogate multilayer perceptron (MLP) model to improve the ANN training efficiency and accuracy. The
results were verified based on the experimental data available in the literature. Likewise, Li
et al. [210] conducted a comparative study on the most effective machine learning model for
predicting the consequences of BLEVEs. The authors found that between the MLP, ResNet,
Transformer, and lightGBM, the transformer neural network achieved the best results for
BLEVE pressure prediction in an open space. In this sense, Li et al. [211] employed the same
machine learning approach to predict the consequences of propane and butane BLEVEs
on structures (rigid obstacles). This study opened the door for using Transformer as a
surrogate model for CFD BLEVE consequences analysis for structural response predictions.
The same authors [212] recently proposed using Graph Neural Networks (GNNs) to predict
overpressure from a BLEVE. The authors found that the GNNs exhibited higher temporal
resolution in pressure-time history prediction compared to the exclusive CFD simulations.
7. Conclusions and Outlook
LPG is increasingly positioned as a link to clean fuels in the current energy transition.
LPG has environmental advantages over other fossil fuels. Moreover, its well-developed infrastructure in storage, transportation, and end-use applications can be utilized, sometimes
without modification, for the production of single-use or blended clean fuels, allowing
them to enter the market while strengthening their supply chain.
Fuels 2025, 6, 45
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However, being such a widely used fuel, there are still accidents related to LPG,
which, although they have a very low probability of occurrence, they have very high
consequences for humans, the environment, and infrastructure. It is precisely the study of
the consequences of possible scenarios caused by incidents at different stages of the LPG
supply chain that allows us to learn lessons and make corrections to avoid new accidents,
minimize their consequences, or respond rapidly to an emergency involving this fuel.
This article provided a comprehensive review of LPG applications in the transportation
and energy sectors, as well as the prospects for biopropane. Especially on the topic of safety,
this review also presented the risks associated with LPG handling and the study of the
consequences of incidents related to this fuel. This work addresses a gap in existing reviews
by connecting the development of safety modeling tools—ranging from empirical methods
to machine learning approaches—with the larger context of how liquefied petroleum gas
(LPG) contributes to the energy transition. Unlike previous studies that have focused solely
on LPG applications or modeling techniques, this review highlights the interplay between
these elements.
Experimental testing provides insight into the phenomena within LPG-related fires
and explosions, serving as feed data for the discussed models. However, experimentation
at a large scale is dangerous and expensive. Therefore, efforts have been focused on
developing predictive models, including empirical, integral, and CFD models. Each model
can be used depending on the profoundness of estimation required. Empirical models are
used for initial screening or as a preliminary assessment of a given study. In addition to
experimental results, they allow the validation of integral or CFD modeling results. This
structured synthesis also clarifies the role of each modeling strategy within the current
challenges of consequence prediction and supports hybrid approaches in risk assessment.
Integral-based models are valuable tools for predicting the consequences of potential
accidents resulting from LPG release, considering factors such as weather conditions and
the scenario type under study, and providing relatively easy and fast estimations. Also,
integral-based tools are widely employed in companies and the competent authorities
for emergency action plans. However, using CFD techniques, a real-time assessment
that considers geographic and structural information to estimate the consequences of an
incident is only possible. Depending on the modeling level of detail, it could take several
hours of calculation, limiting their application in emergency responses.
The Wenling, China accident served as a valuable analysis tool and source of information. It has been studied using various tools for consequence analysis, ranging from simple
models to those with high geometric and analytical complexity levels. Therefore, hybrid
approaches that combine integral tools with CFD methods are an attractive alternative to
reduce calculation times. Moreover, using CFD methods combined with machine learning
enables a reduction in time from hours to seconds, accompanied by a slight increase in error.
At the same time, using machine learning with CFD is the future of achieving detailed
estimations of the consequences of accidents in complex geography or structures in very
short times, which could be used in emergency plans. However, this strategy needs to be
explored more profoundly and requires validation.
Moreover, it is here, considering the boom and the urgent need for implementing
clean fuels, where the studies carried out with LPG can bridge the gap in analyzing the
consequences of fuels such as hydrogen, DME, and ammonia. Human experience in the
handling, storage, transport, and applications of LPG and fuels such as LNG can contribute
to filling the gap that these new fuels present in terms of infrastructure and development
and, in general, data for the validation of the models that are being developed to study
the consequences of probable accidents due to their current and future implementation.
This review offers a knowledge base for LPG safety and a scalable modeling framework
Fuels 2025, 6, 45
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that can be adapted to cleaner fuels, where experimental data are limited and a rapid,
high-resolution risk assessment is urgently needed.
Author Contributions: C.A.-S.: Conceptualization, and Writing—original draft. J.-P.L.: Review and
editing. G.S.: Conceptualization, review and editing. B.R.d.V.: Conceptualization, review and editing.
All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by the Bourse postdoctorale Claire-Deschênes of the Faculté de génie,
Université de Sherbrooke [no grant number applicable].
Data Availability Statement: The original contributions presented in the study are included in the
article, further inquiries can be directed to the corresponding authors.
Acknowledgments: Carolina Ardila-Suarez is deeply thankful to the postdoctoral fellowship ClaireDeschênes of the Faculté de genie from the Université de Sherbrooke for the support Icons made by various
authors from www.flaticon.com are acknowledged for their use in the graphical abstract and figures.
Conflicts of Interest: The authors declare no conflicts of interest.
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