ME 306 Fluid Mechanics II Part 1 Potential Flow

Total Page:16

File Type:pdf, Size:1020Kb

ME 306 Fluid Mechanics II Part 1 Potential Flow Inviscid (Frictionless) Flow ME 306 Fluid Mechanics II • Continuity and Navier-Stokes equations govern the flow of fluids. • For incompressible flows of Newtonian fluids they are Part 1 훻 ⋅ 푉 = 0 퐷푉 휕푉 휌 = 휌 + 푉 ⋅ 훻 푉 = 휌푔 − 훻푝 + 휇훻2푉 Potential Flow 퐷푡 휕푡 • These equations can be solved analytically only for a few problems. • They can be simplified in various ways. These presentations are prepared by −3 Dr. Cüneyt Sert 휇푤푎푡푒푟 = 10 Pa s • Common fluids such as water and air have small viscosities. 휇 = 2 × 10−5 Pa s Department of Mechanical Engineering 푎푖푟 Middle East Technical University • Neglecting the viscous term (zero shear force) gives the Euler’s equation. Ankara, Turkey 퐷푉 [email protected] 휌 = 휌푔 − 훻푝 퐷푡 You can get the most recent version of this document from Dr. Sert’s web site. • Still difficult get a general analytical solution for the unknowns 푝 and 푉. Please ask for permission before using them to teach. You are not allowed to modify them. 1-1 1-2 Inviscid Flow (cont’d) Inviscid and Irrotational Flow • Bernoulli Equation (BE) is Euler’s equation written along a streamline. • To simplify further we can assume the flow to be irrotational. 푝 푉2 휉 = 2휔 = 훻 × 푉 = 0 (irrotational flow) + + 푧 = constant along a streamline 휌푔 2푔 Vorticity (ksi) Angular velocity Exercise: Starting from the Euler’s equation derive the BE. • Question: What’s the logic behind irrotationality assumption? Inviscid flow away from the object (negligible shear forces) • Irrotationality is about velocity gradients. 휕푤 휕푣 휕푢 휕푤 휕푣 휕푢 휉 = − 푖 + − 푗 + − 푘 = 0 휕푦 휕푧 휕푧 휕푥 휕푥 휕푦 Airfoil or 1 휕푉 휕푉 휕푉 휕푉 1 휕 푟푉 1 휕푉 휉 = 푧 − 휃 푖 + 푟 − 푧 푖 + 휃 − 푟 푖 푟 휕휃 휕푧 푟 휕푧 휕푟 휃 푟 휕푟 푟 휕휃 푧 Adapted from http://web.cecs.pdx.edu/~gerry/class/ME322 Viscous flow close to the object and in the wake of it (non negligible shear forces) 1-3 1-4 Inviscid and Irrotational Flow (cont’d) Inviscid and Irrotational Flow (cont’d) • One special irrotational flow is when all velocity gradients are zero. • In an inviscid flow net shear force acting on a fluid element is zero. • An example is uniform flow such as 푢 = 푈, 푣 = 0, 푤 = 0. 푦 푢 = 푈 • Only pressure and body forces act on the fluid element. But they cannot cause 푣 = 0 푥 rotation because • In many flow fields there will be uniform-like flow regions. 푧 푤 = 0 • pressure forces act perpendicular to the element’s surface. Away from the body, flow has small velocity • body forces act through element’s center of gravity. gradients (uniform-like flow), small shear forces and can remain irrotational. In an inviscid flow, a fluid element Uniform that originates from an irrotational approach flow region will remain irrotational. Airfoil velocity (irrotational) Uniform Close to the body velocity gradients upstream are high, shear forces are high and flow Airfoil flow becomes rotational. (irrotational) Exercise: Sketch the developing flow inside a pipe with uniform entrance and Exercise: Show how a fluid element will rotate inside the developing flow region show the uniform and non-uniform flow regions. of a pipe with uniform entrance. 1-5 1-6 Inviscid and Irrotational Flow (cont’d) BE for Irrotational Flow • In general, flow fields are composed of both Note: There are other Exercise: Repeat the exercise of Slide 1-3 (derive BE) for irrotational flow. factors that can cause • irrotational regions with negligible shear forces rotation, but they are • In an irrotational flow BE is valid between any two points of the flow field, not • and rotational regions with considerable shear forces not as common as viscous effects. necessarily two points on the same streamline. • Sometimes rotational regions will be very thin such as high speed external flow over an airfoil. 1 2 • But still neglecting them and assuming the flow to be totally irrotational would 3 Inviscid, irrotational yield unrealistic results. flow over an object Assuming external flow over a body to be inviscid and irrotational everywhere 퐹drag = ? will result in zero air drag, which is not 푝 푉2 푝 푉2 푝 푉2 correct. This is known as d’Alambert’s + + 푧 = + + 푧 = + + 푧 휌푔 2푔 휌푔 2푔 휌푔 2푔 paradox. 1 2 3 Exercise: What will happen if we assume pipe flow with uniform entrance to be inviscid and irrotational? 1-7 1-8 Velocity Potential (휙) Potential Flow 휕휙 휕휙 • For an irrotational flow : 훻 × 푉 = 0 • For a 2D flow in the 푥푦 plane : 푉 = 훻휙 → 푢 = , 푣 = 휕푥 휕푦 • As studied in ME 210, curl of the gradient of any scalar function is zero. 휕휙 1 휕휙 • For a 2D flow in the 푟휃 plane : 푉 = 훻휙 → 푉푟 = , 푉휃 = 훻 × (훻휙) = 0 휕푟 푟 휕휃 • Using these two equations we can define a velocity potential function (휙) as • If the irrotational flow is also incompressible (In ME 306 we’ll NOT study compressible irrotational flows) 푉 = +훻휙 Continuity Equation : 훻 ⋅ 푉 = 0 Some books use a minus sign so that 휙 decreases in the flow direction, similar to Phi: A scalar function 훻 ⋅ 훻휙 = 0 temperature decreasing in the heat flow called velocity potential 2 direction. But we use plus in this course. 훻 휙 = 0 Laplace’s equation 훻2 = 훻 ⋅ 훻 : Laplace operator • In an irrotational flow field, velocity vector can be expressed as the gradient of a scalar function called the velocity potential. • For an incompressible and irrotational flow, velocity potential satisfies the Laplace’s equation. These flows are called potential flows. 1-9 1-10 Velocity Potential (cont’d) Potential Flow Exercises 휕2휙 휕2휙 Exercise : Using Cauchy Riemann equations show that streamfunction also satisfies In the 푥푦 plane : + = 0 휕푥2 휕푦2 the Laplace’s equation for incompressible, potential flows. • 훻2휙 = 0 2 1 휕 휕휙 1 휕 휙 Exercise : Show that constant streamfunction lines (streamlines) are always In the 푟휃 plane : 푟 + 2 2 = 0 푟 휕푟 휕푟 푟 휕휃 perpendicular to constant velocity potential lines for incompressible, potential flows. Streamfunction • Note that the relation between 푉 and 휙 is similar to that of 푉 and 휓. Exercise : Draw constant velocity potential lines of the following flow fields for which streamlines are shown. Constant velocity potential lines and streamlines drawn together form a flow net. What’s the ‘‘heat transfer’’ analogue of a flow net? Cauchy Riemann Equations Flow near a corner Flow over a cylinder In the 푥푦 plane In the 푟휃 plane 휕휙 휕휙 휕휙 1 휕휙 푢 = 푣 = 푉 = 푉 = 휕푥 휕푦 푟 휕푟 휃 푟 휕휃 휕휓 휕휓 1 휕휓 휕휓 푢 = 푣 = − 푉 = 푉 = − 휕푦 휕푥 푟 푟 휕휃 휃 휕푟 1-11 1-12 Potential Flow Exercises (cont’d) Potential Flow Exercises (cont’d) Outer region Exercise : The two-dimensional flow of a nonviscous, incompressible fluid in the Exercise : A horizontal slice through a tornado is 푦 vicinity of a corner is described by the stream function modeled by two distinct regions. The inner or core Inner 푟 region (0 < 푟 < 푅) is modeled by solid body rotation. region 휓 = 2푟2 sin(2휃) 휃 The outer region (푟 > 푅) is modeled as an irrotational where 휓 has units of m2/s when 푟 is in meters. Assume the fluid density is region of flow. The flow is 2D in the 푟휃-plane, and the 푥 1000 kg/m3 and the 푥푦 plane is horizontal. components of the velocity field are given by a) Determine, if possible, the corresponding velocity potential. 휔푟 0 < 푟 < 푅 Inner b) If the pressure at point 1 on the wall is 30 kPa, what is the pressure at point 2? 푉푟 = 0 , 푉휃 = 휔푅2 푟 > 푅 region Outer region Reference: Munson’s book. 푟 0 푦 where 휔 is the magnitude of the angular -0.2 velocity in the inner region. The ambient -0.4 pressure (far away from the tornado) is 푝 − 푝∞ 2 2 1 equal to 푝∞. Obtain the shown nondimen- 휌휔 푅 -0.6 푟 sional pressure distribution. 0.5 m -0.8 휃 푥 Reference: Çengel’s book. -1 2 0 1 2 3 4 5 1 m 1-13 푟/푅 1-14 Superposition of Elementary Potential Flows 1. Uniform Flow • Laplace’s equation is a linear PDE. • Consider uniform flow in the 푥푦 plane in +푥 direction. • Superposition can be applied to both velocity potential and streamfunction. 푢 = 푈 , 푣 = 0 • Let’s find the equation for velocity potential. Potential flow 1 Potential flow 2 Potential flow 3 휕휙 휕휙 푢 = → 푈 = → 휙 = 푈푥 + 푓(푦) + = 휕푥 휕푥 휕휙 휕휙 푑푓 푣 = → 0 = → = 0 → 푓 = constant 휕푦 휕푦 푑푦 • 휙1 + 휙2 = 휙3 , 휓1 + 휓2 = 휓3 , 푉1 + 푉2 = 푉3 • Taking 푓 = 0 for simplicity • To obtain complicated flow fields we can combine elementary ones such as 휙 = 푈푥 • Uniform flow • Constant 휙 lines correspond to constant 푥 lines, i.e. lines parallel to the 푦 axis. • Line source/sink • Vortex Exercise : Show that streamfunction equation is 휓 = 푈푦 1-15 1-16 1. Uniform Flow (cont’d) 2. Line Source at the Origin • Constant 휙 and constant 휓 lines are shown below. • Consider the 2D flow emerging at the origin of the 푥푦 plane and going radially outward in all directions with a total flow rate per depth of 푞. 푦 View from the top 푦 푥 푥 푦 Streamlines 휓 = 휓1 휓 = 휓0 푥 1 0 휙 휙 푞 : Flow rate per depth = = Constant (Strength of source [m2/s]) 휙 휙 휙 lines 푈 푞 푉 = , 푉 = 0 Exercise : Determine the equations of 휙 and 휓 푦 • Conservation of mass: 푞 = 2휋푟 푉푟 → 푟 2휋푟 휃 for uniform flow in a direction making an angle 푥 of 훽 with the 푥 axis.
Recommended publications
  • Variational Formulation of Fluid and Geophysical Fluid Dynamics
    Advances in Geophysical and Environmental Mechanics and Mathematics Gualtiero Badin Fulvio Crisciani Variational Formulation of Fluid and Geophysical Fluid Dynamics Mechanics, Symmetries and Conservation Laws Advances in Geophysical and Environmental Mechanics and Mathematics Series editor Holger Steeb, Institute of Applied Mechanics (CE), University of Stuttgart, Stuttgart, Germany More information about this series at http://www.springer.com/series/7540 Gualtiero Badin • Fulvio Crisciani Variational Formulation of Fluid and Geophysical Fluid Dynamics Mechanics, Symmetries and Conservation Laws 123 Gualtiero Badin Fulvio Crisciani Universität Hamburg University of Trieste Hamburg Trieste Germany Italy ISSN 1866-8348 ISSN 1866-8356 (electronic) Advances in Geophysical and Environmental Mechanics and Mathematics ISBN 978-3-319-59694-5 ISBN 978-3-319-59695-2 (eBook) DOI 10.1007/978-3-319-59695-2 Library of Congress Control Number: 2017949166 © Springer International Publishing AG 2018 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication.
    [Show full text]
  • Chapter 4: Immersed Body Flow [Pp
    MECH 3492 Fluid Mechanics and Applications Univ. of Manitoba Fall Term, 2017 Chapter 4: Immersed Body Flow [pp. 445-459 (8e), or 374-386 (9e)] Dr. Bing-Chen Wang Dept. of Mechanical Engineering Univ. of Manitoba, Winnipeg, MB, R3T 5V6 When a viscous fluid flow passes a solid body (fully-immersed in the fluid), the body experiences a net force, F, which can be decomposed into two components: a drag force F , which is parallel to the flow direction, and • D a lift force F , which is perpendicular to the flow direction. • L The drag coefficient CD and lift coefficient CL are defined as follows: FD FL CD = 1 2 and CL = 1 2 , (112) 2 ρU A 2 ρU Ap respectively. Here, U is the free-stream velocity, A is the “wetted area” (total surface area in contact with fluid), and Ap is the “planform area” (maximum projected area of an object such as a wing). In the remainder of this section, we focus our attention on the drag forces. As discussed previously, there are two types of drag forces acting on a solid body immersed in a viscous flow: friction drag (also called “viscous drag”), due to the wall friction shear stress exerted on the • surface of a solid body; pressure drag (also called “form drag”), due to the difference in the pressure exerted on the front • and rear surfaces of a solid body. The friction drag and pressure drag on a finite immersed body are defined as FD,vis = τwdA and FD, pres = pdA , (113) ZA ZA Streamwise component respectively.
    [Show full text]
  • Future Directions of Computational Fluid Dynamics
    Future Directions of Computational Fluid Dynamics F. D. Witherden∗ and A. Jameson† Stanford University, Stanford, CA, 94305 For the past fifteen years computational fluid dynamics (CFD) has been on a plateau. Due to the inability of current-generation approaches to accurately predict the dynamics of turbulent separated flows, reliable use of CFD has been restricted to a small regionof the operating design space. In this paper we make the case for large eddy simulations as a means of expanding the envelope of CFD. As part of this we outline several key challenges which must be overcome in order to enable its adoption within industry. Specific issues that we will address include the impact of heterogeneous massively parallel computing hardware, the need for new and novel numerical algorithms, and the increasingly complex nature of methods and their respective implementations. I. Introduction Computational fluid dynamics (CFD) is a relatively young discipline, having emerged during the last50 years. During this period advances in CFD have been paced by advances in the available computational hardware, which have enabled its application to progressively more complex engineering and scientific prob- lems. At this point CFD has revolutionized the design process in the aerospace industry, and its use is pervasive in many other fields of engineering ranging from automobiles to ships to wind energy. Itisalso a key tool for scientific investigation of the physics of fluid motion, and in other branches of sciencesuch as astrophysics. Additionally, throughout its history CFD has been an important incubator for the formu- lation and development of numerical algorithms which have been seminal to advances in other branches of computational physics.
    [Show full text]
  • Potential Flow Theory
    2.016 Hydrodynamics Reading #4 2.016 Hydrodynamics Prof. A.H. Techet Potential Flow Theory “When a flow is both frictionless and irrotational, pleasant things happen.” –F.M. White, Fluid Mechanics 4th ed. We can treat external flows around bodies as invicid (i.e. frictionless) and irrotational (i.e. the fluid particles are not rotating). This is because the viscous effects are limited to a thin layer next to the body called the boundary layer. In graduate classes like 2.25, you’ll learn how to solve for the invicid flow and then correct this within the boundary layer by considering viscosity. For now, let’s just learn how to solve for the invicid flow. We can define a potential function,!(x, z,t) , as a continuous function that satisfies the basic laws of fluid mechanics: conservation of mass and momentum, assuming incompressible, inviscid and irrotational flow. There is a vector identity (prove it for yourself!) that states for any scalar, ", " # "$ = 0 By definition, for irrotational flow, r ! " #V = 0 Therefore ! r V = "# ! where ! = !(x, y, z,t) is the velocity potential function. Such that the components of velocity in Cartesian coordinates, as functions of space and time, are ! "! "! "! u = , v = and w = (4.1) dx dy dz version 1.0 updated 9/22/2005 -1- ©2005 A. Techet 2.016 Hydrodynamics Reading #4 Laplace Equation The velocity must still satisfy the conservation of mass equation. We can substitute in the relationship between potential and velocity and arrive at the Laplace Equation, which we will revisit in our discussion on linear waves.
    [Show full text]
  • Literature Review
    SECTION VII GLOSSARY OF TERMS SECTION VII: TABLE OF CONTENTS 7. GLOSSARY OF TERMS..................................................................... VII - 1 7.1 CFD Glossary .......................................................................................... VII - 1 7.2. Particle Tracking Glossary.................................................................... VII - 3 Section VII – Glossary of Terms Page VII - 1 7. GLOSSARY OF TERMS 7.1 CFD Glossary Advection: The process by which a quantity of fluid is transferred from one point to another due to the movement of the fluid. Boundary condition(s): either: A set of conditions that define the physical problem. or: A plane at which a known solution is applied to the governing equations. Boundary layer: A very narrow region next to a solid object in a moving fluid, and containing high gradients in velocity. CFD: Computational Fluid Dynamics. The study of the behavior of fluids using computers to solve the equations that govern fluid flow. Clustering: Increasing the number of grid points in a region to better resolve a geometric or flow feature. Increasing the local grid resolution. Continuum: Having properties that vary continuously with position. The air in a room can be thought of as a continuum because any cube of air will behave much like any other chosen cube of air. Convection: A similar term to Advection but is a more generic description of the Advection process. Convergence: Convergence is achieved when the imbalances in the governing equations fall below an acceptably low level during the solution process. Diffusion: The process by which a quantity spreads from one point to another due to the existence of a gradient in that variable. Diffusion, molecular: The spreading of a quantity due to molecular interactions within the fluid.
    [Show full text]
  • Sensitivity Analysis of Non-Linear Steep Waves Using VOF Method
    Tenth International Conference on ICCFD10-268 Computational Fluid Dynamics (ICCFD10), Barcelona, Spain, July 9-13, 2018 Sensitivity Analysis of Non-linear Steep Waves using VOF Method A. Khaware*, V. Gupta*, K. Srikanth *, and P. Sharkey ** Corresponding author: [email protected] * ANSYS Software Pvt Ltd, Pune, India. ** ANSYS UK Ltd, Milton Park, UK Abstract: The analysis and prediction of non-linear waves is a crucial part of ocean hydrodynamics. Sea waves are typically non-linear in nature, and whilst models exist to predict their behavior, limits exist in their applicability. In practice, as the waves become increasingly steeper, they approach a point beyond which the wave integrity cannot be maintained, and they 'break'. Understanding the limits of available models as waves approach these break conditions can significantly help to improve the accuracy of their potential impact in the field. Moreover, inaccurate modeling of wave kinematics can result in erroneous hydrodynamic forces being predicted. This paper investigates the sensitivity of non-linear wave modeling from both an analytical and a numerical perspective. Using a Volume of Fluid (VOF) method, coupled with the Open Channel Flow module in ANSYS Fluent, sensitivity studies are performed for a variety of non-linear wave scenarios with high steepness and high relative height. These scenarios are intended to mimic the near-break conditions of the wave. 5th order solitary wave models are applied to shallow wave scenarios with high relative heights, and 5th order Stokes wave models are applied to short gravity waves with high wave steepness. Stokes waves are further applied in the shallow regime at high wave steepness to examine the wave sensitivity under extreme conditions.
    [Show full text]
  • Chapter 4: Immersed Body Flow [Pp
    MECH 3492 Fluid Mechanics and Applications Univ. of Manitoba Fall Term, 2017 Chapter 4: Immersed Body Flow [pp. 445-459 (8e), or 374-386 (9e)] Dr. Bing-Chen Wang Dept. of Mechanical Engineering Univ. of Manitoba, Winnipeg, MB, R3T 5V6 When a viscous fluid flow passes a solid body (fully-immersed in the fluid), the body experiences a net force, F, which can be decomposed into two components: a drag force F , which is parallel to the flow direction, and • D a lift force F , which is perpendicular to the flow direction. • L The drag coefficient CD and lift coefficient CL are defined as follows: FD FL CD = 1 2 and CL = 1 2 , (112) 2 ρU A 2 ρU Ap respectively. Here, U is the free-stream velocity, A is the “wetted area” (total surface area in contact with fluid), and Ap is the “planform area” (maximum projected area of an object such as a wing). In the remainder of this section, we focus our attention on the drag forces. As discussed previously, there are two types of drag forces acting on a solid body immersed in a viscous flow: friction drag (also called “viscous drag”), due to the wall friction shear stress exerted on the • surface of a solid body; pressure drag (also called “form drag”), due to the difference in the pressure exerted on the front • and rear surfaces of a solid body. The friction drag and pressure drag on a finite immersed body are defined as FD,vis = τwdA and FD, pres = pdA , (113) ZA ZA Streamwise component respectively.
    [Show full text]
  • Waves and Structures
    WAVES AND STRUCTURES By Dr M C Deo Professor of Civil Engineering Indian Institute of Technology Bombay Powai, Mumbai 400 076 Contact: [email protected]; (+91) 22 2572 2377 (Please refer as follows, if you use any part of this book: Deo M C (2013): Waves and Structures, http://www.civil.iitb.ac.in/~mcdeo/waves.html) (Suggestions to improve/modify contents are welcome) 1 Content Chapter 1: Introduction 4 Chapter 2: Wave Theories 18 Chapter 3: Random Waves 47 Chapter 4: Wave Propagation 80 Chapter 5: Numerical Modeling of Waves 110 Chapter 6: Design Water Depth 115 Chapter 7: Wave Forces on Shore-Based Structures 132 Chapter 8: Wave Force On Small Diameter Members 150 Chapter 9: Maximum Wave Force on the Entire Structure 173 Chapter 10: Wave Forces on Large Diameter Members 187 Chapter 11: Spectral and Statistical Analysis of Wave Forces 209 Chapter 12: Wave Run Up 221 Chapter 13: Pipeline Hydrodynamics 234 Chapter 14: Statics of Floating Bodies 241 Chapter 15: Vibrations 268 Chapter 16: Motions of Freely Floating Bodies 283 Chapter 17: Motion Response of Compliant Structures 315 2 Notations 338 References 342 3 CHAPTER 1 INTRODUCTION 1.1 Introduction The knowledge of magnitude and behavior of ocean waves at site is an essential prerequisite for almost all activities in the ocean including planning, design, construction and operation related to harbor, coastal and structures. The waves of major concern to a harbor engineer are generated by the action of wind. The wind creates a disturbance in the sea which is restored to its calm equilibrium position by the action of gravity and hence resulting waves are called wind generated gravity waves.
    [Show full text]
  • Part III: the Viscous Flow
    Why does an airfoil drag: the viscous problem – André Deperrois – March 2019 Rev. 1.1 © Navier-Stokes equations Inviscid fluid Time averaged turbulence CFD « RANS » Reynolds Averaged Euler’s equations Reynolds equations Navier-stokes solvers irrotational flow Viscosity models, uniform 3d Boundary Layer eq. pressure in BL thickness, Prandlt Potential flow mixing length hypothesis. 2d BL equations Time independent, incompressible flow Laplace’s equation 1d BL Integral 2d BL differential equations equations 2d mixed empirical + theoretical 2d, 3d turbulence and transition models 2d viscous results interpolation The inviscid flow around an airfoil Favourable pressure gradient, the flo! a""elerates ro# $ero at the leading edge%s stagnation point& Adverse pressure gradient, the low decelerates way from the surface, the flow free tends asymptotically towards the stream air freestream uniform flow flow inviscid ◀—▶ “laminar”, The boundary layer way from the surface, the fluid’s velocity tends !ue to viscosity, the asymptotically towards the tangential velocity at the velocity field of an ideal inviscid contact of the foil is " free flow around an airfoil$ stream air flow (magnified scale) The boundary layer is defined as the flow between the foil’s surface and the thic%ness where the fluid#s velocity reaches &&' or &&$(' of the inviscid flow’s velocity. The viscous flow around an airfoil at low Reynolds number Favourable pressure gradient, the low a""elerates ro# $ero at the leading edge%s stagnation point& Adverse pressure gradient, the low decelerates +n adverse pressure gradients, the laminar separation bubble forms. The flow goes flow separates. The velocity close to the progressively turbulent inside the bubble$ surface goes negative.
    [Show full text]
  • Incompressible Irrotational Flow
    Incompressible irrotational flow Enrique Ortega [email protected] Rotation of a fluid element As seen in M1_2, the arbitrary motion of a fluid element can be decomposed into • A translation or displacement due to the velocity. • A deformation (due to extensional and shear strains) mainly related to viscous and compressibility effects. • A rotation (of solid body type) measured through the midpoint of the diagonal of the fluid element. The rate of rotation is defined as the angular velocity. The latter is related to the vorticity of the flow through: d 2 V (1) dt Important: for an incompressible, inviscid flow, the momentum equations show that the vorticity for each fluid element remains constant (see pp. 17 of M1_3). Note that w is positive in the 2 – Irrotational flow counterclockwise sense Irrotational and rotational flow ij 0 According to the Prandtl’s boundary layer concept, thedomaininatypical(high-Re) aerodynamic problem at low can be divided into outer and inner flow regions under the following considerations: Extracted from [1]. • In the outer region (away from the body) the flow is considered inviscid and irrotational (viscous contributions vanish in the momentum equations and =0 due to farfield vorticity conservation). • In the inner region the viscous effects are confined to a very thin layer close to the body (vorticity is created at the boundary layer by viscous stresses) and a thin wake extending downstream (vorticity must be convected with the flow). Under these hypotheses, it is assumed that the disturbance of the outer flow, caused by the body and the thin boundary layer around it, is about the same caused by the body alone.
    [Show full text]
  • Potential Flow
    1.0 POTENTIAL FLOW One of the most important applications of potential flow theory is to aerodynamics and marine hydrodynamics. Key assumption. 1. Incompressibility – The density and specific weight are to be taken as constant. 2. Irrotationality – This implies a nonviscous fluid where particles are initially moving without rotation. 3. Steady flow – All properties and flow parameters are independent of time. (a) (b) Fig. 1.1 Examples of complicated immersed flows: (a) flow near a solid boundary; (b) flow around an automobile. In this section we will be concerned with the mathematical description of the motion of fluid elements moving in a flow field. A small fluid element in the shape of a cube which is initially in one position will move to another position during a short time interval as illustrated in Fig.1.1. Fig. 1.2 1.1 Continuity Equation v u = velocity component x direction y v y y y v = velocity component y direction u u x u x x x v x Continuity Equation Flow inwards = Flow outwards u v uy vx u xy v yx x y u v 0 - 2D x y u v w 0 - 3D x y z 1.2 Stream Function, (psi) y B Stream Line B A A u x -v The stream is continuity d vdx udy if (x, y) d dx dy x y u and v x y Integrated the equations dx dy C x y vdx udy C Continuity equation in 2 2 y x 0 or x y xy yx if 0 not continuity Vorticity equation, (rotational flow) 2 1 v u ; angular velocity (rad/s) 2 x y v u x y or substitute with 2 2 x 2 y 2 Irrotational flow, 0 Rotational flow.
    [Show full text]
  • Introduction to Computational Fluid Dynamics by the Finite Volume Method
    Introduction to Computational Fluid Dynamics by the Finite Volume Method Ali Ramezani, Goran Stipcich and Imanol Garcia BCAM - Basque Center for Applied Mathematics April 12–15, 2016 Overview on Computational Fluid Dynamics (CFD) 1. Overview on Computational Fluid Dynamics (CFD) 2 / 110 Overview on Computational Fluid Dynamics (CFD) What is CFD? I Fluids: mainly liquids and gases I The governing equations are known, but not their analytical solution: thus, we approximate it I By CFD we typically denote the set of numerical techniques used for the approximate solution (prevision) of the motion of fluids and the associated phenomena (heat exchange, combustion, fluid-structure interaction . ) I The solution of the governing differential (or integro-differential) equations is approximated by a discretization of space and time I From the continuum we move to the discrete level I The CFD is deeply connected to the improvement of computers in the last decades 3 / 110 Overview on Computational Fluid Dynamics (CFD) Applications of CFD I Any field where the fluid motion plays a relevant role: Industry Physics Medicine Meteorology Architecture Environment 4 / 110 Overview on Computational Fluid Dynamics (CFD) Applications of CFD II Moreover, the research front is particularly active: Basic research on fluid New numerical methods mechanics (e.g. transition to turbulence) Application oriented (e.g. renewable energy, competition . ) 5 / 110 Overview on Computational Fluid Dynamics (CFD) CFD: limits and potential I Method Advantages Disadvantages Experimental 1. More realistic 1. Need for instrumentation 2. Allows “complex” problems 2. Scale effects 3. Difficulty in measurements & perturbations 4. Operational costs Theoretical 1. Simple information 1.
    [Show full text]