Unsteady Thermal Maxwell Power Law Nanofluid Flow Subject to Forced
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Chapter 4 Solutal Marangoni Convection: Mass Transfer
137 Chapter 4 Solutal Marangoni Convection: Mass Transfer Characteristics 4.1 Introduction In chapter 2, the microgravity experiments with V-shaped containers have been described. In chapter 3, the evolution of Marangoni flow and concentration patterns in these V-shaped containers have been modelled numerically. A reasonable agreement between experiment and model was obtained. In this chapter, the model that has been developed in chapter 3 is used to predict mass transfer characteristics for gas-liquid systems with a non- deformable interface. That is, the influence of Marangoni convection on the gas-liquid mass transfer is examined. In this way, an attempt is made to establish a link between the microgravity experiments and a better understanding of the relation between the Marangoni effect and mass transfer. The parameters varied in this study are the Marangoni, Schmidt and Biot numbers. Literature review Experimentally, the influence of the Marangoni effect on the mass transfer coefficient in gas-liquid systems has been studied by several authors [1, 2, 3, 4, 5, 6, 7]. In the most relevant studies [2, 5, 7], the enhancement of the liquid side mass transfer coefficient kL was correlated by equations of the following type: k L f = * (1) k L n æ Ma ö f = ç ÷ (2) è Ma C ø * In these equations f is the enhancement factor, k L the liquid side mass transfer coefficient in the absence of interfacial turbulence, Ma the Marangoni number, Mac the critical Marangoni number, and n an empirical parameter. Equation (2) is only valid when Ma > Mac. For values of Ma smaller than Mac, the enhancement factor is equal to 1. -
Use of a Fictitious Marangoni Number for Natural
a Use of a fictitious Marangoni number for natural convection simulation Francisco J. Arias∗ and Geoffrey T. Parks Department of Engineering, University of Cambridge Trumpington Street, Cambridge, CB2 1PZ, United Kingdom In this paper, a method based on the use of a fictitious Marangoni number is proposed for the simulation of natural thermocapillary convection as an alternative to the traditional effective diffusivity approach. The fundamental difference between these two methods is that the new method adopts convective mass flows in simulating natural convection. Heat transfer in the natural convection simulation is calculated through the mass transport. Therefore, empirical Nusselt num- bers correlations required in the effective diffusivity method are eliminated. This represents a clear advantage in the context of design studies where flexibility in varying the geometry unconstrained by the availability of appropriate correlations is highly desirable. The new method is demonstrated using a simple geometrical model. An analytical expression of the fictitious Marangoni number associated with convection between vertical plates is derived and a computational fluid dynamics (CFD) simulation is performed to study the efficacy of the proposed method. The results show that the new method can approximate real natural convection quite accurately and can be used to simulate the convective flow in complex, obstructed or finned structures where the specific Nusselt correlation is not known. aKeywords. Natural convection, Effective thermal conductivity, Marangoni convection, Compu- tational Fluid Dynamics (CFD) I. INTRODUCTION ship for the specific geometry, such as finned structures; however, these correlations are often not available. This Natural convection in enclosed cavities is of great im- then motivates us to find an alternative approach that portance in many engineering and scientific applications does not require knowledge of Nusselt number correla- such as energy transfer, boilers, nuclear reactor systems, tions. -
Turbulent Boundary Layers 7 - 1 David Apsley 7.2.3 Radiation
7. HEAT TRANSFER SPRING 2009 7.1 Definitions 7.2 Modes of heat transfer 7.3 The Prandtl number 7.4 Dimensionless numbers in free and forced convection 7.5 The energy equation 7.6 Laminar boundary layers with isothermal walls 7.7 Temperature profile in a turbulent boundary layer 7.8 Heat-transfer coefficients 7.9 Temperature integral results 7.10 Engineering heat-transfer calculations 7.11 References Examples 7.1 Definitions Heat transfer is energy in transit due to a temperature difference. The heat flux qh is the rate of heat transfer per unit area. 7.2 Modes of Heat Transfer 7.2.1 Conduction Heat transfer due to molecular activity in the absence of a bulk motion. Fourier ’s Law = − ∇ qh kh T (1) kh is the conductivity of heat . –1 –1 –1 –1 At 20 ºC, kh(water) = 0.604 W m K ; kh(air) = 0.0257 W m K . 7.2.2 Advection Heat transfer due to bulk motion of fluid. = − qh c p (T Te )u (2) cp is the specific heat capacity (at constant pressure). Te is a reference (usually the external or free-stream) temperature. –1 –1 –1 –1 At 20 ºC, cp(water) = 4182 J kg K ; cp(air) = 1007 J kg K . Turbulent Boundary Layers 7 - 1 David Apsley 7.2.3 Radiation Heat transfer by emission of electromagnetic radiation. Stefan-Boltzmann Law = 4 qh Ts (3) (= 5.670 ×10 -8 W m–2 K–4) is the Stefan-Boltzmann constant . is the emissivity ( = 1 for a perfect black body) 7.2.4 Free and Forced Convection For fluids, conduction and advection are usually combined as convection , which may be either: forced convection – flow driven by external means; free (or natural ) convection – flow driven by buoyancy. -
Chapter 5 Dimensional Analysis and Similarity
Chapter 5 Dimensional Analysis and Similarity Motivation. In this chapter we discuss the planning, presentation, and interpretation of experimental data. We shall try to convince you that such data are best presented in dimensionless form. Experiments which might result in tables of output, or even mul- tiple volumes of tables, might be reduced to a single set of curves—or even a single curve—when suitably nondimensionalized. The technique for doing this is dimensional analysis. Chapter 3 presented gross control-volume balances of mass, momentum, and en- ergy which led to estimates of global parameters: mass flow, force, torque, total heat transfer. Chapter 4 presented infinitesimal balances which led to the basic partial dif- ferential equations of fluid flow and some particular solutions. These two chapters cov- ered analytical techniques, which are limited to fairly simple geometries and well- defined boundary conditions. Probably one-third of fluid-flow problems can be attacked in this analytical or theoretical manner. The other two-thirds of all fluid problems are too complex, both geometrically and physically, to be solved analytically. They must be tested by experiment. Their behav- ior is reported as experimental data. Such data are much more useful if they are ex- pressed in compact, economic form. Graphs are especially useful, since tabulated data cannot be absorbed, nor can the trends and rates of change be observed, by most en- gineering eyes. These are the motivations for dimensional analysis. The technique is traditional in fluid mechanics and is useful in all engineering and physical sciences, with notable uses also seen in the biological and social sciences. -
Mass Transfer with the Marangoni Effect 87 7.1 Objectives
TECHNISCHE UNIVERSITÄT MÜNCHEN Professur für Hydromechanik Numerical investigation of mass transfer at non-miscible interfaces including Marangoni force Tianshi Sun Vollständiger Abdruck der an der Ingenieurfakultät Bau Geo Umwelt der Technischen Universität Munchen zur Erlangung des akademischen Grades eines Doktor-Ingenieurs genehmigten Dissertation. Vorsitzender: Prof. Dr.-Ing. habil. F. Düddeck Prüfer der Dissertation: 1. Prof. Dr.-Ing. M. Manhart 2. Prof. Dr. J.G.M. Kuerten Die Dissertation wurde am 31. 08. 2018 bei der Technischen Universitat München eingereicht und durch die Ingenieurfakultat Bau Geo Umwelt am 11. 12. 2018 angenommen. Zusammenfassung Diese Studie untersucht den mehrphasigen Stofftransport einer nicht-wässrigen flüssigkeit ("Non-aqueous phase liquid", NAPL) im Porenmaßstab, einschließlich der Auswirkungen von Oberflachenspannungs und Marangoni-Kraften. Fur die Mehrphasensträmung wurde die Methode "Conservative Level Set" (CLS) implementiert, um die Grenzflache zu verfol gen, wahrend die Oberflachenspannungskraft mit der Methode "Sharp Surface Tension Force" (SSF) simuliert wird. Zur Messung des Kontaktwinkels zwischen der Oberflache der Flus- sigkeit und der Kontur der Kontaktflaäche wird ein auf der CLS-Methode basierendes Kon taktlinienmodell verwendet; das "Continuum Surface Force" (CSF)-Modell wird zur Model lierung des durch einen Konzentrationsgradienten induzierten Marangoni-Effekts verwendet; ein neues Stofftransfermodell, das einen Quellterm in der Konvektions-Diffusionsgleichungen verwendet, wird zur -
Convective Heat Transfer Due to Thermal Marangoni Flow About Two Bubbles on a Heated Wall Séamus Michael O’Shaughnessy1a, Anthony James Robinson1b
Convective heat transfer due to thermal Marangoni flow about two bubbles on a heated wall Séamus Michael O’Shaughnessy1a, Anthony James Robinson1b 1Department of Mechanical & Manufacturing Engineering Parsons Building, University of Dublin, Trinity College, Dublin 2, Ireland aEmail: Tel: +353 1 896 1061 Fax: +353 1 679 (corresponding author pre-publication) [email protected] 5554 bEmail: [email protected] Tel: +353 1 896 3919 Fax: +353 1 679 (corresponding author post-publication) 5554 Abstract Three dimensional simulations of thermal Marangoni convection about two bubbles situated on a heated wall immersed in a liquid silicone oil layer have been performed to gain some insight into the thermal and flow interactions between them. The distance between the two bubbles’ centres was varied between three and twenty five bubble radii to analyse the influence of the inter-bubble spacing on the flow and temperature fields and the impact upon local wall heat transfer. For zero gravity conditions, it was determined that the local wall heat flux was greatest for the smallest separation of three bubble radii, but that the increase in heat transfer over the whole domain was greatest for a separation of ten bubble radii. When the effects of gravity were included in the model, the behaviour was observed to change between the cases. At large separations between the bubbles, increasing the gravity level was found to decrease the local wall heat flux, which was consistent with two-dimensional work. At small separations however, the increase in gravity led to an increase in the local wall heat flux, which was caused by a buoyancy-driven flow formed by the interaction of secondary vortices. -
Summary of Dimensionless Numbers of Fluid Mechanics and Heat Transfer 1. Nusselt Number Average Nusselt Number: Nul = Convective
Jingwei Zhu http://jingweizhu.weebly.com/course-note.html Summary of Dimensionless Numbers of Fluid Mechanics and Heat Transfer 1. Nusselt number Average Nusselt number: convective heat transfer ℎ퐿 Nu = = L conductive heat transfer 푘 where L is the characteristic length, k is the thermal conductivity of the fluid, h is the convective heat transfer coefficient of the fluid. Selection of the characteristic length should be in the direction of growth (or thickness) of the boundary layer; some examples of characteristic length are: the outer diameter of a cylinder in (external) cross flow (perpendicular to the cylinder axis), the length of a vertical plate undergoing natural convection, or the diameter of a sphere. For complex shapes, the length may be defined as the volume of the fluid body divided by the surface area. The thermal conductivity of the fluid is typically (but not always) evaluated at the film temperature, which for engineering purposes may be calculated as the mean-average of the bulk fluid temperature T∞ and wall surface temperature Tw. Local Nusselt number: hxx Nu = x k The length x is defined to be the distance from the surface boundary to the local point of interest. 2. Prandtl number The Prandtl number Pr is a dimensionless number, named after the German physicist Ludwig Prandtl, defined as the ratio of momentum diffusivity (kinematic viscosity) to thermal diffusivity. That is, the Prandtl number is given as: viscous diffusion rate ν Cpμ Pr = = = thermal diffusion rate α k where: ν: kinematic viscosity, ν = μ/ρ, (SI units : m²/s) k α: thermal diffusivity, α = , (SI units : m²/s) ρCp μ: dynamic viscosity, (SI units : Pa ∗ s = N ∗ s/m²) W k: thermal conductivity, (SI units : ) m∗K J C : specific heat, (SI units : ) p kg∗K ρ: density, (SI units : kg/m³). -
Transient Rayleigh-Bénard-Marangoni Solutal Convection Benoît Trouette, Eric Chénier, F
Transient Rayleigh-Bénard-Marangoni solutal convection Benoît Trouette, Eric Chénier, F. Doumenc, C. Delcarte, B. Guerrier To cite this version: Benoît Trouette, Eric Chénier, F. Doumenc, C. Delcarte, B. Guerrier. Transient Rayleigh-Bénard- Marangoni solutal convection. Physics of Fluids, American Institute of Physics, 2012, 24 (7), pp.074108. 10.1063/1.4733439. hal-00711759 HAL Id: hal-00711759 https://hal-upec-upem.archives-ouvertes.fr/hal-00711759 Submitted on 25 Jun 2012 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Transient Rayleigh-B´enard-Marangoni solutal convection Benoˆıt Trouette,1,2, a) Eric Ch´enier,2, b) Fr´ed´eric Doumenc,3, c) Claudine Delcarte,1, d) and B´eatrice Guerrier3, e) 1)Univ Paris-Sud, CNRS, Lab. LIMSI, Orsay, F-91405 2)Univ Paris-Est, Lab. Mod´elisationet Simulation Multi Echelle, MSME UMR 8208 CNRS, 5 bd Descartes, Marne-la-Vall´ee, F-77454 3)UPMC Univ Paris 06, Univ Paris-Sud, CNRS, Lab. Fast, Orsay, F-91405 Solutal driven flow is studied for a binary solution submitted to solvent evaporation at the upper free surface. Evaporation induces an increase in the solute concen- tration close to the free surface and solutal gradients may induce a convective flow driven by buoyancy and/or surface tension. -
Marangoni Convection in Droplets on Superhydrophobic Surfaces
Under consideration for publication in J. Fluid Mech. 1 Marangoni convection in droplets on superhydrophobic surfaces By DANIEL TAM1, VOLKMAR von ARNIM2 †, G. H. McKINLEY2 A N D A. E. HOSOI2 1Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA 2Hatsopoulos Microfluids Laboratory, Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA (Received ?? and in revised form ??) We consider a small droplet of water sitting on top of a heated superhydrophobic sur- face. A toroidal convection pattern develops in which fluid is observed to rise along the surface of the spherical droplet and to accelerate downwards in the interior towards the liquid/solid contact point. The internal dynamics arise due to the presence of a vertical temperature gradient; this leads to a gradient in surface tension which in turn drives fluid away from the contact point along the interface. We develop a solution to this thermocapillary-driven Marangoni flow analytically in terms of streamfunctions. Quan- titative comparisons between analytical and experimental results are presented as well as effective heat transfer coefficients. 1. Introduction Non-wettability, effective heat transfer coefficients and other material properties of hydrophobic surfaces are of interest in many industrial applications, such as efficient condensing design and waterproofing textiles. Since Wenzel (1936) noted seventy years ago that the hydrophobicity of a substrate can be enhanced through a combination of chemical modification and surface roughness, multiple studies have observed a substantial increase in static contact angles by integrating these two strategies. More recently the non-wetting properties of these substrates have been further enhanced and contact angles close to 180◦ have been achieved by introducing nanoscale roughness (e.g. -
On Dimensionless Numbers
chemical engineering research and design 8 6 (2008) 835–868 Contents lists available at ScienceDirect Chemical Engineering Research and Design journal homepage: www.elsevier.com/locate/cherd Review On dimensionless numbers M.C. Ruzicka ∗ Department of Multiphase Reactors, Institute of Chemical Process Fundamentals, Czech Academy of Sciences, Rozvojova 135, 16502 Prague, Czech Republic This contribution is dedicated to Kamil Admiral´ Wichterle, a professor of chemical engineering, who admitted to feel a bit lost in the jungle of the dimensionless numbers, in our seminar at “Za Plıhalovic´ ohradou” abstract The goal is to provide a little review on dimensionless numbers, commonly encountered in chemical engineering. Both their sources are considered: dimensional analysis and scaling of governing equations with boundary con- ditions. The numbers produced by scaling of equation are presented for transport of momentum, heat and mass. Momentum transport is considered in both single-phase and multi-phase flows. The numbers obtained are assigned the physical meaning, and their mutual relations are highlighted. Certain drawbacks of building correlations based on dimensionless numbers are pointed out. © 2008 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved. Keywords: Dimensionless numbers; Dimensional analysis; Scaling of equations; Scaling of boundary conditions; Single-phase flow; Multi-phase flow; Correlations Contents 1. Introduction ................................................................................................................. -
Module 6 : Lecture 1 DIMENSIONAL ANALYSIS (Part – I) Overview
NPTEL – Mechanical – Principle of Fluid Dynamics Module 6 : Lecture 1 DIMENSIONAL ANALYSIS (Part – I) Overview Many practical flow problems of different nature can be solved by using equations and analytical procedures, as discussed in the previous modules. However, solutions of some real flow problems depend heavily on experimental data and the refinements in the analysis are made, based on the measurements. Sometimes, the experimental work in the laboratory is not only time-consuming, but also expensive. So, the dimensional analysis is an important tool that helps in correlating analytical results with experimental data for such unknown flow problems. Also, some dimensionless parameters and scaling laws can be framed in order to predict the prototype behavior from the measurements on the model. The important terms used in this module may be defined as below; Dimensional Analysis: The systematic procedure of identifying the variables in a physical phenomena and correlating them to form a set of dimensionless group is known as dimensional analysis. Dimensional Homogeneity: If an equation truly expresses a proper relationship among variables in a physical process, then it will be dimensionally homogeneous. The equations are correct for any system of units and consequently each group of terms in the equation must have the same dimensional representation. This is also known as the law of dimensional homogeneity. Dimensional variables: These are the quantities, which actually vary during a given case and can be plotted against each other. Dimensional constants: These are normally held constant during a given run. But, they may vary from case to case. Pure constants: They have no dimensions, but, while performing the mathematical manipulation, they can arise. -
Dimensional Analysis and Modeling
cen72367_ch07.qxd 10/29/04 2:27 PM Page 269 CHAPTER DIMENSIONAL ANALYSIS 7 AND MODELING n this chapter, we first review the concepts of dimensions and units. We then review the fundamental principle of dimensional homogeneity, and OBJECTIVES Ishow how it is applied to equations in order to nondimensionalize them When you finish reading this chapter, you and to identify dimensionless groups. We discuss the concept of similarity should be able to between a model and a prototype. We also describe a powerful tool for engi- ■ Develop a better understanding neers and scientists called dimensional analysis, in which the combination of dimensions, units, and of dimensional variables, nondimensional variables, and dimensional con- dimensional homogeneity of equations stants into nondimensional parameters reduces the number of necessary ■ Understand the numerous independent parameters in a problem. We present a step-by-step method for benefits of dimensional analysis obtaining these nondimensional parameters, called the method of repeating ■ Know how to use the method of variables, which is based solely on the dimensions of the variables and con- repeating variables to identify stants. Finally, we apply this technique to several practical problems to illus- nondimensional parameters trate both its utility and its limitations. ■ Understand the concept of dynamic similarity and how to apply it to experimental modeling 269 cen72367_ch07.qxd 10/29/04 2:27 PM Page 270 270 FLUID MECHANICS Length 7–1 ■ DIMENSIONS AND UNITS 3.2 cm A dimension is a measure of a physical quantity (without numerical val- ues), while a unit is a way to assign a number to that dimension.