numerical computation of a large scale jet fire of high pressure hydrogen in process plant

Hydrogen consumed in a process plant is usually treated and de-livered under high pressure.. Following various Numerical computation of a large- scale jet fire of high- pressure hydroge

Hydrogen is the most abundant element on the Earth

and can be obtained from water and natural gas Once

hydrogen is used as fuel, it returns back to the form of

water, which makes it ecologically crucial in the

produc-tion of cleaner fuels The ideal method of producing

hydrogen involves the use of renewable energy sources

like solar power or wind power, but as these methods

result in considerable cost of production, hydrogen is

often produced using fossil fuel [1, 2] In South Korea,

the annual production of hydrogen amounts to about

9.3 million Nm3, and a significant portion of this is

pro-duced as byproduct gas Hydrogen is mostly consumed

in petrochemical plants, with only about 15% used in

other industries In particular, the rate of hydrogen

con-sumption in the energy industry is about 1%, representing

a very minor portion of consumption [2] Hydrogen

consumed in a process plant is usually treated and

de-livered under high pressure In these conditions, once

hydrogen is leaked from equipment and immediately

ignited, it creates a jet fire, which generally seems to result in less damage compared to explosion or toxic release However, if the facilities and devices installed around the equipment in the process plant are congested,

a severe secondary accident may occur due to the jet fire

Analyses of past accidents have shown that fire accidents represent a primary cause of numerous large- scale accidents [3–5] Moreover, at a process plant, fire represents one

of the frequent accident types [6] Yet, recent studies on the risk of hydrogen gas have been mostly related to explosions of hydrogen charge facilities [7, 8] Preliminary studies on hydrogen fires have been performed to evaluate the flame behavior of small- scale jet fires [9, 10]

In contrast to the aforementioned studies, here, numeri-cal analysis was performed of hydrogen jet fire in a com-plex, large- scale structure within an industrial process plant

to realistically predict its substantial effects Thereafter, through the outcome of computation, the influence of the flame intensity on surrounding process facilities and devices was evaluated and analyzed Following various

Numerical computation of a large- scale jet fire of

high- pressure hydrogen in process plant

Chang Bong Jang1 & Seungho Jung2

1 Korea Occupational Safety and Health Agency, 400 Jongga-ro, Jung-gu, Ulsan, Korea

2 Environmental and Safety Engineering, Ajou University, Suwon, Korea

Keywords

Flame, heat radiation, hydrogen, jet fire,

temperature

Correspondence

Seungho Jung, Environmental and Safety

Engineering, Ajou University, Worldcupro

206, Yeongtong-gu, Suwon, Korea

E-mail: processsafety@ajou.ac.kr

Funding Information

No funding information provided

Received: 23 May 2016; Revised: 10 October

2016; Accepted: 11 October 2016

Energy Science and Engineering 2016;

4(6): 406–417

doi: 10.1002/ese3.143

Abstract

Due to numerous hazardous chemicals to handle, the process plant industry has a higher risk of fire, explosion, and toxic release than other industries Reviewing the accidents at process plants in the past, it is clear that fire acci-dents occur with the highest frequency, leading this study to consider accidental fire scenarios at process plants For the scenario of an incident, a jet fire involv-ing a massive amount of hydrogen gas to be processed or delivered at the process plant has been selected The analysis of incident outcome resulting from the hydrogen jet fire has been implemented through the computational fluid dynamics simulation methodology Kameleon FireEx Based on the outcome of this simulation, the consequences of a jet fire with high temperature and heat radiation are analyzed and evaluated In addition, the results from Phast ver 7.11 simulation for the same scenario are presented for comparison and further validation

references, computational fluid dynamics (CFD)

simula-tions are available for various condisimula-tions such as

conges-tion of the facility and devices, turbulence, obstacles, and

weather effects; their results are very similar to the actual

outcome [11–13]

Numerical Simulation

For the hydrogen jet fire analysis, the Kameleon FireEX

(KFX) CFD code developed by ComputIT for fire analysis

was used KFX applies a precise code based on fire and

gas diffusion within a complex structure and is now

widely used as a safety analysis code in various industrial

fields

The Combustion Model

The governing equations, eqs (1–7) of KFX, determine

the mass conservation (eq 1), the mass species fractional

equation (eq 2), momentum conservation along the

co-ordinate direction using Navier–Stokes equations (eq 3),

and total energy equation for compressible gas flows

(eq 5)

Here, Rliq is a source due to the liquid phase

transi-tion, ρ is the density of gas, the — symbol represents

time- averaged quantities, and the ″ and ~ symbols are

fluctuation and mean of Favre- averaged quantities

Species mass fraction equations

In this equation, Yι is the species mass fraction and

V ιj is the molecular diffusion velocity of species ι in the

direction j In addition, Rι is a chemical source term and

is not considered since hydrogen is all gaseous phase in

the study

Momentum equations

Here, f i are mass forces by which the gas is influenced,

τij is the tension [N/m2], k is the second viscosity

coef-ficient, and δij is the Kronecker delta

The Eddy Dissipation Concept (EDC) is used for tur-bulent combustion Its basis is physical consideration of the structure of turbulent flow The mixing on molecular level, which is a necessity for chemical reactions to occur,

is located in structures where turbulent kinetic energy is dissipated into heat due to action of viscous forces on the local strain [14]

Enthalpy equations

In this equation, Qgs is the heat transport form solid

to gas phase, QRad is the net radiative transfer to the gas phase, ̃Sliq is the net heat transfer for the liquid phase,

k 𝜄 is the conductivity, e T is the total energy, and e is the

total internal energy

The Turbulence Model

For turbulent flow, KFX uses the extended formula of

the conventional k − ε formula for buoyancy and some

low- Reynolds numbers The modeled equation for k and

ε is presented in eq (8), and the rate of dissipation of turbulent kinetic energy ε is given in eq (9) [11]

(1)

𝜕𝜌

𝜕t+

𝜕𝜌̃u j

𝜕x j = 𝜌 ̃ Rliq

(2)

𝜕𝜌 ̃Y 𝜄

𝜕𝜌̃u j ̃Y 𝜄

𝜕x j = −

𝜕

𝜕x j

(

𝜌Y 𝜄 V 𝜄j)− 𝜕

𝜕x j

(

𝜌u��

j Y��

𝜄

)

+ ̄ 𝜌 ̃R 𝜄 + 𝜌 ̃ R liq,𝜄

(3)

𝜕𝜌 ̃u i

𝜕𝜌 ̃u j ̃u i

𝜕x j = −

𝜕p

𝜕x i+

𝜕

𝜕x j

(

𝜏 ij − 𝜌u��

j u��

i

)

+ 𝜌f i + 𝜌 ̃F liq,i

(4)

𝜏 𝜄j = 𝜇

(

𝜕 ̃u i

𝜕x j+

𝜕 ̃u j

𝜕x i

) + (

𝜅 −2

3𝜇)

(

𝜕 � u 𝜅

𝜕x 𝜅

)

𝛿 ij

(5)

𝜕

𝜕t (𝜌̃e T) + 𝜕

𝜕x j (𝜌̃u j ̃e T) = 𝜕

𝜕x j

(

(𝜏 ij − p)u j)+ 𝜕

𝜕x j

(

k 𝜄 𝜕T

𝜕𝜒 j − 𝜌 ̃u

��

j ̃e��

T

)

+Q gs + QRad+ 𝜌̃Sliq

(6)

e T = e +1

2u i u j

(7)

𝜄

Y

𝜄 e

𝜄 (T)

(8)

𝜕 (𝜌k)

𝜕 (𝜌̃u i k)

𝜕

𝜕x i

(𝜇eff

𝜎 k

𝜕k

𝜕x i

)

+ P − 𝜌𝜀 + B.

(9)

𝜕 (𝜌𝜀)

𝜕 (𝜌̃u i 𝜀)

𝜕x i

= 𝜕

𝜕x i

(𝜇eff

𝜎 𝜀

𝜕𝜀

𝜕x i

)

+ C1f1P 𝜀 k

− C2f

2𝜌

2

k + C1C

2

𝜀

k B.

(10)

P = 𝜌𝜈 t

(

𝜕 ̃u i

𝜕x j+

𝜕 ̃u j

𝜕x i

)𝜕 ̃u j

𝜕x i.

(11)

B = 𝜌̃ u��

i 𝜌��g i

(12)

𝜇 t = C�

D f

𝜇 𝜌 k

2

𝜀.

(13)

f u= exp [ −2.5

1 + R t∕50

]

In these equations, P is the production of turbulent

kinetic energy by the mean motion, B is a buoyancy, 𝜇 t

is a turbulence diffusion coefficient, R t is a turbulent Reynolds

number, f1, f2 are the functions in the low- Reynolds number

model, and f u is a low- Reynolds number correction factor

The constants in the turbulence model are as follows:

The accuracy and utility of KFX have been verified

through numerous experiments and on- the- job projects,

and the simulation has shown relatively satisfactory

out-come compared to actual experiments [11–13, 15]

Incident Outcome of a High- Pressure

Hydrogen Leak

While it is one of the essential materials for production

in a petrochemical process plant, hydrogen is

simultane-ously produced as a byproduct within the production process

In the case of oil- refinery processing, hydrocracking, heavy

oil (H- Oil), and desulfurization units require hydrogen,

and the general naphtha reforming unit produces hydrogen

as a byproduct gas The production reaction of hydrogen

in a naphtha reforming unit is as shown below:

For heavy oil upgrading of crude oil, a massive amount

of high- temperature and high- pressure hydrogen gas is

con-sumed Therefore, many chemical factories have installations

to produce hydrogen gas from raw materials like naphtha

to fulfill their hydrogen requirements autonomously Since

numerous installations and devices within such processing

plants are gathered in a limited space, this is regarded as

a high- risk process If the hydrogen gas leaks and causes

a fire, it may cause severe defects in surrounding facilities

and devices, leading to simultaneous accidents [16–18] In

general, the treatment of hydrogen at a process plant is

carried out under a high pressure of over 160 kgf/cm2 In

a scenario where hydrogen leaks from a pipe to cause an

accident, its speed at the leak point is greater than the

speed of sound, as computed by eqs 20 and 21 [19]

Here, S c is the sonic or supersonic flow in the pipe,

P a is the ambient pressure, P1 is the pressure before the

hole, PCF is the choked pressure, γ is the heat capacity ratio, and Ma is the Mach number In the case study, it

is a choked flow due to high pressure, so that an equiva-lent leak position was used instead of the actual leak position The distance between them in this study is around 0.6 m The inlet conditions must also contain some in-formation on the turbulence energy level and the dissipa-tion of turbulence energy Such informadissipa-tion may be obtained from experiments or by resolving the under- expanded jet structure by numerical calculations A similar problem also exists for the jet’s entrainment of ambient fluid, which is neglected in the method since the near- field effects of entrainment are smaller than further downstream

The minimum ignition energy of hydrogen is 0.018 mJ; considering the minimum ignition energy of typical hy-drocarbon – methane (0.28 mJ), propane (0.25 mJ), and butane (0.26 mJ) – hydrogen’s minimum ignition energy

is about 13.9–15.6 times lower [20] This makes it easily ignitable within only a few seconds after a leakage The radiation on KFX is solved by an enhanced version

of the discrete transfer model [21] The basic concept of this model is that radiation exchange is calculated by integration of radiation absorption and emittance along

a huge number of rays (lines) throughout the calculation domain From the boundary of a box inside the calcula-tion domain, rays are sent at a discrete number of direc-tions from each control volume surface on the enclosing box

CFD Modeling Description

The process to be simulated in this study is residue- hydro- desulfurization (RHDS) or Hyvahl, which consumes

a large amount of high- pressure hydrogen within an oil refinery

This process is carried out to reduce the concentration

of metal, asphaltenes, nitrogen, and sulfur from vacuum residue (VR) from a crude distillation unit (CDU), vacuum gas oil (VGO), or atmosphere residue (AR) from a lower CDU Furthermore, it produces hydrotreated (HDT) resi-due by bringing about a chemical reaction, and it is a high- risk chemical process under the operation conditions

of 643–703 K and 160–170 kgf/cm2 [17]

The general RHDS process within an oil refinery is described in Figure 1 For the simulation scenario, the analytical data on jet fire accidents from process plants

(14)

R t=𝜌k2

𝜇𝜀

(15)

𝜇eff= 𝜇 𝜄 + 𝜇 t

(16)

C D = 0.09, 𝜎 k = 1.0, 𝜎 𝜀 = 1.3, C1= 1.44, C2= 1.92

(17)

CnHm(Naptha) + nH2O → nCO + (2n + m) ∕2 H2

(18)

CH4+ H2O → CO + 3H2

(19)

CO + H2O → CO2+ H2

(20)

S C=P a

P1≤

PCF

P1

(21)

PCF

P1

= Ma

√

2 + (𝛾 − 1)Ma2

𝛾 + 1

has been evaluated [4] As the most frequent accident

type, 13 jet fire accidents has been found at a pipework,

with the major cause observed as a “leaking coupling

or flange” due to a mechanical problem Therefore, the

potential hazard of a hydrogen pipe has been confirmed

and selected for the scenario The leak point is a welded

area of the reducer of a pipe used to transfer hydrogen,

and the inner pressure and temperature of the pipe are

161.8 barg and 333 K, respectively The size of the leak

hole at the welded area of the reducer is 0.00157 m2,

and the leakage rate is 15.0 kg/sec Using the

afore-mentioned leak conditions, the proposed form of the

leak point, leakage direction, and wind condition are

illustrated in Figures 2 and 3 The leakage direction is

in the Z- direction from the lower area of the reducer

(Fig 2) The inputs for scenario simulation are shown

in Table 1

The grid is the most influential factor on the outcome

of simulation Since the effect of damage by a jet fire is

generally smaller than accidents caused by explosion or

toxic release, the grid density of the domain where flame

propagation is expected will be high KFX creates this

grid using a grid generator, and based on vertical and

horizontal sizes of domain to be calculated, it decides on

the number of grids independently [22]

In this study, the grid dimensions applied for the jet

fire analysis were 148, 163, and 52 m on the X- axis,

Y- axis, and Z- axis, respectively Following this, to compute

the outcome of jet fire within this domain, the grid was

created Figure 4 indicates the grids in the X- axis, Y- axis, and Z- axis created for the simulation, and the dense grid

was generated in the fire zone domain around the leak position Using this step with the KFX grid generator, 514,371 grids were created

Figure 1 Illustration of the simulated process and leak point: (A)

isometric view, (B) for top view.

Figure 2 Specific position of (A) the hydrogen leak point and (B) the

features of the reducer.

(A)

(B)

Figure 3 Boundary conditions applied in the simulation.

Grid sensitivity analyses have been carried out to ensure

grid independence in this work and other researches using

KFX [23]

The boundary condition is also one of the important

factors in the simulation [22] In this study, various values

were entered to set the boundary conditions as follows:

The wind direction was 79°, the atmospheric stability was

assumed to be very stable, (F), the wind speed was 2.03 m/

sec at a height of 10 m (Fig 3), and the atmospheric

temperature was 294.8 K

Figure 5 shows grids on each X, Y, Z- axis created by

KFX grid generator White lines in the figure represents

locked grid line at the leak position and black lines

un-locked grid lines Smooth and stretch was performed to

the direction of domain boundary For jet release case,

the smallest control volume is generated at the leak point,

and gradually increased toward the boundaries

In the simulation process, the equations of continuity,

momentum, k - ε, components and energy equations are

solved by SIMPLE algorithm

Simulation Results

The outcomes required to estimate the damage or cause

of a fire accident may be categorized as flame,

temperature, and radiant heat As the outcome of the simulation, this study presents the flame propagation step, governing domain, and temperature and radiation heat due to the jet fire

Jet Flame

As one of the results of the jet fire simulation involving the immediate ignition of leaked high- pressure hydrogen, the flame propagation step is shown in Figure 6 This

Table 1 Grid form generated within the simulation domain of

residue- hydro- desulfurization.

Discharge rate (kg/sec) 15.0

Pasquill category F

Figure 4 Grid form generated within the simulation domain of residue-

hydro- desulfurization.

Figure 5 Grid X, Y, Z- axis created by the Kameleon FireEX grid

generator for simulation.

figure indicates the rapid expansion of flame; there was

a rapid volumetric expansion within 3 sec, and from 3

to 9 sec, the propagated flame showed irregular

volu-metric expansion Furthermore, after 9 sec, the average

volumetric expansion of flame reached the equilibrium

Although there was a slight difference due to wind, after

about 9 sec, most of the jet fire maintained similar form

of flame and volume The proposed flame domain of

the jet fire is illustrated in Figure 7 Based on the propa-gation direction of the flame, each flame showed a

dif-ferent form The maximum height (+Z) of flame among

them was 22 m in Figure 7B, of which complex geom-etries are intentionally removed to clearly show the height only for the purpose of display The maximum size on

the X- axis was 47 m, and the maximum size on the

Y- axis was 30 m (Fig 7C) When a jet fire occurs due

Figure 6 Propagation of the jet fire reflected from the ground in the process plant.

to leakage of high- pressure hydrogen, this flame may

have an extreme thermal effect on facilities and devices

around the leak point, thereby causing secondary

acci-dents This may lead to escalation into a large- scale

accident

Temperature

The temperature distribution of the jet fire computed

through the simulation was categorized by height and is

shown in Figure 8 Here, the height of the region of

inter-est was set from 1 to 5 m in the +Z direction, and this

height was again segmented by 1 m The result in Figure 8

indicates that the region around the leak point had the

highest temperature The maxima of temperature at each

height were 2191.16 K at 1 m, 2197.41 K at 2 m, 2143.47 K

at 3 m, 2087.21 K at 4 m, and 2028.62 K at 5 m,

reveal-ing that all maxima of temperature exceeded 2000 K

The area of temperature distribution at 1 m high was

the widest, showing that the facilities and devices in this

region are most affected by heat In addition, centered

on the melting temperature of iron, 1811 K, the

tem-perature distribution form and size were minutely

seg-mented, as shown in Figures 9 and 10 These two figures

indicate that the domain under temperature distribution

within the melting point range of iron was fairly wide;

the maximum height range was from 4.8 to 10 m in the

+Z direction (Fig 10B), the maximum width range from

the leak point was 17 m in the ±Y direction (Fig 10A),

and the maximum length range was 18 m in the ±X

direction (Fig 10A)

Radiant Flux

To evaluate the value of radiant heat and the jet fire’s effect on it, in the simulation domain, the points of interest – monitoring points (MPs) – were set as shown

in Table 2 Each MP was set based on the leak point

(coordinates: X:56.6, Y:73.6, Z:2.8), human height, and

the positional density of process facilities and devices Each MP was set at 2 m high and 4 m high with a

certain displacement in the X- axis and Y- axis direction

The detailed coordinates and values of MPs are in Table 2

Table 2 shows that there are three MPs at 2 m high, with a distance from MP 7 to MP 10 at 21.7 m There are four MPs at 4 m above from the leak point, and the distance between MP 14 and MP 16 is 18 m For the outcome of the simulation, the radiant heat at each MP was evaluated

When the radiant heat reaches 15.8 kW/m2, an opera-tor within a structure may not function, and this heat may be delivered to other devices and under a radiant heat of 19.9 kW/m2, humans may feel pain within 2 sec and under a radiant heat of 37.5 kW/m2, facilities and devices can be damaged [24, 25] The aforementioned standard of damage was compared with the outcome of this damage, and all MPs in this simulation had radiant heat values over 100 kW/m2 (Fig 11) This value has the worst effect on humans, facilities, and devices, and facilities and devices in this domain may receive severe secondary damage, possibly leading to a critical accident

Figure 7 Footprint and three- dimensional features of propagation of the jet fire in the process plant.

(C)

Comparison with the Phast Results

As the Process Hazard Analysis Software Tool (Phast) by

DNVGL is widely used for jet fire and flare simulations

in the chemical and petrochemical industry, version 7.11

was used for comparison of its heat radiation results with

those of KFX for the same scenario The program uses

a model based on Chamberlain and Johnson’s model for

heat radiation calculation from a jet fire It is important

to validate simulated results with experiments, but

ex-perimental results are usually difficult to obtain; thus, we

chose the newest Phast version because the program has

been extensively validated with real flare and jet fire

ex-periments, such as Chamberlain, Johnson, Bennett, and

Thornton field tests [23] The software was also compared with a H2 jet fire experiment with modification [26] For Phast, input values are as following:

• 900 kg H2 inventory with 60-sec fixed duration release (to match the 15.0 kg/sec discharge rate);

• 2.03 m/sec wind speed with F air stability; and

(default)

From the calculation, some important values were reported

as follows:

• Jet velocity: 1272.5 m/sec;

• Fraction of heat radiated: 0.14; and

• Surface emissive power: 344 kw/m2 For comparison, varying heat radiation results from KFX were averaged for 1 min Phast gives a definitive result for each MP because Phast does not assume effects from surrounding equipment or flame propagation; rather, it uses a definitive cone shape for its jet fire Phast cannot handle obstacles, heat reflection from surrounding

Figure 8 Temperature distribution (top view) at each height of 1, 3,

5 m from the ground around the leak point.

1 m height

3 m height

5 m height

(A)

(B)

(C)

Figure 9 Volume of distribution of 1811 K as a result of jet fire

simulation: (A) isometric view, (B) top view.

geometry, and so on The heat radiation results are shown

in Figure 12 The results of the comparison are shown

in Table 3 and exhibit good agreements within ±50%

except for MP 14 The reason for the difference in the

MP 14 results is the hindrance effect because MP 14 is

located right behind a structure, and therefore receives

less heat radiation This shows that the KFX CFD code

can give better predictions in case of a complex geometry

where accurate predictions are needed

Conclusions

The aim of this study was to apply the CFD modeling

on a hydrogen jet fire during the RHDS process in an oil refinery, where a large amount of high- pressure hy-drogen is consumed, to compute the flame, temperature, and radiant heat As a result of simulation, the volume

of the hydrogen jet fire expanded rapidly from ignition

to 3 sec, expanded irregularly from 3 to 9 sec, and fell under the equilibrium state after 9 sec to maintain a steady form of the flame Thereafter, the maximum height

of the flame was 22 m (+Z), the maximum width was

30 m (±Y), and the maximum length was 47 m (±X)

To evaluate the temperature distribution by flame in more detail, the height under the influence of flame was

seg-mented by 1 m from 1 to 5 m in the +Z direction As

a result, the area of temperature distribution at the domain from the ground to 1 m high was the widest The domino effect related to the temperature of flame was also evalu-ated by analyzing the domain of 1811 T – the melting point of iron To analyze the maximum range of this

domain, the maximum height range of 10 m (+Z), the maximum width range of 17 m (±Y), and the maximum length range of 18 m (±X) were evaluated For evaluation

of radiant heat, the regions affected by the flame at 2 m

Figure 10 Volume size of distribution of 1811 K: (A) size through the top view and (B) size through the side view on the Y- axis.

Table 2 Monitor point (MP) and coordinate within the simulation

domain.

Type

Coordinate

X- axis (m) Y- axis (m) Z- axis (m)

Figure 12 Intensity radii for jet Fire by Phast for the monitoring points (2, 4 m height) From inside – Red: 200 kW/m2 ; Green: 100 kW/m 2 ; Blue:

200 kW/m 2

Figure 11 Monitoring points (MPs) to show the effect of radiant heat: (A) MP location 2 m above the ground, (B) 4 m above the ground.