Using Event Location in Finite-Difference Methods for Phase-Change Problems

Furenes, Beathe; Lie, Bernt

doi:10.1080/10407790500459338

Cited by 9 publications

(2 citation statements)

References 13 publications

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“…Farrokhpanah [8] introduced a new smoothed particle hydrodynamics (SPH) method to model the heat transfer with phase change considering the latent heat released (absorbed) during solidification (melting). Furenes [9] used the event location algorithm in the finite difference method for phase-change problems.…”

Section: Introductionmentioning

confidence: 99%

Lattice Boltzmann Simulation for the Forming Process of Artificial Frozen Soil Wall

Shen

Wang

et al. 2018

Energies

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A lattice Boltzmann model is proposed to simulate the forming process of artificial frozen soil wall. The enthalpy method is applied to deal with the latent-heat source term, and the adjustable thermal diffusivity is utilized to handle the change of thermophysical parameters. The model is tested by the heat conduction with solid–liquid phase change in semi-infinite space, which shows a good consistence between the numerical and analytical solutions, and the mesh resolution has little effect on the numerical results. Lastly, the development of frozen soil wall is discussed when the freezing pipes are arranged in a square. The results show that the evolution of temperature field with time is closely related to the distance from the freezing pipe. For the soil near freezing pipe, the temperature gradient is larger, the soil temperature drops rapidly and freezes in a short time. The time history curve of temperature is relatively smooth. For the soil far away from freezing pipe, the temperature evolution curve has obvious multistage, which can be divided into four stages: cooling, phase change, partly frozen and completely frozen. The spacing of freezing pipes has a significant influence on the overlapping time of artificial frozen soil wall, and there is a power function relationship between them.

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Section: Introductionmentioning

confidence: 99%

Lattice Boltzmann Simulation for the Forming Process of Artificial Frozen Soil Wall

Shen

Wang

et al. 2018

Energies

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“…mass density (kg · m − 3 ) σ standard deviation σ p standard deviation in percentage of the average value τ current generation number the functional, genetic algorithms were used [22][23][24], whereas the Stefan problem was solved by generalized alternating phase truncation method [18,25,26] (for others methods see for example [27][28][29][30]). Let Γ 1,2 will designate the common boundary of domains D 1 and D 2 , whilst Γ 2,3 will mean the common boundary of domains D 2 and D 3 .…”

Section: Introductionmentioning

confidence: 99%

Using genetic algorithms for the determination of an heat transfer coefficient in three-phase inverse Stefan problem

Słota

2008

International Communications in Heat and Mass Transfer

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Event driven modeling for the accurate identification of metabolic switches in fed-batch culture of S. cerevisiae

Jouned

Kager²,

Herwig

et al. 2022

Biochemical Engineering Journal

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Using Event Location in Finite-Difference Methods for Phase-Change Problems

Cited by 9 publications

References 13 publications

Lattice Boltzmann Simulation for the Forming Process of Artificial Frozen Soil Wall

Lattice Boltzmann Simulation for the Forming Process of Artificial Frozen Soil Wall

Using genetic algorithms for the determination of an heat transfer coefficient in three-phase inverse Stefan problem

Event driven modeling for the accurate identification of metabolic switches in fed-batch culture of S. cerevisiae

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