Experimental flow characterization and computational model development of aqueous film-forming foam (ARFF) firefighting jets

Menchini, Christopher P.

doi:10.33915/etd.7331

Cited by 2 publications

(5 citation statements)

References 17 publications

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“…The research on fire monitors can be divided into two branches, namely studies on the flow law of the jet working fluid inside fire monitors [4][5][6][7][8][9][10][11][12][13][14] and studies on the jet trajectory, range, and height of fire monitors, that is, the motion trajectory and flow field distribution of fire monitor jets in air [15][16][17][18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, water is used as the working fluid in most of the existing experimental studies, and data on foam jets and the associated trajectory prediction models are lacking. In addition, most of the studies on fire monitors have focused on the flow law of the jet working fluid inside and outside a fire monitor [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22], but there are few studies on the strength parameters of foam jets.…”

Section: Introductionmentioning

confidence: 99%

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Models for Predicting the Jet Trajectory and Intensity Drop Point of Fire Monitors

Hou¹,

Cao²,

Mao³

et al. 2021

Fluid Dynamics &Amp; Materials Processing

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Two models are defined for predicting the trajectory of a foam jet originating from a fire monitor (hydrant) and the related intensity drop point. An experimental framework is also defined and used accordingly to compare real-time data with the predictions of such models. This mixed theoretical-experimental approach is proven to be effective for the determination of otherwise unknown coefficients which take into account several important factors such as the operation pressure, the elevation angle and the nozzle diameter. It is shown that the mean absolute error is smaller than 20%.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Models for Predicting the Jet Trajectory and Intensity Drop Point of Fire Monitors

Hou¹,

Cao²,

Mao³

et al. 2021

Fluid Dynamics &Amp; Materials Processing

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show abstract

“…In addition they observed dry patches in their cavities during simulations which were not observed in the experiments and simulations with higher sub-cavity adaptive mesh grid resolutions of drops under the same impingement conditions in Hillen et al (2012) Chapters 5, 6, and 7 will expand upon the presentations given in Hillen et al (2012 and2013).…”

Section: Section 241: Sub-cavity Film Thicknessmentioning

confidence: 80%

“…Mounted optics configured in back-scatter mode (Menchini, 2013).__________________________ 32 Figure 3.4: Diameter data validation graphs. a) Intensity validation curve.…”

Section: Figuresmentioning

confidence: 99%

“…The current work expands upon the experimental methods developed by Van Hinsberg et al (2010) to radially map the sub-cavity film thickness distribution in the cavity versus time. Subsequent sub-cavity volume histories are then computed through integration along the bottom cavity radius for each time step, as first documented by Hillen et al (2012 and2013). To the author's knowledge no other work has attempted to experimentally measure the sub-cavity film thickness versus both radius and time, or to compute sub-cavity volume histories.…”

Section: Tablesmentioning

confidence: 99%

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Droplet Impact Sub-cavity Histories and PDPA Spray Experiments for Spray Cooling Modeling

Hillen¹

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Spray cooling is a topic of current interest for its ability to uniformly remove high levels of waste heat from densely packed microelectronics. It has demonstrated the ability to achieve very high heat fluxes, up to 500 W/cm 2 with water as the coolant, making it an attractive active thermal management tool. Full Computational Fluid Dynamic (CFD) simulations of spray cooling are infeasible due to the complexity of the spray (drops fluxes of 10 6 drops/cm 2-sec) and heater surface physics requiring impractical resources. Thus a Monte-Carlo (MC) spray cooling simulation model based on empirical data is under development to serve as a cost effective design tool. The initial MC model shows promise, but it lacks additional physics necessary to predict accurate heat fluxes based on nozzle conditions and heated surface geometry. This work reports spray and single drop experiments with the goal of computing the volume beneath a droplet impact cavity (the sub-cavity volume) created by a single impinging droplet on an initial liquid layer. A Phase Doppler Particle Analyzer (PDPA) was utilized to characterize a spray of interest in terms of integrated global Weber, Reynolds, and Froude numbers for varying flow conditions. Results showed that the spray droplet diameters decreased and velocities increased with increasing nozzle gage pressure. A relevant test plan for the single drop experiments has been created from the measured PDPA spray profiles combined with residual spray film thickness measurements from literature resulting in: 140 ≤ We ≤ 1,000, 1,200 ≤ Re ≤ 3,300, and 0.2 ≤ h 0 * ≤ 1.0. Froude numbers were not able to be matched for the current single drop experiments (spray: 32,800 ≤ Fr ≤ 275,000). Liquid film thicknesses under the cavity formed by a single droplet have been measured versus radius and time via a non-contact optical thickness sensor for the selected range of dimensionless numbers (We, Re, and h 0 *). Sub-cavity radius histories have also been analyzed utilizing high-speed imagery techniques to create the cavity thickness traverse profiles. Time dependent sub-cavity volumes have been computed by integrating these subcavity liquid film thicknesses versus radius at various times. It is found that higher We and lower h 0 * result in a more radially uniform sub-cavity surface contour versus time, except for thinner liquid film regions which are observed near the outer bottom cavity radius. The subcavity volume was found to be nearly constant for a majority of the cavity lifetime and increased with We and h 0 *. These results will be incorporated into the MC model to improve its predictive capability in future work. In addition, splashed droplet diameters and velocities have been extracted from PDPA data for a spray impinging normal to a smooth surface. It was found that the splashed droplets had sizes which were similar to the impinging spray droplets, and had velocities that never exceeded 3 m/s. The splashed droplet results have a negligible contribution to cavity formations due to their low Weber number...

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Experimental flow characterization and computational model development of aqueous film-forming foam (ARFF) firefighting jets

Abstract: In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if material had to be removed, a note will indicate the deletion.

Cited by 2 publications

References 17 publications

Models for Predicting the Jet Trajectory and Intensity Drop Point of Fire Monitors

Models for Predicting the Jet Trajectory and Intensity Drop Point of Fire Monitors

Droplet Impact Sub-cavity Histories and PDPA Spray Experiments for Spray Cooling Modeling

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