Heat Transfer and Flowfields in Short Microchannels Using Direct Simulation Monte Carlo

Mavriplis, Catherine; Ahn, Joon; Goulard, R.

doi:10.2514/2.6278

Cited by 62 publications

(44 citation statements)

References 14 publications

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“…This DSMC method does not calculate the collisions exactly as in molecular dynamics, but generates collisions stochastically with scattering rates and post-collision velocity distributions determined from the kinetic theory of a dilute gas. Several authors [7,8,10] used this method successfully to study flow and heat transfer in microchannels for a dilute gas. However, for cooling purposes (high pressure or phase transition) we have also to model a dense gas in a microchannel.…”

Section: Molecular Dynamics and Monte Carlo Methodsmentioning

confidence: 99%

Molecular Dynamics and Monte Carlo Simulations for Heat Transfer in Micro and Nano-channels

Frijns

Nedea

Markvoort

et al. 2004

Computational Science - ICCS 2004

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Abstract. There is a tendency to cool mechanical and electrical components by microchannels. When the channel size decreases, the continuum approach starts to fail and particle based methods should be used. In this paper, a dense gas in micro and nano-channels is modelled by molecular dynamics and Monte Carlo simulations. It is shown that in the limit situation both methods yield the same solution. Molecular dynamics is an accurate but computational expensive method. The Monte Carlo method is more efficient, but is less accurate near the boundaries. Therefore a new coupling algorithm for molecular dynamics and Monte Carlo is introduced in which the advantages of both methods are used.

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Section: Molecular Dynamics and Monte Carlo Methodsmentioning

confidence: 99%

Molecular Dynamics and Monte Carlo Simulations for Heat Transfer in Micro and Nano-channels

Frijns

Nedea

Markvoort

et al. 2004

Computational Science - ICCS 2004

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“…The balance between computational expense and accuracy has been studied by many authors [20][21][22][23], and 30-40 par-135 ticles per cell is commonly employed [24][25][26][27][28]. However, there are some DSMC simulations [29,30] that employed as few as 10 particles per cell, and some computations [31] as many as 50 to 120. The number of particles required is heavily influenced by the choice of collision model, and it is well-known that the majorant frequency scheme can use fewer particles than the no time-counter-method 140 (NTC).…”

Section: Code Sensitivitymentioning

confidence: 99%

“…As Kn increases (0.01 < Kn < 0.1), 25 regions of non-equilibrium begin to appear near surfaces as the molecule-surface interaction frequency is reduced; the most recognizable effect of this is velocity slip and temperature jump, and the NSF equations with slip and jump boundary conditions can still be used effectively. However, once the Knudsen number increases into the transition-continuum (0.1 < Kn < 10) and free-molecular 30 (Kn > 10) regimes, the NSF equations cannot predict the gas behavior. Recourse to solutions of the Boltzmann equation must be made, and DSMC has proven to be the most reliable method for this purpose in the transition regime, where non-equilibrium effects dominate the gas behavior but inter-molecular collisions are still important.…”

Section: Introductionmentioning

confidence: 99%

Benchmark numerical simulations of rarefied non-reacting gas flows using an open-source DSMC code

et al. 2015

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Validation and verification represent an important element in the development of a computational code. The aim is establish both confidence in the algorithm and its suitability for the intended purpose. In this paper, a direct simulation Monte Carlo solver, called dsmcF oam, is carefully investigated for its ability to solve low and high speed non-reacting gas flows in simple and complex geometries.The test cases are: flow over sharp and truncated flat plates, the Mars Pathfinder probe, a micro-channel with heated internal steps, and a simple micro-channel.For all the cases investigated, dsmcF oam demonstrates very good agreement with experimental and numerical data available in the literature.

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“…This makes it possible for this type of scheme to be used as a mesoscale model for systems that are too small for continuum models but large compared to molecular dimensions. DSMC models have been used to predict transport in a variety of microscale systems (see, for example, the models described in the literature [33][34][35][36][37][38][39][40]). The discussion here will focus on one specific model type.…”

Section: Dsmc Models Of Postnucleation Growth Of Water Dropletsmentioning

confidence: 99%

A Review of Heat Transfer Physics

Carey

Chen

Grigoropoulos

et al. 2008

Nanoscale & Microscale Thermophysical Eng.

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With rising science contents of the engineering research and education, we give examples of the quest for fundamental understanding of heat transfer at the atomic level. These include transport as well as interactions (energy conversion) involving phonon, electron, fluid particle, and photon (or electromagnetic wave). Examples are 1. development of MD and DSMC fluid simulations as tools in nanoscale and microscale thermophysical engineering. 2. nanoscale thermal radiation, where the characteristic structural size becomes comparable to or smaller than the radiation (electromagnetic) wavelength. 3. laser-based nanoprocessing, where the surface topography, texture, etc., are modified with nanometer lateral feature definition using pulsed laser beams and confining optical energy by coupling to near-field scanning optical microscopes. 4. photon-electron-phonon couplings in laser cooling of solids, where the thermal vibrational energy (phonon) is removed by the anti-Stokes fluorescence; i.e., the photons emitted by an optical material have a mean energy higher than that of the absorbed photons.Nanoscale and Microscale Thermophysical Engineering, 12: 1-60, 2008 Copyright Ó Taylor 5. exploring the limits of thermal transport in nanostructured materials using spectrally dependent phonon scattering and vibrational spectra mismatching, to impede a particular phonon bands.These examples suggest that the atomic-level heat transfer builds on and expands electromagnetism (EM), atomic-molecular-optical physics, and condensed-matter physics. The theoretical treatments include ab initio calculations, molecular dynamics simulations, Boltzmann transport theory, and near-field EM thermal emission prediction. Experimental methods include near-field microscopy.Heat transfer physics describes the kinetics of storage, transport, and transformation of microscale energy carriers (phonon, electron, fluid particle, and photon). Sensible heat is stored in the thermal motion of atoms in various phases of matter. The atomic energy states and their populations are described by the classical and the quantum statistical mechanics (partition function and combinatoric energy distribution probabilities). Transport of thermal energy by the microscale carriers is based on their particle, quasi-particle, and wave descriptions; their diffusion, flow, and propagation; and their scattering and transformation encountered as they travel. The mechanisms of energy transitions among these energy carriers, and their rates (kinetics), are governed by the match of their energies, their interaction probabilities, and the various hindering-mechanism rate (kinetics) limits. Conservation of energy describes the interplay among energy storage, transport, and conversion, from the atomic to the continuum scales.With advances in micro-and nanotechnology, heat transfer engineering of micro-and nanostructured systems has offered new opportunities for research and education. New journals, including Nanoscale and Microscale Thermophysical Engineering, have allowed communi...

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Heat Transfer and Flowfields in Short Microchannels Using Direct Simulation Monte Carlo

Cited by 62 publications

References 14 publications

Molecular Dynamics and Monte Carlo Simulations for Heat Transfer in Micro and Nano-channels

Molecular Dynamics and Monte Carlo Simulations for Heat Transfer in Micro and Nano-channels

Benchmark numerical simulations of rarefied non-reacting gas flows using an open-source DSMC code

A Review of Heat Transfer Physics

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