General Navier-Stokes-Like Momentum and Mass-Energy Equations
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Chapter 5 Constitutive Modelling
Chapter 5 Constitutive Modelling 5.1 Introduction Lecture 14 Thus far we have established four conservation (or balance) equations, an entropy inequality and a number of kinematic relationships. The overall set of governing equations are collected in Table 5.1. The Eulerian form has a one more independent equation because the density must be determined, 1 whereas in the Lagrangian form it is directly related to the prescribed initial densityρ 0. Physical Law Eulerian FormN Lagrangian Formn DR ∂r Kinematics: Dt =V , 3, ∂t =v, 3; Dρ ∇ · Mass: Dt +ρ R V=0, 1,ρ 0 =ρJ, 0; DV ∇ · ∂v ∇ · Linear momentum:ρ Dt = R T+ρF , 3,ρ 0 ∂t = r p+ρ 0f, 3; Angular momentum:T=T T , 3,s=s T , 3; DΦ ∂φ Energy:ρ =T:D+ρB ∇ ·Q, 1,ρ =s: e˙+ρ b ∇ r ·q, 1; Dt − R 0 ∂t 0 − Dη ∂η0 Entropy inequality:ρ ∇ ·(Q/Θ)+ρB/Θ, 0,ρ ∇r (q/θ)+ρ b/θ, 0. Dt ≥ − R 0 ∂t ≥ − 0 Independent Equations: 11 10 Table 5.1: The governing equations for continuum mechanics in Eulerian and Lagrangian form. N is the number of independent equations in Eulerian form andn is the number of independent equations in Lagrangian form. Examining the equations reveals that they involve more unknown variables than equations, listed in Table 5.2. Once again the fact that the density in the Lagrangian formulation is prescribed means that there is one fewer unknown compared to the Eulerian formulation. Thus, in either formulation and additional eleven equations are required to close the system. -
Correct Expression of Material Derivative and Application to the Navier-Stokes Equation —– the Solution Existence Condition of Navier-Stokes Equation
Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 15 June 2020 doi:10.20944/preprints202003.0030.v4 Correct Expression of Material Derivative and Application to the Navier-Stokes Equation |{ The solution existence condition of Navier-Stokes equation Bo-Hua Sun1 1 School of Civil Engineering & Institute of Mechanics and Technology Xi'an University of Architecture and Technology, Xi'an 710055, China http://imt.xauat.edu.cn email: [email protected] (Dated: June 15, 2020) The material derivative is important in continuum physics. This paper shows that the expression d @ dt = @t + (v · r), used in most literature and textbooks, is incorrect. This article presents correct d(:) @ expression of the material derivative, namely dt = @t (:) + v · [r(:)]. As an application, the form- solution of the Navier-Stokes equation is proposed. The form-solution reveals that the solution existence condition of the Navier-Stokes equation is that "The Navier-Stokes equation has a solution if and only if the determinant of flow velocity gradient is not zero, namely det(rv) 6= 0." Keywords: material derivative, velocity gradient, tensor calculus, tensor determinant, Navier-Stokes equa- tions, solution existence condition In continuum physics, there are two ways of describ- derivative as in Ref. 1. Therefore, to revive the great ing continuous media or flows, the Lagrangian descrip- influence of Landau in physics and fluid mechanics, we at- tion and the Eulerian description. In the Eulerian de- tempt to address this issue in this dedicated paper, where scription, the material derivative with respect to time we revisit the material derivative to show why the oper- d @ dv @v must be defined. -
An Introduction to Fluid Mechanics: Supplemental Web Appendices
An Introduction to Fluid Mechanics: Supplemental Web Appendices Faith A. Morrison Professor of Chemical Engineering Michigan Technological University November 5, 2013 2 c 2013 Faith A. Morrison, all rights reserved. Appendix C Supplemental Mathematics Appendix C.1 Multidimensional Derivatives In section 1.3.1.1 we reviewed the basics of the derivative of single-variable functions. The same concepts may be applied to multivariable functions, leading to the definition of the partial derivative. Consider the multivariable function f(x, y). An example of such a function would be elevations above sea level of a geographic region or the concentration of a chemical on a flat surface. To quantify how this function changes with position, we consider two nearby points, f(x, y) and f(x + ∆x, y + ∆y) (Figure C.1). We will also refer to these two points as f x,y (f evaluated at the point (x, y)) and f . | |x+∆x,y+∆y In a two-dimensional function, the “rate of change” is a more complex concept than in a one-dimensional function. For a one-dimensional function, the rate of change of the function f with respect to the variable x was identified with the change in f divided by the change in x, quantified in the derivative, df/dx (see Figure 1.26). For a two-dimensional function, when speaking of the rate of change, we must also specify the direction in which we are interested. For example, if the function we are considering is elevation and we are standing near the edge of a cliff, the rate of change of the elevation in the direction over the cliff is steep, while the rate of change of the elevation in the opposite direction is much more gradual. -
Continuum Mechanics SS 2013
F x₁′ x₁ xₑ xₑ′ x₀′ x₀ F Continuum Mechanics SS 2013 Prof. Dr. Ulrich Schwarz Universität Heidelberg, Institut für theoretische Physik Tel.: 06221-54-9431 EMail: [email protected] Homepage: http://www.thphys.uni-heidelberg.de/~biophys/ Latest Update: July 16, 2013 Address comments and suggestions to [email protected] Contents 1. Introduction 2 2. Linear viscoelasticity in 1d 4 2.1. Motivation . 4 2.2. Elastic response . 5 2.3. Viscous response . 6 2.4. Maxwell model . 7 2.5. Laplace transformation . 9 2.6. Kelvin-Voigt model . 11 2.7. Standard linear model . 12 2.8. Boltzmanns Theory of Linear Viscoelasticity . 14 2.9. Complex modulus . 15 3. Distributed forces in 1d 19 3.1. Continuum equation for an elastic bar . 19 3.2. Elastic chain . 22 4. Elasticity theory in 3d 25 4.1. Material and spatial temporal derivatives . 25 4.2. The displacement vector field . 29 4.3. The strain tensor . 30 4.4. The stress tensor . 33 4.5. Linear elasticity theory . 39 4.6. Non-linear elasticity theory . 41 5. Applications of LET 46 5.1. Reminder on isotropic LET . 46 5.2. Pure Compression . 47 5.3. Pure shear . 47 5.4. Uni-axial stretch . 48 5.5. Biaxial strain . 50 5.6. Elastic cube under its own weight . 51 5.7. Torsion of a bar . 52 5.8. Contact of two elastic spheres (Hertz solution 1881) . 54 5.9. Compatibility conditions . 57 5.10. Bending of a plate . 57 5.11. Bending of a rod . 60 2 1 Contents 6. -
Continuum Fluid Mechanics
CONTINUUM FLUID MECHANICS Motion A body is a collection of material particles. The point X is a material point and it is the position of the material particles at time zero. x3 Definition: A one-to-one one-parameter mapping X3 x(X, t ) x = x(X, t) X x X 2 x 2 is called motion. The inverse t =0 x1 X1 X = X(x, t) Figure 1. Schematic of motion. is the inverse motion. X k are referred to as the material coordinates of particle x , and x is the spatial point occupied by X at time t. Theorem: The inverse motion exists if the Jacobian, J of the transformation is nonzero. That is ∂x ∂x J = det = det k ≠ 0 . ∂X ∂X K This is the statement of the fundamental theorem of calculus. Definition: Streamlines are the family of curves tangent to the velocity vector field at time t . Given a velocity vector field v, streamlines are governed by the following equations: dx1 dx 2 dx 3 = = for a given t. v1 v 2 v3 Definition: The streak line of point x 0 at time t is a line, which is made up of material points, which have passed through point x 0 at different times τ ≤ t . Given a motion x i = x i (X, t) and its inverse X K = X K (x, t), it follows that the 0 0 material particle X k will pass through the spatial point x at time τ . i.e., ME639 1 G. Ahmadi 0 0 0 X k = X k (x ,τ). -
Geosc 548 Notes R. Dibiase 9/2/2016
Geosc 548 Notes R. DiBiase 9/2/2016 1. Fluid properties and concept of continuum • Fluid: a substance that deforms continuously under an applied shear stress (e.g., air, water, upper mantle...) • Not practical/possible to treat fluid mechanics at the molecular level! • Instead, need to define a representative elementary volume (REV) to average quantities like velocity, density, temperature, etc. within a continuum • Continuum: smoothly varying and continuously distributed body of matter – no holes or discontinuities 1.1 What sets the scale of analysis? • Too small: bad averaging • Too big: smooth over relevant scales of variability… An obvious length scale L for ideal gases is the mean free path (average distance traveled by before hitting another molecule): = ( 1 ) 2 2 where kb is the Boltzman constant, πr is the effective4√2 cross sectional area of a molecule, T is temperature, and P is pressure. Geosc 548 Notes R. DiBiase 9/2/2016 Mean free path of atmosphere Sea level L ~ 0.1 μm z = 50 km L ~ 0.1 mm z = 150 km L ~ 1 m For liquids, not as straightforward to estimate L, but typically much smaller than for gas. 1.2 Consequences of continuum approach Consider a fluid particle in a flow with a gradient in the velocity field : �⃑ For real fluids, some “slow” molecules get caught in faster flow, and some “fast” molecules get caught in slower flow. This cannot be reconciled in continuum approach, so must be modeled. This is the origin of fluid shear stress and molecular viscosity. For gases, we can estimate viscosity from first principles using ideal gas law, calculating rate of momentum exchange directly. -
Ch.1. Description of Motion
CH.1. DESCRIPTION OF MOTION Multimedia Course on Continuum Mechanics Overview 1.1. Definition of the Continuous Medium 1.1.1. Concept of Continuum Lecture 1 1.1.2. Continuous Medium or Continuum 1.2. Equations of Motion 1.2.1 Configurations of the Continuous Medium 1.2.2. Material and Spatial Coordinates Lecture 2 1.2.3. Equation of Motion and Inverse Equation of Motion 1.2.4. Mathematical Restrictions 1.2.5. Example Lecture 3 1.3. Descriptions of Motion 1.3.1. Material or Lagrangian Description Lecture 4 1.3.2. Spatial or Eulerian Description 1.3.3. Example Lecture 5 2 Overview (cont’d) 1.4. Time Derivatives Lecture 6 1.4.1. Material and Local Derivatives 1.4.2. Convective Rate of Change Lecture 7 1.4.3. Example Lecture 8 1.5. Velocity and Acceleration 1.5.1. Velocity Lecture 9 1.5.2. Acceleration 1.5.3. Example 1.6. Stationarity and Uniformity 1.6.1. Stationary Properties Lecture 10 1.6.2. Uniform Properties 3 Overview (cont’d) 1.7. Trajectory or Pathline 1.7.1. Equation of the Trajectories 1.7.2. Example 1.8. Streamlines Lecture 11 1.8.1. Equation of the Streamlines 1.8.2. Trajectories and Streamlines 1.8.3. Example 1.8.4. Streamtubes 1.9. Control and Material Surfaces 1.9.1. Control Surface 1.9.2. Material Surface Lecture 12 1.9.3. Control Volume 1.9.4. Material Volume 4 1.1 Definition of the Continuous Medium Ch.1. Description of Motion 5 The Concept of Continuum Microscopic scale: Matter is made of atoms which may be grouped in molecules. -
Numerical Analysis and Fluid Flow Modeling of Incompressible Navier-Stokes Equations
UNLV Theses, Dissertations, Professional Papers, and Capstones 5-1-2019 Numerical Analysis and Fluid Flow Modeling of Incompressible Navier-Stokes Equations Tahj Hill Follow this and additional works at: https://digitalscholarship.unlv.edu/thesesdissertations Part of the Aerodynamics and Fluid Mechanics Commons, Applied Mathematics Commons, and the Mathematics Commons Repository Citation Hill, Tahj, "Numerical Analysis and Fluid Flow Modeling of Incompressible Navier-Stokes Equations" (2019). UNLV Theses, Dissertations, Professional Papers, and Capstones. 3611. http://dx.doi.org/10.34917/15778447 This Thesis is protected by copyright and/or related rights. It has been brought to you by Digital Scholarship@UNLV with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in UNLV Theses, Dissertations, Professional Papers, and Capstones by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact [email protected]. NUMERICAL ANALYSIS AND FLUID FLOW MODELING OF INCOMPRESSIBLE NAVIER-STOKES EQUATIONS By Tahj Hill Bachelor of Science { Mathematical Sciences University of Nevada, Las Vegas 2013 A thesis submitted in partial fulfillment of the requirements -
1. Transport and Mixing 1.1 the Material Derivative Let Be The
1. Transport and mixing 1.1 The material derivative LetV() x, t be the velocity of a fluid at the pointx = ()x,, y z and timet . Consider also some scalar fieldχ()x, t such as the temperature or density. We are interested not only in the partial derivative ofχ with respect to time,∂χ ∂⁄ t , but also in the time derivative following the motion of the fluid,dχ ⁄ dt . The latter is the so-called material derivative: dχ ⁄dt = lim [] χ(x+ V() x, t δt, t+ δ t )– χ()x, t δ⁄ t δt → 0 . (1.1) = (∂⁄ ∂t + V ⋅ ∇ )χ (),, ∇() ∂ ,,∂ ∂ In Cartesian coordinates,V = u v w ,= x y z and dχ ⁄dt = ∂ χ ∂⁄ t + u∂χ ∂⁄ x +v∂χ ∂⁄ y + w∂χ ∂⁄ z . (1.2) We will also be using spherical coordinates. The notation()u,, v w is conventional for the (eastward, northward, radially outward) components of the velocity field. In addition to the radial distance from the origin,r , we use the symbolθ for latitude (–π ⁄ 2 at the south pole,π ⁄ 2 at the north pole) andλ for longitude (ranging for zero to2π ). The gradient operator in these coordi- nates is ∇= λˆ ()r cosθ –1(∂⁄ ∂λ )+ θˆ r–1()∂⁄ ∂θ + rˆ()∂⁄ ∂r , (1.3) so that d⁄ dt = ∂⁄ ∂t +()r cosθ –1u()∂⁄ ∂λ +r–1v()∂⁄ ∂θ + w()∂⁄ ∂r . (1.4) The material derivative of a vector, such as the velocityV itself, is defined just as in 1.1. But care is required when considering the material derivative of a component of a vector if the unit vectors of one’s coordinate system are position dependent, as they are in spherical coordi- nates. -
24 Aug 2017 the Shape Derivative of the Gauss Curvature
The shape derivative of the Gauss curvature∗ An´ıbal Chicco-Ruiz, Pedro Morin, and M. Sebastian Pauletti UNL, Consejo Nacional de Investigaciones Cient´ıficas y T´ecnicas, FIQ, Santiago del Estero 2829, S3000AOM, Santa Fe, Argentina. achicco,pmorin,[email protected] August 25, 2017 Abstract We introduce new results about the shape derivatives of scalar- and vector-valued functions. They extend the results from [8] to more general surface energies. In [8] Do˘gan and Nochetto consider surface energies defined as integrals over surfaces of functions that can depend on the position, the unit normal and the mean curvature of the surface. In this work we present a systematic way to derive formulas for the shape derivative of more general geometric quantities, including the Gauss curvature (a new result not available in the literature) and other geometric invariants (eigenvalues of the second fundamental form). This is done for hyper-surfaces in the Euclidean space of any finite dimension. As an application of the results, with relevance for numerical methods in applied problems, we introduce a new scheme of Newton-type to approximate a minimizer of a shape functional. It is a mathematically sound generalization of the method presented in [5]. We finally find the particular formulas for the first and second order shape derivative of the area and the Willmore functional, which are necessary for the Newton-type method mentioned above. 2010 Mathematics Subject Classification. 65K10, 49M15, 53A10, 53A55. arXiv:1708.07440v1 [math.OC] 24 Aug 2017 Keywords. Shape derivative, Gauss curvature, shape optimization, differentiation formulas. 1 Introduction Energies that depend on the domain appear in applications in many areas, from materials science, to biology, to image processing. -
Ch.2. Deformation and Strain
CH.2. DEFORMATION AND STRAIN Multimedia Course on Continuum Mechanics Overview Introduction Lecture 1 Deformation Gradient Tensor Material Deformation Gradient Tensor Lecture 2 Lecture 3 Inverse (Spatial) Deformation Gradient Tensor Displacements Lecture 4 Displacement Gradient Tensors Strain Tensors Green-Lagrange or Material Strain Tensor Lecture 5 Euler-Almansi or Spatial Strain Tensor Variation of Distances Stretch Lecture 6 Unit elongation Variation of Angles Lecture 7 2 Overview (cont’d) Physical interpretation of the Strain Tensors Lecture 8 Material Strain Tensor, E Spatial Strain Tensor, e Lecture 9 Polar Decomposition Lecture 10 Volume Variation Lecture 11 Area Variation Lecture 12 Volumetric Strain Lecture 13 Infinitesimal Strain Infinitesimal Strain Theory Strain Tensors Stretch and Unit Elongation Lecture 14 Physical Interpretation of Infinitesimal Strains Engineering Strains Variation of Angles 3 Overview (cont’d) Infinitesimal Strain (cont’d) Polar Decomposition Lecture 15 Volumetric Strain Strain Rate Spatial Velocity Gradient Tensor Lecture 16 Strain Rate Tensor and Rotation Rate Tensor or Spin Tensor Physical Interpretation of the Tensors Material Derivatives Lecture 17 Other Coordinate Systems Cylindrical Coordinates Lecture 18 Spherical Coordinates 4 2.1 Introduction Ch.2. Deformation and Strain 5 Deformation Deformation: transformation of a body from a reference configuration to a current configuration. Focus on the relative movement of a given particle w.r.t. the particles in its neighbourhood (at differential level). It includes changes of size and shape. 6 2.2 Deformation Gradient Tensors Ch.2. Deformation and Strain 7 Continuous Medium in Movement Ω0: non-deformed (or reference) Ω or Ωt: deformed (or present) configuration, at reference time t0. configuration, at present time t. -
150A Review Session 2/13/2014 Fluid Statics • • Pressure Acts in All
150A Review Session 2/13/2014 Fluid Statics Pressure acts in all directions, normal to the surrounding surfaces or Whenever a pressure difference is the driving force, use gauge pressure o Bernoulli equation o Momentum balance with Patm everywhere outside Whenever you are looking for the total pressure, use absolute pressure o Force balances Hydrostatic head = pressure from a static column of fluid From a z-direction force balance on a differential cube: o Differential form: use when a variable is changing continuously . Compressible (changing density) fluid, i.e. altitude . Force in x or y direction (changing height), i.e. column support o Integrated form: use when all variables are constant . Total pressure in z direction, i.e. manometer Buoyancy o Recommended to NOT use a “buoyant force” . “Buoyant force” is simply a pressure difference o Do a force balance including all the different pressures & weights . Downward: gravity (W=mg) and atmospheric pressure (Patm*A) . Upward: pressure from fluid below submerged container (ρgΔz*A) 150A Review Session 2/13/2014 Manometers o Pressures are equal at the two points that are at the same height and connected by the same fluid o Work up or down from that equality point, including all fluids (& Patm) Compressible fluids o At constant elevation, from ideal gas law, o 3 ways to account for changing elevation using the ideal gas law . Isothermal ( ) . Linear temperature gradient ( ) . Isentropic ( ) Macroscopic Momentum Balances [Accumulation = In – Out + Generation] for momentum of fluid