Hydraulics of Stratified Flow--First Progress Report--An
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Laws of Similarity in Fluid Mechanics 21
Laws of similarity in fluid mechanics B. Weigand1 & V. Simon2 1Institut für Thermodynamik der Luft- und Raumfahrt (ITLR), Universität Stuttgart, Germany. 2Isringhausen GmbH & Co KG, Lemgo, Germany. Abstract All processes, in nature as well as in technical systems, can be described by fundamental equations—the conservation equations. These equations can be derived using conservation princi- ples and have to be solved for the situation under consideration. This can be done without explicitly investigating the dimensions of the quantities involved. However, an important consideration in all equations used in fluid mechanics and thermodynamics is dimensional homogeneity. One can use the idea of dimensional consistency in order to group variables together into dimensionless parameters which are less numerous than the original variables. This method is known as dimen- sional analysis. This paper starts with a discussion on dimensions and about the pi theorem of Buckingham. This theorem relates the number of quantities with dimensions to the number of dimensionless groups needed to describe a situation. After establishing this basic relationship between quantities with dimensions and dimensionless groups, the conservation equations for processes in fluid mechanics (Cauchy and Navier–Stokes equations, continuity equation, energy equation) are explained. By non-dimensionalizing these equations, certain dimensionless groups appear (e.g. Reynolds number, Froude number, Grashof number, Weber number, Prandtl number). The physical significance and importance of these groups are explained and the simplifications of the underlying equations for large or small dimensionless parameters are described. Finally, some examples for selected processes in nature and engineering are given to illustrate the method. 1 Introduction If we compare a small leaf with a large one, or a child with its parents, we have the feeling that a ‘similarity’ of some sort exists. -
Constraints on the Magnetic Buoyancy Instabilities of a Shear-Generated Magnetic Layer
Submitted to The Astrophysical Journal Constraints on the magnetic buoyancy instabilities of a shear-generated magnetic layer Geoffrey M. Vasil JILA and Dept. of Atmospheric & Oceanic Sciences, University of Colorado, Boulder, CO 80309-0440 Nicholas H. Brummell Dept. of Applied Mathematics & Statistics, University of California, Santa Cruz, CA 95064 [email protected] ABSTRACT In a recent paper (Vasil & Brummell 2008), we found that the action of vertical (radial) shear on the vertical component of poloidal magnetic field could induce magnetic buoyancy instabilities that produced rising, undulating tubular magnetic structures as often envisaged arising from the solar tachocline, but only under extreme circumstances. Herein, we examine, in greater detail, the reasons underpinning the difficulties in obtaining magnetic buoyancy. Under a variety of assumptions about the maintenance of the shear, we herein discuss some analytic limits on the ability of the Ω-effect to produce toroidal magnetic field. Firstly, we consider the Ω-effect in a local time-dependent context, where an unmaintained shear is allowed to build a magnetic layer over time. In this case, we find amplitude estimates of the magnetic field made through such a process in terms of the shear-flow Richardson number. Secondly, we consider the Ω-effect in a local time-independent context, where the shear is forced, such that under certain circumstances it would be maintained. In this situation, we derive a variety of mathematical bounds on the toroidal magnetic energy that can be realized, and its gradients, in terms of the magnitude and the magnetic Prandtl number. This result implies that at low σM , unreasonably strong shear flows must be forced to produce magnetic buoyancy, as was found in our earlier paper. -
Laboratory Studies of Turbulent Mixing J.A
Laboratory Studies of Turbulent Mixing J.A. Whitehead Woods Hole Oceanographic Institution, Woods Hole, MA, USA Laboratory measurements are required to determine the rates of turbulent mixing and dissipation within flows of stratified fluid. Rates based on other methods (theory, numerical approaches, and direct ocean measurements) require models based on assumptions that are suggested, but not thoroughly verified in the laboratory. An exception to all this is recently provided by direct numerical simulations (DNS) mentioned near the end of this article. Experiments have been conducted with many different devices. Results span a wide range of gradient or bulk Richardson number and more limited ranges of Reynolds number and Schmidt number, which are the three most relevant dimensionless numbers. Both layered and continuously stratified flows have been investigated, and velocity profiles include smooth ones, jets, and clusters of eddies from stirrers or grids. The dependence of dissipation through almost all ranges of Richardson number is extensively documented. The buoyancy flux ratio is the turbulent kinetic energy loss from raising the potential energy of the strata to loss of kinetic energy by viscous dissipation. It rises from zero at small Richardson number to values of about 0.1 at Richardson number equal to 1, and then falls off for greater values. At Richardson number greater than 1, a wide range of power laws spanning the range from −0.5 to −1.5 are found to fit data for different experiments. Considerable layering is found at larger values, which causes flux clustering and may explain both the relatively large scatter in the data as well as the wide range of proposed power laws. -
Applied Fluid Dynamics Handbook
APPLIED FLUID DYNAMICS HANDBOOK ROBERT D. BLEVINS H iMhnisdia ttodisdiule Darmstadt Fachbereich Mechanik 'rw.-Nr.. [VNR1 VAN NOSTRAND REINHOLD COMPANY ' ' New York Contents Preface / v 5.4 The Bernoulli Equations / 29 5.4.1 Presentation of the Equations / 29 1. Definitions / 1 5.4.2 Example of the Bernoulli Equations / 30 5.5 Conservation of Momentum / 32 2. Symbols / 5 5.5.1 The Momentum Equations / 32 5.5.2 Examples of Conservation of 3. Units / 6 Momentum / 33 4. Dimensional Analysis / 8 4.1 Introduction / 8 6. Pipe and Duct Flow / 38 4.2 Boundary Geometry / 8 6.1 General Considerations / 38 4.3 Euler Number / 10 6.1.1 General Assumptions / 38 4.4 Reynolds Number / 10 6.1.2 Principles of Pipe Flow / 38 4.5 Mach Number / 11 6.2 Velocity Profiles for Fully Developed Pipe 4.6 Froude Number / 11 Flow / 39 4.7 Weber Number / 11 6.2.1 Inlet Length / 39 4.8 Cavitation Number / 12 6.2.2 Fully Developed Profiles / 40 4.9 Richardson Number / 12 6.3 Straight Uniform Pipes and Ducts / 42 4.10 Rayleigh Number / 12 6.3.1 General Form for Incompressible 4.11 Strouhal Number / 12 Flow / 42 4.12 Kolmogoroff Scales / 13 6.3.2 Friction Factor for Laminar Flow 4.13 Application / 13 (Re<2000) / 42 4.13.1 Then-Theorem / 13 6.3.3 Friction Factor for Transitional Flow 4.13.2 Example: Model Testing a Nuclear (2000 <Re <4000) / 48 Reactor / 14 6.3.4 Friction Factor for Turbulent Flow 4.13.3 Example: Model Testing of a (Re>4000) / 50 Surfboard / 15 6.4 Curved Pipes and Bends / 55 6.4.1 General Form ./ 55 5. -
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. -
Global Stability of Buoyant Jets and Plumes
This draft was prepared using the LaTeX style file belonging to the Journal of Fluid Mechanics 1 Global stability of buoyant jets and plumes R. V. K. Chakravarthy, L. Lesshafft and P. Huerre Laboratoire d’Hydrodynamique, CNRS/Ecole´ polytechnique, 91128 Palaiseau, France. (Received xx; revised xx; accepted xx) The linear global stability of laminar buoyant jets and plumes is investigated under the low Mach number approximation. For Richardson numbers in the range 10−4 6 Ri 6 103 and density ratios S = ρ∞/ρjet between 1.05 and 7, only axisymmetric perturbations are found to exhibit global instability, consistent with experimental observations in helium jets. By varying the Richardson number over seven decades, the effects of buoyancy on the base flow and on the instability dynamics are characterised, and distinct behaviour is observed in the low-Ri (jet) and in the high-Ri (plume) regimes. A sensitivity analysis indicates that different physical mechanisms are responsible for the global instability dynamics in both regimes. In buoyant jets at low Richardson number, the baroclinic torque enhances the basic shear instability, whereas buoyancy provides the dominant instability mechanism in plumes at high Richardson number. The onset of axisymmetric global instability in both regimes is consistent with the presence of absolute instability. While absolute instability also occurs for helical perturbations, it appears to be too weak or too localised in order to give rise to a global instability. 1. Introduction Vertical injection of light fluid into a denser ambient creates a flow that either bears the characteristics of a jet, if the injected momentum is dominant over the buoyant forces, or those of a plume, if the momentum that is generated by buoyancy is dominant over the momentum that is imparted at the orifice. -
CFD Analysis of Heat Transfer and Wind Shear Near Air-Water Interface Zimeng Wu Clemson University, [email protected]
Clemson University TigerPrints All Theses Theses 5-2019 CFD Analysis of Heat Transfer and Wind Shear near Air-Water Interface Zimeng Wu Clemson University, [email protected] Follow this and additional works at: https://tigerprints.clemson.edu/all_theses Recommended Citation Wu, Zimeng, "CFD Analysis of Heat Transfer and Wind Shear near Air-Water Interface" (2019). All Theses. 3049. https://tigerprints.clemson.edu/all_theses/3049 This Thesis is brought to you for free and open access by the Theses at TigerPrints. It has been accepted for inclusion in All Theses by an authorized administrator of TigerPrints. For more information, please contact [email protected]. CFD ANALYSIS OF HEAT TRANSFER AND WIND SHEAR NEAR AIR-WATER INTERFACE A Thesis Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Master of Science Civil Engineering by Zimeng Wu May 2019 Accepted by: Dr. Abdul Khan, Committee Chair Dr. Nigel Kaye, Co-committee Chair Dr. Ashok Mishra, Committee Member ABSTRACT This research was undertaken to examine a problem with respect to heat transfer and fluid dynamics, and this problem was simulated by CFD (Computational Fluid Dynamics). A tank of water with high initial temperature was exposed to an atmosphere with lower temperature than the water, which produced heat transfer at the air-water interface. The air had various magnitudes of velocity for different cases, which also generated wind shear near the interface. These two factors interacted and eventually got balanced for both thermodynamics and kinematics. The cooling plumes were observed in the initial stage when heat transfer was large due to the large difference of temperature between air and water. -
Asymmetrical Thermal Boundary Condition Influence on the Flow
fluids Article Asymmetrical Thermal Boundary Condition Influence on the Flow Structure and Heat Transfer Performance of Paramagnetic Fluid-Forced Convection in the Strong Magnetic Field Lukasz Pleskacz , Elzbieta Fornalik-Wajs * and Sebastian Gurgul Department of Fundamental Research in Energy Engineering, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Kraków, Poland; [email protected] (L.P.); [email protected] (S.G.) * Correspondence: [email protected] Received: 15 November 2020; Accepted: 14 December 2020; Published: 16 December 2020 Abstract: Continuous interest in space journeys opens the research fields, which might be useful in non-terrestrial conditions. Due to the lack of the gravitational force, there will be a need to force the flow for mixing or heat transfer. Strong magnetic field offers the conditions, which can help to obtain the flow. In light of this origin, presented paper discusses the dually modified Graetz-Brinkman problem. The modifications were related to the presence of the magnetic field influencing the flow and asymmetrical thermal boundary condition. Dimensionless numerical analysis was performed, and two dimensionless numbers (magnetic Grashof number and magnetic Richardson number) were defined for paramagnetic fluid flow. The results revealed the heat transfer enhancement due to the strong magnetic field influence accompanied by possible but not essential flow structure modifications. On the other hand, the flow structure changes can be utilized to prevent the solid particles’ sedimentation. The explanation of the heat transfer enhancement including energy budget and vorticity distribution was presented. Keywords: computational fluid dynamics; strong magnetic field; thermo-magnetic convection; forced convection; Nusselt number; magnetic Richardson number 1. -
Numerical Simulation of the Natural, Forced and Mixed Convection in a Tunnel with a Flat Track of Sinusoidal Shape and a Roof Opening
E3S Web of Conferences 85, 02001 (2019) https://doi.org/10.1051/e3sconf/20198502001 EENVIRO 2018 Numerical simulation of the natural, forced and mixed convection in a tunnel with a flat track of sinusoidal shape and a roof opening Oumar Drame1,*, Cheikh Mbow1, Florin Bode2, Samba Dia1, and Omar Ngor Thiam1 1Cheikh Anta Diop University of Dakar, Faculty of Science and Technology Department of Physics; fluid mechanics laboratory and applications BP 5005 Dakar-Fann 2Technical University of Cluj-Napoca, Dept. of Mechanical Engineering, Bd. Muncii 103-105, 400641, Cluj-Napoca, Romani Abstract. In this work, we studied the mixed convection of the airflow in a tunnel open at both ends. The tunnel has a sinusoidal trace and the horizontal ceiling is provided with an opening in the center. The tunnel floor is uniformly heated. Although of interest for many industrial applications, the configuration of this study has been studied very little from an academic point of view. Coupled equations of Naiver-Stokes and energy are solved numerically by the finite volume method with the Boussinesq hypothesis. We analyzed the effect of the parameters that characterize heat transfer, and the flow structure. Several situations have been considered by varying the Richardson number (1.3610-3≤Ri≤2.17.104) for a Prandtl number Pr = 0.71. Nomenclature Nu Nusselt number; Pr a amplitude of the sinusoidal part (m) Prandlt number; -2 gp gravitational acceleration (ms ) PeT Peclet number; height between the ceiling and the bottom of Re Reynolds number; h the sinusoid -
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. -
Dimensional Analysis Autumn 2013
TOPIC T3: DIMENSIONAL ANALYSIS AUTUMN 2013 Objectives (1) Be able to determine the dimensions of physical quantities in terms of fundamental dimensions. (2) Understand the Principle of Dimensional Homogeneity and its use in checking equations and reducing physical problems. (3) Be able to carry out a formal dimensional analysis using Buckingham’s Pi Theorem. (4) Understand the requirements of physical modelling and its limitations. 1. What is dimensional analysis? 2. Dimensions 2.1 Dimensions and units 2.2 Primary dimensions 2.3 Dimensions of derived quantities 2.4 Working out dimensions 2.5 Alternative choices for primary dimensions 3. Formal procedure for dimensional analysis 3.1 Dimensional homogeneity 3.2 Buckingham’s Pi theorem 3.3 Applications 4. Physical modelling 4.1 Method 4.2 Incomplete similarity (“scale effects”) 4.3 Froude-number scaling 5. Non-dimensional groups in fluid mechanics References White (2011) – Chapter 5 Hamill (2011) – Chapter 10 Chadwick and Morfett (2013) – Chapter 11 Massey (2011) – Chapter 5 Hydraulics 2 T3-1 David Apsley 1. WHAT IS DIMENSIONAL ANALYSIS? Dimensional analysis is a means of simplifying a physical problem by appealing to dimensional homogeneity to reduce the number of relevant variables. It is particularly useful for: presenting and interpreting experimental data; attacking problems not amenable to a direct theoretical solution; checking equations; establishing the relative importance of particular physical phenomena; physical modelling. Example. The drag force F per unit length on a long smooth cylinder is a function of air speed U, density ρ, diameter D and viscosity μ. However, instead of having to draw hundreds of graphs portraying its variation with all combinations of these parameters, dimensional analysis tells us that the problem can be reduced to a single dimensionless relationship cD f (Re) where cD is the drag coefficient and Re is the Reynolds number. -
Effects of Reynolds Number on the Energy Conversion and Near-Wake Dynamics of a High Solidity Vertical-Axis Cross-Flow Turbine
Article Effects of Reynolds Number on the Energy Conversion and Near-Wake Dynamics of a High Solidity Vertical-Axis Cross-Flow Turbine Peter Bachant and Martin Wosnik * Center for Ocean Renewable Energy, University of New Hampshire, 24 Colovos Rd., Durham, NH 03824, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-603-862-1891 Academic Editor: Sukanta Basu Received: 1 November 2015; Accepted: 15 January 2016; Published: 26 January 2016 Abstract: Experiments were performed with a large laboratory-scale high solidity cross-flow turbine to investigate Reynolds number effects on performance and wake characteristics and to establish scale thresholds for physical and numerical modeling of individual devices and arrays. It was demonstrated that the performance of the cross-flow turbine becomes essentially Re-independent 6 at a Reynolds number based on the rotor diameter ReD ≈ 10 or an approximate average Reynolds 5 number based on the blade chord length Rec ≈ 2 × 10 . A simple model that calculates the peak torque coefficient from static foil data and cross-flow turbine kinematics was shown to be a reasonable predictor for Reynolds number dependence of an actual cross-flow turbine operating under dynamic conditions. Mean velocity and turbulence measurements in the near-wake showed subtle differences over the range of Re investigated. However, when transport terms for the streamwise momentum and mean kinetic energy were calculated, a similar Re threshold was revealed. These results imply 6 that physical model studies of cross-flow turbines should achieve ReD ∼ 10 to properly approximate both the performance and wake dynamics of full-scale devices and arrays.