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Research-scale three-phase jet foam generator design and foaming condition optimization based on Box–Behnken design
Process Safety and Environmental Protection 134 (2020) 217–225
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Research-scale three-phase jet foam generator design and foaming condition optimization based on Box–Behnken design Gang Fu a,b , Juncheng Jiang a,b,c,∗ , Lei Ni a,b a b c
College of Safety Science and Engineering, Nanjing Tech University, 200 Zhongshan North Rd., Nanjing 210009, China Institute of Fire Science and Engineering, Nanjing Tech University, 30 Puzhu South Rd., Nanjing 211800, China Changzhou University, Changzhou 213164, China
a r t i c l e
i n f o
Article history: Received 10 October 2019 Received in revised form 14 December 2019 Accepted 17 December 2019 Keywords: Three-phase foam Fire extinguishing Foam generator Box–Behnken design Optimization
a b s t r a c t Three-phase foam, namely surfactant-particle stabilized foam is a promising material in pool fire extinguishment. However, its effectiveness has not been validated. In this study, a research-scale three-phase jet foam generator, which allowed adjustments of foam slurry composition, nozzle type, air flow rate and screen aperture, was developed. In order to optimize the foaming condition, a three-factor three-level Box–Behnken design (BBD) was adopted. Fly ash (FA) particles were used as the solid phase to generate three-phase foams. As a result, the FA supported foam exhibited better stability over conventional fire-fighting foam, especially when the particle concentration exceeded a threshold value. In addition, the BBD results presented a good agreement between experimental data and fitted models. The optimal foaming condition was determined by numerical optimization. Small-scale fire extinguishing experiments were carried out and three-phase foam manifested better burnback performance compared to conventional fire-fighting foam. The design in this work can be used to study the firefighting efficiency of different three-phase foams and serve as a prototype to develop better generators for both lab research and practical application. © 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
1. Introduction With the development of industry, the demand for oil is increasing consistently (BP, 2019). Oil tanks are getting larger and more centralized than ever (Zhang et al., 2015). As a result, the risk of pool fire is getting higher and fire control is more demanding. Aqueous foams are widely used to extinguish pool fires with the advantage of high efficiency and low cost. During the fire-fighting process, foam is jetted by a nozzle, accumulating and spreading on the fuel surface. A physical barrier of foam, which can insulate the oil from the heat radiation and suppress the oil vaporization, is gradually building up and finally leads to the extinguishment of the fire (Hinnant et al., 2017; Kuprin, 2017; Schaefer et al., 2008). Thus, foam stability is vital in extinguishing. However, foam is thermodynamically unstable and it will decay through drainage, coalescence and coarsening (Farhadi et al., 2016; Qin et al., 2014; Yekeen et al., 2017). Reignition may occur though the flame was put out because of foam’s poor stability.
∗ Corresponding author at: College of Safety Science and Engineering, Nanjing Tech University, 200 Zhongshan North Rd., Nanjing 210009, China. E-mail address: jcjiang [email protected] (J. Jiang).
In order to improve foam stability, surfactant-particle stabilized foam, which is also called three-phase foam, has been widely investigated and used (Lv et al., 2018; Muganda et al., 2011; Shao et al., 2015; Xi and Li, 2016). Wang et al. (2012) and Zhou et al. (2006) innovatively added fly ash (FA) as solid phase into conventional fire-fighting foam to control coal spontaneous combustion and mine dust. It was demonstrated that FA three-phase foam had higher static and dynamic stability over the conventional foam (Qin et al., 2014; Wang et al., 2014). Wang et al. also achieved success with the practical application of three phased foam (Ren et al., 2012; Wang et al., 2013). Sani and Mohanty (2009) incorporated clay nano-particles into foam to control the emission of volatile organic compounds. The results showed an improvement of foam stability and reduction of vapor emission. In view of these, researchers foresaw the prospects of three-phase foam in pool fire extinguishing. Tang (2014) and Tang and Wu (2015) modified hollow glass microspheres with tridecafluorooctyltriethoxysilane (F8261) under different conditions and added it into conventional fire-fighting foam. As a result, foamability was enhanced. The stability and anti-burning properties of three-phase foam on oil were both improved significantly. Fu et al. studied the stability of FA three-phase foam in typical liquidus hydrocarbons (Fu et al., 2019). It showed that foaming capacity and oil resistance of foam can be
https://doi.org/10.1016/j.psep.2019.12.015 0957-5820/© 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
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G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225 Table 1 Experimental parameters and levels for Box–Behnken design. Factors
Symbol
Air flow rate (L/min) Nozzle aperture (mm) Screen aperture (mm)
X1 X2 X3
Level −1
0
1
45 2 0.4
60 4 0.7
75 6 1.0
perform the fire extinguishing experiments. n-Heptane purchased from Sinopharm Chemical Reagent Co. was also used in this work. 3.2. Determination of FA concentration
Fig. 1. Diagram of research-scale three-phase jet foam generator.
improved with a certain amount of FA particles. Nevertheless, all these experiments were not conducted in the presence of a real pool fire. The effectiveness of three-phase foam to put out a fire and the anti-reignition property of foam need to be validated. Such studies are seldom reported because significant quantities of the three-phase foams were needed. As of now, three-phase foams are mostly generated using the Waring Blender method and cannot be jetted. Here the development of a three-phase jet foam generator for lab scale research is reported. To determine the optimal foaming condition of the generator, the so-called response surface methodology (RSM) was adopted, which can optimize multiple parameters in a well-designed experiment with a minimum but required number of experiments (Myers et al., 2009; Nam et al., 2018; Pandey et al., 2018). Small-scale fire extinguishing experiments were also carried out to study the performance of the three-phase foam.
In order to generate three-phase foam, FA particles need to be added to the foam solution. The mass fraction of particles in the foam solution has an influence on foam stability as has been shown previously (Alyousef et al., 2017; Carn et al., 2009; Li et al., 2017). A suitable FA concentration needs to be determined first. To address this, a self-designed foam stability testing apparatus was adopted (Fu et al., 2019). 3.3. Experimental design for foam generator Box–Behnken design (BBD), which is one of the most common designs of RSM, was adopted to optimize the foaming condition of the three-phase jet foam generator. In this work, air flow rate (X1 ), nozzle aperture (X2 ) and screen aperture (X3 ) were selected as variables. A three-factor three-level design consisting of 17 experiments, including five replications at the center point, was applied. Design-Expert software was used for the design of experiments, model establishing and data analysis. Table 1 shows the levels of the factors. According to the experimental data, a second-order model can be developed as follows (Pandey et al., 2018):
2. Design of three-phase jet foam generator Y = ˇ0 + The structure of the research-scale three-phase jet foam generator proposed in this work is shown in Fig. 1. It shares some similarities of previous foam generators (Qin et al., 2014; Ren et al., 2012; Harding et al., 2016). It allows the adjustments of foam slurry composition, nozzle type, air flow rate and screen aperture. The foam generation process is as follows: Firstly, foam solution is prepared in the tank according to the ratio of ingredients. Then accurately weighed solid particles are added. The resultant slurry is fully stirred until a homogeneous condition is reached. After the preparation, the valve is opened and the pump is turned on. The slurry first goes through the Venturi tube and reaches the highest speed at the throat. Then air is introduced by self-suction through the air inlet on the tube and mixed with the slurry. Some bubbles are formed here but most of the slurry flows forward for lacking of enough air. The mixtures are then sprayed through the nozzle onto the screen, where pressurized air creates foams. Finally, uniform and stable three-phase foams are jetted by the air through the outlet for fire extinguishing. 3. Experiments 3.1. Materials Coal fly ash was used in this work to generate three-phase foams, which is the by-product of coal combustion. Fluoroprotein foam (FP) solution of 6%, purchased from Yunlong Fire Equipment Co., Guangzhou, China, was used as foam stock solution. It was diluted with tap water according to the ratio of 6:94. Diesel from China National Offshore Oil Corporation was used as the fuel to
k i=1
ˇi Xi +
k i=1
ˇii Xi2 +
k−1 k
ˇij Xi Xj
(1)
i=1 j=i+1
where Y is the response, ˇ0 is a constant coefficient, ˇi , ˇii and ˇij are the linear regression coefficient, quadric coefficient and crossproduct coefficient, respectively. Xi and Xj are independent factors, k is the number of factors. Analysis of variance (ANOVA) can be used to obtain the regression coefficients, which determine the extent of significance of factors over responses. Furthermore, a secondorder polynomial equation can be used to predict the response (Nam et al., 2018). 3.4. Foaming performance characterization In order to test and optimize the foaming condition of the threephase jet foam generator, foam was produced and characterized. For extinguishing a pool fire, foam jet distance (Y1 ) and application rate (Y2 ) are two crucial parameters. These were selected as responses for the performance characterization of the foam generator. Jet distance is the representation of the kinetic energy of foams. It should be as far as possible for the sake of safety. Foam application rate relates to the speed of foam to cover fuel surface and can be determined by dividing the foam volume by application time. After the foam jetting was steady, the distance can be measured. 3.5. Small-scale fire extinguishing and burnback experiment In accordance with the Chinese national standard (GB153082006, 2006), small-scale fire extinguishing and burnback experi-
G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225
ments were conducted using the three-phase jet foam generator. The experimental steps were as follows: 9 L diesel was poured into a circular oil pan, the diameter of which was 565 mm. Then the fuel was ignited. After 60 s of preburning, foam was applied to extinguish the fire and the time was recorded. The generator was turned off until the oil pan was totally filled by foam. The burnback pot with 1 L diesel was placed at the center of oil pan and was ignited after 60 s to conduct the burnback test. The time from ignition of burnback pot to reignition of the oil in oil pan was called burnback time, which represented the fire-resistance of the foam. The whole process was recorded by a camera. The performance of FA three-phase foam was evaluated by comparing to conventional fire-fighting foam.
4. Results and discussion 4.1. FA concentration determination Time to half-height is defined as the time the foam takes to settle to half of its original height (Harding et al., 2016). It is straightforward to measure and can be used as a stability metric of foam. However, different from conventional fire-fighting foams, the solid phase in three-phase foam can either serve as stabilizing or destabilizing material when it contacts with the fuel. That depends on whether the solid phase is lipophilic. If the particles are oleophilic, the oil will spread on its surface quickly and force the desorption of particles from the gas/liquid interface, accelerating the rupture of bubbles (Fu et al., 2019). Therefore, the influence of oil on the stability of three-phase foam should be taken into account. As a result, time to half-height of foam was measured in the presence of n-heptane in this work. Table 2 shows the influence of FA concentration on foam stability. For general aqueous two-phase foams, the time to half-height was relatively short. Within 40 min, half of the bubbles broke. When 2.4 wt.% FA particles were added, foam stability was improved, but not significantly. The prolongation of time to half-height was only about 10 min. However, when the mass fraction of FA particles reached 4.8 wt.%, there was a sharp increase in time to halfheight. The enhancement of foam stability of three-phase foam was attributed to the existence of particles, including the ones attached to the gas/liquid interface as well as the ones dispersed in the
219
Table 2 Time to half height of foam with different FA concentrations in the presence of n-heptane. FA concentration (wt.%)
Time to half-height (min)
0 2.4 4.8 9.1 13.0 20.0
39.1 ± 0.4 48.1 ± 5.6 90.6 ± 2.8 94.1 ± 3.9 >100 >100
film. Foam drainage is the result of gravity and resistance including viscosity and topological structure (Gao et al., 2016).Forced by gravity and Laplace pressure difference, the water in the film flows to the Plateau border, which leads to film thinning (Fu et al., 2019). The attached particles decrease the pressure difference between film and Plateau border, slowing down the drainage process (Ip et al., 1999). And they also acted as physical barrier to retard coalescence and coarsening to further stabilize bubbles (Farhadi et al., 2016). Moreover, unlike the adsorption of surface-active agents, the attachment of particles to the air-liquid surface is pretty strong, which means the energy required to detach particles is high (Farhadi et al., 2016; Arriaga et al., 2012). Thus, the three-phase foam can maintain its origin structure for a long time. As for the particles dispersed in the film, they may form a layered structure and make the flow passages more tortuous (Fu et al., 2019; Ip et al., 1999). As a result, foam drainage is hindered. However, when the FA concentration was low (2.4 wt.%), there were not enough particles to enforce these two effects. Consequently, the time to half-height was still short. As the FA concentration increased to 4.8 wt.%, more particles were available to stabilize bubbles and most of the foam surface got covered by particles (Fu et al., 2019). Accordingly, the time to half-height was prolonged significantly. With the increasing FA concentration, the time to half-height increased. Nevertheless, the rate of prolongation decreased. This may indicate that the FA concentration reached saturation and the excess particles had little effect in stabilizing foams. Therefore, about 4.8 wt.% FA particles should be added to generate three-phase foams, which is economical and effective. Besides, this concentration would not have significant effect on foamability (Fu et al., 2019). In the remainder the FA concentration was kept at 5 wt.%.
Table 3 BBD with responses of the dependent variables to foaming conditions. Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 a b
Independent variables
Dependent variables Screen aperture (X3 )
Air flow rate (X1 )
Nozzle aperture (X2 )
Coded value
Actual value (L/min)
Coded value
Actual value (mm)
Coded value
0 0 −1 −1 1 0 0 1 0 −1 0 0 −1 0 0 1 1
60 60 45 45 75 60 60 75 60 45 60 60 45 60 60 75 75
−1 0 0 0 0 −1 0 −1 0 1 1 0 −1 1 0 0 1
2 4 4 4 4 2 4 2 4 6 6 4 2 6 4 4 6
−1 0 −1 1 1 1 0 0 0 0 1 0 0 −1 0 −1 0
Experimental data. Predicted value.
Foam jet distance (Y1 ) (m)
Foam application rate (Y2 ) (L/min)
Actual value (mm)
Exp. a
Pre. b
Exp.
Pre.
0.4 0.7 0.4 1.0 1.0 1.0 0.7 0.7 0.7 0.7 1.0 0.7 0.7 0.4 0.7 0.4 0.7
0.66 1.36 1.44 1.28 1.69 0.69 1.45 0.85 1.50 1.78 2.05 1.57 0.54 2.12 1.45 2.17 2.47
0.73 1.46 1.38 1.37 1.75 0.61 1.46 0.88 1.46 1.76 1.98 1.46 0.52 2.20 1.46 2.08 2.48
38.87 133.73 123.34 116.4 123.78 33.38 117.12 34.52 117.76 142.10 158.90 126.95 38.62 143.99 132.62 130.40 151.05
43.07 125.64 121.66 120.50 125.45 31.84 125.64 34.39 125.64 142.24 154.70 125.64 36.10 145.52 125.64 126.34 153.57
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Table 4 ANOVA results for the fitted quadratic models. Source
Foam jet distance
Foam application rate
Sum of squares
F-value
p-value
Sum of squares
F-value
p-value
Model
4.90 Significant
53.56
<0.0001
29,938.86 Significant
68.13
<0.0001
X1 X2 X3 X1 X2 X1 X3 X2 X3 X12 X22 X32
0.57 4.03 0.06 0.04 0.03 0.00 0.05 0.11 0.02
56.15 395.54 5.67 3.54 2.51 0.25 4.51 10.64 2.29
0.0001 <0.0001 0.0488 0.1019 0.1571 0.6356 0.0713 0.0138 0.1738
46.27 25,385.68 2.09 42.58 0.02 104.04 19.97 4280.78 0.00
0.95 519.90 0.04 0.87 0.00 2.13 0.41 87.67 0.00
0.3627 <0.0001 0.8419 0.3815 0.9851 0.1877 0.5428 <0.0001 0.9922
Lack of fit
0.048 Not significant
2.68
0.1825
91.22 Not significant
0.49
0.7105
Table 5 Regression coefficients of polynomial prediction models. Regression coefficients (ˇ)
Intercept, X0 Linear X1 X2 X3 Cross-product X1 X2 X1 X3 X2 X3 Quadratic X12 X22 X32 R2 2 RAdj. 2 RPred.
Foam jet distance
Foam application rate
1.47
125.64
0.27 0.71 −0.09
2.41 56.33 −0.51
0.10 −0.08 −0.03
3.26 0.07 5.10
0.10 −0.16 0.08 0.9856 0.9672
−2.18 −31.89 0.03 0.9887 0.9742
0.8391
0.9389
4.2. Model fitting Box–Behnken design was used to optimize foaming factors. Table 3 summarizes the complete experimental design matrix and responses based on experimental runs. The ANOVA results are shown in Table 4. According to the F-value and p-value, both models are significant (p < 0.05). The lack of fit is the variation of the data around the fitted model (Nam et al., 2018). In this work, nonsignificant lack of fit was obtained, indicating that the two models were properly fitted to the experimental data and could be used for prediction (Samiee-Zafarghandi et al., 2018). Table 5 shows the regression coefficient (ˇ) values. In this study, the values of R2 were 0.9856 and 0.9887, which showed a good fit of the models. In addi2 2 tion, the small difference between RAdj. and RPred. (<0.2) implies reasonable agreement between them. Fig. 2 shows the predicted values versus the experimental data, which also suggests a good agreement. 4.3. Effect of different factors on responses 4.3.1. Effect of foaming parameters on foam jet distance According to Table 4, foam jet distance was significantly (p < 0.05) affected by air flow rate, nozzle aperture and screen aperture. Its second-order polynomial equation in terms of coded factors is as follows after removing all non-significant terms: Y1 = 1.47 + 0.27X1 + 0.71X2 − 0.085X3 − 0.16X22
(2)
Fig. 2. Plots of predicted values by the models versus experimental data (a) foam jet distance; (b) foam application rate.
G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225
221
Fig. 3. Three-dimensional response surface graphs for foam jet distance (a) effect of air flow rate and nozzle aperture; (b) effect of air flow rate and screen aperture; (c) effect of nozzle aperture and screen aperture. Table 6 Expansion ratio of three-phase foam under different foaming conditions. Run
1 6 3 4 16 5 14 11
Independent variables
Expansion ratio
Air flow rate (X1 ) (L/min)
Nozzle aperture (X2 ) (mm)
Screen aperture (X3 ) (mm)
60 60 45 45 75 75 60 60
2 2 4 4 4 4 6 6
0.4 1.0 0.4 1.0 0.4 1.0 0.4 1.0
Fig. 3 shows the influence of different foaming parameters on foam jet distance. It was plotted when two variables changed in their ranges while the other was kept at its midpoint. With increasing air flow rate and nozzle aperture, foam jet distance increases. And the distance reaches a maximum when the two factors are at their high levels (Fig. 3a). A smaller nozzle constrains the flow of foaming slurry and uses more energy, and hence, the total energy for foam jetting reduced. Therefore, as the nozzle aperture increases, more energy is used for foam jetting. That causes the increase of jet distance. Air is another energy source. When the air flow rate increases, more energy is supplied to blow the foam out from the generator. Thus, the jet distance increases with an increase of the air flow rate. However, increasing the screen aperture has a negative effect on the foam jet distance (Fig. 3b and 3 c). This is due to the fact that the foams generated by the small aperture screen are more uniform and delicate. So the air can blow them much farther. When a bigger aperture screen is used, foams contain more water and become heavier. As a result, the jet distance decreases. Table 6 shows the expansion ratio of three-phase foam with different screens. It can be seen that the expansion ratio is always higher when the 0.4 mm aperture screen is used, though the difference is not significant. This can explain the small negative effect of increasing screen aperture on foam jet distance. Among the significant terms, nozzle aperture (X2 ) yields the most influence on foam jet distance. It indicates that in the setting of this foam generator, energy for foam jetting is mostly supplied by the pump and is mainly regulated by nozzle aperture. The air flow rate (X1 ) has a minor impact. Air is used to generate foams as well as to blow them out. However, its energy is small compared to the pump. Accordingly, it is influence on foam jet distance is smaller. Furthermore, the screen aperture (X3 ) is the least significant factor. This can also be concluded from the p-values in Table 4.
4.3.2. Effect of foaming parameters on foam application rate Foam application rate was significantly (p < 0.05) dependent on nozzle aperture (X2 ) and its quadratic effect. The other factors didn’t
7.9 6.8 7.8 7.0 8.4 7.8 7.3 5.3
show any significant influence. This can be seen from Fig. 4 as well. In Fig. 4b, the surface is nearly flat, which indicates there is no effect of air flow rate (X1 ) or screen aperture (X3 ) on foam application rate. Similarly, by removing the non-significant terms, the polynomial equation for foam application rate becomes as follows: Y2 = 125.64 + 56.33X2 − 31.89X22
(3)
With increasing nozzle aperture from 2 to 6 mm, the foam application rate increases from 40 to more than 140 L/min (Fig. 4a and c). Foam application rate is related to the flow rate of foaming slurry and expansion ratio. The former largely depends on nozzle aperture (X2 ). The latter is affected by air flow rate (X1 ) and screen aperture (X3 ). However, within the level range of X1 and X3 , the expansion ratio varies slightly. When compared to the influence caused by change of X2 , it can be neglected. As such, air flow rate and screen aperture show no significant influence on foam application rate. 4.3.3. Optimization of foaming condition In order to optimize the foaming condition for multiple responses simultaneously, the desirability method was used. It makes use of an objective function, D(X), which is a geometric mean of desirability for each response (Myers et al., 2009; Nam et al., 2018): D = (d1 · d2 · · · · · dn )
1/n
=
n 1/n di
(4)
i=1
where di is the desirability of the ith response and n is the number of responses in the experiment. The whole desirability D ranges from zero to one according to the desirability values of each individual response. Numerical optimization of Design-Expert was used to find a point that maximizes the desirability function. In the software, all the factors were set to ‘in range’ and responses were set to ‘maximize’. Fig. 5 shows the optimization result with the highest desirability. Thus, the optimal foaming condition for this three-
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Fig. 4. Three-dimensional response surface graphs for foam application rate (a) effect of air flow rate and nozzle aperture; (b) effect of air flow rate and screen aperture; (c) effect of nozzle aperture and screen aperture.
Fig. 5. Desirability ramp for numerical optimization.
Table 7 Comparison of fire extinguishing performance between two-phase foam and 5 wt.% FA three-phase foam. Foam type
Two-phase foam Three-phase foam
Fire extinguishing time (s) 1
2
3
Average
20 21
21 23
18 22
19.7 ± 1.5 22.0 ± 1.0
phase jet foam generator was found to be an air flow rate (X1 ) of 75 L/min, nozzle aperture (X2 ) of 6 mm and screen aperture (X3 ) of 4 mm. Under this foaming condition, foam jet distance and application rate were predicted to be 2.7 m and 149.0 L/min, respectively. 4.4. Application performances 4.4.1. Fire extinguishing performance Small-scale fire extinguishing experiments were conducted using the three-phase jet foam generator. However, as the oil pan was small, foam application rate was too large under the optimal foaming condition. In other words, the fire would be extinguished within few seconds by both two-phase and three-phase foam and it cannot be determined whether it was caused by experimental deviation. Thus, a small application rate was needed. The foaming condition was adjusted to an air flow rate of 45 L/min, nozzle aperture of 3 mm and screen aperture of 4 mm after initial experiments. Fig. 6 shows the fire extinguishing processes of two-phase foam and three-phase foam, which are quite similar. There was a fire enhancement phenomenon for both foams at the first moment. The flame did not weaken when foam was supplied for 5 s and there was a lot of white smoke. That is the vaporized water from the foams. At 15 s, the flame still blazed though the fuel surface was completely covered by foam. Finally, there was not enough fuel vapor and the flame extinguished. Table 7 summarizes the extinguishing time after three repeated cycles. The fire extinguishing time of three-phase foam, which
contained 5 wt.% FA, was same as two-phase foam. However, the expansion ratio of three-phase foam was lower than two-phase foam, which meant the application rate of three-phase foam was lower. As the application time of the two kinds of foams was close, the extinguishing performance of unit three-phase foam was better than two-phase foam. 4.4.2. Burnback performance Burnback performances of two-phase foam and three-phase foam are shown in Fig. 7. Effective coverage time was introduced to characterize burnback performance, which meant the time from ignition of burnback pot to failure of foam blanketing. At the beginning, the oil pan was filled with foam. Exposed to a flame directly, two-phase foams collapsed quickly because of evaporation and drainage. Within 5 min, there was an obvious decline of foam height. At about 9.8 min, pores appeared on the foam blanket surface, which meant the screening effect of foam failed. By contrast, the stability of three-phase foam was better. Its effective coverage time was up to 24.5 min. However, the diesel in the oil pan did not reignite because the provided heat radiation was insufficient. The prolongation of the effective coverage time of three-phase foam was partly due to the enhancement of stability, including low drainage and coarsening rate which was mentioned above. Moreover, the physical cover of FA also played a major role in protecting foams. As shown in Fig. 7, the color of three-phase foam deepened during the burnback experiment. That is because the upper layer of the bubbles ruptured due to the heat radiation and the black fly ash was exposed to form a solid cover. The dense physical barrier may attenuate the radiation and protect the lower foams. As a result, the effective coverage time was prolonged. However, the expansion ratio of three-phase jet foam was lower than two-phase foam under the same foaming condition, which meant it would cost more foam solution for three-phase jet foam to fill the same oil pan. If this excess foam solution was transferred into two-phase foam, its effective coverage time would undoubtedly be extended. In consideration of this, an index, which is called
G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225
Fig. 6. Fire extinguishing performance comparison (a) two-phase foam; (b) three-phase foam of 5 wt.% FA.
Fig. 7. Burnback performance comparison between two-phase foam and three-phase foam.
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Table 8 Comparison of effective coverage time between two-phase foam and 5 wt.% FA three-phase foam. Foam type
Two-phase foam Three-phase foam
Effective coverage time provided by unit foam supply time (s/s) 1
2
3
Average
21.0 38.7
17.7 32.8
23.3 31.8
20.7 ± 2.8 34.4 ± 3.7
the effective coverage time per unit foam supply time, can be used because the supply rate of foam solution was the same for both foams. Table 8 shows the effective coverage time per unit foam supply time for two kind of foams. 5. Conclusions A new research-scale three-phase jet foam generator was designed and developed. The apparatus allowed adjustments of nozzle type, air flow rate and screen aperture. A Box–Behnken design was adopted to study the influence of these factors on foam jet distance and application rate, so as to optimize the foaming condition. To generate three-phase foam, FA particles were used as solid phase. Compared with the general aqueous two-phase foam, foams stabilized by FA particles manifested much better stability when the particle concentration exceeded 4.8 wt.%. According to the analysis of variance (ANOVA), both quadratic models were significant and well fitted to experimental data. By using numerical optimization, the optimum foaming condition of the foam generator was determined. Moreover, small-scale fire extinguishing and burnback experiments were carried out to study the performance of three-phase foam. Compared to general aqueous two-phase foam, the three-phase foam, which contained 5 wt.% fly ash particles, exhibited much better fire resistance while its extinguishing performance was close. However, the applicability of three-phase foam in real oil tank fires needs to be validated by more researches. But as it has been successfully used for real coal combustion prevention, the performance scalability of three-phase foam in pool fire can be anticipated. Overall, three-phase foam is a promising material for pool fire extinguishing and prevention. Conflict of interest None declared. Acknowledgement The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (NSFC) under Grant No. 51476075 and Postgraduate Research & Practice Innovation Program of Jiangsu Province under Grant KYCX18 1053. References AlYousef, Z., Almobarky, M., Schechter, D., 2017. Enhancing the stability of foam by the use of nanoparticles. Energy Fuels 31 (10), 10620–10627, http://dx.doi.org/ 10.1021/acs.energyfuels.7b01697. Arriaga, L.R., Drenckhan, W., Salonen, A., Rodrigues, J.A., Iguez-Palomares, R., Rio, E., Langevin, D., 2012. On the long-term stability of foams stabilised by mixtures of nano-particles and oppositely charged short chain surfactants. Soft Matter 8 (43), 1185–1197, http://dx.doi.org/10.1039/c2sm26461g. 2019. BP Statistical Review of World Energy, ResReport, BP p.l.c. https://www. bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energyeconomics/statistical-review/bp-stats-review-2019-full-report.pdf. Carn, F., Colin, A., Pitois, O., Vignes-Adler, M., Backov, R., 2009. Foam drainage in the presence of nanoparticle-surfactant mixtures. Langmuir 25 (14), 7847–7856, http://dx.doi.org/10.1021/la900414q. Farhadi, H., Riahi, S., Ayatollahi, S., Ahmadi, H., 2016. Experimental study of nanoparticle-surfactant-stabilized CO2 foam: stability and mobility control.
Chem. Eng. Res. Des. 111, 449–460, http://dx.doi.org/10.1016/j.cherd.2016.05. 024. Fu, G., Jiang, J., Wei, D., Ni, L., Dou, Z., Chen, Q., Cheng, Z., 2019. The study of the stability of aqueous three-phase fire-resistant foam in typical liquidus hydrocarbons. J. Dispers. Sci. Technol. 40 (8), 1075–1084, http://dx.doi.org/10.1080/01932691. 2018.1480385. Gao, H., Zhang, M., Xia, J., Song, B., Wang, Y., 2016. Time and surfactant types dependent model of foams based on the Herschel–Bulkley model. Colloids Surf. A: Physicochem. Eng. Aspects 509, 203–213, http://dx.doi.org/10.1016/j.colsurfa. 2016.09.010. GB15308-2006, 2006. Foam Extinguishing Agent. Harding, B., Zhang, B., Liu, Y., Chen, H., Mannan, M.S., 2016. Improved research-scale foam generator design and performance characterization. J. Loss Prev. Process Ind. 39, 173–180, http://dx.doi.org/10.1016/j.jlp.2015.11.016. Hinnant, K.M., Conroy, M.W., Ananth, R., 2017. Influence of fuel on foam degradation for fluorinated and fluorine-free foams. Colloids Surf. A: Physicochem. Eng. Aspects 522, 1–17, http://dx.doi.org/10.1016/j.colsurfa.2017.02.082. Ip, S.W., Wang, Y., Toguri, J.M., 1999. Aluminum foam stabilization by solid particles. Can. Metall. Quart. 38 (1), 81–92, http://dx.doi.org/10.1016/S00084433(98)00024-X. Kuprin, D.S., 2017. Physicalchemical explanation of fire-fighting efficiency of FHF (fast-hardening foam) based on structured silica particles. J. Sol–Gel Sci. Technol. 81 (1), 36–41, http://dx.doi.org/10.1007/s10971-016-4285-8. Li, S., Qiao, C., Li, Z., Wanambwa, S., 2017. Properties of carbon dioxide foam stabilized by hydrophilic nanoparticles and hexadecyltrimethylammonium bromide. Energy Fuels 31 (2), 1478–1488, http://dx.doi.org/10.1021/acs.energyfuels. 6b03130. Lv, Q., Li, Z., Li, B., Husein, M., Li, S., Shi, D., Liu, W., Bai, H., Sheng, L., 2018. Synergistic mechanism of particulate matter (PM) from coal combustion and saponin from camellia seed pomace in stabilizing CO2 foam. Energy Fuels 32 (3), 3733–3742, http://dx.doi.org/10.1021/acs.energyfuels.8b00245. Muganda, S., Zanin, M., Grano, S.R., 2011. Influence of particle size and contact angle on the flotation of chalcopyrite in a laboratory batch flotation cell. Int. J. Miner. Process. 98 (3–4), 150–162, http://dx.doi.org/10.1016/j.minpro.2010.11.004. Myers, R.H., Anderson-Cook, C.M., Montgomery, D.C., 2009. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. Wiley, Hoboken, NJ. Nam, S.-N., Cho, H., Han, J., Her, N., Yoon, J., 2018. Photocatalytic degradation of acesulfame K: optimization using the Box–Behnken design (BBD). Process Saf. Environ. Protect. 113, 10–21, http://dx.doi.org/10.1016/j.psep.2017.09.002. Pandey, A., Belwal, T., Sekar, K.C., Bhatt, I.D., Rawal, R.S., 2018. Optimization of ultrasonic-assisted extraction (UAE) of phenolics and antioxidant compounds from rhizomes of Rheum moorcroftianum using response surface methodology (RSM). Ind. Crops Prod. 119, 218–225, http://dx.doi.org/10.1016/j.indcrop.2018. 04.019. Qin, B., Lu, Y., Li, Y., Wang, D., 2014. Aqueous three-phase foam supported by fly ash for coal spontaneous combustion prevention and control. Adv. Powder Technol. 25 (5SI), 1527–1533, http://dx.doi.org/10.1016/j.apt.2014.04.010. Ren, X.W., Wang, M.D., Kang, H.Z., Lu, X.X., 2012. A new method for reducing the prevalence of pneumoconiosis among coal miners: foam technology for dust control. J. Occup. Environ. Hyg. 9 (4), D77–D83, http://dx.doi.org/10.1080/ 15459624.2012.667288. Samiee-Zafarghandi, R., Karimi-Sabet, J., Abdoli, M.A., Karbassi, A., 2018. Supercritical water gasification of microalga chlorella PTCC 6010 for hydrogen production: Box–Behnken optimization and evaluating catalytic effect of MnO2/SiO2 and NiO/SiO2. Renew. Energy 126, 189–201, http://dx.doi.org/10.1016/j.renene. 2018.03.043. Sani, A.M., Mohanty, K.K., 2009. Incorporation of clay nano-particles in aqueous foams. Colloids Surf. A: Physicochem. Eng. Aspects 340 (1–3), 174–181, http:// dx.doi.org/10.1016/j.colsurfa.2009.03.026. Schaefer, T.H., Dlugogorski, B.Z., Kennedy, E.M., 2008. Sealability properties of fluorine-free fire-fighting foams (FfreeF). Fire Technol. 44 (3), 297–309, http:// dx.doi.org/10.1007/s10694-007-0030-8. Shao, Z., Wang, D., Wang, Y., Zhong, X., Tang, X., Hu, X., 2015. Controlling coal fires using the three-phase foam and water mist techniques in the Anjialing Open Pit Mine, China. Nat. Haz. 75 (2), 1833–1852, http://dx.doi.org/10.1007/s11069014-1401-3. Tang, B.H., 2014. Fire resistance of three-phase foam with modified hollow glass microspheres. Asian J. Chem. 26 (17), 5453–5456, http://dx.doi.org/10.14233/ ajchem.2014.18130. Tang, B., Wu, Z., 2015. Oleophobic modification of hollow glass microspheres and its effect on the foaming capacity and stability of foam extinguishing agent. J. Chem. 2015, 1–6, http://dx.doi.org/10.1155/2015/923894. Wang, H., Wang, D., Lu, X., Gao, Q., Ren, W., Zhang, Y., 2012. Experimental investigations on the performance of a new design of foaming agent adding device
G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225 used for dust control in underground coal mines. J. Loss Prev. Process Ind. 25 (6), 1075–1084, http://dx.doi.org/10.1016/j.jlp.2012.07.023. Wang, H., Wang, D., Ren, W., Lu, X., Han, F., Zhang, Y., 2013. Application of foam to suppress rock dust in a large cross-section rock roadway driven with roadheader. Adv. Powder Technol. 24 (1), 257–262, http://dx.doi.org/10.1016/j.apt.2012.06. 012. Wang, H., Wang, D., Tang, Y., Qin, B., Xin, H., 2014. Experimental investigation of the performance of a novel foam generator for dust suppression in underground coal mines. Adv. Powder Technol. 25 (3), 1053–1059, http://dx.doi.org/10.1016/ j.apt.2014.02.011. Xi, Z., Li, A., 2016. Characteristics of thermoplastic powder in an aqueous foam carrier for inhibiting spontaneous coal combustion. Process Saf. Environ. Protect. 104, 268–276, http://dx.doi.org/10.1016/j.psep.2016.09.012.
225
Yekeen, N., Idris, A.K., Manan, M.A., Samin, A.M., Risal, A.R., Kun, T.X., 2017. Bulk and bubble-scale experimental studies of influence of nanoparticles on foam stability. Chin. J. Chem. Eng. 25 (3), 347–357, http://dx.doi.org/10.1016/j.cjche. 016.08.012. Zhang, Q., Wang, L., Bi, Y., Xu, D., Zhi, H., Qiu, P., 2015. Experimental investigation of foam spread and extinguishment of the large-scale methanol pool fire. J. Hazard. Mater. 287, 87–92, http://dx.doi.org/10.1016/j.jhazmat.2015.01.017. Zhou, F., Ren, W., Wang, D., Song, T., Li, X., Zhang, Y., 2006. Application of three-phase foam to fight an extraordinarily serious coal mine fire. Int. J. Coal Geol. 67 (1–2), 95–100, http://dx.doi.org/10.1016/j.coal.2005.09.006.
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Research-scale three-phase jet foam generator design and foaming condition optimization based on Box–Behnken design Gang Fu a,b , Juncheng Jiang a,b,c,∗ , Lei Ni a,b a b c
College of Safety Science and Engineering, Nanjing Tech University, 200 Zhongshan North Rd., Nanjing 210009, China Institute of Fire Science and Engineering, Nanjing Tech University, 30 Puzhu South Rd., Nanjing 211800, China Changzhou University, Changzhou 213164, China
a r t i c l e
i n f o
Article history: Received 10 October 2019 Received in revised form 14 December 2019 Accepted 17 December 2019 Keywords: Three-phase foam Fire extinguishing Foam generator Box–Behnken design Optimization
a b s t r a c t Three-phase foam, namely surfactant-particle stabilized foam is a promising material in pool fire extinguishment. However, its effectiveness has not been validated. In this study, a research-scale three-phase jet foam generator, which allowed adjustments of foam slurry composition, nozzle type, air flow rate and screen aperture, was developed. In order to optimize the foaming condition, a three-factor three-level Box–Behnken design (BBD) was adopted. Fly ash (FA) particles were used as the solid phase to generate three-phase foams. As a result, the FA supported foam exhibited better stability over conventional fire-fighting foam, especially when the particle concentration exceeded a threshold value. In addition, the BBD results presented a good agreement between experimental data and fitted models. The optimal foaming condition was determined by numerical optimization. Small-scale fire extinguishing experiments were carried out and three-phase foam manifested better burnback performance compared to conventional fire-fighting foam. The design in this work can be used to study the firefighting efficiency of different three-phase foams and serve as a prototype to develop better generators for both lab research and practical application. © 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
1. Introduction With the development of industry, the demand for oil is increasing consistently (BP, 2019). Oil tanks are getting larger and more centralized than ever (Zhang et al., 2015). As a result, the risk of pool fire is getting higher and fire control is more demanding. Aqueous foams are widely used to extinguish pool fires with the advantage of high efficiency and low cost. During the fire-fighting process, foam is jetted by a nozzle, accumulating and spreading on the fuel surface. A physical barrier of foam, which can insulate the oil from the heat radiation and suppress the oil vaporization, is gradually building up and finally leads to the extinguishment of the fire (Hinnant et al., 2017; Kuprin, 2017; Schaefer et al., 2008). Thus, foam stability is vital in extinguishing. However, foam is thermodynamically unstable and it will decay through drainage, coalescence and coarsening (Farhadi et al., 2016; Qin et al., 2014; Yekeen et al., 2017). Reignition may occur though the flame was put out because of foam’s poor stability.
∗ Corresponding author at: College of Safety Science and Engineering, Nanjing Tech University, 200 Zhongshan North Rd., Nanjing 210009, China. E-mail address: jcjiang [email protected] (J. Jiang).
In order to improve foam stability, surfactant-particle stabilized foam, which is also called three-phase foam, has been widely investigated and used (Lv et al., 2018; Muganda et al., 2011; Shao et al., 2015; Xi and Li, 2016). Wang et al. (2012) and Zhou et al. (2006) innovatively added fly ash (FA) as solid phase into conventional fire-fighting foam to control coal spontaneous combustion and mine dust. It was demonstrated that FA three-phase foam had higher static and dynamic stability over the conventional foam (Qin et al., 2014; Wang et al., 2014). Wang et al. also achieved success with the practical application of three phased foam (Ren et al., 2012; Wang et al., 2013). Sani and Mohanty (2009) incorporated clay nano-particles into foam to control the emission of volatile organic compounds. The results showed an improvement of foam stability and reduction of vapor emission. In view of these, researchers foresaw the prospects of three-phase foam in pool fire extinguishing. Tang (2014) and Tang and Wu (2015) modified hollow glass microspheres with tridecafluorooctyltriethoxysilane (F8261) under different conditions and added it into conventional fire-fighting foam. As a result, foamability was enhanced. The stability and anti-burning properties of three-phase foam on oil were both improved significantly. Fu et al. studied the stability of FA three-phase foam in typical liquidus hydrocarbons (Fu et al., 2019). It showed that foaming capacity and oil resistance of foam can be
https://doi.org/10.1016/j.psep.2019.12.015 0957-5820/© 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
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G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225 Table 1 Experimental parameters and levels for Box–Behnken design. Factors
Symbol
Air flow rate (L/min) Nozzle aperture (mm) Screen aperture (mm)
X1 X2 X3
Level −1
0
1
45 2 0.4
60 4 0.7
75 6 1.0
perform the fire extinguishing experiments. n-Heptane purchased from Sinopharm Chemical Reagent Co. was also used in this work. 3.2. Determination of FA concentration
Fig. 1. Diagram of research-scale three-phase jet foam generator.
improved with a certain amount of FA particles. Nevertheless, all these experiments were not conducted in the presence of a real pool fire. The effectiveness of three-phase foam to put out a fire and the anti-reignition property of foam need to be validated. Such studies are seldom reported because significant quantities of the three-phase foams were needed. As of now, three-phase foams are mostly generated using the Waring Blender method and cannot be jetted. Here the development of a three-phase jet foam generator for lab scale research is reported. To determine the optimal foaming condition of the generator, the so-called response surface methodology (RSM) was adopted, which can optimize multiple parameters in a well-designed experiment with a minimum but required number of experiments (Myers et al., 2009; Nam et al., 2018; Pandey et al., 2018). Small-scale fire extinguishing experiments were also carried out to study the performance of the three-phase foam.
In order to generate three-phase foam, FA particles need to be added to the foam solution. The mass fraction of particles in the foam solution has an influence on foam stability as has been shown previously (Alyousef et al., 2017; Carn et al., 2009; Li et al., 2017). A suitable FA concentration needs to be determined first. To address this, a self-designed foam stability testing apparatus was adopted (Fu et al., 2019). 3.3. Experimental design for foam generator Box–Behnken design (BBD), which is one of the most common designs of RSM, was adopted to optimize the foaming condition of the three-phase jet foam generator. In this work, air flow rate (X1 ), nozzle aperture (X2 ) and screen aperture (X3 ) were selected as variables. A three-factor three-level design consisting of 17 experiments, including five replications at the center point, was applied. Design-Expert software was used for the design of experiments, model establishing and data analysis. Table 1 shows the levels of the factors. According to the experimental data, a second-order model can be developed as follows (Pandey et al., 2018):
2. Design of three-phase jet foam generator Y = ˇ0 + The structure of the research-scale three-phase jet foam generator proposed in this work is shown in Fig. 1. It shares some similarities of previous foam generators (Qin et al., 2014; Ren et al., 2012; Harding et al., 2016). It allows the adjustments of foam slurry composition, nozzle type, air flow rate and screen aperture. The foam generation process is as follows: Firstly, foam solution is prepared in the tank according to the ratio of ingredients. Then accurately weighed solid particles are added. The resultant slurry is fully stirred until a homogeneous condition is reached. After the preparation, the valve is opened and the pump is turned on. The slurry first goes through the Venturi tube and reaches the highest speed at the throat. Then air is introduced by self-suction through the air inlet on the tube and mixed with the slurry. Some bubbles are formed here but most of the slurry flows forward for lacking of enough air. The mixtures are then sprayed through the nozzle onto the screen, where pressurized air creates foams. Finally, uniform and stable three-phase foams are jetted by the air through the outlet for fire extinguishing. 3. Experiments 3.1. Materials Coal fly ash was used in this work to generate three-phase foams, which is the by-product of coal combustion. Fluoroprotein foam (FP) solution of 6%, purchased from Yunlong Fire Equipment Co., Guangzhou, China, was used as foam stock solution. It was diluted with tap water according to the ratio of 6:94. Diesel from China National Offshore Oil Corporation was used as the fuel to
k i=1
ˇi Xi +
k i=1
ˇii Xi2 +
k−1 k
ˇij Xi Xj
(1)
i=1 j=i+1
where Y is the response, ˇ0 is a constant coefficient, ˇi , ˇii and ˇij are the linear regression coefficient, quadric coefficient and crossproduct coefficient, respectively. Xi and Xj are independent factors, k is the number of factors. Analysis of variance (ANOVA) can be used to obtain the regression coefficients, which determine the extent of significance of factors over responses. Furthermore, a secondorder polynomial equation can be used to predict the response (Nam et al., 2018). 3.4. Foaming performance characterization In order to test and optimize the foaming condition of the threephase jet foam generator, foam was produced and characterized. For extinguishing a pool fire, foam jet distance (Y1 ) and application rate (Y2 ) are two crucial parameters. These were selected as responses for the performance characterization of the foam generator. Jet distance is the representation of the kinetic energy of foams. It should be as far as possible for the sake of safety. Foam application rate relates to the speed of foam to cover fuel surface and can be determined by dividing the foam volume by application time. After the foam jetting was steady, the distance can be measured. 3.5. Small-scale fire extinguishing and burnback experiment In accordance with the Chinese national standard (GB153082006, 2006), small-scale fire extinguishing and burnback experi-
G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225
ments were conducted using the three-phase jet foam generator. The experimental steps were as follows: 9 L diesel was poured into a circular oil pan, the diameter of which was 565 mm. Then the fuel was ignited. After 60 s of preburning, foam was applied to extinguish the fire and the time was recorded. The generator was turned off until the oil pan was totally filled by foam. The burnback pot with 1 L diesel was placed at the center of oil pan and was ignited after 60 s to conduct the burnback test. The time from ignition of burnback pot to reignition of the oil in oil pan was called burnback time, which represented the fire-resistance of the foam. The whole process was recorded by a camera. The performance of FA three-phase foam was evaluated by comparing to conventional fire-fighting foam.
4. Results and discussion 4.1. FA concentration determination Time to half-height is defined as the time the foam takes to settle to half of its original height (Harding et al., 2016). It is straightforward to measure and can be used as a stability metric of foam. However, different from conventional fire-fighting foams, the solid phase in three-phase foam can either serve as stabilizing or destabilizing material when it contacts with the fuel. That depends on whether the solid phase is lipophilic. If the particles are oleophilic, the oil will spread on its surface quickly and force the desorption of particles from the gas/liquid interface, accelerating the rupture of bubbles (Fu et al., 2019). Therefore, the influence of oil on the stability of three-phase foam should be taken into account. As a result, time to half-height of foam was measured in the presence of n-heptane in this work. Table 2 shows the influence of FA concentration on foam stability. For general aqueous two-phase foams, the time to half-height was relatively short. Within 40 min, half of the bubbles broke. When 2.4 wt.% FA particles were added, foam stability was improved, but not significantly. The prolongation of time to half-height was only about 10 min. However, when the mass fraction of FA particles reached 4.8 wt.%, there was a sharp increase in time to halfheight. The enhancement of foam stability of three-phase foam was attributed to the existence of particles, including the ones attached to the gas/liquid interface as well as the ones dispersed in the
219
Table 2 Time to half height of foam with different FA concentrations in the presence of n-heptane. FA concentration (wt.%)
Time to half-height (min)
0 2.4 4.8 9.1 13.0 20.0
39.1 ± 0.4 48.1 ± 5.6 90.6 ± 2.8 94.1 ± 3.9 >100 >100
film. Foam drainage is the result of gravity and resistance including viscosity and topological structure (Gao et al., 2016).Forced by gravity and Laplace pressure difference, the water in the film flows to the Plateau border, which leads to film thinning (Fu et al., 2019). The attached particles decrease the pressure difference between film and Plateau border, slowing down the drainage process (Ip et al., 1999). And they also acted as physical barrier to retard coalescence and coarsening to further stabilize bubbles (Farhadi et al., 2016). Moreover, unlike the adsorption of surface-active agents, the attachment of particles to the air-liquid surface is pretty strong, which means the energy required to detach particles is high (Farhadi et al., 2016; Arriaga et al., 2012). Thus, the three-phase foam can maintain its origin structure for a long time. As for the particles dispersed in the film, they may form a layered structure and make the flow passages more tortuous (Fu et al., 2019; Ip et al., 1999). As a result, foam drainage is hindered. However, when the FA concentration was low (2.4 wt.%), there were not enough particles to enforce these two effects. Consequently, the time to half-height was still short. As the FA concentration increased to 4.8 wt.%, more particles were available to stabilize bubbles and most of the foam surface got covered by particles (Fu et al., 2019). Accordingly, the time to half-height was prolonged significantly. With the increasing FA concentration, the time to half-height increased. Nevertheless, the rate of prolongation decreased. This may indicate that the FA concentration reached saturation and the excess particles had little effect in stabilizing foams. Therefore, about 4.8 wt.% FA particles should be added to generate three-phase foams, which is economical and effective. Besides, this concentration would not have significant effect on foamability (Fu et al., 2019). In the remainder the FA concentration was kept at 5 wt.%.
Table 3 BBD with responses of the dependent variables to foaming conditions. Run
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 a b
Independent variables
Dependent variables Screen aperture (X3 )
Air flow rate (X1 )
Nozzle aperture (X2 )
Coded value
Actual value (L/min)
Coded value
Actual value (mm)
Coded value
0 0 −1 −1 1 0 0 1 0 −1 0 0 −1 0 0 1 1
60 60 45 45 75 60 60 75 60 45 60 60 45 60 60 75 75
−1 0 0 0 0 −1 0 −1 0 1 1 0 −1 1 0 0 1
2 4 4 4 4 2 4 2 4 6 6 4 2 6 4 4 6
−1 0 −1 1 1 1 0 0 0 0 1 0 0 −1 0 −1 0
Experimental data. Predicted value.
Foam jet distance (Y1 ) (m)
Foam application rate (Y2 ) (L/min)
Actual value (mm)
Exp. a
Pre. b
Exp.
Pre.
0.4 0.7 0.4 1.0 1.0 1.0 0.7 0.7 0.7 0.7 1.0 0.7 0.7 0.4 0.7 0.4 0.7
0.66 1.36 1.44 1.28 1.69 0.69 1.45 0.85 1.50 1.78 2.05 1.57 0.54 2.12 1.45 2.17 2.47
0.73 1.46 1.38 1.37 1.75 0.61 1.46 0.88 1.46 1.76 1.98 1.46 0.52 2.20 1.46 2.08 2.48
38.87 133.73 123.34 116.4 123.78 33.38 117.12 34.52 117.76 142.10 158.90 126.95 38.62 143.99 132.62 130.40 151.05
43.07 125.64 121.66 120.50 125.45 31.84 125.64 34.39 125.64 142.24 154.70 125.64 36.10 145.52 125.64 126.34 153.57
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Table 4 ANOVA results for the fitted quadratic models. Source
Foam jet distance
Foam application rate
Sum of squares
F-value
p-value
Sum of squares
F-value
p-value
Model
4.90 Significant
53.56
<0.0001
29,938.86 Significant
68.13
<0.0001
X1 X2 X3 X1 X2 X1 X3 X2 X3 X12 X22 X32
0.57 4.03 0.06 0.04 0.03 0.00 0.05 0.11 0.02
56.15 395.54 5.67 3.54 2.51 0.25 4.51 10.64 2.29
0.0001 <0.0001 0.0488 0.1019 0.1571 0.6356 0.0713 0.0138 0.1738
46.27 25,385.68 2.09 42.58 0.02 104.04 19.97 4280.78 0.00
0.95 519.90 0.04 0.87 0.00 2.13 0.41 87.67 0.00
0.3627 <0.0001 0.8419 0.3815 0.9851 0.1877 0.5428 <0.0001 0.9922
Lack of fit
0.048 Not significant
2.68
0.1825
91.22 Not significant
0.49
0.7105
Table 5 Regression coefficients of polynomial prediction models. Regression coefficients (ˇ)
Intercept, X0 Linear X1 X2 X3 Cross-product X1 X2 X1 X3 X2 X3 Quadratic X12 X22 X32 R2 2 RAdj. 2 RPred.
Foam jet distance
Foam application rate
1.47
125.64
0.27 0.71 −0.09
2.41 56.33 −0.51
0.10 −0.08 −0.03
3.26 0.07 5.10
0.10 −0.16 0.08 0.9856 0.9672
−2.18 −31.89 0.03 0.9887 0.9742
0.8391
0.9389
4.2. Model fitting Box–Behnken design was used to optimize foaming factors. Table 3 summarizes the complete experimental design matrix and responses based on experimental runs. The ANOVA results are shown in Table 4. According to the F-value and p-value, both models are significant (p < 0.05). The lack of fit is the variation of the data around the fitted model (Nam et al., 2018). In this work, nonsignificant lack of fit was obtained, indicating that the two models were properly fitted to the experimental data and could be used for prediction (Samiee-Zafarghandi et al., 2018). Table 5 shows the regression coefficient (ˇ) values. In this study, the values of R2 were 0.9856 and 0.9887, which showed a good fit of the models. In addi2 2 tion, the small difference between RAdj. and RPred. (<0.2) implies reasonable agreement between them. Fig. 2 shows the predicted values versus the experimental data, which also suggests a good agreement. 4.3. Effect of different factors on responses 4.3.1. Effect of foaming parameters on foam jet distance According to Table 4, foam jet distance was significantly (p < 0.05) affected by air flow rate, nozzle aperture and screen aperture. Its second-order polynomial equation in terms of coded factors is as follows after removing all non-significant terms: Y1 = 1.47 + 0.27X1 + 0.71X2 − 0.085X3 − 0.16X22
(2)
Fig. 2. Plots of predicted values by the models versus experimental data (a) foam jet distance; (b) foam application rate.
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Fig. 3. Three-dimensional response surface graphs for foam jet distance (a) effect of air flow rate and nozzle aperture; (b) effect of air flow rate and screen aperture; (c) effect of nozzle aperture and screen aperture. Table 6 Expansion ratio of three-phase foam under different foaming conditions. Run
1 6 3 4 16 5 14 11
Independent variables
Expansion ratio
Air flow rate (X1 ) (L/min)
Nozzle aperture (X2 ) (mm)
Screen aperture (X3 ) (mm)
60 60 45 45 75 75 60 60
2 2 4 4 4 4 6 6
0.4 1.0 0.4 1.0 0.4 1.0 0.4 1.0
Fig. 3 shows the influence of different foaming parameters on foam jet distance. It was plotted when two variables changed in their ranges while the other was kept at its midpoint. With increasing air flow rate and nozzle aperture, foam jet distance increases. And the distance reaches a maximum when the two factors are at their high levels (Fig. 3a). A smaller nozzle constrains the flow of foaming slurry and uses more energy, and hence, the total energy for foam jetting reduced. Therefore, as the nozzle aperture increases, more energy is used for foam jetting. That causes the increase of jet distance. Air is another energy source. When the air flow rate increases, more energy is supplied to blow the foam out from the generator. Thus, the jet distance increases with an increase of the air flow rate. However, increasing the screen aperture has a negative effect on the foam jet distance (Fig. 3b and 3 c). This is due to the fact that the foams generated by the small aperture screen are more uniform and delicate. So the air can blow them much farther. When a bigger aperture screen is used, foams contain more water and become heavier. As a result, the jet distance decreases. Table 6 shows the expansion ratio of three-phase foam with different screens. It can be seen that the expansion ratio is always higher when the 0.4 mm aperture screen is used, though the difference is not significant. This can explain the small negative effect of increasing screen aperture on foam jet distance. Among the significant terms, nozzle aperture (X2 ) yields the most influence on foam jet distance. It indicates that in the setting of this foam generator, energy for foam jetting is mostly supplied by the pump and is mainly regulated by nozzle aperture. The air flow rate (X1 ) has a minor impact. Air is used to generate foams as well as to blow them out. However, its energy is small compared to the pump. Accordingly, it is influence on foam jet distance is smaller. Furthermore, the screen aperture (X3 ) is the least significant factor. This can also be concluded from the p-values in Table 4.
4.3.2. Effect of foaming parameters on foam application rate Foam application rate was significantly (p < 0.05) dependent on nozzle aperture (X2 ) and its quadratic effect. The other factors didn’t
7.9 6.8 7.8 7.0 8.4 7.8 7.3 5.3
show any significant influence. This can be seen from Fig. 4 as well. In Fig. 4b, the surface is nearly flat, which indicates there is no effect of air flow rate (X1 ) or screen aperture (X3 ) on foam application rate. Similarly, by removing the non-significant terms, the polynomial equation for foam application rate becomes as follows: Y2 = 125.64 + 56.33X2 − 31.89X22
(3)
With increasing nozzle aperture from 2 to 6 mm, the foam application rate increases from 40 to more than 140 L/min (Fig. 4a and c). Foam application rate is related to the flow rate of foaming slurry and expansion ratio. The former largely depends on nozzle aperture (X2 ). The latter is affected by air flow rate (X1 ) and screen aperture (X3 ). However, within the level range of X1 and X3 , the expansion ratio varies slightly. When compared to the influence caused by change of X2 , it can be neglected. As such, air flow rate and screen aperture show no significant influence on foam application rate. 4.3.3. Optimization of foaming condition In order to optimize the foaming condition for multiple responses simultaneously, the desirability method was used. It makes use of an objective function, D(X), which is a geometric mean of desirability for each response (Myers et al., 2009; Nam et al., 2018): D = (d1 · d2 · · · · · dn )
1/n
=
n 1/n di
(4)
i=1
where di is the desirability of the ith response and n is the number of responses in the experiment. The whole desirability D ranges from zero to one according to the desirability values of each individual response. Numerical optimization of Design-Expert was used to find a point that maximizes the desirability function. In the software, all the factors were set to ‘in range’ and responses were set to ‘maximize’. Fig. 5 shows the optimization result with the highest desirability. Thus, the optimal foaming condition for this three-
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Fig. 4. Three-dimensional response surface graphs for foam application rate (a) effect of air flow rate and nozzle aperture; (b) effect of air flow rate and screen aperture; (c) effect of nozzle aperture and screen aperture.
Fig. 5. Desirability ramp for numerical optimization.
Table 7 Comparison of fire extinguishing performance between two-phase foam and 5 wt.% FA three-phase foam. Foam type
Two-phase foam Three-phase foam
Fire extinguishing time (s) 1
2
3
Average
20 21
21 23
18 22
19.7 ± 1.5 22.0 ± 1.0
phase jet foam generator was found to be an air flow rate (X1 ) of 75 L/min, nozzle aperture (X2 ) of 6 mm and screen aperture (X3 ) of 4 mm. Under this foaming condition, foam jet distance and application rate were predicted to be 2.7 m and 149.0 L/min, respectively. 4.4. Application performances 4.4.1. Fire extinguishing performance Small-scale fire extinguishing experiments were conducted using the three-phase jet foam generator. However, as the oil pan was small, foam application rate was too large under the optimal foaming condition. In other words, the fire would be extinguished within few seconds by both two-phase and three-phase foam and it cannot be determined whether it was caused by experimental deviation. Thus, a small application rate was needed. The foaming condition was adjusted to an air flow rate of 45 L/min, nozzle aperture of 3 mm and screen aperture of 4 mm after initial experiments. Fig. 6 shows the fire extinguishing processes of two-phase foam and three-phase foam, which are quite similar. There was a fire enhancement phenomenon for both foams at the first moment. The flame did not weaken when foam was supplied for 5 s and there was a lot of white smoke. That is the vaporized water from the foams. At 15 s, the flame still blazed though the fuel surface was completely covered by foam. Finally, there was not enough fuel vapor and the flame extinguished. Table 7 summarizes the extinguishing time after three repeated cycles. The fire extinguishing time of three-phase foam, which
contained 5 wt.% FA, was same as two-phase foam. However, the expansion ratio of three-phase foam was lower than two-phase foam, which meant the application rate of three-phase foam was lower. As the application time of the two kinds of foams was close, the extinguishing performance of unit three-phase foam was better than two-phase foam. 4.4.2. Burnback performance Burnback performances of two-phase foam and three-phase foam are shown in Fig. 7. Effective coverage time was introduced to characterize burnback performance, which meant the time from ignition of burnback pot to failure of foam blanketing. At the beginning, the oil pan was filled with foam. Exposed to a flame directly, two-phase foams collapsed quickly because of evaporation and drainage. Within 5 min, there was an obvious decline of foam height. At about 9.8 min, pores appeared on the foam blanket surface, which meant the screening effect of foam failed. By contrast, the stability of three-phase foam was better. Its effective coverage time was up to 24.5 min. However, the diesel in the oil pan did not reignite because the provided heat radiation was insufficient. The prolongation of the effective coverage time of three-phase foam was partly due to the enhancement of stability, including low drainage and coarsening rate which was mentioned above. Moreover, the physical cover of FA also played a major role in protecting foams. As shown in Fig. 7, the color of three-phase foam deepened during the burnback experiment. That is because the upper layer of the bubbles ruptured due to the heat radiation and the black fly ash was exposed to form a solid cover. The dense physical barrier may attenuate the radiation and protect the lower foams. As a result, the effective coverage time was prolonged. However, the expansion ratio of three-phase jet foam was lower than two-phase foam under the same foaming condition, which meant it would cost more foam solution for three-phase jet foam to fill the same oil pan. If this excess foam solution was transferred into two-phase foam, its effective coverage time would undoubtedly be extended. In consideration of this, an index, which is called
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Fig. 6. Fire extinguishing performance comparison (a) two-phase foam; (b) three-phase foam of 5 wt.% FA.
Fig. 7. Burnback performance comparison between two-phase foam and three-phase foam.
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Table 8 Comparison of effective coverage time between two-phase foam and 5 wt.% FA three-phase foam. Foam type
Two-phase foam Three-phase foam
Effective coverage time provided by unit foam supply time (s/s) 1
2
3
Average
21.0 38.7
17.7 32.8
23.3 31.8
20.7 ± 2.8 34.4 ± 3.7
the effective coverage time per unit foam supply time, can be used because the supply rate of foam solution was the same for both foams. Table 8 shows the effective coverage time per unit foam supply time for two kind of foams. 5. Conclusions A new research-scale three-phase jet foam generator was designed and developed. The apparatus allowed adjustments of nozzle type, air flow rate and screen aperture. A Box–Behnken design was adopted to study the influence of these factors on foam jet distance and application rate, so as to optimize the foaming condition. To generate three-phase foam, FA particles were used as solid phase. Compared with the general aqueous two-phase foam, foams stabilized by FA particles manifested much better stability when the particle concentration exceeded 4.8 wt.%. According to the analysis of variance (ANOVA), both quadratic models were significant and well fitted to experimental data. By using numerical optimization, the optimum foaming condition of the foam generator was determined. Moreover, small-scale fire extinguishing and burnback experiments were carried out to study the performance of three-phase foam. Compared to general aqueous two-phase foam, the three-phase foam, which contained 5 wt.% fly ash particles, exhibited much better fire resistance while its extinguishing performance was close. However, the applicability of three-phase foam in real oil tank fires needs to be validated by more researches. But as it has been successfully used for real coal combustion prevention, the performance scalability of three-phase foam in pool fire can be anticipated. Overall, three-phase foam is a promising material for pool fire extinguishing and prevention. Conflict of interest None declared. Acknowledgement The authors gratefully acknowledge the financial support from the National Natural Science Foundation of China (NSFC) under Grant No. 51476075 and Postgraduate Research & Practice Innovation Program of Jiangsu Province under Grant KYCX18 1053. References AlYousef, Z., Almobarky, M., Schechter, D., 2017. Enhancing the stability of foam by the use of nanoparticles. Energy Fuels 31 (10), 10620–10627, http://dx.doi.org/ 10.1021/acs.energyfuels.7b01697. Arriaga, L.R., Drenckhan, W., Salonen, A., Rodrigues, J.A., Iguez-Palomares, R., Rio, E., Langevin, D., 2012. On the long-term stability of foams stabilised by mixtures of nano-particles and oppositely charged short chain surfactants. Soft Matter 8 (43), 1185–1197, http://dx.doi.org/10.1039/c2sm26461g. 2019. BP Statistical Review of World Energy, ResReport, BP p.l.c. https://www. bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energyeconomics/statistical-review/bp-stats-review-2019-full-report.pdf. Carn, F., Colin, A., Pitois, O., Vignes-Adler, M., Backov, R., 2009. Foam drainage in the presence of nanoparticle-surfactant mixtures. Langmuir 25 (14), 7847–7856, http://dx.doi.org/10.1021/la900414q. Farhadi, H., Riahi, S., Ayatollahi, S., Ahmadi, H., 2016. Experimental study of nanoparticle-surfactant-stabilized CO2 foam: stability and mobility control.
Chem. Eng. Res. Des. 111, 449–460, http://dx.doi.org/10.1016/j.cherd.2016.05. 024. Fu, G., Jiang, J., Wei, D., Ni, L., Dou, Z., Chen, Q., Cheng, Z., 2019. The study of the stability of aqueous three-phase fire-resistant foam in typical liquidus hydrocarbons. J. Dispers. Sci. Technol. 40 (8), 1075–1084, http://dx.doi.org/10.1080/01932691. 2018.1480385. Gao, H., Zhang, M., Xia, J., Song, B., Wang, Y., 2016. Time and surfactant types dependent model of foams based on the Herschel–Bulkley model. Colloids Surf. A: Physicochem. Eng. Aspects 509, 203–213, http://dx.doi.org/10.1016/j.colsurfa. 2016.09.010. GB15308-2006, 2006. Foam Extinguishing Agent. Harding, B., Zhang, B., Liu, Y., Chen, H., Mannan, M.S., 2016. Improved research-scale foam generator design and performance characterization. J. Loss Prev. Process Ind. 39, 173–180, http://dx.doi.org/10.1016/j.jlp.2015.11.016. Hinnant, K.M., Conroy, M.W., Ananth, R., 2017. Influence of fuel on foam degradation for fluorinated and fluorine-free foams. Colloids Surf. A: Physicochem. Eng. Aspects 522, 1–17, http://dx.doi.org/10.1016/j.colsurfa.2017.02.082. Ip, S.W., Wang, Y., Toguri, J.M., 1999. Aluminum foam stabilization by solid particles. Can. Metall. Quart. 38 (1), 81–92, http://dx.doi.org/10.1016/S00084433(98)00024-X. Kuprin, D.S., 2017. Physicalchemical explanation of fire-fighting efficiency of FHF (fast-hardening foam) based on structured silica particles. J. Sol–Gel Sci. Technol. 81 (1), 36–41, http://dx.doi.org/10.1007/s10971-016-4285-8. Li, S., Qiao, C., Li, Z., Wanambwa, S., 2017. Properties of carbon dioxide foam stabilized by hydrophilic nanoparticles and hexadecyltrimethylammonium bromide. Energy Fuels 31 (2), 1478–1488, http://dx.doi.org/10.1021/acs.energyfuels. 6b03130. Lv, Q., Li, Z., Li, B., Husein, M., Li, S., Shi, D., Liu, W., Bai, H., Sheng, L., 2018. Synergistic mechanism of particulate matter (PM) from coal combustion and saponin from camellia seed pomace in stabilizing CO2 foam. Energy Fuels 32 (3), 3733–3742, http://dx.doi.org/10.1021/acs.energyfuels.8b00245. Muganda, S., Zanin, M., Grano, S.R., 2011. Influence of particle size and contact angle on the flotation of chalcopyrite in a laboratory batch flotation cell. Int. J. Miner. Process. 98 (3–4), 150–162, http://dx.doi.org/10.1016/j.minpro.2010.11.004. Myers, R.H., Anderson-Cook, C.M., Montgomery, D.C., 2009. Response Surface Methodology: Process and Product Optimization Using Designed Experiments. Wiley, Hoboken, NJ. Nam, S.-N., Cho, H., Han, J., Her, N., Yoon, J., 2018. Photocatalytic degradation of acesulfame K: optimization using the Box–Behnken design (BBD). Process Saf. Environ. Protect. 113, 10–21, http://dx.doi.org/10.1016/j.psep.2017.09.002. Pandey, A., Belwal, T., Sekar, K.C., Bhatt, I.D., Rawal, R.S., 2018. Optimization of ultrasonic-assisted extraction (UAE) of phenolics and antioxidant compounds from rhizomes of Rheum moorcroftianum using response surface methodology (RSM). Ind. Crops Prod. 119, 218–225, http://dx.doi.org/10.1016/j.indcrop.2018. 04.019. Qin, B., Lu, Y., Li, Y., Wang, D., 2014. Aqueous three-phase foam supported by fly ash for coal spontaneous combustion prevention and control. Adv. Powder Technol. 25 (5SI), 1527–1533, http://dx.doi.org/10.1016/j.apt.2014.04.010. Ren, X.W., Wang, M.D., Kang, H.Z., Lu, X.X., 2012. A new method for reducing the prevalence of pneumoconiosis among coal miners: foam technology for dust control. J. Occup. Environ. Hyg. 9 (4), D77–D83, http://dx.doi.org/10.1080/ 15459624.2012.667288. Samiee-Zafarghandi, R., Karimi-Sabet, J., Abdoli, M.A., Karbassi, A., 2018. Supercritical water gasification of microalga chlorella PTCC 6010 for hydrogen production: Box–Behnken optimization and evaluating catalytic effect of MnO2/SiO2 and NiO/SiO2. Renew. Energy 126, 189–201, http://dx.doi.org/10.1016/j.renene. 2018.03.043. Sani, A.M., Mohanty, K.K., 2009. Incorporation of clay nano-particles in aqueous foams. Colloids Surf. A: Physicochem. Eng. Aspects 340 (1–3), 174–181, http:// dx.doi.org/10.1016/j.colsurfa.2009.03.026. Schaefer, T.H., Dlugogorski, B.Z., Kennedy, E.M., 2008. Sealability properties of fluorine-free fire-fighting foams (FfreeF). Fire Technol. 44 (3), 297–309, http:// dx.doi.org/10.1007/s10694-007-0030-8. Shao, Z., Wang, D., Wang, Y., Zhong, X., Tang, X., Hu, X., 2015. Controlling coal fires using the three-phase foam and water mist techniques in the Anjialing Open Pit Mine, China. Nat. Haz. 75 (2), 1833–1852, http://dx.doi.org/10.1007/s11069014-1401-3. Tang, B.H., 2014. Fire resistance of three-phase foam with modified hollow glass microspheres. Asian J. Chem. 26 (17), 5453–5456, http://dx.doi.org/10.14233/ ajchem.2014.18130. Tang, B., Wu, Z., 2015. Oleophobic modification of hollow glass microspheres and its effect on the foaming capacity and stability of foam extinguishing agent. J. Chem. 2015, 1–6, http://dx.doi.org/10.1155/2015/923894. Wang, H., Wang, D., Lu, X., Gao, Q., Ren, W., Zhang, Y., 2012. Experimental investigations on the performance of a new design of foaming agent adding device
G. Fu et al. / Process Safety and Environmental Protection 134 (2020) 217–225 used for dust control in underground coal mines. J. Loss Prev. Process Ind. 25 (6), 1075–1084, http://dx.doi.org/10.1016/j.jlp.2012.07.023. Wang, H., Wang, D., Ren, W., Lu, X., Han, F., Zhang, Y., 2013. Application of foam to suppress rock dust in a large cross-section rock roadway driven with roadheader. Adv. Powder Technol. 24 (1), 257–262, http://dx.doi.org/10.1016/j.apt.2012.06. 012. Wang, H., Wang, D., Tang, Y., Qin, B., Xin, H., 2014. Experimental investigation of the performance of a novel foam generator for dust suppression in underground coal mines. Adv. Powder Technol. 25 (3), 1053–1059, http://dx.doi.org/10.1016/ j.apt.2014.02.011. Xi, Z., Li, A., 2016. Characteristics of thermoplastic powder in an aqueous foam carrier for inhibiting spontaneous coal combustion. Process Saf. Environ. Protect. 104, 268–276, http://dx.doi.org/10.1016/j.psep.2016.09.012.
225
Yekeen, N., Idris, A.K., Manan, M.A., Samin, A.M., Risal, A.R., Kun, T.X., 2017. Bulk and bubble-scale experimental studies of influence of nanoparticles on foam stability. Chin. J. Chem. Eng. 25 (3), 347–357, http://dx.doi.org/10.1016/j.cjche. 016.08.012. Zhang, Q., Wang, L., Bi, Y., Xu, D., Zhi, H., Qiu, P., 2015. Experimental investigation of foam spread and extinguishment of the large-scale methanol pool fire. J. Hazard. Mater. 287, 87–92, http://dx.doi.org/10.1016/j.jhazmat.2015.01.017. Zhou, F., Ren, W., Wang, D., Song, T., Li, X., Zhang, Y., 2006. Application of three-phase foam to fight an extraordinarily serious coal mine fire. Int. J. Coal Geol. 67 (1–2), 95–100, http://dx.doi.org/10.1016/j.coal.2005.09.006.