Particle coalescing with angular momentum conservation in SPH simulations

Havasi-Tóth, Balázs

doi:10.1016/j.compfluid.2019.104384

Cited by 3 publications

(2 citation statements)

References 40 publications

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“…To investigate the coalescence process in a numerical way, the source term S i was added to the right side of the momentum equation: 23…”

Section: Mathematical Model Descriptionmentioning

confidence: 99%

“…To investigate the coalescence process in a numerical way, the source term S i was added to the right side of the momentum equation: S i = prefix− ( B + A · v s → ) A = C 2 1 2 ρ v normals → B = μ a v normals → where S i is the source term in the direction of i and v normals → is the velocity vector of the particle. The first term B on the right side of the equation is the Darcy flow term, and the second term on the right side of equation A is the inertial resistance term.…”

Section: Numerical Simulationmentioning

confidence: 99%

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Improving the Dust Removal Efficiency of a Natural Gas Filter: An Experimental and Numerical Simulation Study

Zheng,

Dai,

Wang

et al. 2023

ACS Omega

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This study aims to evaluate the dust removal efficiency and working conditions of a filter separator through a pressure drop under various operating conditions. Typical horizontal filter separators in natural gas stations were taken as the research objects, and the computational fluid dynamics method was first attempted to investigate the static and dynamic characteristics of the pressure drop and the dust removal efficiency under different operating times and pressures. Then, the simulated results were compared with those obtained from online dust detection. At a constant standard flow rate, the detected pressure drop deviated from the fitted optimal quadratic curve with an increase in the operation duration of the filter separator, and the dust removal efficiency also tended to decline. The declining trend was particularly faster at lower operating pressures caused by the fast air flow, which leads to more coalesced particles flowing out and increases the dust concentration downstream. A higher initial pressure drop of the filter separator was also maintained at a low operating pressure. The dust removal efficiency rapidly decreased at a higher throughput load, and the decreasing rate became moderate at a lower input load. An optimum operating throughput of the filter was obtained when the input load varied in the range of 100 × 104–270 × 104 Nm3/d. Good agreement was achieved between the simulated and experimental dust removal efficiency, and the relative errors are within ±20%. Both methods applied in this work were verified to have high accuracy and reliability through the actual on-site amount of dust captured.

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“…To investigate the coalescence process in a numerical way, the source term S i was added to the right side of the momentum equation: 23…”

Section: Mathematical Model Descriptionmentioning

confidence: 99%