Spread of hydrogen vapor cloud during continuous liquid hydrogen spills

Liu, Yuanliang; Wei, Jianjian; Lei, Gang; Chen, Hong; Lan, Yuqi; Gao, Xu; Wang, Tianxiang; Jin, Tao

doi:10.1016/j.cryogenics.2019.102975

Cited by 12 publications

(4 citation statements)

References 20 publications

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“…Vapor cloud profiles for released LNG and liquid hydrogen have been determined from several studies (Ivings et al 2016). The influence of wind speed is shown in Figure 5 for low wind speeds (<5 mph), and Figure 6 for higher wind velocities (>5 mph) (Lin et al 2019, Sklavounos and Rigas 2005, Thyer 2003, Witcofski and Chirivella 1984.…”

Section: Pressurized Gaseous Fuelsmentioning

confidence: 99%

Spill Behavior, Detection, and Mitigation for Emerging Nontraditional Marine Fuels

Kass,

Sluder,

Kaul

2021

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Section: Pressurized Gaseous Fuelsmentioning

confidence: 99%

Spill Behavior, Detection, and Mitigation for Emerging Nontraditional Marine Fuels

Kass,

Sluder,

Kaul

2021

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“…In Reference 10, researchers found that reducing the liquid hydrogen release speed helps the upward movement of hydrogen clouds, thus reducing the explosion risk close to the ground. Liu et al found that the mass flow rate of a liquid spill is positively correlated with the maximum length of the combustible clouds, while the effect of ambient ground temperature on hydrogen cloud spread is not significant for common weather conditions 11 . The evaporation and diffusion processes of liquid hydrogen leaking in tunnel scenarios and under special weather conditions were investigated in References 12, 13.…”

Section: Introductionmentioning

confidence: 99%

Computational fluid dynamics model based artificial neural network prediction of flammable vapor clouds formed by liquid hydrogen releases

Xiao

et al. 2022

Intl J of Energy Research

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Summary The flammable vapor clouds formed by liquid hydrogen release potentially leads to explosions and serious fires. In this paper, an artificial neural network (ANN) model based on the back propagation algorithm was developed to predict the horizontal and vertical hydrogen diffusion distances (the maximum distance of flammable vapor cloud with a hydrogen volume concentration of 4% to the release source in downwind and height direction). For this purpose, liquid hydrogen releases were modeled using a computational fluid dynamics (CFD) model, which was validated by experimental data. The single hidden layer ANN model used the wind speed, ground temperature, leakage duration, and leakage mass flow rate as input parameters. Then, the ANN model was trained and verified using 50 sets of sample data derived from the CFD simulations selected via the orthogonal experiment method. The results show that the ANN model well predicts the hydrogen diffusion distances, with the percentage error of the horizontal diffusion distance within 10% and the prediction error of the vertical diffusion distance less than 1.5 m for 90% of test points. The overall correlation coefficient between ANN predicted output and target results reaches 0.99329. Furthermore, the ANN model predicts four orders of magnitude faster than the CFD simulation and reduces the root means square error and the maximum relative error by more than 23% compared to predictions by the empirical correlation fitted from the CFD data. Then, the effects of the four input parameters on the diffusion distances were analyzed using the ANN model.

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“…Verfondern et al [9] conducted liquid hydrogen pool spread experiments on the surface of water and solid ground. Due to the huge cost and the safety issues related to the experiment, many researchers also investigated the leakage and dispersion of liquid hydrogen numerically [10][11][12][13][14][15][16][17][18][19][20][21], which revealed the underlying mechanisms and the effects of various conditions, such as spill source, season, wind flow, air humidity, etc.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of the Flow Characteristics of Liquid Hydrogen in a Pipe Suffering from External Transient Impact

Liu

Qiu²,

et al. 2022

Energies

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Pipes can be subjected to external transient impacts such as accidental collision, which affects the safe operation of storage and transportation systems for liquid hydrogen. Fluid–structure coupling calculation for a pipe under external transient impact is performed, and the flow characteristics of liquid hydrogen in the pipe are analyzed. The pipe deforms and vibrates when suffering from external transient impact. Liquid hydrogen pressure in a cross-section plane increases along the pipe deformation direction. Additionally, external transient impact enhances the disturbance of liquid hydrogen near the pipe wall. The increased flow resistance and the energy induced by the deformed pipe both affect the flow of liquid hydrogen, and contribute to the fluctuated characteristics of liquid pressure drop. In addition, the phase state of liquid hydrogen remains unchanged in the pipe, indicating that little of the induced energy is transformed into the internal energy of liquid hydrogen. The work provides theoretical guidance for the safe operation of liquid hydrogen storage and transportation systems.

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Spread of hydrogen vapor cloud during continuous liquid hydrogen spills

Cited by 12 publications

References 20 publications

Spill Behavior, Detection, and Mitigation for Emerging Nontraditional Marine Fuels

Spill Behavior, Detection, and Mitigation for Emerging Nontraditional Marine Fuels

Computational fluid dynamics model based artificial neural network prediction of flammable vapor clouds formed by liquid hydrogen releases

Modeling and Analysis of the Flow Characteristics of Liquid Hydrogen in a Pipe Suffering from External Transient Impact

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