The velocity vector, for an incompressible fluid, must satisfy the continuity equation
|
|
- Randall Woods
- 7 years ago
- Views:
Transcription
1 Chapter D Vortex Methods Vortex methods are powerful numerical methods to study the evolution of inviscid flow fields. The idea behind the method will be developed in the following notes.. Vorticity and Streamfunction The 3D vorticity is defined as the curl of the velocity vector: ω = u (.) The velocity vector, for an incompressible fluid, must satisfy the continuity equation u =. (.) This condition is immediately satisfied by introducing a vector streamfunction Ψ such that the velocity is its curl: u = Ψ (.3) since vector identities guarantees that the divergence of a curl is always zero u = Ψ =. The vorticity can now be written in terms of the streamfunction guaranteeing that the resultant flow field is divergence-free: ω = Ψ = ( Ψ) Ψ (.4) The above equation can be further simplified by requiring that the streamfunction vector be divergence-free. We then obtain a vector Poisson equation for the streamfunction for a given vorticity field: Ψ = ω (.5) 99
2 CHAPTER. D VORTEX METHODS The situation is considerably simpler in D where the streamfunction is a scalar, ψ, and where only the vorticity component perpendicular to the plane is non-zero ω = ωk. The vector Poisson equation reduces to a scalar Poisson equation: ψ = ω (.6) The important point about vorticity is that for two-dimensional inviscid flows, and in the absence of vorticity sources, the equation governing the evolution of the vorticity is simple and states that the vorticity is conserved following the flow: dω dt = ω + u ω = (.7) t The idea behind vortex method is then simply to represent the vorticity fields as a collection of vortex patches carrying an intrinsic amount of vorticity. This vorticity has associated with it a flow field which in turn will advect these patches around without changing their intrinsic vorticity. The flow field will of course change once the patches change position, and one merely has to track them in order to simulate the flow evolution.. Flow due to point vortices Here we derive the relationship between a vorticity source and the induced streamfunction and velocity in an infinite plane with no boundaries. This derivation uses the Green function approach where the forcing, the vorticity source, is concentrated at points and has infinite strength in a pointwise sense, but finite strength in an area-averaged sense. We first look at the impact of a single point vortex then use the linearity of the equations to superpose solution when multiple vortex points are located... Flow due to single point vortex An analytical expression for the streamfunction equation can be derived for the special case where there is a single impulse vorticity in an infinite domain ψ = ω δ(r) πr, r = x x, r = x x (.8) where ω is now simply the strength of a concentrated vortex point. The Green function solution is then simply ψ(x) = ω(x ) ln r π = ω(x ) ln x x π (.9)
3 .. FLOW DUE TO POINT VORTICES The velocity associated with this streamfunction field is then: u = (ψk) = ω(x ) (rk) πr = ω(x ) r k πr (.) Since r = (x x ) + (y y ) we have r = r/r. The velocity induced by a point vortex with strength ω is then: u(x) = ω(x ) r k πr = ω(x ) (x x ) k π x x = ω(x ) k (x x ) π x x (.).. Flow due to multiple point vortices The linearity of equations.8,., and. makes it possible to invoke the principle of superposition to account for the presence of multiple point vortices in the flow. Tagging each point vortex by a subscript i, we can immediately write down the expression of the streamfunction and velocity imparted by each of them to the point located at x: ψ i (x) = ω(x i ) ln x x i π (.) u i (x) = ω(x i ) k (x x i) π x x i (.3) where x i is the location of the i-th vortex and ω(x i ) is its strength. The total imparted velocity/streamfunction can be obtained by summing the individual contributions: ψ(x) = ψ i (x) = u(x) = u i (x) = ω(x i ) ln x x i π (.4) ω(x i ) k (x x i) π x x i (.5) Figure. shows the streamfunction field and the velocity induced by,, 3 and 4 point vortices of similar strengths. The streamlines are shown by contours and the velocity field by arrows. If an infinite number of vortex element are present, the summation becomes an area integral: u(x) = ω(x ) k (x x ) dx Ω π x x (.6) The integration is carried out on the location of the impulse x, and where dx represents an area element. The above equation is often written in the form u(x) =
4 CHAPTER. D VORTEX METHODS Figure.: Streamfunction contours and flow field induced by a unit-strong vortex located on the diamond (±, ) and (, ±).
5 .3. FROM POINTS TO BLOBS 3 K(x x ) ω(x ) where the the stands for a convolution operation and K is called the Kernel. Equation.6 is the D version of the Biot-Savart law, and can be seen as the continuous form of equation.5. We have derived the continuous Biot-Savart law starting from discrete impulses to continuum forcing of the form ω(x ). It is useful to reverse this trajectory and re-derive the discrete system starting from the continuum. If the vorticity consists of particles carrying a certain amount of vorticity distributed according to: ω i (x ) = α i ζ i ( x x i ) with ζ( x x i ) as x x i (.7) where α i is the circulation around the i th particle. We require further that ζ decays fairly quickly with distance from the center. u(x) = α i Ω ζ(x x i ) k (x x ) π x x dx (.8) In the limiting case where the ζ(x x i ) is the D Dirac delta function the expression simplifies to: k (x x i ) u(x) = α i (.9) π x x i.3 From points to blobs One problem with approximating the vorticity with delta functions, i.e. infinite spikes, is the associated singularity in the streamfunction and velocity fields. This singularity appears when the distance to the point vortex becomes very small, r = x x = : both streamfunction and velocity become very large; the first blows up logarithmically fast and the other like r. This is quite problematic in the evaluation of the sums. It is therefore most useful to replace the spiky representation of the vorticity by blobs; these blobs will have finite widths and hence the associated singularity is removed. The questions become how do we construct the vorticity representation of the blobs, and what are the streamfunction and velocity Kernels associated with it? In order to build these representations we retrace the path followed in the derivation of the point vortex methods. We thus assume that each vortex blob has associated with it a localized shape function, ω = ζ(r) that is radially symmetric about the center of the blob, that decays as we move away from the center, and whose integral over the entire plane is unity. Under these assumptions, the solution to the Poisson equation is still expected to be radially symmetric and reduces to: r ( r r G r ) = ζ(r) (.)
6 4 CHAPTER. D VORTEX METHODS where ζ(r) is yet an undetermined function and G its corresponding Green function. The above equation can be integrated twice to yield: G r = r G(r) = r r t sζ(s) ds (.) ( t ) sζ(s) ds dt (.) Here r and s are integration variables. Once a vortex representation ζ(r) is chosen, equation. can be used to compute the velocity kernel, and equation. to compute the streamfunction kernel. It is the former that is most critical and we have K(x) = k (x x ) G r r = k (x x ) r sζ(s) ds (.3) r.3. Gaussian blobs of second order A common choice for the representation of the vorticity is to use a Gaussian function that has the form: /ǫ ζ(r) = e r (.4) πǫ where ǫ is the width of the blob, the proportionality factor is simply for normalization so that the integral of the above function over the infinite plane is. The vorticity distribution peaks at at r = and decays exponentially fast as we πǫ get away from the blob center; the parameter ǫ determines how fast the function decays. Notice that this function approaches the Dirac delta function as ǫ : its width narrows to a point, its amplitude goes to, and its area integral remains unity. The corresponding velocity kernel can be obtained by plugging the above expression in. and evaluating the integral to obtain: K(x) = k (x x ) πr ( e r /ǫ ) (.5) Figure. shows the impact of the width parameter on the vortex blob. The primary effect is to remove the effect of the singularity in the vicinity of the blob center while mimicking the behavior of a point vortex as we move away from the center..3. Gaussian blobs of high order The Gaussian blobs of the previous section can be shown to be second order in the parameter ǫ, it is however, possible to derive higher order shape functions: ζ 6 (r) = ǫ π ζ 4 (r) = ǫ ( ) 4 r e r π K 4 = k (x x [ ) + ( r ) e ] r π x x ( 6 6 r + r 4) e r K 6 = k (x x ) π x x [ ( r + ) ] r4 e r
7 .3. FROM POINTS TO BLOBS 5 Figure.: Left panels: vortex blob Gaussian decay for several values of the blob width ǫ:.4 (blue),. (green) and. (red). The right panels show the velocity Kernel amplitude as a function of r; the black line refers to the point vortex case. Top to bottom are the Gaussian blobs of order, 4 and 6, respectively.
8 6 CHAPTER. D VORTEX METHODS where r = r/ǫ is a scaled radius. The radial shape functions associated with the 4 and 6-th order Gaussian blobs are shown in figures.. Again, the trend is clear in that a Dirac delta function is approached as the width parameter ǫ shrinks, and as the order increases. The corresponding velocity kernel amplitudes are shown in the left panels. They all mimic the behavior of the point vortex away from the blob center but decay to zero once at the vortex center instead of behaving singularly..4 The vortex method algorithm In this section we summarize the steps required to implement the vortex method as a computational code. The steps are as follows: Choose a shape function for the vorticity and the associated velocity Kernel. To make the steps more concrete we assume that we have chosen the second order Gaussian distribution and its velocity Kernel. So we have the following approximations for the vorticity field and velocity: ω(x) = u(x) = e r i α i (.6) πǫ α i k (x x i ) π x x i ( e r ) (.7) r = x x i, r i = r i /ǫ (.8) Determine the width, ǫ, positions, x n i and strengths, α n i of the vortex blobs at an initial time; here the superscript n refers to the time step. Determine the velocity field induced by all vortex blobs on all other blobs: use equation.7 to compute u(x j ) for all particles j =,,..., N. Update the particles position by integrating the equation dx i dt = u(x j) (.9) using a Runge-Kutta 4 integrator (this requires 4 stages). In the absence of vorticity sources, the strength of each vortex blobs is preserved, so α n i remains constant Return to step.4 and repeat until final time. throughtout the calculation.
9 .5. THE PRESENCE OF BOUNDARIES 7.5 The presence of boundaries The vortex method is ideal for boundaries-free problem where the flow domain is infinite. Accounting for boundaries in vortex methods is complicated provided the formulation is modified. The procedure hinges on the Helmholtz decomposition of a flow field into its potential (and irrotational) part and its solenoidal (and rotational part). The solenoidal part can be evolved with the vortex method ignoring the presence of boundaries. The potential part is then introduced to correct the solenoidal fields and account for the no-flow conditions at the solid boundaries. The potential part is governed by a Laplace equation and can be solved efficiently with a Boundary Element Method. The flow components can then be solved with points and lines only..5. The Helmholtz decomposition It is well known that any flow field u can be decomposed into u = u s + u p (.3) where u s = and u p =. These two properties can be guaranteed if we introduce a potential function and a streamfunction such that u p = φ and u s = Ψ. (.3) Inserting these expressions in the Helmholtz decomposition we obtain the following pair of equations u = ( Ψ + φ) = Ψ = Ψ (.3) u = ( Ψ + φ) = φ = φ (.33) where we have assumed again, and without loss of generality, that the streamfunction is divergence-free (this is certainly the case in D). Given the divergence and rotation of the original flow velocity equations.3 and.33 can be inverted for the streamfunction and potential, respectively. The solution steps are as follow:. The rotational part of the flow is evolved according to the vorticity evolution equation and the associated solenoidal velocity is obtained from the Biot- Savart law as outlined in the discussion on the vortex method. This velocity field will violate the boundary conditions of no-through flow.. The introduction of the potential velocity allows us to rectify the situation and enforce the no-through condition. For an incompressible flow the governing equation for the potential is the Laplace equation coupled with a Neumann boundary conditions at the boundaries: where Γ refers to the solid boundaries. φ =, and φ n = u s n on Γ (.34)
Differential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation
Differential Relations for Fluid Flow In this approach, we apply our four basic conservation laws to an infinitesimally small control volume. The differential approach provides point by point details of
More informationChapter 7. Potential flow theory. 7.1 Basic concepts. 7.1.1 Velocity potential
Chapter 7 Potential flow theory Flows past immersed bodies generate boundary layers within which the presence of the body is felt through viscous effects. Outside these boundary layers, the flow is typically
More information6 J - vector electric current density (A/m2 )
Determination of Antenna Radiation Fields Using Potential Functions Sources of Antenna Radiation Fields 6 J - vector electric current density (A/m2 ) M - vector magnetic current density (V/m 2 ) Some problems
More informationState of Stress at Point
State of Stress at Point Einstein Notation The basic idea of Einstein notation is that a covector and a vector can form a scalar: This is typically written as an explicit sum: According to this convention,
More informationMODULE VII LARGE BODY WAVE DIFFRACTION
MODULE VII LARGE BODY WAVE DIFFRACTION 1.0 INTRODUCTION In the wave-structure interaction problems, it is classical to divide into two major classification: slender body interaction and large body interaction.
More information3. Diffusion of an Instantaneous Point Source
3. Diffusion of an Instantaneous Point Source The equation of conservation of mass is also known as the transport equation, because it describes the transport of scalar species in a fluid systems. In this
More informationSolving Simultaneous Equations and Matrices
Solving Simultaneous Equations and Matrices The following represents a systematic investigation for the steps used to solve two simultaneous linear equations in two unknowns. The motivation for considering
More informationPhysics of the Atmosphere I
Physics of the Atmosphere I WS 2008/09 Ulrich Platt Institut f. Umweltphysik R. 424 Ulrich.Platt@iup.uni-heidelberg.de heidelberg.de Last week The conservation of mass implies the continuity equation:
More informationThe continuous and discrete Fourier transforms
FYSA21 Mathematical Tools in Science The continuous and discrete Fourier transforms Lennart Lindegren Lund Observatory (Department of Astronomy, Lund University) 1 The continuous Fourier transform 1.1
More informationIntroduction to the Finite Element Method
Introduction to the Finite Element Method 09.06.2009 Outline Motivation Partial Differential Equations (PDEs) Finite Difference Method (FDM) Finite Element Method (FEM) References Motivation Figure: cross
More information4.3 Results... 27 4.3.1 Drained Conditions... 27 4.3.2 Undrained Conditions... 28 4.4 References... 30 4.5 Data Files... 30 5 Undrained Analysis of
Table of Contents 1 One Dimensional Compression of a Finite Layer... 3 1.1 Problem Description... 3 1.1.1 Uniform Mesh... 3 1.1.2 Graded Mesh... 5 1.2 Analytical Solution... 6 1.3 Results... 6 1.3.1 Uniform
More informationCBE 6333, R. Levicky 1 Differential Balance Equations
CBE 6333, R. Levicky 1 Differential Balance Equations We have previously derived integral balances for mass, momentum, and energy for a control volume. The control volume was assumed to be some large object,
More informationElasticity Theory Basics
G22.3033-002: Topics in Computer Graphics: Lecture #7 Geometric Modeling New York University Elasticity Theory Basics Lecture #7: 20 October 2003 Lecturer: Denis Zorin Scribe: Adrian Secord, Yotam Gingold
More informationNonlinear evolution of unstable fluid interface
Nonlinear evolution of unstable fluid interface S.I. Abarzhi Department of Applied Mathematics and Statistics State University of New-York at Stony Brook LIGHT FLUID ACCELERATES HEAVY FLUID misalignment
More informationChapter 28 Fluid Dynamics
Chapter 28 Fluid Dynamics 28.1 Ideal Fluids... 1 28.2 Velocity Vector Field... 1 28.3 Mass Continuity Equation... 3 28.4 Bernoulli s Principle... 4 28.5 Worked Examples: Bernoulli s Equation... 7 Example
More informationEquations of Lines and Planes
Calculus 3 Lia Vas Equations of Lines and Planes Planes. A plane is uniquely determined by a point in it and a vector perpendicular to it. An equation of the plane passing the point (x 0, y 0, z 0 ) perpendicular
More informationElectrostatic Fields: Coulomb s Law & the Electric Field Intensity
Electrostatic Fields: Coulomb s Law & the Electric Field Intensity EE 141 Lecture Notes Topic 1 Professor K. E. Oughstun School of Engineering College of Engineering & Mathematical Sciences University
More informationCorrelation and Convolution Class Notes for CMSC 426, Fall 2005 David Jacobs
Correlation and Convolution Class otes for CMSC 46, Fall 5 David Jacobs Introduction Correlation and Convolution are basic operations that we will perform to extract information from images. They are in
More informationDivergence and Curl of the Magnetic Field
Divergence and Curl of the Magnetic Field The static electric field E(x,y,z such as the field of static charges obeys equations E = 1 ǫ ρ, (1 E =. (2 The static magnetic field B(x,y,z such as the field
More information2-1 Position, Displacement, and Distance
2-1 Position, Displacement, and Distance In describing an object s motion, we should first talk about position where is the object? A position is a vector because it has both a magnitude and a direction:
More informationRAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A
RAJALAKSHMI ENGINEERING COLLEGE MA 26 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS. Solve (D 2 + D 2)y = 0. 2. Solve (D 2 + 6D + 9)y = 0. PART A 3. Solve (D 4 + 4)x = 0 where D = d dt 4. Find Particular Integral:
More informationThe Quantum Harmonic Oscillator Stephen Webb
The Quantum Harmonic Oscillator Stephen Webb The Importance of the Harmonic Oscillator The quantum harmonic oscillator holds a unique importance in quantum mechanics, as it is both one of the few problems
More informationQuasi-static evolution and congested transport
Quasi-static evolution and congested transport Inwon Kim Joint with Damon Alexander, Katy Craig and Yao Yao UCLA, UW Madison Hard congestion in crowd motion The following crowd motion model is proposed
More informationThe Basics of FEA Procedure
CHAPTER 2 The Basics of FEA Procedure 2.1 Introduction This chapter discusses the spring element, especially for the purpose of introducing various concepts involved in use of the FEA technique. A spring
More informationChapter 33. The Magnetic Field
Chapter 33. The Magnetic Field Digital information is stored on a hard disk as microscopic patches of magnetism. Just what is magnetism? How are magnetic fields created? What are their properties? These
More informationCONSERVATION LAWS. See Figures 2 and 1.
CONSERVATION LAWS 1. Multivariable calculus 1.1. Divergence theorem (of Gauss). This states that the volume integral in of the divergence of the vector-valued function F is equal to the total flux of F
More informationExam 1 Practice Problems Solutions
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Physics 8 Spring 13 Exam 1 Practice Problems Solutions Part I: Short Questions and Concept Questions Problem 1: Spark Plug Pictured at right is a typical
More informationRotation: Moment of Inertia and Torque
Rotation: Moment of Inertia and Torque Every time we push a door open or tighten a bolt using a wrench, we apply a force that results in a rotational motion about a fixed axis. Through experience we learn
More informationThe Matrix Elements of a 3 3 Orthogonal Matrix Revisited
Physics 116A Winter 2011 The Matrix Elements of a 3 3 Orthogonal Matrix Revisited 1. Introduction In a class handout entitled, Three-Dimensional Proper and Improper Rotation Matrices, I provided a derivation
More informationElectromagnetism - Lecture 2. Electric Fields
Electromagnetism - Lecture 2 Electric Fields Review of Vector Calculus Differential form of Gauss s Law Poisson s and Laplace s Equations Solutions of Poisson s Equation Methods of Calculating Electric
More informationS. Boyd EE102. Lecture 1 Signals. notation and meaning. common signals. size of a signal. qualitative properties of signals.
S. Boyd EE102 Lecture 1 Signals notation and meaning common signals size of a signal qualitative properties of signals impulsive signals 1 1 Signals a signal is a function of time, e.g., f is the force
More informationα = u v. In other words, Orthogonal Projection
Orthogonal Projection Given any nonzero vector v, it is possible to decompose an arbitrary vector u into a component that points in the direction of v and one that points in a direction orthogonal to v
More informationLecture 2: Homogeneous Coordinates, Lines and Conics
Lecture 2: Homogeneous Coordinates, Lines and Conics 1 Homogeneous Coordinates In Lecture 1 we derived the camera equations λx = P X, (1) where x = (x 1, x 2, 1), X = (X 1, X 2, X 3, 1) and P is a 3 4
More informationPYKC Jan-7-10. Lecture 1 Slide 1
Aims and Objectives E 2.5 Signals & Linear Systems Peter Cheung Department of Electrical & Electronic Engineering Imperial College London! By the end of the course, you would have understood: Basic signal
More informationLecture L6 - Intrinsic Coordinates
S. Widnall, J. Peraire 16.07 Dynamics Fall 2009 Version 2.0 Lecture L6 - Intrinsic Coordinates In lecture L4, we introduced the position, velocity and acceleration vectors and referred them to a fixed
More informationSTA 4273H: Statistical Machine Learning
STA 4273H: Statistical Machine Learning Russ Salakhutdinov Department of Statistics! rsalakhu@utstat.toronto.edu! http://www.cs.toronto.edu/~rsalakhu/ Lecture 6 Three Approaches to Classification Construct
More informationMoving Least Squares Approximation
Chapter 7 Moving Least Squares Approimation An alternative to radial basis function interpolation and approimation is the so-called moving least squares method. As we will see below, in this method the
More informationAmpere's Law. Introduction. times the current enclosed in that loop: Ampere's Law states that the line integral of B and dl over a closed path is 0
1 Ampere's Law Purpose: To investigate Ampere's Law by measuring how magnetic field varies over a closed path; to examine how magnetic field depends upon current. Apparatus: Solenoid and path integral
More informationNUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES
Vol. XX 2012 No. 4 28 34 J. ŠIMIČEK O. HUBOVÁ NUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES Jozef ŠIMIČEK email: jozef.simicek@stuba.sk Research field: Statics and Dynamics Fluids mechanics
More informationATM 316: Dynamic Meteorology I Final Review, December 2014
ATM 316: Dynamic Meteorology I Final Review, December 2014 Scalars and Vectors Scalar: magnitude, without reference to coordinate system Vector: magnitude + direction, with reference to coordinate system
More informationDecember 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B. KITCHENS
December 4, 2013 MATH 171 BASIC LINEAR ALGEBRA B KITCHENS The equation 1 Lines in two-dimensional space (1) 2x y = 3 describes a line in two-dimensional space The coefficients of x and y in the equation
More informationHow do we obtain the solution, if we are given F (t)? First we note that suppose someone did give us one solution of this equation
1 Green s functions The harmonic oscillator equation is This has the solution mẍ + kx = 0 (1) x = A sin(ωt) + B cos(ωt), ω = k m where A, B are arbitrary constants reflecting the fact that we have two
More informationWhen the fluid velocity is zero, called the hydrostatic condition, the pressure variation is due only to the weight of the fluid.
Fluid Statics When the fluid velocity is zero, called the hydrostatic condition, the pressure variation is due only to the weight of the fluid. Consider a small wedge of fluid at rest of size Δx, Δz, Δs
More informationDifferentiation of vectors
Chapter 4 Differentiation of vectors 4.1 Vector-valued functions In the previous chapters we have considered real functions of several (usually two) variables f : D R, where D is a subset of R n, where
More informationBlind Deconvolution of Barcodes via Dictionary Analysis and Wiener Filter of Barcode Subsections
Blind Deconvolution of Barcodes via Dictionary Analysis and Wiener Filter of Barcode Subsections Maximilian Hung, Bohyun B. Kim, Xiling Zhang August 17, 2013 Abstract While current systems already provide
More informationMethod of Green s Functions
Method of Green s Functions 8.303 Linear Partial ifferential Equations Matthew J. Hancock Fall 006 We introduce another powerful method of solving PEs. First, we need to consider some preliminary definitions
More informationLecture 16. Newton s Second Law for Rotation. Moment of Inertia. Angular momentum. Cutnell+Johnson: 9.4, 9.6
Lecture 16 Newton s Second Law for Rotation Moment of Inertia Angular momentum Cutnell+Johnson: 9.4, 9.6 Newton s Second Law for Rotation Newton s second law says how a net force causes an acceleration.
More information7. DYNAMIC LIGHT SCATTERING 7.1 First order temporal autocorrelation function.
7. DYNAMIC LIGHT SCATTERING 7. First order temporal autocorrelation function. Dynamic light scattering (DLS) studies the properties of inhomogeneous and dynamic media. A generic situation is illustrated
More informationStability of Evaporating Polymer Films. For: Dr. Roger Bonnecaze Surface Phenomena (ChE 385M)
Stability of Evaporating Polymer Films For: Dr. Roger Bonnecaze Surface Phenomena (ChE 385M) Submitted by: Ted Moore 4 May 2000 Motivation This problem was selected because the writer observed a dependence
More informationThe elements used in commercial codes can be classified in two basic categories:
CHAPTER 3 Truss Element 3.1 Introduction The single most important concept in understanding FEA, is the basic understanding of various finite elements that we employ in an analysis. Elements are used for
More informationChapter 2. Derivation of the Equations of Open Channel Flow. 2.1 General Considerations
Chapter 2. Derivation of the Equations of Open Channel Flow 2.1 General Considerations Of interest is water flowing in a channel with a free surface, which is usually referred to as open channel flow.
More informationChapter 4. Electrostatic Fields in Matter
Chapter 4. Electrostatic Fields in Matter 4.1. Polarization A neutral atom, placed in an external electric field, will experience no net force. However, even though the atom as a whole is neutral, the
More information1.Name the four types of motion that a fluid element can experience. YOUR ANSWER: Translation, linear deformation, rotation, angular deformation.
CHAPTER 06 1.Name the four types of motion that a fluid element can experience. YOUR ANSWER: Translation, linear deformation, rotation, angular deformation. 2.How is the acceleration of a particle described?
More informationA RIGOROUS AND COMPLETED STATEMENT ON HELMHOLTZ THEOREM
Progress In Electromagnetics Research, PIER 69, 287 304, 2007 A RIGOROU AND COMPLETED TATEMENT ON HELMHOLTZ THEOREM Y. F. Gui and W. B. Dou tate Key Lab of Millimeter Waves outheast University Nanjing,
More informationarxiv:1111.4354v2 [physics.acc-ph] 27 Oct 2014
Theory of Electromagnetic Fields Andrzej Wolski University of Liverpool, and the Cockcroft Institute, UK arxiv:1111.4354v2 [physics.acc-ph] 27 Oct 2014 Abstract We discuss the theory of electromagnetic
More informationIntroduction to Flow Visualization
Introduction to Flow Visualization This set of slides developed by Prof. Torsten Moeller, at Simon Fraser Univ and Professor Jian Huang, at University of Tennessee, Knoxville And some other presentation
More information5.4 The Heat Equation and Convection-Diffusion
5.4. THE HEAT EQUATION AND CONVECTION-DIFFUSION c 6 Gilbert Strang 5.4 The Heat Equation and Convection-Diffusion The wave equation conserves energy. The heat equation u t = u xx dissipates energy. The
More informationAlgebra 2 Chapter 1 Vocabulary. identity - A statement that equates two equivalent expressions.
Chapter 1 Vocabulary identity - A statement that equates two equivalent expressions. verbal model- A word equation that represents a real-life problem. algebraic expression - An expression with variables.
More informationMathematical Modeling and Engineering Problem Solving
Mathematical Modeling and Engineering Problem Solving Berlin Chen Department of Computer Science & Information Engineering National Taiwan Normal University Reference: 1. Applied Numerical Methods with
More informationReview of Vector Analysis in Cartesian Coordinates
R. evicky, CBE 6333 Review of Vector Analysis in Cartesian Coordinates Scalar: A quantity that has magnitude, but no direction. Examples are mass, temperature, pressure, time, distance, and real numbers.
More informationG(s) = Y (s)/u(s) In this representation, the output is always the Transfer function times the input. Y (s) = G(s)U(s).
Transfer Functions The transfer function of a linear system is the ratio of the Laplace Transform of the output to the Laplace Transform of the input, i.e., Y (s)/u(s). Denoting this ratio by G(s), i.e.,
More informationQUADRATIC, EXPONENTIAL AND LOGARITHMIC FUNCTIONS
QUADRATIC, EXPONENTIAL AND LOGARITHMIC FUNCTIONS Content 1. Parabolas... 1 1.1. Top of a parabola... 2 1.2. Orientation of a parabola... 2 1.3. Intercept of a parabola... 3 1.4. Roots (or zeros) of a parabola...
More informationFeature Detection in Vector Fields Using the Helmholtz-Hodge Decomposition Diploma-Thesis
Feature Detection in Vector Fields Using the Helmholtz-Hodge Decomposition Diploma-Thesis http://www.karman.au.com/dorothy/cruise-2912.html Author: Supervisor: Organization: Alexander Wiebel Dr. Gerik
More informationInteractive simulation of an ash cloud of the volcano Grímsvötn
Interactive simulation of an ash cloud of the volcano Grímsvötn 1 MATHEMATICAL BACKGROUND Simulating flows in the atmosphere, being part of CFD, is on of the research areas considered in the working group
More informationOrbits of the Lennard-Jones Potential
Orbits of the Lennard-Jones Potential Prashanth S. Venkataram July 28, 2012 1 Introduction The Lennard-Jones potential describes weak interactions between neutral atoms and molecules. Unlike the potentials
More informationTesting dark matter halos using rotation curves and lensing
Testing dark matter halos using rotation curves and lensing Darío Núñez Instituto de Ciencias Nucleares, UNAM Instituto Avanzado de Cosmología A. González, J. Cervantes, T. Matos Observational evidences
More informationvector calculus 2 Learning outcomes
29 ontents vector calculus 2 1. Line integrals involving vectors 2. Surface and volume integrals 3. Integral vector theorems Learning outcomes In this Workbook you will learn how to integrate functions
More informationMechanics 1: Conservation of Energy and Momentum
Mechanics : Conservation of Energy and Momentum If a certain quantity associated with a system does not change in time. We say that it is conserved, and the system possesses a conservation law. Conservation
More informationSection 1.7 22 Continued
Section 1.5 23 A homogeneous equation is always consistent. TRUE - The trivial solution is always a solution. The equation Ax = 0 gives an explicit descriptions of its solution set. FALSE - The equation
More informationStokes flow. Chapter 7
Chapter 7 Stokes flow We have seen in section 6.3 that the dimensionless form of the Navier-Stokes equations for a Newtonian viscous fluid of constant density and constant viscosity is, now dropping the
More informationMEL 807 Computational Heat Transfer (2-0-4) Dr. Prabal Talukdar Assistant Professor Department of Mechanical Engineering IIT Delhi
MEL 807 Computational Heat Transfer (2-0-4) Dr. Prabal Talukdar Assistant Professor Department of Mechanical Engineering IIT Delhi Time and Venue Course Coordinator: Dr. Prabal Talukdar Room No: III, 357
More informationRepresentation of functions as power series
Representation of functions as power series Dr. Philippe B. Laval Kennesaw State University November 9, 008 Abstract This document is a summary of the theory and techniques used to represent functions
More informationThe purposes of this experiment are to test Faraday's Law qualitatively and to test Lenz's Law.
260 17-1 I. THEORY EXPERIMENT 17 QUALITATIVE STUDY OF INDUCED EMF Along the extended central axis of a bar magnet, the magnetic field vector B r, on the side nearer the North pole, points away from this
More informationIntroduction to COMSOL. The Navier-Stokes Equations
Flow Between Parallel Plates Modified from the COMSOL ChE Library module rev 10/13/08 Modified by Robert P. Hesketh, Chemical Engineering, Rowan University Fall 2008 Introduction to COMSOL The following
More informationFigure 1.1 Vector A and Vector F
CHAPTER I VECTOR QUANTITIES Quantities are anything which can be measured, and stated with number. Quantities in physics are divided into two types; scalar and vector quantities. Scalar quantities have
More informationDIRECT ORBITAL DYNAMICS: USING INDEPENDENT ORBITAL TERMS TO TREAT BODIES AS ORBITING EACH OTHER DIRECTLY WHILE IN MOTION
1 DIRECT ORBITAL DYNAMICS: USING INDEPENDENT ORBITAL TERMS TO TREAT BODIES AS ORBITING EACH OTHER DIRECTLY WHILE IN MOTION Daniel S. Orton email: dsorton1@gmail.com Abstract: There are many longstanding
More informationThin Airfoil Theory. Charles R. O Neill School of Mechanical and Aerospace Engineering Oklahoma State University Stillwater, OK 74078
13 Thin Airfoil Theory Charles R. O Neill School of Mechanical and Aerospace Engineering Oklahoma State University Stillwater, OK 7478 Project One in MAE 3253 Applied Aerodynamics and Performance March
More informationParabolic Equations. Chapter 5. Contents. 5.1.2 Well-Posed Initial-Boundary Value Problem. 5.1.3 Time Irreversibility of the Heat Equation
7 5.1 Definitions Properties Chapter 5 Parabolic Equations Note that we require the solution u(, t bounded in R n for all t. In particular we assume that the boundedness of the smooth function u at infinity
More informationInner Product Spaces
Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and
More informationA Primer on Index Notation
A Primer on John Crimaldi August 28, 2006 1. Index versus Index notation (a.k.a. Cartesian notation) is a powerful tool for manipulating multidimensional equations. However, there are times when the more
More information4 Microscopic dynamics
4 Microscopic dynamics In this section we will look at the first model that people came up with when they started to model polymers from the microscopic level. It s called the Oldroyd B model. We will
More informationThe potential (or voltage) will be introduced through the concept of a gradient. The gradient is another sort of 3-dimensional derivative involving
The potential (or voltage) will be introduced through the concept of a gradient. The gradient is another sort of 3-dimensional derivative involving the vector del except we don t take the dot product as
More informationMulti-Block Gridding Technique for FLOW-3D Flow Science, Inc. July 2004
FSI-02-TN59-R2 Multi-Block Gridding Technique for FLOW-3D Flow Science, Inc. July 2004 1. Introduction A major new extension of the capabilities of FLOW-3D -- the multi-block grid model -- has been incorporated
More informationHEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi
HEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi 2 Rajesh Dudi 1 Scholar and 2 Assistant Professor,Department of Mechanical Engineering, OITM, Hisar (Haryana)
More informationVector surface area Differentials in an OCS
Calculus and Coordinate systems EE 311 - Lecture 17 1. Calculus and coordinate systems 2. Cartesian system 3. Cylindrical system 4. Spherical system In electromagnetics, we will often need to perform integrals
More informationω h (t) = Ae t/τ. (3) + 1 = 0 τ =.
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Mechanical Engineering 2.004 Dynamics and Control II Fall 2007 Lecture 2 Solving the Equation of Motion Goals for today Modeling of the 2.004 La s rotational
More information13 MATH FACTS 101. 2 a = 1. 7. The elements of a vector have a graphical interpretation, which is particularly easy to see in two or three dimensions.
3 MATH FACTS 0 3 MATH FACTS 3. Vectors 3.. Definition We use the overhead arrow to denote a column vector, i.e., a linear segment with a direction. For example, in three-space, we write a vector in terms
More informationPlates and Shells: Theory and Computation - 4D9 - Dr Fehmi Cirak (fc286@) Office: Inglis building mezzanine level (INO 31)
Plates and Shells: Theory and Computation - 4D9 - Dr Fehmi Cirak (fc286@) Office: Inglis building mezzanine level (INO 31) Outline -1-! This part of the module consists of seven lectures and will focus
More informationG U I D E T O A P P L I E D O R B I T A L M E C H A N I C S F O R K E R B A L S P A C E P R O G R A M
G U I D E T O A P P L I E D O R B I T A L M E C H A N I C S F O R K E R B A L S P A C E P R O G R A M CONTENTS Foreword... 2 Forces... 3 Circular Orbits... 8 Energy... 10 Angular Momentum... 13 FOREWORD
More informationProblem 1 (25 points)
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Physics 8.02 Spring 2012 Exam Three Solutions Problem 1 (25 points) Question 1 (5 points) Consider two circular rings of radius R, each perpendicular
More informationComputational Foundations of Cognitive Science
Computational Foundations of Cognitive Science Lecture 15: Convolutions and Kernels Frank Keller School of Informatics University of Edinburgh keller@inf.ed.ac.uk February 23, 2010 Frank Keller Computational
More informationOpenFOAM Optimization Tools
OpenFOAM Optimization Tools Henrik Rusche and Aleks Jemcov h.rusche@wikki-gmbh.de and a.jemcov@wikki.co.uk Wikki, Germany and United Kingdom OpenFOAM Optimization Tools p. 1 Agenda Objective Review optimisation
More informationConceptual: 1, 3, 5, 6, 8, 16, 18, 19. Problems: 4, 6, 8, 11, 16, 20, 23, 27, 34, 41, 45, 56, 60, 65. Conceptual Questions
Conceptual: 1, 3, 5, 6, 8, 16, 18, 19 Problems: 4, 6, 8, 11, 16, 20, 23, 27, 34, 41, 45, 56, 60, 65 Conceptual Questions 1. The magnetic field cannot be described as the magnetic force per unit charge
More informationLecture L17 - Orbit Transfers and Interplanetary Trajectories
S. Widnall, J. Peraire 16.07 Dynamics Fall 008 Version.0 Lecture L17 - Orbit Transfers and Interplanetary Trajectories In this lecture, we will consider how to transfer from one orbit, to another or to
More informationLinear Programming. March 14, 2014
Linear Programming March 1, 01 Parts of this introduction to linear programming were adapted from Chapter 9 of Introduction to Algorithms, Second Edition, by Cormen, Leiserson, Rivest and Stein [1]. 1
More informationSolutions to Math 51 First Exam January 29, 2015
Solutions to Math 5 First Exam January 29, 25. ( points) (a) Complete the following sentence: A set of vectors {v,..., v k } is defined to be linearly dependent if (2 points) there exist c,... c k R, not
More informationSecond Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.
Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients We will now turn our attention to nonhomogeneous second order linear equations, equations with the standard
More informationNodal and Loop Analysis
Nodal and Loop Analysis The process of analyzing circuits can sometimes be a difficult task to do. Examining a circuit with the node or loop methods can reduce the amount of time required to get important
More informationIntegrals of Rational Functions
Integrals of Rational Functions Scott R. Fulton Overview A rational function has the form where p and q are polynomials. For example, r(x) = p(x) q(x) f(x) = x2 3 x 4 + 3, g(t) = t6 + 4t 2 3, 7t 5 + 3t
More informationFinite Element Formulation for Plates - Handout 3 -
Finite Element Formulation for Plates - Handout 3 - Dr Fehmi Cirak (fc286@) Completed Version Definitions A plate is a three dimensional solid body with one of the plate dimensions much smaller than the
More information