Chapter 4 Continuity, Energy, and Momentum Equations
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Derivation of Fluid Flow Equations
TPG4150 Reservoir Recovery Techniques 2017 1 Fluid Flow Equations DERIVATION OF FLUID FLOW EQUATIONS Review of basic steps Generally speaking, flow equations for flow in porous materials are based on a set of mass, momentum and energy conservation equations, and constitutive equations for the fluids and the porous material involved. For simplicity, we will in the following assume isothermal conditions, so that we not have to involve an energy conservation equation. However, in cases of changing reservoir temperature, such as in the case of cold water injection into a warmer reservoir, this may be of importance. Below, equations are initially described for single phase flow in linear, one- dimensional, horizontal systems, but are later on extended to multi-phase flow in two and three dimensions, and to other coordinate systems. Conservation of mass Consider the following one dimensional rod of porous material: Mass conservation may be formulated across a control element of the slab, with one fluid of density ρ is flowing through it at a velocity u: u ρ Δx The mass balance for the control element is then written as: ⎧Mass into the⎫ ⎧Mass out of the ⎫ ⎧ Rate of change of mass⎫ ⎨ ⎬ − ⎨ ⎬ = ⎨ ⎬ , ⎩element at x ⎭ ⎩element at x + Δx⎭ ⎩ inside the element ⎭ or ∂ {uρA} − {uρA} = {φAΔxρ}. x x+ Δx ∂t Dividing by Δx, and taking the limit as Δx approaches zero, we get the conservation of mass, or continuity equation: ∂ ∂ − (Aρu) = (Aφρ). ∂x ∂t For constant cross sectional area, the continuity equation simplifies to: ∂ ∂ − (ρu) = (φρ) . ∂x ∂t Next, we need to replace the velocity term by an equation relating it to pressure gradient and fluid and rock properties, and the density and porosity terms by appropriate pressure dependent functions. -
A Brief Tour of Vector Calculus
A BRIEF TOUR OF VECTOR CALCULUS A. HAVENS Contents 0 Prelude ii 1 Directional Derivatives, the Gradient and the Del Operator 1 1.1 Conceptual Review: Directional Derivatives and the Gradient........... 1 1.2 The Gradient as a Vector Field............................ 5 1.3 The Gradient Flow and Critical Points ....................... 10 1.4 The Del Operator and the Gradient in Other Coordinates*............ 17 1.5 Problems........................................ 21 2 Vector Fields in Low Dimensions 26 2 3 2.1 General Vector Fields in Domains of R and R . 26 2.2 Flows and Integral Curves .............................. 31 2.3 Conservative Vector Fields and Potentials...................... 32 2.4 Vector Fields from Frames*.............................. 37 2.5 Divergence, Curl, Jacobians, and the Laplacian................... 41 2.6 Parametrized Surfaces and Coordinate Vector Fields*............... 48 2.7 Tangent Vectors, Normal Vectors, and Orientations*................ 52 2.8 Problems........................................ 58 3 Line Integrals 66 3.1 Defining Scalar Line Integrals............................. 66 3.2 Line Integrals in Vector Fields ............................ 75 3.3 Work in a Force Field................................. 78 3.4 The Fundamental Theorem of Line Integrals .................... 79 3.5 Motion in Conservative Force Fields Conserves Energy .............. 81 3.6 Path Independence and Corollaries of the Fundamental Theorem......... 82 3.7 Green's Theorem.................................... 84 3.8 Problems........................................ 89 4 Surface Integrals, Flux, and Fundamental Theorems 93 4.1 Surface Integrals of Scalar Fields........................... 93 4.2 Flux........................................... 96 4.3 The Gradient, Divergence, and Curl Operators Via Limits* . 103 4.4 The Stokes-Kelvin Theorem..............................108 4.5 The Divergence Theorem ...............................112 4.6 Problems........................................114 List of Figures 117 i 11/14/19 Multivariate Calculus: Vector Calculus Havens 0. -
Continuity Equation in Pressure Coordinates
Continuity Equation in Pressure Coordinates Here we will derive the continuity equation from the principle that mass is conserved for a parcel following the fluid motion (i.e., there is no flow across the boundaries of the parcel). This implies that δxδyδp δM = ρ δV = ρ δxδyδz = − g is conserved following the fluid motion: 1 d(δM ) = 0 δM dt 1 d()δM = 0 δM dt g d ⎛ δxδyδp ⎞ ⎜ ⎟ = 0 δxδyδp dt ⎝ g ⎠ 1 ⎛ d(δp) d(δy) d(δx)⎞ ⎜δxδy +δxδp +δyδp ⎟ = 0 δxδyδp ⎝ dt dt dt ⎠ 1 ⎛ dp ⎞ 1 ⎛ dy ⎞ 1 ⎛ dx ⎞ δ ⎜ ⎟ + δ ⎜ ⎟ + δ ⎜ ⎟ = 0 δp ⎝ dt ⎠ δy ⎝ dt ⎠ δx ⎝ dt ⎠ Taking the limit as δx, δy, δp → 0, ∂u ∂v ∂ω Continuity equation + + = 0 in pressure ∂x ∂y ∂p coordinates 1 Determining Vertical Velocities • Typical large-scale vertical motions in the atmosphere are of the order of 0. 01-01m/s0.1 m/s. • Such motions are very difficult, if not impossible, to measure directly. Typical observational errors for wind measurements are ~1 m/s. • Quantitative estimates of vertical velocity must be inferred from quantities that can be directly measured with sufficient accuracy. Vertical Velocity in P-Coordinates The equivalent of the vertical velocity in p-coordinates is: dp ∂p r ∂p ω = = +V ⋅∇p + w dt ∂t ∂z Based on a scaling of the three terms on the r.h.s., the last term is at least an order of magnitude larger than the other two. Making the hydrostatic approximation yields ∂p ω ≈ w = −ρgw ∂z Typical large-scale values: for w, 0.01 m/s = 1 cm/s for ω, 0.1 Pa/s = 1 μbar/s 2 The Kinematic Method By integrating the continuity equation in (x,y,p) coordinates, ω can be obtained from the mean divergence in a layer: ⎛ ∂u ∂v ⎞ ∂ω ⎜ + ⎟ + = 0 continuity equation in (x,y,p) coordinates ⎝ ∂x ∂y ⎠ p ∂p p2 p2 ⎛ ∂u ∂v ⎞ ∂ω = − ⎜ + ⎟ ∂p rearrange and integrate over the layer ∫p ∫ ⎜ ⎟ 1 ∂x ∂y p1⎝ ⎠ p ⎛ ∂u ∂v ⎞ ω(p )−ω(p ) = (p − p )⎜ + ⎟ overbar denotes pressure- 2 1 1 2 ⎜ ⎟ weighted vertical average ⎝ ∂x ∂y ⎠ p To determine vertical motion at a pressure level p2, assume that p1 = surface pressure and there is no vertical motion at the surface. -
Chapter 3 Newtonian Fluids
CM4650 Chapter 3 Newtonian Fluid 2/5/2018 Mechanics Chapter 3: Newtonian Fluids CM4650 Polymer Rheology Michigan Tech Navier-Stokes Equation v vv p 2 v g t 1 © Faith A. Morrison, Michigan Tech U. Chapter 3: Newtonian Fluid Mechanics TWO GOALS •Derive governing equations (mass and momentum balances •Solve governing equations for velocity and stress fields QUICK START V W x First, before we get deep into 2 v (x ) H derivation, let’s do a Navier-Stokes 1 2 x1 problem to get you started in the x3 mechanics of this type of problem solving. 2 © Faith A. Morrison, Michigan Tech U. 1 CM4650 Chapter 3 Newtonian Fluid 2/5/2018 Mechanics EXAMPLE: Drag flow between infinite parallel plates •Newtonian •steady state •incompressible fluid •very wide, long V •uniform pressure W x2 v1(x2) H x1 x3 3 EXAMPLE: Poiseuille flow between infinite parallel plates •Newtonian •steady state •Incompressible fluid •infinitely wide, long W x2 2H x1 x3 v (x ) x1=0 1 2 x1=L p=Po p=PL 4 2 CM4650 Chapter 3 Newtonian Fluid 2/5/2018 Mechanics Engineering Quantities of In more complex flows, we can use Interest general expressions that work in all cases. (any flow) volumetric ⋅ flow rate ∬ ⋅ | average 〈 〉 velocity ∬ Using the general formulas will Here, is the outwardly pointing unit normal help prevent errors. of ; it points in the direction “through” 5 © Faith A. Morrison, Michigan Tech U. The stress tensor was Total stress tensor, Π: invented to make the calculation of fluid stress easier. Π ≡ b (any flow, small surface) dS nˆ Force on the S ⋅ Π surface V (using the stress convention of Understanding Rheology) Here, is the outwardly pointing unit normal of ; it points in the direction “through” 6 © Faith A. -
Part IA — Vector Calculus
Part IA | Vector Calculus Based on lectures by B. Allanach Notes taken by Dexter Chua Lent 2015 These notes are not endorsed by the lecturers, and I have modified them (often significantly) after lectures. They are nowhere near accurate representations of what was actually lectured, and in particular, all errors are almost surely mine. 3 Curves in R 3 Parameterised curves and arc length, tangents and normals to curves in R , the radius of curvature. [1] 2 3 Integration in R and R Line integrals. Surface and volume integrals: definitions, examples using Cartesian, cylindrical and spherical coordinates; change of variables. [4] Vector operators Directional derivatives. The gradient of a real-valued function: definition; interpretation as normal to level surfaces; examples including the use of cylindrical, spherical *and general orthogonal curvilinear* coordinates. Divergence, curl and r2 in Cartesian coordinates, examples; formulae for these oper- ators (statement only) in cylindrical, spherical *and general orthogonal curvilinear* coordinates. Solenoidal fields, irrotational fields and conservative fields; scalar potentials. Vector derivative identities. [5] Integration theorems Divergence theorem, Green's theorem, Stokes's theorem, Green's second theorem: statements; informal proofs; examples; application to fluid dynamics, and to electro- magnetism including statement of Maxwell's equations. [5] Laplace's equation 2 3 Laplace's equation in R and R : uniqueness theorem and maximum principle. Solution of Poisson's equation by Gauss's method (for spherical and cylindrical symmetry) and as an integral. [4] 3 Cartesian tensors in R Tensor transformation laws, addition, multiplication, contraction, with emphasis on tensors of second rank. Isotropic second and third rank tensors. -
Generalized Stokes' Theorem
Chapter 4 Generalized Stokes’ Theorem “It is very difficult for us, placed as we have been from earliest childhood in a condition of training, to say what would have been our feelings had such training never taken place.” Sir George Stokes, 1st Baronet 4.1. Manifolds with Boundary We have seen in the Chapter 3 that Green’s, Stokes’ and Divergence Theorem in Multivariable Calculus can be unified together using the language of differential forms. In this chapter, we will generalize Stokes’ Theorem to higher dimensional and abstract manifolds. These classic theorems and their generalizations concern about an integral over a manifold with an integral over its boundary. In this section, we will first rigorously define the notion of a boundary for abstract manifolds. Heuristically, an interior point of a manifold locally looks like a ball in Euclidean space, whereas a boundary point locally looks like an upper-half space. n 4.1.1. Smooth Functions on Upper-Half Spaces. From now on, we denote R+ := n n f(u1, ... , un) 2 R : un ≥ 0g which is the upper-half space of R . Under the subspace n n n topology, we say a subset V ⊂ R+ is open in R+ if there exists a set Ve ⊂ R open in n n n R such that V = Ve \ R+. It is intuitively clear that if V ⊂ R+ is disjoint from the n n n subspace fun = 0g of R , then V is open in R+ if and only if V is open in R . n n Now consider a set V ⊂ R+ which is open in R+ and that V \ fun = 0g 6= Æ. -
LECTURE 27: the LAPLAST ONE Monday, November 25, 2019 5:23 PM
LECTURE 27: THE LAPLAST ONE Monday, November 25, 2019 5:23 PM Today: Three little remaining topics related to Laplace I- 3 DIMENSIONS Previously: Solved Laplace's equation in 2 dimensions by converting it into polar coordinates. The same idea works in 3 dimensions if you use spherical coordinates. 3 Suppose u = u(x,y,z) solves u xx + u yy + u zz = 0 in R Using spherical coordinates, you eventually get urr + 2 ur + JUNK = 0 r (where r = x 2 + y 2 + z 2 and JUNK doesn't depend on r) If we're looking for radial solutions, we set JUNK = 0 Get u rr + 2 u r = 0 which you can solve to get r u(x,y,z) = -C + C' solves u xx + u yy + u zz = 0 r Finally, setting C = -1/(4π) and C' = 0, you get Fundamental solution of Laplace for n = 3 S(x,y,z) = 1 = 4πr 4π x 2 + y 2 + z 2 Note: In n dimensions, get u rr + n-1 ur = 0 r => u( r ) = -C + C' rn-2 => S(x) = Blah (for some complicated Blah) rn-1 Why fundamental? Because can build up other solutions from this! Fun Fact: A solution of -Δ u = f (Poisson's equation) in R n is u(x) = S(x) * f(x) = S(x -y) f(y) dy (Basically the constant is chosen such that -ΔS = d0 <- Dirac at 0) II - DERIVATION OF LAPLACE Two goals: Derive Laplace's equation, and also highlight an important structure of Δu = 0 A) SETTING n Definition: If F = (F 1, …, F n) is a vector field in R , then div(F) = (F 1)x1 + … + (F n)xn Notice : If u = u(x 1, …, x n), then u = (u x1 , …, u xn ) => div( u) = (u x1 )x1 + … + (u xn )xn = u x1 x1 + … + u xn xn = Δu Fact: Δu = div( u) "divergence structure" In particular, Laplace's equation works very well with the divergence theorem Divergence Theorem: F n dS = div(F) dx bdy D D B) DERIVATION Suppose you have a fluid F that is in equilibrium (think F = temperature or chemical concentration) Equilibrium means that for any region D, the net flux of F is 0. -
Green Gauss Theorem Yesterday, We Continued Discussions on Index Notations That Can Be Used to Represent Tensors
15/02/2017 LECTURE – 15 Green Gauss Theorem Yesterday, we continued discussions on index notations that can be used to represent tensors. In index notations we saw the Gradient of a scalar Divergence of a vector Cross product of vector etc. We also saw that a second rank tensor can be written as a sum of a symmetric & asymmetric tensor. 11 i.e, BBBBB[][] ij22 ij ji ij ji First part is symmetric & second part is asymmetric Today we will briefly discuss about Green Gauss Theorem etc. Green Gauss Theorem relates the volume & surface integrals. The most common form of Gauss’s theorem is the Gauss divergence theorem which you have studied in previous courses. 푛 푣 ds If you have a volume U formed by surface S, the Gauss divergence theorem for a vector v suggest that v.. ndSˆ vdU SU where, S = bounding surface on closed surface U = volumetric domain nˆ = the unit outward normal vector of the elementary surface area ds This Gauss Divergence theorem can also be represented using index notations. v v n dS i dU ii SUxi For any scalar multiple or factor for vector v , say v , the Green Gauss can be represented as (v . nˆ ) dS .( v ) dU SU i.e. (v . nˆ ) dS ( . v ) dU ( v . ) dU SUU v or v n dSi dU v dU i i i SUUxxii Gauss’s theorem is applicable not only to a vector . It can be applied to any tensor B (say) B B n dSij dU B dU ij i ij SUUxxii Stoke’s Theorem Stoke’s theorem relates the integral over an open surface S, to line integral around the surface’s bounding curve (say C) You need to appropriately choose the unit outward normal vector to the surface 푛 푡 dr v. -
Vector Calculus Applicationsž 1. Introduction 2. the Heat Equation
Vector Calculus Applications 1. Introduction The divergence and Stokes’ theorems (and their related results) supply fundamental tools which can be used to derive equations which can be used to model a number of physical situations. Essentially, these theorems provide a mathematical language with which to express physical laws such as conservation of mass, momentum and energy. The resulting equations are some of the most fundamental and useful in engineering and applied science. In the following sections the derivation of some of these equations will be outlined. The goal is to show how vector calculus is used in applications. Generally speaking, the equations are derived by first using a conservation law in integral form, and then converting the integral form to a differential equation form using the divergence theorem, Stokes’ theorem, and vector identities. The differential equation forms tend to be easier to work with, particularly if one is interested in solving such equations, either analytically or numerically. 2. The Heat Equation Consider a solid material occupying a region of space V . The region has a boundary surface, which we shall designate as S. Suppose the solid has a density and a heat capacity c. If the temperature of the solid at any point in V is T.r; t/, where r x{ y| zkO is the position vector (so that T depends upon x, y, z and t), then theE total heatE eergyD O containedC O C in the solid is • cT dV : V Heat energy can get in or out of the region V by flowing across the boundary S, or it can be generated inside V . -
CONTINUITY EQUATION Another Principle on Which We Can Derive a New Equation Is the Conservation of Mass
ESCI 342 – Atmospheric Dynamics I Lesson 7 – The Continuity and Additional Equations Suggested Reading: Martin, Chapter 3 THE SYSTEM OF EQUATIONS IS INCOMPLETE The momentum equations in component form comprise a system of three equations with 4 unknown quantities (u, v, p, and ). Du1 p fv (1) Dt x Dv1 p fu (2) Dt y p g (3) z They are not a closed set, because there are four dependent variables (u, v, p, and ), but only three equations. We need to come up with some more equations in order to close the set. DERIVATION OF THE CONTINUITY EQUATION Another principle on which we can derive a new equation is the conservation of mass. The equation derived from this principle is called the mass continuity equation, or simply the continuity equation. Imagine a cube at a fixed point in space. The net change in mass contained within the cube is found by adding up the mass fluxes entering and leaving through each face of the cube.1 The mass flux across a face of the cube normal to the x-axis is given by u. Referring to the picture below, these fluxes will lead to a rate of change in mass within the cube given by m u yz u yz (4) t x xx 1 A flux is a quantity per unit area per unit time. Mass flux is therefore the rate at which mass moves across a unit area, and would have units of kg s1 m2. The mass in the cube can be written in terms of the density as m xyz so that m x y z . -
On the Modeling and Design of Zero-Net Mass Flux Actuators
ON THE MODELING AND DESIGN OF ZERO-NET MASS FLUX ACTUATORS By QUENTIN GALLAS A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2005 Copyright 2005 by Quentin Gallas Pour ma famille et mes amis, d’ici et de là-bas… (To my family and friends, from here and over there…) ACKNOWLEDGMENTS Financial support for the research project was provided by a NASA-Langley Research Center Grant and an AFOSR grant. First, I would like to thank my advisor, Dr. Louis N. Cattafesta. His continual guidance and support gave me the motivation and encouragement that made this work possible. I would also like to express my gratitude especially to Dr. Mark Sheplak, and to the other members of my committee (Dr. Bruce Carroll, Dr. Bhavani Sankar, and Dr. Toshikazu Nishida) for advising and guiding me with various aspects of this project. I thank the members of the Interdisciplinary Microsystems group and of the Mechanical and Aerospace Engineering department (particularly fellow student Ryan Holman) for their help with my research and their friendship. I thank everyone who contributed in a small but significant way to this work. I also thank Dr. Rajat Mittal (George Washington University) and his student Reni Raju, who greatly helped me with the computational part of this work. Finally, special thanks go to my family and friends, from the States and from France, for always encouraging me to pursue my interests and for making that pursuit possible. iv TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................................................................................ -
1 the Continuity Equation 2 the Heat Equation
1 The Continuity Equation Imagine a fluid flowing in a region R of the plane in a time dependent fashion. At each point (x; y) R2 it has a velocity v = v (x; y; t) at time t. Let ρ = ρ(x; y; t) be the density of the fluid 2 −! −! at (x; y) at time t. Let P be any point in the interior of R and let Dr be the closed disk of radius r > 0 and center P . The mass of fluid inside Dr at any time t is ρ dxdy: ZZDr If matter is neither created nor destroyed inside Dr, the rate of decrease of this quantity is equal to the flux of the vector field −!J = ρ−!v across Cr, the positively oriented boundary of Dr. We therefore have d ρ dxdy = −!J −!N ds; dt − · ZZDr ZCr where N~ is the outer normal and ds is the element of arc length. Notice that the minus sign is needed since positive flux at time t represents loss of total mass at that time. Also observe that the amount of fluid transported across a small piece ds of the boundary of Dr at time t is ρ−!v −!N ds. Differentiating under the integral sign on the left-hand side and using the flux form of Green’s· Theorem on the right-hand side, we get @ρ dxdy = −!J dxdy: @t − r · ZZDr ZZDr Gathering terms on the left-hand side, we get @ρ ( + −!J ) dxdy = 0: @t r · ZZDr If the integrand was not zero at P it would be different from zero on Dr for some sufficiently small r and hence the integral would not be zero which is not the case.