Molecular Dynamic Simulations of a Simplified Nanofluid

Sergis, A.; Hardalupas, Y.

doi:10.12921/cmst.2014.20.04.113-127

Cited by 8 publications

(8 citation statements)

References 32 publications

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“…The second test involved plotting the radial distribution functions (RDF) of the system before and after a nanoparticle was formed. The third and final test involved plotting the normalised velocity autocorrelation function (VACF) of a nanoparticle and a normal argon fluid atom (more information can be found in an earlier study performed [ 25 ]). All three tests indicated good agreement with the literature [ 26 – 35 ].…”

Section: Methodsmentioning

confidence: 99%

“…Developing the code and obtaining the results took about eight million CPU hours. More information regarding the methodology involved in composing, running and developing the code and the HTCondor system can be obtained from [ 25 ].…”

Section: Methodsmentioning

confidence: 99%

“…The current study is a continuation of an earlier investigation [ 25 ] to build and run a large-scale deployment of a molecular dynamics simulation (MDS) code and to simulate from first principles and with minimal assumptions a novel single particle nanofluid to study the conductive heat transfer mechanisms employed. The analysis is achieved by comparing the nanoparticle trajectories across thousands of simulations and iterations with those of a carrier fluid molecule to quantify the effects of thermal diffusivity.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Revealing the complex conduction heat transfer mechanism of nanofluids

Sergis

Hardalupas

2015

Nanoscale Res Lett

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Nanofluids are two-phase mixtures consisting of small percentages of nanoparticles (sub 1–10 %vol) inside a carrier fluid. The typical size of nanoparticles is less than 100 nm. These fluids have been exhibiting experimentally a significant increase of thermal performance compared to the corresponding carrier fluids, which cannot be explained using the classical thermodynamic theory. This study deciphers the thermal heat transfer mechanism for the conductive heat transfer mode via a molecular dynamics simulation code. The current findings are the first of their kind and conflict with the proposed theories for heat transfer propagation through micron-sized slurries and pure matter. The authors provide evidence of a complex new type of heat transfer mechanism, which explains the observed abnormal heat transfer augmentation. The new mechanism appears to unite a number of popular speculations for the thermal heat transfer mechanism employed by nanofluids as predicted by the majority of the researchers of the field into a single one. The constituents of the increased diffusivity of the nanoparticle can be attributed to mismatching of the local temperature profiles between parts of the surface of the solid and the fluid resulting in increased local thermophoretic effects. These effects affect the region surrounding the solid manifesting interfacial layer phenomena (Kapitza resistance). In this region, the activity of the fluid and the interactions between the fluid and the nanoparticle are elevated. Isotropic increased nanoparticle mobility is manifested as enhanced Brownian motion and diffusion effects

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Revealing the complex conduction heat transfer mechanism of nanofluids

Sergis

Hardalupas

2015

Nanoscale Res Lett

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“…Furthermore, it is not just simulation that need to be carried out but for the data quantification, the data that are gathered requires huge memory for storage. Thereby, requiring the random access memory (RAM) and hard disk drive (HDD) to be large enough to store the required data easily [51].…”

Section: Problems Faced For Simulating Nanofluidsmentioning

confidence: 99%

Problems Faced While Simulating Nanofluids

Loya¹

2017

Nanofluid Heat and Mass Transfer in Engineering Problems

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Problems are faced when something is already been adopted for a considerable amount of time-here the problem that is discussed is related with nanofluids. The nanofluids have been considered for different engineering applications since last three decades; however, the work on its simulation has been started since last two decades. With the time, nanofluid simulations are increasing as compared to experimental testing. Researchers conducting nanofluid simulations do find difficulties and problems while trying to simulate this system. In addition to this, most of the time researchers are unaware of some basic problems and they find themselves stuck in relentless difficulties. Most of the time, these problems are very basic and can waste a lot of useful time of a research. Therefore, this chapter introduces some fundamental problems which a researcher can find while simulating nanofluids and with a simple way of dealing with it. Moreover, the chapter withholds lots of information regarding the way to design and to model a nanofluid system. Not only this, it also tends to elaborate the nanofluid simulation methodology in a precise manner. Moreover, the literature shows that nanofluid simulation has gained high consideration since last two decades, as experimental techniques are out of reach for everyone. In addition to experimental techniques, they are expensive, time-consuming and require high skills. However, it seems the simulation is picking pace with the due time and is considerably being adopted by the expertise dealing with nanofluids. This opens a high prospect of simulating nanofluids in future. Nevertheless, it seems there will be user-friendly software to conduct nanofluid simulations. Finally, issues and their resolution have also been conveyed which is the main aspect of this topic.

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“…The second test involved plotting the radial distribution functions (RDF) of the system before and after a nanoparticle was formed. The third and final test involved plotting the normalised velocity autocorrelation function (VACF) of a nanoparticle and a normal argon fluid atom (more information can be found in an earlier study performed [25]). All three tests indicated good agreement with the literature [26][27][28][29][30][31][32][33][34][35].…”

Section: Code Developmentmentioning

confidence: 99%

Revealing the complex conduction heat transfer mechanism of nanofluids

Sergis¹,

Hardalupas²

2016

Nano Online

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Nanofluids are two-phase mixtures consisting of small percentages of nanoparticles (sub 1-10 %vol) inside a carrier fluid. The typical size of nanoparticles is less than 100 nm. These fluids have been exhibiting experimentally a significant increase of thermal performance compared to the corresponding carrier fluids, which cannot be explained using the classical thermodynamic theory. This study deciphers the thermal heat transfer mechanism for the conductive heat transfer mode via a molecular dynamics simulation code. The current findings are the first of their kind and conflict with the proposed theories for heat transfer propagation through micron-sized slurries and pure matter. The authors provide evidence of a complex new type of heat transfer mechanism, which explains the observed abnormal heat transfer augmentation. The new mechanism appears to unite a number of popular speculations for the thermal heat transfer mechanism employed by nanofluids as predicted by the majority of the researchers of the field into a single one. The constituents of the increased diffusivity of the nanoparticle can be attributed to mismatching of the local temperature profiles between parts of the surface of the solid and the fluid resulting in increased local thermophoretic effects. These effects affect the region surrounding the solid manifesting interfacial layer phenomena (Kapitza resistance). In this region, the activity of the fluid and the interactions between the fluid and the nanoparticle are elevated. Isotropic increased nanoparticle mobility is manifested as enhanced Brownian motion and diffusion effects

show abstract

Molecular Dynamic Simulations of a Simplified Nanofluid

Cited by 8 publications

References 32 publications

Revealing the complex conduction heat transfer mechanism of nanofluids

Revealing the complex conduction heat transfer mechanism of nanofluids

Problems Faced While Simulating Nanofluids

Revealing the complex conduction heat transfer mechanism of nanofluids

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