Analysis of thermophoresis and Brownian motion effect in heat transfer for nanofluid immersed distribution transformer

Das, Anu Kumar; Chatterjee, Saibal

doi:10.1007/s00202-017-0676-2

Cited by 15 publications

(9 citation statements)

References 24 publications

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“…Thermophoresis describes the motion of a charged colloidal particle with respect to the aqueous media in response to an external applied temperature gradient [ 1 , 2 , 3 ]. The thermophoresis approach has been used to separate, trap, and concentrate nanoparticles in liquid media [ 4 , 5 , 6 , 7 ]. For biological and biocompatible compounds [ 8 ] in aqueous solutions, the thermophoretic techniques provide useful tools to quantify the protein−ligand binding constants [ 9 ] and the copy numbers of noncoding RNA [ 10 ], examine the hydration layer [ 11 ], and determine the biomolecular interactions [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Numerical Analysis of Thermophoresis of a Charged Spheroidal Colloid in Aqueous Media

et al. 2021

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Thermophoresis of charged colloids in aqueous media has wide applications in biology. Most existing studies of thermophoresis focused on spherical particles, but biological compounds are usually non-spherical. The present paper reports a numerical analysis of the thermophoresis of a charged spheroidal colloid in aqueous media. The model accounts for the strongly coupled temperature field, the flow field, the electric potential field, and the ion concentration field. Numerical simulations revealed that prolate spheroids move faster than spherical particles, and oblate spheroids move slower than spherical particles. For the arbitrary electric double layer (EDL) thickness, the thermodiffusion coefficient of prolate (oblate) spheroids increases (decreases) with the increasing particle’s dimension ratio between the major and minor semiaxes. For the extremely thin EDL case, the hydrodynamic effect is significant, and the thermodiffusion coefficient for prolate (oblate) spheroids converges to a fixed value with the increasing particle’s dimension ratio. For the extremely thick EDL case, the particle curvature’s effect also becomes important, and the increasing (decreasing) rate of thermodiffusion coefficient for prolate (oblate) spheroids is reduced slightly.

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Section: Introductionmentioning

confidence: 99%

Numerical Analysis of Thermophoresis of a Charged Spheroidal Colloid in Aqueous Media

et al. 2021

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“…Thermophoresis, Brownian motion, Soret-Dufour and time-dependent chemical reaction effects have been considered in this problem. Under these assumptions, the governing boundary layer along with the continuity, momentum, energy and concentration species can be written as (Das and Chatterjee [6], Pakravan and Yaghoubi [19] and Pal and Mondal [20])…”

Section: Governing Equations and Mathematical Formulationmentioning

confidence: 99%

“…where ζ is the similarity variable, and ψ is the stream function. Now substituting (6) into Eqs. (1)-(5), we get the following equations:…”

Section: Governing Equations and Mathematical Formulationmentioning

confidence: 99%

“…The effect of nonuniform magnetic field in a lid driven semi-annulus enclosure filled with Fe 3 O 4 -water nanofluid was presented by Sheikholeslami et al [33]. Das and Chatterjee [6] analyzed the thermophoresis and Brownian motion effect in heat transfer behaviour of a three-phase distribution transformer filled with nanofluid. The results of the parametric study show that nanofluid circulated with the magnetite nanoparticles has greater in maximum temperature (∼ 11 K) followed by silica nanoparticles (∼ 7.3 K) and quartz nanoparticles (∼ 6 K).…”

Section: Introductionmentioning

confidence: 99%

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Influence of Soret and Dufour effects on unsteady 3D MHD slip flow of Carreau nanofluid over a slendering stretchable sheet with chemical reaction

Reddy

Chamkha

2019

NAMC

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This paper presents a numerical exploration on the unsteady three-dimensional hydromagnetic flow of Carreau nanofluid over a slendering stretchable sheet in the presence of thermal radiation and chemical reaction. Furthermore, the effects of velocity slip, thermal slip, solutal slip, Soret and Dufour are taken into account. The prevailing time-dependent partial differential equations are metamorphosed into a system of coupled nonlinear ordinary differential equations by using the appropriate similarity transformations. The resultant nonlinear coupled differential equations are solved numerically by using the Runge–Kutta fourth-order method along with shooting scheme. The sway of sundry parameters on velocity, temperature, concentration, shear stress, temperature gradient and concentration gradient has been premeditated, and numerical results are presented graphically and in tabular form. Comparison amid the previously published results, and the current numerical results are made for the limiting cases, which are found to be in a virtuous agreement.

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“…As a new mathematical method for processing various default data, the big data mining theory has been widely applied in the fault diagnosis of electric transformers. In the current studies, the big data mining and artificial intelligence technology 18 have been combined, which has dramatically improved the accuracy of the health status diagnosis for distribution transformers. However, this type of optimization algorithms has the defect that the reduction degree of data discretization is not high 19…”

Section: Introductionmentioning

confidence: 99%

Health status diagnosis of distribution transformers based on big data mining

Wang

Chen

et al. 2019

Trans Emerging Tel Tech

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In the fault detection technology of distribution transformer, the traditional artificial intelligence algorithm has been unable to achieve its efficient analysis and processing, but also unable to achieve the elimination of misdiagnosis caused by improper interval segmentation in the process of fault diagnosis of distribution transformer. In a word, the problem that always exists in transformer fault diagnosis technology is the problem of discretization of fault data. In order to solve this problem, this paper creatively proposes a health condition diagnosis method of distribution transformer based on large data. This method innovatively proposes that the dissolved gas analysis value of distribution transformer is the conditional attribute, and the fault type is the decision attribute, and the fault decision table is established. The continuous attribute data in the decision table are discretized by using the optimization behavior of large data sets. Subsequently, the discretized decision table is simplified by using the big data theory, and the decision table of fault diagnosis rules is established, which greatly simplifies the difficulty of attribute simplification of decision table and makes diagnosis more convenient. Finally, an example shows that the proposed method can effectively discretize and reduce samples. Compared with traditional methods, it improves the accuracy of fault diagnosis.

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Analysis of thermophoresis and Brownian motion effect in heat transfer for nanofluid immersed distribution transformer

Cited by 15 publications

References 24 publications

Numerical Analysis of Thermophoresis of a Charged Spheroidal Colloid in Aqueous Media

Numerical Analysis of Thermophoresis of a Charged Spheroidal Colloid in Aqueous Media

Influence of Soret and Dufour effects on unsteady 3D MHD slip flow of Carreau nanofluid over a slendering stretchable sheet with chemical reaction

Health status diagnosis of distribution transformers based on big data mining

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