scholarly journals Upside/Downside statistical mechanics of nonequilibrium Brownian motion. II. Heat transfer and energy partitioning of a free particle

2018 ◽  
Vol 149 (10) ◽  
pp. 104103
Author(s):  
Galen T. Craven ◽  
Renai Chen ◽  
Abraham Nitzan
Keyword(s):  
Heat Transfer ◽  
Brownian Motion ◽  
Statistical Mechanics ◽  
Free Particle ◽  
Energy Partitioning

Numerical Simulation for Microconvection Around Nano-Particle With Brownian Motion in Liquid

2003 ◽  
Author(s):  
B. X. Wang ◽  
H. Li ◽  
X. F. Peng ◽  
L. X. Yang
Keyword(s):  
Heat Transfer ◽  
Numerical Simulation ◽  
Brownian Motion ◽  
Numerical Model ◽  
Temperature Gradient ◽  
Transfer Process ◽  
Heat Transfer Process ◽  
Nano Particles ◽  
Analytic Method ◽  
Nano Particle

The development of a numerical model for analyzing the effect of the nano-particles’ Brownian motion on the heat transfer is described. By using the Maxwell velocity distribution relations to calculate the most possible velocity of fluid molecules at certain temperature gradient location around the nano-particle, the interaction between fluid molecules and one single nano-particle is analyzed and calculated. Based on this, a syntonic system is proposed and the coupled effect that Brownian motion of nano-particles has on fluid molecules is simulated. This is used to formulate a reasonable analytic method, facilitating laboratory study. The results provide the essential features of the heat transfer process, contributed by micro-convection to be considered.

Possible Mechanisms for Thermal Conductivity Enhancement in Nanofluids

2006 ◽  
Author(s):  
Amit Gupta ◽  
Xuan Wu ◽  
Ranganathan Kumar
Keyword(s):  
Heat Transfer ◽  
Thermal Conductivity ◽  
Brownian Motion ◽  
Brownian Dynamics ◽  
Lattice Vibration ◽  
Experimental Studies ◽  
High Heat ◽  
Conductivity Enhancement ◽  
High Heat Transfer ◽  
Dynamics Simulations

This study discusses the merits of various physical mechanisms that are responsible for enhancing the heat transfer in nanofluids. Experimental studies have cemented the claim that ‘seeding’ liquids with nanoparticles can increase the thermal conductivity of the nanofluid by up to 40% for metallic and oxide nanoparticles dispersed in a base liquid. Experiments have also shown that the rise in conductivity of the nanofluid is highly dependent on the size and concentration of the nanoparticles. On the theoretical side, traditional models like Maxwell or Hamilton-Crosser models cannot explain this unusually high heat transfer. Several mechanisms have been postulated in the literature such as Brownian motion, thermal diffusion in nanoparticles and thermal interaction of nanoparticles with the surrounding fluid, the formation of an ordered liquid layer on the surface of the nanoparticle and microconvection. This study concentrates on 3 possible mechanisms: Brownian dynamics, microconvection and lattice vibration of nanoparticles in the fluid. By considering two nanofluids, copper particles dispersed in ethylene glycol, and silica in water, it is determined that translational Brownian motion of the nanoparticles, presence of an interparticle potential and the microconvection heat transfer are mechanisms that play only a smaller role in the enhancement of thermal conductivity. On the other hand, the lattice vibrations, determined by molecular dynamics simulations show a great deal of promise in increasing the thermal conductivity by as much as 23%. In a simplistic sense, the lattice vibration can be regarded as a means to simulate the phononic transport from solid to liquid at the interface.

Impact of Stefan blowing and magnetic dipole on bio-convective flow of Maxwell nanofluid over a stretching sheet

2021 ◽  
pp. 095440892110581
Author(s):  
A. Alhadhrami ◽  
Hassan A. H. Alzahrani ◽  
B. M. Prasanna ◽  
N. Madhukeshwara ◽  
K. C. Rajendraprasad ◽  
...  
Keyword(s):  
Heat Transfer ◽  
Brownian Motion ◽  
Magnetic Dipole ◽  
Stretching Sheet ◽  
High Heat ◽  
Hard Drives ◽  
Linear System Of Equations ◽  
High Heat Transfer ◽  
Non Linear System ◽  
The Impact

The features of ferromagnetic fluids make it supportive for an extensive usage in loudspeakers, magnetic resonance imaging, computer hard drives, directing of magnetic drug and magnetic hyperthermia. Owing to all such potential applications, the current investigation is to understand the relationship between the thermal distribution, magnetic field and resulting fluid flow of Maxwell liquid over a stretching sheet. Investigation of thermal energy and concentration is carried out in the presence of thermal radiation, non-uniform heat sink/source, chemical reaction, Stefan blowing, magnetic dipole, thermophoresis and Brownian motion. Also, microorganisms are considered just to stabilize the suspended nanoparticles. Boundary layer approximation is employed during mathematical derivation. Based on a new constitutive relation, the governing equations are formulated and are reduced into a coupled non-linear system of equations using appropriate transformations. Further, these equations are solved numerically using fourth-order Runge–Kutta method with shooting technique. The impact of involved parameters is discussed and analysed graphically. Outcomes disclose that Newtonian liquid shows high heat transfer when compared to non-Newtonian (Maxwell) liquid for increased values of Brownian motion and thermophoresis parameters. Increased values of Peclet number declines the rate of gyrotactic microorganisms. Finally, an increase in Brownian and thermophoresis motion parameters declines the rate of heat transfer.

scholarly journals SYMMETRY REDUCTION OF BROWNIAN MOTION AND QUANTUM CALOGERO–MOSER MODELS

2012 ◽  
Vol 13 (01) ◽  
pp. 1250007
Author(s):  
SIMON HOCHGERNER
Keyword(s):  
Brownian Motion ◽  
Schrödinger Equation ◽  
Jacobi Equation ◽  
Schrodinger Equation ◽  
Free Particle ◽  
Symmetry Reduction ◽  
Reduction Scheme ◽  
Polar Actions ◽  
Stochastic Setting ◽  
Hamilton Jacobi Equation

Let Q be a Riemannian G-manifold. This paper is concerned with the symmetry reduction of Brownian motion in Q and ramifications thereof in a Hamiltonian context. Specializing to the case of polar actions, we discuss various versions of the stochastic Hamilton–Jacobi equation associated to the symmetry reduction of Brownian motion and observe some similarities to the Schrödinger equation of the quantum–free particle reduction as described by Feher and Pusztai [10]. As an application we use this reduction scheme to derive examples of quantum Calogero–Moser systems from a stochastic setting.

scholarly journals Numerical Prediction of Heat Transfer Characteristics of Nanofluids in a Minichannel Flow

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Arjumand Adil ◽  
Sonam Gupta ◽  
Pradyumna Ghosh
Keyword(s):  
Heat Transfer ◽  
Brownian Motion ◽  
Pressure Drop ◽  
Laminar Flow ◽  
Computational Model ◽  
Flow Regime ◽  
Cfd Simulation ◽  
Computational Results ◽  
Heat Transfer Characteristics ◽  
Simulation Process

CFD simulation of the heat transfer and pressure drop characteristics of different nanofluids in a minichannel flow has been explained using FLUENT version 6.3.26. Different nanofluids with nanoparticles of Al2O3, CuO, SiO2, and TiO2have been used in the simulation process. A comparison of the experimental and computational results has been made for the heat transfer and pressure drop characteristics for the case of Al2O3-water nanofluid for the laminar flow. Also, computations have been made by considering Brownian motion as well as without considering Brownian motion of the nanoparticles. After verification of the computational model with the experimental results for Al2O3-water nanofluid, the simulations were performed for the same experimental readings for different nanofluids in the laminar flow regime to find out the heat transfer and pressure drop characteristics.

Brownian Motion

2018 ◽  
pp. 1-24
Author(s):  
Giovanni Zocchi
Keyword(s):  
Brownian Motion ◽  
Statistical Mechanics ◽  
Concentration Gradient ◽  
Nonequilibrium Statistical Mechanics ◽  
Thermal Fluctuations ◽  
Nonequilibrium System ◽  
Individual Particle ◽  
Equilibrium Concept ◽  
Self Diffusion ◽  
Main Ideas

This chapter provides an introduction to the main ideas of Brownian motion. Brownian motion connects equilibrium and nonequilibrium statistical mechanics. It connects diffusion—a nonequilibrium phenomenon—with thermal fluctuations—an equilibrium concept. More precisely, diffusion with a net flow of particles, driven by a concentration gradient, pertains to a nonequilibrium system, since there is a net current. Without a concentration gradient, the system is macroscopically in equilibrium, but each individual particle undergoes self-diffusion just the same. In this sense, Brownian motion is at the border of equilibrium and nonequilibrium statistical mechanics.

Free convection in a square porous cavity filled with a nanofluid using thermal non equilibrium and Buongiorno models

2016 ◽  
Vol 26 (3/4) ◽  
pp. 671-693 ◽  
Author(s):  
Ioan Pop ◽  
Mohammad Ghalambaz ◽  
Mikhail Sheremet
Keyword(s):  
Heat Transfer ◽  
Nusselt Number ◽  
Brownian Motion ◽  
Base Fluid ◽  
Average Nusselt Number ◽  
Solid Phase ◽  
Porous Matrix ◽  
Governing Equations ◽  
Content Type ◽  
Brownian Motion And Thermophoresis

Purpose – The purpose of this paper is to theoretically analysis the steady-state natural convection flow and heat transfer of nanofluids in a square enclosure filled with a porous medium saturated with a nanofluid considering local thermal non-equilibrium (LTNE) effects. Different local temperatures for the solid phase of the nanoparticles, the solid phase of porous matrix and the liquid phase of the base fluid are taken into account. Design/methodology/approach – The Buongiorno’s model, incorporating the Brownian motion and thermophoresis effects, is utilized to take into account the migration of nanoparticles. Using appropriate non-dimensional variables, the governing equations are transformed into the non-dimensional form, and the finite element method is utilized to solve the governing equations. Findings – The results show that the increase of buoyancy ratio parameter (Nr) decreases the magnitude of average Nusselt number. The increase of the nanoparticles-fluid interface heat transfer parameter (Nhp) increases the average Nusselt number for nanoparticles and decreases the average Nusselt number for the base fluid. The nanofluid and porous matrix with large values of modified thermal capacity ratios (γ p and γ s ) are of interest for heat transfer applications. Originality/value – The three phases of nanoparticles, base fluid and the porous matrix are in the LTNE. The effect of mass transfer of nanoparticles due to the Brownian motion and thermophoresis effects are also taken into account.

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