2012
DOI: 10.1021/ie3003864
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Modeling of Water-Spray Application in the Forced Dispersion of LNG Vapor Cloud Using a Combined Eulerian–Lagrangian Approach

Abstract: The safety and security of liquefied natural gas (LNG) facilities has prompted the need for continued study of LNG mitigation systems. Water-spray curtains are widely recognized as an effective measure for dispersing LNG vapor clouds ( Martinsen Martinsen Hydrocarbon Process.197756260). Currently, there are no engineering guidelines available for water-curtain applications in the LNG industry because of a lack of understanding of the complex interactions between the LNG vapor cloud and water droplets. This wo… Show more

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Cited by 11 publications
(12 citation statements)
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“…13 A Eulerian−Lagrangian spray model was coupled with the vapor flow using the CFD modeling to investigate the LNG forced dispersion. 14 The effectiveness of the dilution phenomena of LNG vapors dramatically improved as the momentum imparted from the water droplets increased, which is in agreement with the correlations provided by the additional study conducted by Hald et al (2005). 13 The dimensionless quantity is used to evaluate the momentum imparted from the water droplets.…”
Section: Physical Mechanisms Of Water Spray Applicationsupporting
confidence: 74%
See 1 more Smart Citation
“…13 A Eulerian−Lagrangian spray model was coupled with the vapor flow using the CFD modeling to investigate the LNG forced dispersion. 14 The effectiveness of the dilution phenomena of LNG vapors dramatically improved as the momentum imparted from the water droplets increased, which is in agreement with the correlations provided by the additional study conducted by Hald et al (2005). 13 The dimensionless quantity is used to evaluate the momentum imparted from the water droplets.…”
Section: Physical Mechanisms Of Water Spray Applicationsupporting
confidence: 74%
“…The previous work by the authors discussed the details on setting up the LNG forced dispersion model with the Eulerian−Lagrangian spray model, coupled with the LNG flow. 14 The water droplets were characterized as inert with spherical drag law combined with the two-way coupling heat The momentum effect is evaluated by coupling the drag force of the water droplets with the momentum flux of the LNG vapors, and by considering any other additional interaction forces (F other ), such as the virtual mass force and pressure gradient force. μ is the viscosity, C D is the drag coefficient, Re is the Reynolds number, ρ p is the droplet density, and d is the droplet diameter.…”
Section: Numerical Modeling Setupmentioning
confidence: 99%
“…[4,5]. Kim et al (2012) experimented LNG dispersions with the full cone type water spray curtains and compared the concentrations near the release source with CFD dispersion simulations. Cheng et al (2014) also did field test for ammonia to compare CFD simulation results with the experiments [6,7].…”
Section: Introductionmentioning
confidence: 99%
“…Kim et al (2012) experimented LNG dispersions with the full cone type water spray curtains and compared the concentrations near the release source with CFD dispersion simulations. Cheng et al (2014) also did field test for ammonia to compare CFD simulation results with the experiments [6,7]. However, in these previous researches, the effectiveness to mitigate gas dispersions are significantly different for the peacock tail type.…”
Section: Introductionmentioning
confidence: 99%
“…In contrast, CFD simulations for engineering applications are typically performed with well-established CFD packages such as ANSYS FLUENT, ANSYS CFX, STAR CCM+ and OpenFOAM (for recent examples, see Burlutskiy & Turangan, 2015;Kim, Ng, Mentzer, & Mannan, 2012;Lin, Lan, Xu, Dong, & Barber, 2015;Saffari & Hosseinnia, 2009;Torti, Sibilla, & Raboni, 2013;Weber, Schaffel-Mancini, Mancini, & Kupka, 2013). In these studies, the performance of the numerical model is often tested via the comparison of numerical and experimental process parameters, e.g., pressure losses in pipe flows or species concentration.…”
Section: Introductionmentioning
confidence: 99%