On derivation and verification of a kinetic model for quantum vibrational energy of polyatomic gases in the gas-kinetic unified algorithm

Wu, Junlin; Li, Zhihui; Zhang, Zibin; Peng, Ao‐Ping

doi:10.1016/j.jcp.2020.109938

Cited by 13 publications

(5 citation statements)

References 56 publications

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“…The dipoles of the water molecules was popped due to the strained molecular orbital which has a similar effect as a mechanical fatigue in macroscale solid objects [27] . The vibration mode of a molecule is defined by the energy state which defined by the Hamiltonian of the electrons in the orbital which also include the kinetic energy [28] . The magnetic vibrational response is in the form of directed vibration which is different from the heat induced vibration mode.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Chaotic Flux Reflection Field on Hydrogen Evolution Reaction of Water Electrolysis

Nugroho,

Esiliy,

Purnami

et al. 2024

MECHTA

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Water electrolysis promises the capability to produce green hydrogen in the future. The efficiency and hydrogen evolution reaction rate (HER) of water electrolysis can be improved through magnetic field assisted electrolysis. External magnetic field exposure improves hydrogen production without requiring complex catalyst synthesis technique. The purpose of this study is to introduce chaos into a magnetic field assisted electrolysis system which disturbs the water molecules stability. The chaos effect was triggered by irregular flux reflection technique. The flux reflection was generated using diamagnetic tourmaline stones which sticked all over the electrolyzer wall. Consequently, the rotational speed of DMF does not reduce the effectiveness of chaotic flux. As a result, the hydrogen bond of the water molecules is destabilized irregularly. In conjuction with that, the bonds are unable to be reformed which make the water molecules continuously in movement. The critical effect of chaotic flux is the shear force that experienced by water molecules. The paramagnetic OH- ion movement is also slowed down so that H+ ion and electrons interaction were occurred in less restrictive manner. Hence, the chaotic magnetic field able to improve HER. The chaotic flux reflection improves hydrogen production in magnetic field assisted water electrolysis through water properties and ion transfer mechanism modification.

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Section: Discussionmentioning

confidence: 99%

The Impact of Chaotic Flux Reflection Field on Hydrogen Evolution Reaction of Water Electrolysis

Nugroho,

Esiliy,

Purnami

et al. 2024

MECHTA

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“…2006; Gao & Sun 2014; Watari 2016); internal degrees of freedom (Rykov 1975) and even quantum vibrational energy (Wu et al. 2021 a ); and appropriate kinetic boundary conditions (Wagner & Pagonabarraga 2002; Sbragaglia & Succi 2005; Sofonea & Sekerka 2005; Toschi & Succi 2005; Benzi et al. 2006; Chikatamarla, Ansumali & Karlin 2006; Chen, Zhang & Zhang 2013).…”

Section: Dbm For Multiphase Flows Far From Equilibriummentioning

confidence: 99%

“…In addition, the BGK-like models used widely in the study of complex fluids include several other physical modelling improvements, for example: relaxation times related to local macroscopic quantities (Li & Zhang 2004;Li et al 2015) and collision frequency (Struchtrup 1997); pseudo-equilibrium distribution functions that contain non-equilibrium information (Holway 1966;Shakhov 1968;Shan et al 2006;Gao & Sun 2014;Watari 2016); internal degrees of freedom (Rykov 1975) and even quantum vibrational energy (Wu et al 2021a); and appropriate kinetic boundary conditions (Wagner & Pagonabarraga 2002;Sbragaglia & Succi 2005;Sofonea & Sekerka 2005;Toschi & Succi 2005;Benzi et al 2006;Chikatamarla, Ansumali & Karlin 2006;Chen, Zhang & Zhang 2013). These improved models permit to capture a wider range of Knudsen numbers and a higher degree of non-equilibrium.…”

Section: Discrete Formulation Of Density Functional Kinetic Theorymentioning

confidence: 99%

Discrete Boltzmann multi-scale modelling of non-equilibrium multiphase flows

Gan

Xu²,

Lai³

et al. 2022

J. Fluid Mech.

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The aim of this paper is twofold: the first aim is to formulate and validate a multi-scale discrete Boltzmann method (DBM) based on density functional kinetic theory for thermal multiphase flow systems, ranging from continuum to transition flow regime; the second aim is to present some new insights into the thermo-hydrodynamic non-equilibrium (THNE) effects in the phase separation process. Methodologically, for bulk flow, DBM includes three main pillars: (i) the determination of the fewest kinetic moment relations, which are required by the description of significant THNE effects beyond the realm of continuum fluid mechanics; (ii) the construction of an appropriate discrete equilibrium distribution function recovering all the desired kinetic moments; (iii) the detection, description, presentation and analysis of THNE based on the moments of the non-equilibrium distribution ( $f-f^{(eq)}$ ). The incorporation of appropriate additional higher-order thermodynamic kinetic moments considerably extends the DBM's capability of handling larger values of the liquid–vapour density ratio, curbing spurious currents, and ensuring mass/momentum/energy conservation. Compared with the DBM with only first-order THNE (Gan et al., Soft Matt., vol. 11 (26), 2015, pp. 5336–5345), the model retrieves kinetic moments beyond the third-order super-Burnett level, and is accurate for weak, moderate and strong THNE cases even when the local Knudsen number exceeds $1/3$ . Physically, the ending point of the linear relation between THNE and the concerned physical parameter provides a distinct criterion to identify whether the system is near or far from equilibrium. Besides, the surface tension suppresses the local THNE around the interface, but expands the THNE range and strengthens the THNE intensity away from the interface through interface smoothing and widening.

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“…The DVM solves the Boltzmann equation in both the molecular velocity space and the physical space. In the framework of DVM, various numerical method has been developed, such as the gas kinetic unified algorithm (GKUA) [32][33], the unified gas kinetic scheme (UGKS) [34][35], the discrete unified gas kinetic scheme (DUGKS) [36][37], the improved discrete velocity method (IDVM) [38][39], the general synthetic iterative scheme (GSIS) [40][41], and so on. Among them, the UGKS, DUGKS and IDVM solve the discrete velocity Boltzmann equation (DVBE) by the finite volume method (FVM) and evaluates the numerical fluxes at the cell interface by coupling the motion and collision processes of molecules.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Partitioning-based Discrete Unified Gas-Kinetic Scheme for Flows in All Flow Regimes

Yang

Liang

Ding

et al. 2022

Preprint

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The discrete unified gas kinetic scheme (DUGKS) is a multiscale approach, which can be used to obtain reasonable results in all flow regimes. The key of this method is the reconstruction of numerical fluxes at the cell interface by coupling the motion of particles from their collisions, namely the use of the discrete characteristic solution to the Boltzmann-BGK equation at the cell interface to calculate numerical fluxes. But like all the discrete velocity methods (DVMs), the computational cost of DUGKS is determined by the discretization in both the physical space and the velocity space. For the continuous flow region in the computational domain, the discretization in the velocity space is unnecessary since the distribution function can be reconstructed from the Chapman-Enskog expansion directly. To improve the efficiency of DUGKS in capturing cross-scale flow physics, an adaptive partitioning-based discrete unified gas kinetic scheme (ADUGKS) is developed in this work. The ADUGKS is designed from the discrete characteristic solution to the Boltzmann-BGK equation, which contains the initial distribution function and the local equilibrium state. The initial distribution function contributes to the calculation of free streaming fluxes and the local equilibrium state contributes to the calculation of equilibrium fluxes. If the contribution of the initial distribution function is negative., the local flow field can be regarded as the continuous flow and the Navier-Stokes (N-S) equations can be used to obtain the solution directly. Otherwise, the discrete distribution functions should be updated by the Boltzmann equation to capture the rarefied effect. Given this, the computational domain is divided into the DUGKS cell and the N-S cell based on the contribution of the initial distribution function to the calculation of free streaming fluxes. In the N-S cell, the local flow field is evolved by solving the Navier-Stokes equations, while in the DUGKS cell, both the discrete velocity Boltzmann equation and the corresponding macroscopic governing equations are solved by a modified DUGKS. Since more and more cells turn into the N-S cell with the decrease of the Knudsen number, a significant acceleration can be achieved for the ADUGKS in the continuum flow regime as compared with the DUGKS.

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On derivation and verification of a kinetic model for quantum vibrational energy of polyatomic gases in the gas-kinetic unified algorithm

Cited by 13 publications

References 56 publications

The Impact of Chaotic Flux Reflection Field on Hydrogen Evolution Reaction of Water Electrolysis

The Impact of Chaotic Flux Reflection Field on Hydrogen Evolution Reaction of Water Electrolysis

Discrete Boltzmann multi-scale modelling of non-equilibrium multiphase flows

Adaptive Partitioning-based Discrete Unified Gas-Kinetic Scheme for Flows in All Flow Regimes

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