Numerical analysis of how ventilation conditions impact compartment fire suppression by water mist

Annals of Nuclear Energy 136 (2020) 107021

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Numerical analysis of how ventilation conditions impact compartment fire suppression by water mist Jaiho Lee Advanced Reactor Development Lab., Korea Hydro & Nuclear Power Co., Ltd., Central Research Institute, 70, 1312-gil, Yuseong-daero, Yuseong-gu, Daejeon 34101, Republic of Korea

a r t i c l e

i n f o

Article history: Received 13 October 2018 Received in revised form 8 July 2019 Accepted 31 August 2019

Keywords: Water mist Fire suppression Ventilation FDS CFAST

a b s t r a c t This study presents a numerical analysis of how changing door size and forced ventilation flowrate affect fire suppression using water mist. Sensitivity analysis was conducted to determine the optimal grid size for FDS (Fire Dynamics Simulator), and optimal values of input parameters for CFAST were determined by comparing heat release rate (HRR) curves obtained using CFAST with those using FDS. A newly-defined time average HRR was used to synchronize the time interval of the simulation output data frames for FDS and CFAST. The FDS simulation results showed that increasing the door aspect ratio (AR) for the same opening ratio (OR) is a more beneficial way of lowering the maximum temperature and suppressing the fire early. In addition, lower levels of forced ventilation flowrate delayed the fire suppression more than natural ventilation, whereas forced ventilation with an increased flowrate of 2 m3/s suppressed the fire more quickly than natural ventilation. Ó 2019 Published by Elsevier Ltd.

1. Introduction Nuclear power plants have typically applied the defense-indepth fire protection design concept to safely shut down the reactor in the event of a fire (NRC RG 1.189, 2009). The purpose of the defense-in-depth design is to prevent the occurrence of fires, reduce damage by promptly detecting and suppressing fires, and minimize the impact on the safe shutdown function by preventing the spread of fires that are not easily suppressed. Depending on the fire protection systems’ design and operating considerations, nuclear power plants generally consist of dozens to several hundred fire areas, parts of a building or buildings separated from other areas by fire rated structures to prevent the spread of fire. A fire compartment defined specifically for fire risk analysis in nuclear power plants refers to an enclosed room that is surrounded by walls, but not necessarily by fire barriers, and may have openings such as stairs, doors, and penetration holes. In terms of fire safety, it is possible that a fire compartment maps to a fire area, or that multiple fire compartments fall within a fire area (NUREG/CR-6850, 2005). As a matter of fact, a nuclear power plant is partitioned into lots of small fire compartments. The fire behavior and extinguishing process in a small fire compartment is affected by the size and shape of the openings. Many studies (Blomqvist and Lönnermark., 2001; Lock et al., 2008; Sahu et al., 2017; He et al., 2008; Cai and Chow, 2012; Yuan and

E-mail address: [email protected] https://doi.org/10.1016/j.anucene.2019.107021 0306-4549/Ó 2019 Published by Elsevier Ltd.

Lazzara, 2004) have investigated the effect of various ventilation conditions on the fire generated conditions in a compartment where there is no fire suppression system. Blomqvist and Lönnermark (2001) studied the characteristics of ventilation on indoor fire by applying openings of various sizes and shapes. Lock et al. (2008) studied the room temperature and combustion gas distribution by changing the type and size of the fire ignition source and changing the opening area. Sahu et al. (2017) experimentally investigated the impact of different door aspect ratios of 0.5, 0.25, 0.1, and 0.025 on fire behavior in a methanol pool fire in a cube compartment with 4 cm sides. They observed that the heat release rate (HRR) significantly decreased under the very low ventilation condition. Cai and Chow (2012) conducted a numerical analysis of the effect of different ventilation factors of openings on the HRR and mass flowrate through the opening in a small compartment of 3.6 m
2.4 m
2.4 m. Their simulation results showed that the HRR profile was little affected by changing door height when door width was maintained, except at the lowest ventilation factor of 0.28. Based on these previous studies without a fire suppression system, one of the concerns is how the ventilation conditions in a small compartment in the nuclear power plant might affect fire suppression by a fire protection system. To achieve the second objective of the defense-in-depth fire protection design in a nuclear power plant, fire compartments are equipped with detection and suppression fire protection systems. Consideration is given to the type of equipment or components located in the fire compartment. Water-based fire

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J. Lee / Annals of Nuclear Energy 136 (2020) 107021

extinguishing systems, which are representative of the automatic fire extinguishing systems used in nuclear power plants, have been widely adopted to suppress or extinguish a fire in most fire compartments. Also, gas-type fire extinguishing systems using an extinguishing agent such as a clean agent or carbon dioxide have been specially installed in fire compartments with electrical equipment or diesel fuel storage. However, it is not easy to install and control gas-type fire extinguishing systems, and it can be challenging to meet the performance test requirements, due to leakage of the extinguishing agent through open doors or vents. Water mist has proved to be a good candidate to replace the gas-type fire extinguishing systems (Liu et al., 2003). Under natural ventilation conditions such as an open door, or with forced ventilation such as an exhaust fan running in a compartment, the gas-type fire extinguishing system has often been found to be ineffective at suppressing the fire, while water mist was able to suppress it. To be considered as an alternative to the gas-type fire extinguishing system, it is important that the water mist method demonstrate its ability to effectively suppress a fire under various ventilation conditions. Over the past several decades, many experimental and numerical studies have investigated the efficacy of the water mist system, including for the following factors: ventilation condition (Liu and Kim, 2001; Yu et al., 2008; Zhang et al., 2011; Zhou et al., 2018), fire size (Shrigondekar et al., 2018; Yu et al., 2017), type and location of ignition source in the fire compartment (Liu et al., 2007; Xishi et al., 2001; Liang et al., 2015), and spray characteristics (Ndubizu et al., 2000; Gupta et al., 2013; Wang et al., 2016; Mahmud et al., 2016; Yu et al., 2015). Liu et al. (2001) experimentally investigated the effect of different ventilation conditions on fire suppression using two types of water mist systems, one with a single fluid and higher injection pressure, and the other with twin fluids at lower injection pressure. Their measurements showed that under natural ventilation the fire was suppressed more efficiently by the single fluid water mist system, whereas under forced ventilation it was difficult to extinguish due to the increase in fresh air flowrate. Yu et al. (2008) experimentally investigated the effect of various door sizes on propane fire suppression by water mist in two compartments: an original compartment, and a scaled compartment. With the same door height, as the door width decreased, the HRR value decreased sooner. Their experiments also showed good agreement between the cooling rates in the original and the scaled compartments. However, most studies investigating the effects of changing ventilation conditions on fire suppression by water mist have concentrated on the types of ventilation, such as no ventilation, natural ventilation, and forced ventilation. This does not address how the door size, in terms of opening ratio (OR) and aspect ratio (AR), affects the fire suppression time when using water mist in a small compartment. Numerical studies on water mist fire suppression have been performed using various fire modeling tools. The zone model is a very useful fire modeling tool, and only requires a short simulation time to predict the fire generated conditions in a confined fire com-

partment (Yang et al., 2008). Plumecocq et al. (2017) suggested a new calibration method to determine input parameters such as drop size distributions and initial droplets velocities, which could be used in the fire suppression simulation of water spray systems using a two zone model. However, studies on water mist suppression using a zone model are very rare. Accordingly, to assess the applicability of a zone model for water mist suppression simulation, it can be compared with a computational fluid dynamics (CFD) model. In this study, the effect of changing door size in terms of aspect ratio and opening ratio, and varying forced ventilation flowrate, on fire suppression in a small compartment of 2.7 m
3 m
2.4 m, was numerically investigated using the CFAST 7.1.1 (Consolidated Fire and Smoke Transport) and FDS 6.4.0 (Fire Dynamics Simulator) models. A sensitivity analysis was conducted to determine the optimal grid size for the FDS model. The optimal values of three input parameters for the CFAST model were determined by finding the input values yielding an HRR reduction curve similar to that obtained with the FDS model. A newly-defined time average HRR was used to match the time interval of the simulated output data of FDS and CFAST. The simulated results using CFAST were not affected by ventilation condition changes, but the FDS results were affected: they showed that increasing the door aspect ratio for the same opening ratio was more efficient for water mist fire suppression. Additionally, under forced ventilation the water mist fire suppression was affected by the air flowrate and velocity through the opening. 2. Numerical methodology 2.1. Fire modeling tools Performance-based and risk-informed fire protection technology standards such as NFPA-805 (National Fire Protection Association Inc., 2001) have been employed for the design of fire protection for nuclear power plants. For this reason, interest in fire modeling has increased and the nuclear industry has developed various fire analysis models. In general, the fire models can be categorized into three types: hand calculation, zone model, and field model, which is also known as the computational fluid dynamics (CFD) model. The representative hand calculation tool is Fire Dynamics Tools (FDT) written in Microsoft Excel using fundamental fire dynamics equations and empirical correlations (Iqbal and Salley, 2006). The main zone model is Consolidated Fire and Smoke Transport (CFAST) which numerically computes ordinary differential equations based on the FDT’s basic equations, and predicts the effect of a specific fire based on temperature, gas concentration and smoke layer height in buildings with single or multiple compartments. Although there are various commercial field models available, the main field model used for detailed fire simulation in the nuclear industry is the Fire Dynamics Simulator (FDS) which computes partial differential equations using finite volume methods. In the FDS, several numerical models are used: the large eddy simulation (LES) turbulent model for the gas flow produced by a fire,

Table 1 Validation for fire modeling input parameters in NUREG 1824 (2016). Quantity

Normalized Parameter

Validation Range of NUREG-1824

Present Values

Fire Froude Number

Q_ * = Q_ /[q1CDT1D2(gD)0.5] Q_ * = (Hf + Lf)/Hc, Lf/D = 3.7(Q_ *)2/5-1.02 U = Q_ /(DHo2m_o2)

0.2  9.1

3.25

0.0  1.6

1.09

0.0  0.6

0.12

0.6  8.3

0.9

Flame Length Ratio Equivalence Ratio Compartment Aspect Ratio

m_o2 = 0.23
0.5A0H0.5 0 (Natural), 0.23q1V_ (Mechanical) L/Hc or W/Hc

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J. Lee / Annals of Nuclear Energy 136 (2020) 107021

the eddy dissipation combustion model for fuel combustion, the Eulerian-Lagrangian two phase model for calculating the interaction between the gas phase as a continuum and water droplets as individual particles, and a thermal radiation model based on the MIE scattering theory. Regardless of which model is applied, the analysis results need to be verified and validated by comparison with experiments, as well as sensitivity and uncertainty analyses. Table 1 shows the validation range for various dimensionless numbers which was developed for the verification and validation of fire models for nuclear power plant applications. If the quantities of the dimensionless numbers used for the fire modeling are in the validation range of Table 1, no validation is needed. For dimensionless number values above or below the range, an additional validation would be needed. The dimensionless quantities applied in this study fall within the validation range of the NUREG-1824; however, the verification and validation of fire suppression by water spray is not included in the NUREG-1824 (2016). Although verification and validation for the water spray suppression simulation has not yet been incorporated in the NUREG-1824, many studies have validated simulation results for water spray fire suppression using comparisons with experiments. Most of those studies (Wang et al., 2016; Jenft et al., 2014; Mahmud et al., 2016; Lee, 2019) have shown that the water mist fire suppression time modeled using FDS was in good agreement with experiments. In this study, therefore, separate validation and verification of the water spray fire suppression was not considered. 2.2. Simulation input parameters The effect of the changed door configuration and ventilation condition on the fire suppression time by the water mist system was numerically investigated using the two fire models of CFAST and FDS. Fig. 1 shows the computation domain extended to the outside space. A door opening with an original door height of 1.9 m and width of 1.1 m was opened on the right wall of the fire compartment which had a length of 2.7 m, width of 3 m, and height of 2.4 m. Steel walls and concrete floor were assumed as the boundary surface materials.

As an ignition source an n-Heptane pool with a length of 0.3 m and width of 0.3 m was placed 0.3 m above the floor surface near the door opening to maximize the ventilation condition effect on the fire suppression. The n-Heptane fuel was located on the top surface of the pool. It was assumed that the fire reaches a peak heat release rate (HRR) of 224.45 kW, with growth rate of t2 function assuming that the HRR of the fire grows continususly, proportional to the squre of time. To investigate the fire suppression characteristics in terms of temperature, numerical thermocouples were installed at four different locations of 0.25 m, 0.65 m, 1.05 m, and 1.45 m high directly above the fuel pool surface. A water mist nozzle was placed 1.7 m vertically above from the fuel surface, 0.05 m horizontally further away from the center of the fuel pool. The activation time of the water mist nozzle used was 10 s. The spray characteristics of the water mist can be referenced in the author’s previous work (Lee, 2019). Table 2 the shows simulation input parameters for the water mist nozzle. In a real fire suppression process using the water spray system, the fire is suppressed by cooling and evaporation due to interactions of the surrounding air, combustion gas, and water droplets. Of course, the spray characteristics such as spray injection pressure, flowrate, spray angle, and droplet sizes play an important role in suppressing the fire. In the CFAST model, however, the specific simulation parameters, such as water spray nozzle specification and spray characteristics, are not considered in the calculation. Instead, only three input parameters can be set as input parameters for the simulation: the sprinkler activation temperature (SAT) that is the temperature at or above which a sprinkler activates, sprinkler spray density (SSD) that is the amount of water sprayed by a sprinkler, and sprinkler response time index (RTI) that is a parameter to show the thermal response sensitivity of a sprinker. The sprinkler response time is determined by the RTI (ms)0.5 which is a reaction time index indicating how sensitive the sprinkler is to the heat transmitted by the fire. Section 3.6 of ISO 6182-1 (2004) classifies sprinklers into three types based on different RTI values for the sprinkler conductivity factor (C, [(m/s)0.5]). The values of RTI for common standard sprinklers are between 80 and 350 (ms)0.5. When the reaction time index is less than 50 (ms)0.5, it is classified as a fast response sprinkler. In the CFAST model, the SAT and RTI only affect the spray activation time, whereas the SSD determines the reduction rate of the HRR produced by the water spray. The SSD, used as an input parameter in CFAST, is an empirical coefficient which should be correlated for each test condition using experiments. Madrzykowski and Vettori (1992) determined the average spray density by dividing the volumetric flow rate by the sprayed area on the floor. They placed twenty-four pans adjacent to one another on the floor to measure the amount of water in each pan. The measurement was performed in the absence of any fire. The local spray density varied within the area of floor. For the fuel area on the floor, however, the average spray density was measured consistently at 0.07 mm/s through their experiments.

Table 2 Simulation input parameters for water spray nozzle.

Fig. 1. Computation domain extended to the outside open space (L = 2.7 m, W = 3 m, H = 2.4 m, w0 = 1.1 m, h0 = 1.9 m); the orange flame represents the area where heat release rate per unit volume is less than 200 kW/m3. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Input parameter

Values

Flow Rate on a Nozzle Full Cone type Initial temperature of water K-factor Operating Pressure Median Volumetric Diameter Drop Size Distribution Function

22.15 lpm 76° 20°C 7.1 l/min/atm0.5 9.87 bar 124.6 mm Rosin-Rammler-Lognormal, Gamma_D = 2.22

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J. Lee / Annals of Nuclear Energy 136 (2020) 107021

When the fire is extinguished by the sprinkler, the time constant for the fire suppression is determined as follows Evans (1993).

ingly, details of the input parameters of the FDS model are not repeated here.

s ¼ 2:0
105 ðw00 =Hc Þ1:85

2.3. Test conditions

ð1Þ

In this equation, s [s] is a time constant, w00 [mm/s] is the spray density, and Hc [mm] is the wood crib height. Madrzykowski and Vettori (1992) used a wood crib consisting of a floor area of 610
610 mm2 and a height of 610 mm. Therefore, the time constant in Eq. (1) can be expressed as the following equation when the height of the wood crib is 610 mm.

s ¼ 3:0ðw00 Þ1:85

To investigate the effect of the door size on the fire suppression time, various door aspect ratios and opening ratios were applied by reducing the original door area as follows:

ð2Þ

ð3Þ

In the above equation, t is a given time, tact is time of water spray activation, and t-tact is a time period after water spray activation. Q_ (tact) is the HRR at time of water spray activation, Q_(t-tact) is the HRR after water spray activation at a given time. In reality, there is a strong interaction between the air in the compartment, the gases generated by the fire, and the water spray while the fire is being suppressed by the water spray system. However, Eq. (3) ignores such interactions. In the study by Madrzykowski and Vettori (1992), the time constant was 410 s when the spray density was 0.07 mm/s. Again, the reduction factor of the HRR, Q_ (t-tact)/Q_ (tact), can be expressed as follows.

Q_ ðt  tact Þ=Q_ ðtact Þ ¼ exp½0:0023ðt  tact Þ

ð5Þ

Opening Ratio ¼ A=A0 ¼ wh=w0 h0

ð6Þ

The aspect ratio is expressed by the ratio of the door width (w) to the door height (h); and the opening ratio is expressed by the ratio of the reduced door area (A) to the original door area (A0), the product of the original door width (w0) and the original door height (h0). Table 3 shows the simulation conditions for different aspect ratios and opening ratios of the reduced door. When the door aspect ratio is changed, the original door width is reduced while keeping the original door height, which results in a change in opening ratio. The conditions should be as realistic possible; that is, how open the sliding door is on a compartment wall should be realistically considered. To change the opening ratio, the original door width and height are reduced at the same time with maintaining the aspect ratio of the original door. Test conditions where both the door width and height are reduced would not be realistic. However, an opening ratio of 0.3 or 0.05 could represent the use of natural or dynamic ventilation through a damper opening in the bottom region of the closed door. Test conditions with an opening ratio of 0.8 or 0.6 can represent smaller doors in a small compartment. Additionally, I investigated how the reduction in the rate of the HRR changed when the air flow rate into and out of the compartment was increased. In order to evaluate the effect of forced ventilation on fire suppression, a supply vent with an area of 0.3 m
0.3 m and an exhaust vent with the same size were placed on different walls of the compartment, respectively. It was assumed that the same amount of air inflowing through the supply vent would be blown out through the exhaust vent, e.g., by the operation of a blower to avoid an under-ventilated condition in the compartment.

Considering the time constant in Eq. (2), the HRR after water application can be expressed as:

h
00 1:85 i _ Q_ ðt  tact Þ ¼ Q_ ðtact Þ exp ðt  tact Þ=3:0 w

Aspect Ratio ¼ w=h

ð4Þ

In CFAST, the reduction rate of the HRR is calculated using Eq. (3). Evans (1993) found that the spray density values for all experimental data in previous studies were greater than 0.07 mm/s. The analyst may use a spray density of 0.07 mm/s as the default value of the input parameter when using CFAST. However, the use of this conservative value of 0.07 mm/s should be only limited to a similar water sprinkler fire suppression. The value of spray density as an input parameter in CFAST should be obtained from experiments because it determines the reduction rate of the HRR by water spray in the simulation. In this study, to find the appropriate spray density value, a sensitivity analysis was performed by applying various values of spray density between 133
105 to 26
105. Various HRR curves with different spray density were plotted together with those obtained by FDS. The optimal spray density was determined by finding the curve most similar to the FDS. Unlike CFAST, when using FDS, the fire modeling analyst can set specific input parameters related to water spray properties. The sensitivity of those input parameters on the fire suppression was investigated in the author’s previous work (Lee, 2019). Accord-

3. Results and discussions 3.1. Sensitivity analyses 3.1.1. FDS Sensitivity analysis of the simulation input parameters is necessary to correlate the results of the fire simulation to the experimental results because the values of some simulation input parameters have great impact on the simulation results. To

Table 3 Various aspect ratios and opening ratios for the reduced door configuration. Configuration

Door width (W)

Door height (H)

Aspect Ratio

Opening Ratio

Original door Door reduced by changing aspect ratio with the same door height

1.1 0.88 0.66 0.33 0.06 1 0.85 0.6 0.25

1.9 1.9 1.9 1.9 1.9 1.7 1.47 1.04 0.4

0.58 0.46 0.35 0.17 0.03 0.58 0.58 0.58 0.58

1.0 0.8 0.6 0.3 0.05 0.8 0.6 0.3 0.05

Door reduced by changing the opening ratio with the same aspect ratio

J. Lee / Annals of Nuclear Energy 136 (2020) 107021

simulate fire suppression by water mist, sensitivity and uncertainty analyses are needed for the input parameters, such as spray characteristics, numerical droplets per second, and extinguishing coefficient. In this study, however, no separate experiments were conducted to analyze the sensitivity and uncertainty of the simulation input parameters. For the FDS simulation, only grid sensitivity analysis was performed, changing the total number of cells with six different cubic cells. Other parameters, e.g., the droplets per second and extinguishing coefficient, which have a considerable effect on the water mist fire suppression simulation, were set equal to the input parameters investigated in a previous sensitivity analysis (Lee, 2019) with the same nozzle specification and spray characteristics. In this study, 50,000 droplets per second and an extinguishing coefficient of 16.4 were applied as input parameters. The optimal number of cells used in the fire simulation with the field model should be determined through the grid sensitivity analysis, in terms of the characteristic diameter (D*), as follows (NUREG1824, 2016):


 2=5 D ¼ ½Q_ = q1 Cp T1 g0:5 

ð7Þ

where D* [m] is the characteristic diameter, Q_ [kW] is the HRR, q1 [kg/m3] is the ambient density, Cp [kJ/kg·K] is the ambient specific heat, T1 [K] is the ambient temperature, and g [m/s2] is gravity. Table 4 shows the total number of cubic cells and each cell size used for the grid sensitivity analysis in the FDS model. The more cells that are used, the more reliably the simulated result can be predicted, but that also requires additional computation time. He et al. (2008) studied the effect of computation domain and grid on the simulation of propane fires in a confined compartment of 4 m
4 m
2.5 m without a fire suppression system. They showed that simulations modeled only to compartment walls can reduce the ventilation effect affecting the HRR by about 15%,

Table 4 Cell numbers for grid sensitivity analysis. Total cells

Cell coverage

Cubic cell size(m)

D*/dx

20,880 98,000 584,584 1,336,320 1,989,240 3,625,236

29
30
24 49
50
40 88
91
73 116
120
96 132
137
110 162
167
134

0.1 0.06 0.033 0.025 0.022 0.018

5.5 9.1 16.5 21.8 24.8 30.3

Fig. 2. Temperature profile measured 1.05 m above the center of the fuel surface.

5

in comparison with those modeled to include external space. They suggested that the fire modeling analyst should extend the computation domain more than half the hydraulic diameter of the door for a confined enclosure fire, and the full hydraulic diameter for a ventilation controlled fire. In this study, accordingly, the computation domain was extended more than the hydraulic diameter of the original door to the outside open space. The grid sensitivity analysis was conducted for two simulation results: 1) with the temperature at a location 1.05 m in height above the center of the liquid fuel surface, and 2) with the cooling times when the HRR reaches 100 kW, 50 kW, 10 kW, 5 kW, and 1 kW, respectively. Fig. 2 shows the variation in the temperature distribution curves for different total cell numbers, measured using a numerical thermocouple at a height of 1.05 m above the liquid fuel pool surface. Irrespective of the total number of cells, the temperature curves exhibit three typical regimes of fire suppression due to water spray: fire growth regime, rapid cooling regime, and slow cooling regime. The temperature was observed to increase with the growth of the fire at t = 0  10 s, and reached maximum value at t = 10 s when the water mist was sprayed. The maximum values of temperature varied, ranging from 310 °C to 750 °C depending on the total number of cells; the more cells, the greater the maximum temperature because the measurement resolution increases. In the rapid cooling regime of t = 10–20 s, the temperature rapidly decreases to around 100–150 °C, with different temperature reduction rates for different cell sizes. In the slow cooling regime after t = 20 s, the temperature gradually decreases with a reduction rate similar to when the cubic cell size was less than 2.5 cm. According to the NUREG-1824, without considering water spray suppression, the simulation results for a given fire size could be reasonably predicted to be D*/dx = 5–10. In this study, however, the optimal cell size was 2.5 cm considering the maximum temperature and reduction pattern of the temperature curve, due to the applied water spray. Fig. 3 shows the variation in cooling times for different cell numbers when the HRR reached five specific values of 1 kW, 5 kW, 10 kW, 50 kW, and 100 kW after the water mist application. When the cell number increases with decrese in the cell size, the cooling time for each HRR criteria also decreased. For a given cell size, the cooling time interval range of HRR = 1–150 kW also decreased with a decrease in cell size. When the cell size was less than 2.2 cm, the cooling time became similar for each HRR criteria

Fig. 3. Variation in cooling time with different cell numbers.

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regardless of the cell size. Accordingly, a cubic cell size of 2.2 cm was determined to be the appropriate FDS simulation cell size to investigate the impact of changing door sizes and ventilation conditions on fire suppression time. 3.1.2. CFAST To find the optimal value of the input parameters for the CFAST simulation, a sensitivity analysis for three input parameters, SAT, RTI, and SSD, was performed to compare with the FDS simulation results. In CFAST, the SSD is the most important input parameter for determining the reduction rate of the HRR. Fig. 4 shows how the SSD in the CFAST model affects the HRR reduction rate, in comparison with the HRR profile obtained with the FDS. Since the HRR curve for time in the FDS simulation varies significantly, the time average HRR should be used to effectively find the HRR curve by CFAST, which best matches that by FDS. In Fig. 4, two HRR profiles by FDS are shown in the blue curve with a time interval of 0.01 s, and the red curve with triangle symbols with a 1 s time interval. Each of the triangle symbols represents a time averaged HRR for 100 data with a 0.01 s time interval. The standard deviation for each time averaged HRR is indicated by the error bar. The general formula of time averaged HRR by FDS can be expressed as follows:

_ Q_ jt¼n½s m1 Rm k¼1 Q jt

¼fkDt FDS þ n0:5Dt AVG g½s

Fig. 4. HRR reduction rate for different spray density values.

ð8Þ

Here, Q_ is the time average HRR, Q_ is the heat release rate at each time frame by FDS, n is arithmetic progression with initial term of 0.5DtAVG and common difference of DtAVG, k is the index of a natural number between 1 and m, m is the number of FDS output data falling within an average time interval, DtFDS is the time interval of the FDS data, and DtAVG is the time interval of the averaged data. In this study, the time average HRR with m = 100 and DtAVG = 1 s for DtFDS = 0.01 s was used to find the best match with HRR curves by CFAST with time interval of 0.1 s. The flame displacement phenomenon occurs when a water spray jet with high speed reaches the flame surface, and the HRR may increase rapidly (Lee, 2019). In Fig. 4, the original and time average HRR curves obtained by FDS show an instantaneously rapid increase in the HRR due to flame displacement at the moment the high-speed water spray reaches the flame surface. However, this is not observed in the HRR curves using CFAST, because the CFAST model calculates the HRR reduction by considering only the amount of water sprayed in terms of the SSD, regardless of the instantaneous interaction between the water droplets and ambient gas. When the SSD increases from 26
105(m/ s) to 88
105(m/s), the reduction rate of the HRR is gradually increased. Therefore, it would be better to use the FDS model to simulate complicated fire phenomenon such as the flame displacement by water spray application. Fig. 5 shows the effect of changing RTI and SSD on the reduction rate of the HRR for the different SATs of (a) 65 °C, (b) 75 °C, and (c) 85 °C. Unlike the FDS model, where the water spray injection time can be determined by either of time or temperature, the spray injection time in the CFAST model is determined only by the SAT and RTI of the spray nozzle. If the RTI of the nozzle increases, the application timing of the water spray is delayed regardless of the different SSD conditions for a given SAT. For a given SAT of 65 °C of Fig. 5(a), for example, the water is sprayed at t = 9 s for RTI = 23 (ms)0.5, t = 10 s for RTI = 33(ms)0.5, and t = 11.5 s for RTI = 43(ms)0.5. However, the water is injected at t = 10 s for RTI = 23 (ms)0.5, t = 11.2 s for RTI = 33(ms)0.5, and t = 12.5 s for RTI = 43(ms)0.5 in Fig. 5(b). These differences between Fig. 5(a) and (b) show that the increased SAT for the same RTI increasingly delays the water spray activation time. In Fig. 5(c), the spray injection time for the same RTI is more delayed than Fig. 5(a) and (b) because the SAT increases more. Through Fig. 5(a)–(c), as the SSD increases from 39
105(m/s) to 133
105(m/s), the reduction rate of the HRR increases. In the sensitivity analysis, the best match with the reduction rate of the HRR by FDS is shown for the conditions of SAT = 85 °C, RTI = 33 (ms)0.5, and SSD = 67
105(m/s). The optimal value of

Fig. 5. Sensitivity of changing SSD and RTI on the reduction rate of the HRR for different SAT conditions of (a) 65 °C, (b) 75 °C, and (c) 85 °C.

J. Lee / Annals of Nuclear Energy 136 (2020) 107021

7

Fig. 6. The effect of changing door aspect ratio (AR) and opening ratio (OR) with the same door height on suppression time in terms of (a) cooling time and (b) HRR.

the input parameters through the sensitivity analysis was applied to the CFAST model to investigate the impact of changing door sizes on the fire suppression time.

3.2. The effect of changes in door size door configuration For gas type fire extinguishing systems such as Halon or clean agent or carbon dioxide extinguishing systems, when the area of the opening on the wall increases, more time is required to extinguish the fire because more oxygen flows through the opening. In this subsection, the effect of changes in the size and shape of openings on water mist fire suppression time is described in terms of the aspect ratio and opening ratio of the door opening.

3.2.1. Aspect ratio (AR) change The test conditions for changing the aspect ratio of the door opening are shown in Table 3. To change the aspect ratio of the door, the width of the opening was decreased more than that of the original door while keeping the door height the same as the original door. Fig. 6 shows the effect of changes in the aspect ratio of the door opening on the water mist fire suppression time, using the CFAST and FDS models. The cooling time was numerically measured to be the time at which the HRR reaches the specific values of 1 kW and 0.1 kW, respectively. The cooling time by CFAST is determined by the HRR reduction curve according to the Eq. (4). However, the cooling time and the HRR reduction rate by FDS are dominated by extinguishing coefficient and water flow rate per unit area (Lee, 2019). In the CFAST model, the input parameter values were set to yield the HRR reduction rate most similar to that of the FDS as determined by the sensitivity analysis. As shown in Fig. 6(a), the difference between cooling times for the different HRR criteria of 0.1 kW and 1 kW was about 10 s for FDS and about 15 s for CFAST, regardless of the door aspect ratio. In the CFAST model, the cooling times for HRR = 0.1 kW and 1 kW were not much affected by the change in the aspect ratio of the door. In the FDS model, it was found that the cooling time tended to decrease with increasing door aspect ratio, except for AR = 0.35. This is because the greater the door size is, the more the cooling effect increases because there is increased air flowrate through the door with increased width. At AR = 0.35, however, the width of the fire flame is similar to that of the door, so that the fresh air from the outside cannot easily flow into the compartment through the door, and thus the cooling time slightly increases.

Fig. 6(b) shows the effect of different door aspect ratios on the reduction rate of the HRR after the water is sprayed at t = 10 s. The variation in reduction rate of the HRR for different door aspect ratios can be prominently observed using just the FDS model. The different patterns of the HRR reduction curves results in different cooling times to reach the specific HRR values of 1 kW and 0.1 kW. On the other hand, the HRR curves produced by CFAST are superimposed on one curve, indicating a very similar cooling time without regard for changing door aspect ratio. This means that the reduction curve and cooling time by CFAST are dominated by the simulation input parameters of SAT, SSD, and RTI. Fig. 7 shows the variation in temperature distribution for different door aspect ratios, numerically measured at heights of 0.25 m, 0.65 m, 1.05 m, and 1.45 m vertically from the center (x = 0 m and y = 0 m) of the fuel pool surface. The temperature initially increases with the growth of the fire, reaches the maximum value, then decreases due to water application at t = 10 s. The higher the measurement point in the vertical direction away from the fuel surface, the smaller the maximum temperature. It can also be seen that the fire is perfectly suppressed after about t = 40 s. In Fig. 7(a), however, the temperature increases again around at t = 20 s in spite of the fact that the water mist was sprayed. This is because, while the fire flame height decreases due to interaction with the water mist, it is still intense near the measurement point of 0.25 m. When the door aspect ratio is reduced from AR = 0.58 to AR = 0.03, the maximum temperature decreases at all the measurement points because the reduced opening area prevents fresh air from flowing into the compartment from the outside. For example, the maximum temperature decreases at a rate of (a) 28.7% from 837 °C to 597 °C at 0.25 m, (b) 58.9% from 824 °C to 339 °C at 0.65 m, (c) 66.2% from 715 °C to 242 °C at 1.05 m, and (d) 67.4% from 460 °C to 150 °C at 1.45 m. The further away the measurement point is vertically from the fire, the greater the rate of reduction in maximum temperature from AR = 0.58 to AR = 0.03. The reason the rate decreases less at the lower measurement point is because the flame height is reduced due to the interaction with the water mist, so that most of the combustion occurs near the fuel pool surface. 3.2.2. Influence of changes in the opening ratio of the wall opening on fire suppression time To change the opening ratio of the door, the width and height of the openings were reduced while keeping the aspect ratio of the original door. Fig. 8 shows the effect of changing the opening ratio of the door on the water mist fire suppression in terms of the cool-

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Fig. 7. Variation in temperature distribution with changing door aspect ratio at different locations of (a) 0.25 m, (b) 0.65 m, (c) 1.05 m, and (d) 1.45 m vertically above from the center of the fuel surface (FDS simulation only).

Fig. 8. Effect of changing door opening ratio (OR) on suppression time in terms of (a) cooling time and (b) HRR.

ing time and the HRR. The HRR criteria for the cooling time and the values of the input parameters for the FDS and CFAST models are the same as those shown in Fig. 6, except for the door size. In the CFAST model, the cooling time needed to reach HRR = 1 kW and 0.1 kW was the same as that in Fig. 6, regardless of the door open-

ing ratio. This demonstrates that the reduction rate of the HRR due to water spray application in the CFAST model depends on the SSD alone, without regard for door size. On the other hand, the cooling times in the FDS model were similar for OR = 0.6, 0.8, and 1, but increased at OR = 0.3. This is

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because the fresh air supply from the outside became restricted through the reduced opening area. However, the cooling time for OR = 0.05 was smaller than that for OR = 0.3 in spite of more reduced opening area. This is because most of the combustion gases from the fuel pool surface, which were 0.3 m above the floor, could not be easily discharged to the outside through the door with a height of 0.4 m and width of 0.25 m. In this case the oxygen concentration in the containment is reduced early. This is also reflected in the reduction rate of the HRR shown in Fig. 8(b). The HRR for OR = 0.05 rapidly decreased after the water mist application, resulting in early suppression in comparison with the others. Compared with Fig. 6(a), the cooling time to reach HRR = 1 kW in Fig. 8(a) increased 1.8% with the same conditions as OR = 0.3, and decreased 2.7%, 14.5%, and 8.69% corresponding to the same conditions as OR = 0.8, 0.6, and 0.05. Accordingly, increasing the door aspect ratio for the same opening ratio is more effective for suppressing the fire in terms of cooling time. Fig. 9 shows the temperature distribution measured at the same measurement locations as those in Fig. 7, while changing the door opening ratio and keeping the aspect ratio of the original door. A temperature distribution pattern similar to that in Fig. 7 is also seen in Fig. 9. For example, the further away the measurement position is from the fuel surface, the smaller the temperature maximum value is. When the door opening ratio decreases, the maximum temperature decreases due to the reduction in mass transfer through the reduced door. In Fig. 9, the decrease in rate of maximum temperature from OR = 1 to OR = 0.05 is 37.5% at 0.25 m, 69.9% at 0.65 m, 75.6% at 1.05 m and 70% at 1.45 m. Com-

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pared with Fig. 7, the decrease in rate of maximum temperature from OR = 1 to OR = 0.05 in Fig. 9 becomes larger at each measurement location. Therefore, increasing the aspect ratio for the same opening ratio would be a more beneficial way of lowering the maximum value of the temperature and suppressing the fire early. 3.3. Effect of mechanical ventilation on fire suppression time When outside air is introduced into a compartment through an opening by a forced ventilation system, the effectiveness of the water mist fire suppression system will be influenced by supply air flowrate and exhaust flowrate. Fig. 10 shows the results of FDS simulations performed under natural ventilation, and forced ventilation. Before the water mist is sprayed, at the forced ventilation condition, the fire flame has shifted away from the opening, due to inflowing fresh air. Under natural ventilation conditions, however, the fire flame forms vertically upward due to the weak mass change between the outside space and the compartment. When the water mist is sprayed, the flame becomes shorter due to interactions between the water mist, combustion gas, and fresh air, and keeps a pattern similar to that before water mist application for each ventilation condition. Fig. 11 shows how the change in flowrate produced by the forced ventilation system affects the water mist fire suppression. The FDS simulation results show that the increase in air flowrate through the opening causes the HRR curve to decrease more rapidly. For the same flow rate of 0.23 m3/s, increasing the opening size to 0.4 m
0.4 m causes a more gradual decrease in the HRR

Fig. 9. Variation in temperature distribution after changing the door opening ratio but with the same aspect ratio at different locations of (a) 0.25 m, (b) 0.65 m, (c) 1.05 m, and (d) 1.45 m high vertically from the center of the fuel surface (FDS simulation only).

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Fig. 10. Dynamic behavior of the fire flame before and after water mist application under natural ventilation through an opening of 1.1 m
1.9 m, and forced ventilation with a flowrate of 0.43 m3/s through a supply vent of 0.3 m
0.3 m.

Fig. 11. Effect of different forced ventilation conditions on the HRR reduction rate of (a) the time average HRR curve by FDS and (b) the HRR curve by CFAST.

curve. This means that the water mist fire suppression is affected by air velocity and flowrate through the opening. With a natural ventilation condition, when there is no forced flowrate, the fire is suppressed faster than when lower levels of forced flowrate are applied. At the forced ventilation flow rate of 2 m3/s, however, the fire is suppressed very rapidly because the strong air crossflow helps to suppress it. In the CFAST calculations, the HRR curve is little affected by changing the air flowrate of the

forced ventilation system, since it is unaffected by changes in the door size. That is because, in the CFAST model, the HRR reduction rate produced by water application is not determined by calculating the interactions of the water mist, combustion gas, and air. Rather, it only depends on the SSD. At higher levels of flowrate greater than 2.4 m3/s, the increase in the forced flowrate further increases the fire suppression time because the increased air flowrate may delay the start time of

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the HRR reduction by water mist. This demonstrates the inconvenience of using the CFAST model to simulate fire suppression by water spray although the CFAST model has been conveniently used to predict the fire induced damage of the safe shutdown cables with the computation time in the order of minutes. As described in Section 2.2, in the CFAST simulation, the sprinkler activation time can be adjusted by SAT and RTI. With increase in the flow rate through the door opening for the same SAT condition, the temperature near the sprinkler decreased, and the activation time would be delayed. To remove this delay time for the sprinkler activation, the analyst should reset the sprinkler activation temperature less than 85 °C. However, the HRR reduction rate would not be changed because it is dominated by SSD alone. Accordingly, the fire modeling analyst should set an appropriate SSD separately for each case under different ventilation conditions, when using the CFAST model for water spray fire suppression. 4. Summary In this study, the effects of different ventilation conditions on water mist fire suppression were numerically investigated using FDS and CFAST. The main conclusions are as follows: 1. In the FDS, the HRR calculated using the same simulation input parameter values varied for the different ventilation conditions. However, the HRR reduction rate due to water mist calculated using the CFAST model was not affected by changes in the ventilation conditions. When using the CFAST model to simulate fire suppression by water mist, the main input parameters, such as the SSD, which determines the HRR reduction rate, should be set separately for each ventilation condition. 2. In the sensitivity analysis, the optimal computation grid size for FDS was determined in terms of temperature and cooling time criteria. The optimal values of SAT = 85 °C, RTI = 33 (ms)0.5, and SSD = 67
105(m/s) for CFAST were determined by using the newly-defined time average HRR calculated by FDS. 3. FDS simulation results showed that decreasing the door size decreased the HRR more rapidly. For the same opening ratio, increasing the door aspect ratio was a more efficient way of decreasing the maximum temperature above the fuel surface and suppressing the fire early. In the CFAST simulation, however, the change of door opening size did not affect the cooling time. 4. Under the forced ventilation condition, FDS simulations showed that an increase in flowrate decreased the HRR more rapidly; in addition, the increase in opening area increased the suppression time because of the reduction in air crossflow velocity. The HRR under forced ventilation with lower levels of flowrate decreased more slowly than under natural ventilation without flowrate. When the flowrate increased up to 2 m3/s, the fire was suppressed most rapidly, because the strong air crossflow helped suppress it. In the CFAST simulation, the reduction rate of the time averaged HRR curve was constant regardless of the flowrate change. However, when the flowrate was larger than 2.4 m3/s, the activation time of water spray nozzle was delayed.

Acknowledgements This work was sponsored by the Korea Hydro & Nuclear Power Co., Ltd. (KHNP) of South Korea [Grant Number A15LP07]. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.anucene.2019.107021.

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