This document provides notes on advanced fluid mechanics. It introduces fluid particle kinematics, including definitions of the particle position, velocity, and acceleration vectors in both Lagrangian and Eulerian descriptions. It defines the material derivative and discusses its use in describing how a fluid property changes as it moves with the flow. Pathlines and streamlines are also defined. Two examples of fluid flow in a convergent duct are provided to illustrate the concepts.
The document discusses the calculus of variations and derives Euler's equation. It explains that the fundamental problem is to find an unknown function that makes a functional (function of a function) an extremum. Euler's equation provides the necessary condition for a functional to be extremized. As an example, it derives the Euler-Lagrange equation for the shortest distance between two points in Cartesian coordinates, showing the path is a straight line.
Differential equations model real-world phenomena involving continuously changing quantities and their rates of change. Some examples include:
1) Population growth modeled by an exponential growth differential equation where the rate of change of population is proportional to the current population.
2) The motion of a falling object modeled by a differential equation where acceleration due to gravity relates the rate of change of velocity to the rate of change of height over time.
3) Newton's law of cooling modeled by a differential equation where the rate of change of temperature is proportional to the difference between the temperature of an object and its environment.
4) The electric current in an RL circuit modeled by a differential equation relating the rate of change of current to
This document provides an introduction to fluid mechanics. It discusses how fluids are essential to life and have shaped history. It then provides brief biographies of some important figures in the history of fluid mechanics, such as Archimedes, Newton, Euler, Stokes, and Reynolds. It also discusses the significance of fluid mechanics across many fields including weather, vehicles, physiology, sports, and engineering. The document concludes by outlining the key components of analytical fluid dynamics, experimental fluid dynamics, and computational fluid dynamics.
Magnetohydrodynamic Rayleigh Problem with Hall Effect in a porous PlateIJERA Editor
This paper gives very significant analytical and numerical results to the magnetohydrodynamic flow version of
the classical Rayleigh problem including Hall Effect in a porous plate. An exact solution of the MHD flow of
incompressible, electrically conducting, viscous fluid past an uniformly accelerated and insulated infinite porous
plate has been presented. Numerical values for the effects of the Hall parameter N, the Hartmann number M and
the Porosity parameter P0 on the velocity components u and v are tabulated and their profiles are shown
graphically. The numerical results show that the velocity component u and v increases with the increase of N,
decreases with the increase of P0 and u decreases and v increases with the increase of M.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
This document provides an overview of classical and quantum mechanics concepts relevant to statistical thermodynamics. It begins with an introduction to classical mechanics using Lagrangian and Hamiltonian formulations. It then discusses limitations of classical mechanics and introduces key concepts in quantum mechanics, including the Schrodinger equation. Examples are provided of a particle in a box and harmonic oscillator to illustrate differences between classical and quantum descriptions of particle behavior.
This document discusses differential equations, which are equations involving derivatives of an unknown function. It provides examples of first and second order differential equations. Differential equations have applications in science and engineering, such as modeling Newton's laws of cooling, the rate of decay of radioactive materials, Newton's second law of dynamics, the Schrodinger wave equation, RL circuits, and the heat equation in thermodynamics. The document also covers the order, degree, and types of differential equations, as well as their use in modeling natural growth/decay, free falling objects, springs, and Jacobian properties.
The document discusses the calculus of variations and derives Euler's equation. It explains that the fundamental problem is to find an unknown function that makes a functional (function of a function) an extremum. Euler's equation provides the necessary condition for a functional to be extremized. As an example, it derives the Euler-Lagrange equation for the shortest distance between two points in Cartesian coordinates, showing the path is a straight line.
Differential equations model real-world phenomena involving continuously changing quantities and their rates of change. Some examples include:
1) Population growth modeled by an exponential growth differential equation where the rate of change of population is proportional to the current population.
2) The motion of a falling object modeled by a differential equation where acceleration due to gravity relates the rate of change of velocity to the rate of change of height over time.
3) Newton's law of cooling modeled by a differential equation where the rate of change of temperature is proportional to the difference between the temperature of an object and its environment.
4) The electric current in an RL circuit modeled by a differential equation relating the rate of change of current to
This document provides an introduction to fluid mechanics. It discusses how fluids are essential to life and have shaped history. It then provides brief biographies of some important figures in the history of fluid mechanics, such as Archimedes, Newton, Euler, Stokes, and Reynolds. It also discusses the significance of fluid mechanics across many fields including weather, vehicles, physiology, sports, and engineering. The document concludes by outlining the key components of analytical fluid dynamics, experimental fluid dynamics, and computational fluid dynamics.
Magnetohydrodynamic Rayleigh Problem with Hall Effect in a porous PlateIJERA Editor
This paper gives very significant analytical and numerical results to the magnetohydrodynamic flow version of
the classical Rayleigh problem including Hall Effect in a porous plate. An exact solution of the MHD flow of
incompressible, electrically conducting, viscous fluid past an uniformly accelerated and insulated infinite porous
plate has been presented. Numerical values for the effects of the Hall parameter N, the Hartmann number M and
the Porosity parameter P0 on the velocity components u and v are tabulated and their profiles are shown
graphically. The numerical results show that the velocity component u and v increases with the increase of N,
decreases with the increase of P0 and u decreases and v increases with the increase of M.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
This document provides an overview of classical and quantum mechanics concepts relevant to statistical thermodynamics. It begins with an introduction to classical mechanics using Lagrangian and Hamiltonian formulations. It then discusses limitations of classical mechanics and introduces key concepts in quantum mechanics, including the Schrodinger equation. Examples are provided of a particle in a box and harmonic oscillator to illustrate differences between classical and quantum descriptions of particle behavior.
This document discusses differential equations, which are equations involving derivatives of an unknown function. It provides examples of first and second order differential equations. Differential equations have applications in science and engineering, such as modeling Newton's laws of cooling, the rate of decay of radioactive materials, Newton's second law of dynamics, the Schrodinger wave equation, RL circuits, and the heat equation in thermodynamics. The document also covers the order, degree, and types of differential equations, as well as their use in modeling natural growth/decay, free falling objects, springs, and Jacobian properties.
Heat Transfer in the flow of a Non-Newtonian second-order fluid over an enclo...IJMERJOURNAL
ABSTRACT : The problem of the heat transfer in the flow of an incompressible non-Newtonian second-order fluid over an enclosed torsionally oscillating discs in the presence of the magnetic field has been discussed. The obtained differential equations are highly non-linear and contain upto fifth order derivatives of the flow and energy functions. Hence exact or numerical solutions of the differential equations are not possible subject to the given natural boundary conditions; therefore the regular perturbation technique is applied. The flow functions 퐻, 퐺, 퐿 and 푀 are expanded in the powers of the amplitude (taken small) of the oscillations. The behaviour of the temperature distribution at different values of Reynolds number, phase difference, magnetic field and second-order parameters has been studied and shown graphically. The results obtained are compared with those for the infinite torsionally oscillating discs by taking the Reynolds number of out-flow 푅푚 and circulatory flow 푅퐿 equals to zero. Nusselt number at oscillating and stator disc has also been calculated and its behaviour is represented graphically.
Estimate the hidden States, Parameters, Signals of a Linear Dynamic Stochastic System from Noisy Measurements. It requires knowledge of probability theory. Presentation at graduate level in math., engineering
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://solohermelin.com. Since a few Figure were not downloaded I recommend to see the presentation on my website at RADAR Folder, Tracking subfolder.
This presentation is intended for undergraduate students in physics and engineering.
Please send comments to solo.hermelin@gmail.com.
For more presentations on different subjects please visit my homepage at http://www.solohermelin.com.
This presentation is in the Physics folder.
An object experiencing the acceleration of gravity is described. The acceleration of gravity on Earth is approximately 9.8 m/s2 downward. Equations of motion are provided for falling bodies, including simplified equations that assume the object starts from rest. Examples are worked through comparing the traditional method of using negative signs for downward motion to an alternative method where downward is considered positive to simplify the signs.
This document presents the mathematical modeling of heat transfer and phase change in three dimensions using the finite element method. It begins with the governing equations - the continuity, Navier-Stokes, and heat equations along with the Stefan free boundary condition. It then derives the variational formulation and discretizes the equations using finite elements. The nonlinear system is solved using Newton's method to find the numerical solution for temperature, velocity, and the moving solid-liquid interface over time.
Describes the mathematics of the Calculus of Variations.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website on http://www.solohermelin.com
Basic differential equations in fluid mechanicsTarun Gehlot
This document provides an overview of fluid dynamics concepts including the continuity equation, Navier-Stokes equations, and examples of their application to laminar flow situations. It derives the 1-dimensional continuity equation and uses it to describe flow between parallel plates. It then derives the equation for laminar flow velocity profile between infinite horizontal parallel plates based on the Navier-Stokes equations and applies it to calculate discharge rate. Finally, it provides an example problem calculating discharge rate and power for an oil skimming device.
- Thermodynamics describes the equilibrium states of systems and the spontaneous processes between those states.
- The first law of thermodynamics states that the total energy of an isolated system is conserved. It can be expressed as ΔU = Q + W, where ΔU is the change in internal energy, Q is heat, and W is work.
- For a closed system, the first law takes the form ΔU = Q - PΔV, where PΔV is the work done by expansion or compression. For a constant volume process where no work is done, ΔU = Q.
- The enthalpy H is a state function defined as H = U + PV. For a
The document provides solutions to two heat equation problems using separation of variables. For the first problem, the solution is found to be a sum of sine functions with decaying exponentials in time. For the second problem, a similar approach is taken, but the eigenfunctions are determined to be cosines instead of sines due to the different boundary condition. In both cases, the solutions involve finding eigenvalues and eigenfunctions by considering different cases for the separation constant and applying the boundary conditions.
Non equilibrium thermodynamics in multiphase flowsSpringer
This chapter discusses the principle of microscopic reversibility and its implications. It can be summarized as follows:
1) The principle of microscopic reversibility states that the probability of a molecular process occurring is equal to the probability of the reverse process at equilibrium.
2) This leads to the rule of detailed balances and Onsager's reciprocity relations, which relate the linear response of a system to external perturbations to its intrinsic fluctuation properties.
3) The reciprocity relations require that the Onsager coefficients relating fluxes to forces be symmetric. Various formulations of the fluctuation-dissipation theorem are also derived from microscopic reversibility.
The one-dimensional heat equation describes heat flow along a rod. It can be solved using separation of variables. For a rod with insulated sides initially at uniform temperature u0 and ends suddenly cooled to 0°C:
1) The solution is a Fourier series involving eigenfunctions that satisfy the boundary conditions.
2) The temperature is the sum of the eigenfunctions weighted by Fourier coefficients involving u0.
3) As time increases, the temperature decreases towards the boundary values according to exponential decay governed by the eigenvalues.
This document discusses differential equations and their applications. It defines ordinary and partial differential equations, and describes various types of ordinary differential equations including separable, homogeneous, non-homogeneous, exact, and linear equations. It also discusses exponential growth and decay models using differential equations. Examples are provided to illustrate radioactive decay modeling using half-life equations and carbon dating to determine the age of fossils.
The document outlines the basic equations of fluid mechanics, beginning with an introduction. It then summarizes the continuity equation in 3 parts - the differential formulation, integral formulation of continuity equation, and Reynolds transport theorem. Finally, it discusses the Navier-Stokes equation by outlining the balance of forces, constitutive relations of Stokes, and differential and integral formulations of momentum equations.
Two basic topics of heat transfer have been covered up by me based on the famous books of :-
1) John H. Lienhard (Professor Emeritus, University of Houston)
2) J.P. Holman (Professor, Southern Methodist University)
3) Prabal Talukdar (Associate Professor, IIT, India)
This document discusses anomaly and parity odd transport coefficients in 1+1 dimensions. It begins by defining what an anomaly is, noting that a symmetry of classical physics may not hold at the quantum level. It then relates anomalies to hydrodynamics, showing how anomalies can constrain transport coefficients. The document evaluates the U(1) chiral anomaly using the Fujikawa method and relates it to hydrodynamic equations. It then uses the Kubo formula from linear response theory to evaluate the relevant current-stress tensor correlator from finite temperature field theory and performs Matsubara sums to obtain an expression for the parity odd transport coefficient.
The document discusses the lumped element method (LEM) for analyzing transient heat transfer problems. It defines a lumped system as one where the interior temperature remains uniform over time. The lumped element approach provides a simplification to heat transfer calculations using a lumped parameter called the time constant. The document also covers using the method of separation of variables to solve the heat equation for transient conduction problems, reducing the partial differential equation to ordinary differential equations that can be solved. It provides an example of applying separation of variables to a one-dimensional conduction problem between fixed temperatures.
Quantum Interrogation: Interaction-Free Determination of Existence (Physics 1...BenjaminKan4
In this report, we summarize the given scenario behind the “Quantum Interrogation" problem, and offer historical background of the development of quantum “interaction-free measurement" theory. We then describe some real-world applications of this procedure, whether already verified experimentally or as potential applications in the future. Finally, we exhibit our calculations that display the feasibility of this quantum effect, and summarize the key takeaways from this problem.
Proceedings A Method For Finding Complete Observables In Classical Mechanicsvcuesta
1. The document presents a new method for finding complete observables in classical mechanics, which are gauge invariant quantities.
2. The method starts with partial observables and clocks, which are non-gauge invariant phase space functions. Using constants of motion, the partial observables can be written in terms of the clocks to obtain complete observables.
3. As an example, the method is applied to a particle in a gravitational field, where the Hamiltonian is used as a constant of motion to write the position variable as a function of the momentum and time.
Oscillations are ubiquitous in nature and occur in many systems when disturbed from equilibrium. The document introduces the simple harmonic oscillator (SHO) model to describe small oscillations near equilibrium. A SHO undergoes sinusoidal oscillations with an angular frequency that depends on the spring constant and mass. Complex numbers provide a useful way to represent the amplitude and phase of oscillations. The SHO model applies to many systems locally, as potentials can often be approximated as quadratic near equilibrium points.
This document summarizes applications of differential equations to real world systems including cooling/warming, population growth, radioactive decay, electrical circuits, survivability with AIDS, economics, drug distribution in the human body, and a pursuit problem. Examples are provided for each application to illustrate solutions to related differential equations. Key concepts covered include Newton's law of cooling, population models, carbon dating, series circuits, survival models, supply and demand models, compound interest, drug concentration in the body over time, and a mathematical model for a dog chasing a rabbit.
Heat Transfer in the flow of a Non-Newtonian second-order fluid over an enclo...IJMERJOURNAL
ABSTRACT : The problem of the heat transfer in the flow of an incompressible non-Newtonian second-order fluid over an enclosed torsionally oscillating discs in the presence of the magnetic field has been discussed. The obtained differential equations are highly non-linear and contain upto fifth order derivatives of the flow and energy functions. Hence exact or numerical solutions of the differential equations are not possible subject to the given natural boundary conditions; therefore the regular perturbation technique is applied. The flow functions 퐻, 퐺, 퐿 and 푀 are expanded in the powers of the amplitude (taken small) of the oscillations. The behaviour of the temperature distribution at different values of Reynolds number, phase difference, magnetic field and second-order parameters has been studied and shown graphically. The results obtained are compared with those for the infinite torsionally oscillating discs by taking the Reynolds number of out-flow 푅푚 and circulatory flow 푅퐿 equals to zero. Nusselt number at oscillating and stator disc has also been calculated and its behaviour is represented graphically.
Estimate the hidden States, Parameters, Signals of a Linear Dynamic Stochastic System from Noisy Measurements. It requires knowledge of probability theory. Presentation at graduate level in math., engineering
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website at http://solohermelin.com. Since a few Figure were not downloaded I recommend to see the presentation on my website at RADAR Folder, Tracking subfolder.
This presentation is intended for undergraduate students in physics and engineering.
Please send comments to solo.hermelin@gmail.com.
For more presentations on different subjects please visit my homepage at http://www.solohermelin.com.
This presentation is in the Physics folder.
An object experiencing the acceleration of gravity is described. The acceleration of gravity on Earth is approximately 9.8 m/s2 downward. Equations of motion are provided for falling bodies, including simplified equations that assume the object starts from rest. Examples are worked through comparing the traditional method of using negative signs for downward motion to an alternative method where downward is considered positive to simplify the signs.
This document presents the mathematical modeling of heat transfer and phase change in three dimensions using the finite element method. It begins with the governing equations - the continuity, Navier-Stokes, and heat equations along with the Stefan free boundary condition. It then derives the variational formulation and discretizes the equations using finite elements. The nonlinear system is solved using Newton's method to find the numerical solution for temperature, velocity, and the moving solid-liquid interface over time.
Describes the mathematics of the Calculus of Variations.
For comments please contact me at solo.hermelin@gmail.com.
For more presentations on different subjects visit my website on http://www.solohermelin.com
Basic differential equations in fluid mechanicsTarun Gehlot
This document provides an overview of fluid dynamics concepts including the continuity equation, Navier-Stokes equations, and examples of their application to laminar flow situations. It derives the 1-dimensional continuity equation and uses it to describe flow between parallel plates. It then derives the equation for laminar flow velocity profile between infinite horizontal parallel plates based on the Navier-Stokes equations and applies it to calculate discharge rate. Finally, it provides an example problem calculating discharge rate and power for an oil skimming device.
- Thermodynamics describes the equilibrium states of systems and the spontaneous processes between those states.
- The first law of thermodynamics states that the total energy of an isolated system is conserved. It can be expressed as ΔU = Q + W, where ΔU is the change in internal energy, Q is heat, and W is work.
- For a closed system, the first law takes the form ΔU = Q - PΔV, where PΔV is the work done by expansion or compression. For a constant volume process where no work is done, ΔU = Q.
- The enthalpy H is a state function defined as H = U + PV. For a
The document provides solutions to two heat equation problems using separation of variables. For the first problem, the solution is found to be a sum of sine functions with decaying exponentials in time. For the second problem, a similar approach is taken, but the eigenfunctions are determined to be cosines instead of sines due to the different boundary condition. In both cases, the solutions involve finding eigenvalues and eigenfunctions by considering different cases for the separation constant and applying the boundary conditions.
Non equilibrium thermodynamics in multiphase flowsSpringer
This chapter discusses the principle of microscopic reversibility and its implications. It can be summarized as follows:
1) The principle of microscopic reversibility states that the probability of a molecular process occurring is equal to the probability of the reverse process at equilibrium.
2) This leads to the rule of detailed balances and Onsager's reciprocity relations, which relate the linear response of a system to external perturbations to its intrinsic fluctuation properties.
3) The reciprocity relations require that the Onsager coefficients relating fluxes to forces be symmetric. Various formulations of the fluctuation-dissipation theorem are also derived from microscopic reversibility.
The one-dimensional heat equation describes heat flow along a rod. It can be solved using separation of variables. For a rod with insulated sides initially at uniform temperature u0 and ends suddenly cooled to 0°C:
1) The solution is a Fourier series involving eigenfunctions that satisfy the boundary conditions.
2) The temperature is the sum of the eigenfunctions weighted by Fourier coefficients involving u0.
3) As time increases, the temperature decreases towards the boundary values according to exponential decay governed by the eigenvalues.
This document discusses differential equations and their applications. It defines ordinary and partial differential equations, and describes various types of ordinary differential equations including separable, homogeneous, non-homogeneous, exact, and linear equations. It also discusses exponential growth and decay models using differential equations. Examples are provided to illustrate radioactive decay modeling using half-life equations and carbon dating to determine the age of fossils.
The document outlines the basic equations of fluid mechanics, beginning with an introduction. It then summarizes the continuity equation in 3 parts - the differential formulation, integral formulation of continuity equation, and Reynolds transport theorem. Finally, it discusses the Navier-Stokes equation by outlining the balance of forces, constitutive relations of Stokes, and differential and integral formulations of momentum equations.
Two basic topics of heat transfer have been covered up by me based on the famous books of :-
1) John H. Lienhard (Professor Emeritus, University of Houston)
2) J.P. Holman (Professor, Southern Methodist University)
3) Prabal Talukdar (Associate Professor, IIT, India)
This document discusses anomaly and parity odd transport coefficients in 1+1 dimensions. It begins by defining what an anomaly is, noting that a symmetry of classical physics may not hold at the quantum level. It then relates anomalies to hydrodynamics, showing how anomalies can constrain transport coefficients. The document evaluates the U(1) chiral anomaly using the Fujikawa method and relates it to hydrodynamic equations. It then uses the Kubo formula from linear response theory to evaluate the relevant current-stress tensor correlator from finite temperature field theory and performs Matsubara sums to obtain an expression for the parity odd transport coefficient.
The document discusses the lumped element method (LEM) for analyzing transient heat transfer problems. It defines a lumped system as one where the interior temperature remains uniform over time. The lumped element approach provides a simplification to heat transfer calculations using a lumped parameter called the time constant. The document also covers using the method of separation of variables to solve the heat equation for transient conduction problems, reducing the partial differential equation to ordinary differential equations that can be solved. It provides an example of applying separation of variables to a one-dimensional conduction problem between fixed temperatures.
Quantum Interrogation: Interaction-Free Determination of Existence (Physics 1...BenjaminKan4
In this report, we summarize the given scenario behind the “Quantum Interrogation" problem, and offer historical background of the development of quantum “interaction-free measurement" theory. We then describe some real-world applications of this procedure, whether already verified experimentally or as potential applications in the future. Finally, we exhibit our calculations that display the feasibility of this quantum effect, and summarize the key takeaways from this problem.
Proceedings A Method For Finding Complete Observables In Classical Mechanicsvcuesta
1. The document presents a new method for finding complete observables in classical mechanics, which are gauge invariant quantities.
2. The method starts with partial observables and clocks, which are non-gauge invariant phase space functions. Using constants of motion, the partial observables can be written in terms of the clocks to obtain complete observables.
3. As an example, the method is applied to a particle in a gravitational field, where the Hamiltonian is used as a constant of motion to write the position variable as a function of the momentum and time.
Oscillations are ubiquitous in nature and occur in many systems when disturbed from equilibrium. The document introduces the simple harmonic oscillator (SHO) model to describe small oscillations near equilibrium. A SHO undergoes sinusoidal oscillations with an angular frequency that depends on the spring constant and mass. Complex numbers provide a useful way to represent the amplitude and phase of oscillations. The SHO model applies to many systems locally, as potentials can often be approximated as quadratic near equilibrium points.
This document summarizes applications of differential equations to real world systems including cooling/warming, population growth, radioactive decay, electrical circuits, survivability with AIDS, economics, drug distribution in the human body, and a pursuit problem. Examples are provided for each application to illustrate solutions to related differential equations. Key concepts covered include Newton's law of cooling, population models, carbon dating, series circuits, survival models, supply and demand models, compound interest, drug concentration in the body over time, and a mathematical model for a dog chasing a rabbit.
The document discusses the wave equation and its application to modeling vibrating strings and wind instruments. It describes how the wave equation can be separated into independent equations for time and position using the assumption that displacement is the product of separate time and position functions. This separation leads to trigonometric solutions that satisfy the boundary conditions of strings fixed at both ends. The solutions represent standing waves with discrete frequencies determined by the length, tension, and density of the string. Similar methods apply to wind instruments with different boundary conditions.
Non equilibrium thermodynamics in multiphase flowsSpringer
This chapter discusses the principle of microscopic reversibility and its implications. It can be summarized as follows:
1) The principle of microscopic reversibility states that the probability of a molecular process occurring is equal to the probability of the reverse process at equilibrium.
2) This leads to the rule of detailed balances and Onsager's reciprocity relations, which relate the linear response of a system to external perturbations to its intrinsic fluctuation properties.
3) The reciprocity relations require that the Onsager coefficients relating fluxes to forces be symmetric. Various formulations of the fluctuation-dissipation theorem are also derived from microscopic reversibility.
1) The document presents three theoretical physics problems involving spinning balls, charged particles in loops, and laser cooling of atoms.
2) Problem 1 considers a spinning ball falling and rebounding, calculating the rebound angle, horizontal distance traveled, and minimum spin rate. Problem 2 analyzes relativistic effects on charged particles in a moving loop in an electric field.
3) Problem 3 describes using lasers to cool atoms by resonant absorption. It calculates the laser frequency needed, velocity range absorbed, direction change upon emission, maximum velocity decrease, number of absorption events to slow to zero velocity, and distance traveled during cooling.
Text Book: An Introduction to Mechanics by Kleppner and Kolenkow
Chapter 1: Vectors and Kinematics
-Explain the concept of vectors.
-Explain the concepts of position, velocity and acceleration for different kinds of motion.
References:
Halliday, Resnick and Walker
Berkley Physics Volume-1
The document discusses the concept of derivative as a rate of change. It defines the average rate of change and instantaneous rate of change over an interval and as the limit as the interval approaches zero respectively. It provides examples of calculating average and instantaneous rates of change from graphs and data tables.
This document presents the basic flow equations, including the Navier-Stokes equation and Euler's equations for frictionless flow. It also introduces several dimensionless numbers that are used to characterize different types of fluid flow and heat and mass transfer, such as the Reynolds number, Prandtl number, Schmidt number, and more. These equations and numbers provide a theoretical framework for analyzing fluid flow, while practical applications require further assumptions and simplifications.
This document introduces the concept of gauge invariance and gauge field theories. It discusses both global and local gauge symmetries:
- Global gauge symmetries lead to conserved currents and charges via Noether's theorem. They result in massless scalar bosons if spontaneously broken.
- Local gauge symmetries require the introduction of gauge fields which transform in a way that cancels out non-invariant terms under local transformations. This avoids the massless bosons and allows gauge fields to acquire mass. Quantum electrodynamics possesses a local U(1) gauge symmetry.
- Non-Abelian gauge groups were introduced by Yang and Mills, allowing the construction of gauge field theories with non-commuting gauge groups. Covariant derivatives are
This document discusses equations related to heat transfer through pipes and the temperature gradient that results from fluid flow. It then speculates that quantum mechanical equations like the Fermi-Dirac distribution and theories of relativity may help explain the relationship between temperature and the movement of water particles through pipes. The document proposes that the velocity of water particles must be connected to temperature, that velocity is infinite, and that the movement of an inertial system through a vacuum must be related to the movement of the system.
1. The document provides a list of 2 mark questions and answers related to the Signals and Systems subject for the 3rd semester IT students.
2. It includes definitions of key terms like signal, system, different types of signals and their classifications. Properties of Fourier series and Fourier transforms are also covered.
3. The questions address topics ranging from periodic/aperiodic signals, even/odd signals, unit step and impulse functions, Fourier series, Fourier transforms, Laplace transforms, linear and time invariant systems.
GEN PHYSICS 1 WEEK 2 KINEMATICS IN ONE DIMENSION.pptxAshmontefalco4
This document provides an overview of kinematics in one dimension, including graphical representations of motion, motion along a straight line, and motion with constant acceleration. It discusses topics like displacement, velocity, acceleration, and their relationships. Examples are provided to demonstrate calculating variables like position, velocity and acceleration from graphs or equations of motion. Kinematic formulas are also introduced for problems involving constant acceleration.
Thermal diffusivity describes how quickly heat diffuses through a material. It is calculated as the thermal conductivity divided by the density and specific heat. Fick's laws of diffusion quantitatively describe steady-state and non-steady-state diffusion. For a heat pulse experiment passing through a brass tube, the temperature was measured at two points over time. Fourier analysis was used to determine the amplitude and phase of the temperature waves. The ratio of amplitudes and difference in phases was used to calculate the thermal diffusivity, found to be 0.231 cm^2/s, close to the actual value for brass of 0.3 cm^2/s.
1) The document introduces basic principles of fluid mechanics, including Lagrangian and Eulerian descriptions of fluid flow. The Lagrangian description follows individual particles, while the Eulerian description observes flow properties at fixed points in space.
2) It describes three governing laws of fluid motion within a control volume: conservation of mass (the net flow in and out of a control volume is zero), conservation of momentum (Newton's second law applied to a fluid system), and conservation of energy.
3) It derives Bernoulli's equation, which relates pressure, velocity, and elevation along a streamline for inviscid, steady, incompressible flow. Bernoulli's equation is an application of conservation of momentum along a streamline.
Classical mechanics failed to explain certain phenomena observed at the microscopic level like black body radiation and the photoelectric effect. This led to the development of quantum mechanics, with key aspects being the wave function Ψ, Schrodinger's time-independent and time-dependent wave equations, and operators like differentiation that act on wave functions to produce other wave functions. The wave function Ψ relates to the probability of finding a particle, with |Ψ|2 representing the probability.
The document discusses Fourier series and two of their applications. Fourier series can be used to represent periodic functions as an infinite series of sines and cosines. This allows approximating functions that are not smooth using trigonometric polynomials. Two key applications are representing forced oscillations, where a periodic driving force can be modeled as a Fourier series, and solving the heat equation, where the method of separation of variables results in a Fourier series representation of temperature over space and time.
The document discusses Fourier series and two of its applications. It provides an overview of Fourier series, including its definition as an infinite series representation of periodic functions in terms of sine and cosine terms. It also discusses two key applications of Fourier series: (1) modeling forced oscillations, where a Fourier series is used to represent periodic forcing functions; and (2) solving the heat equation, where Fourier series are used to represent temperature distributions over time.
The document discusses quantum mechanical concepts including:
1) The time derivative of the momentum expectation value satisfies an equation involving the potential gradient.
2) For an infinite potential well, the kinetic energy expectation value is proportional to n^2/a^2 and the potential energy expectation value vanishes.
3) Eigenfunctions of an eigenvalue problem under certain boundary conditions correspond to positive eigenvalues that are sums of squares of integer multiples of pi.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
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1. Azzeddine Soulaijmani
M¶ecanique des °uides avanc¶ee
SYS 860
Notes de cours
21 septembre 2006
¶Ecole de technologie sup¶erieure
Montr¶eal
2.
3. 1
Introduction
In °uid mechanics analysis the °uid is considered as a continuum material. Any in¯nitesimal
volume in space contains a large number of molecules in mutual interactions and only global
e®ects such as pressure, temperature or velocity are analyzed. In the sequel, a °uid particle
refers to such an in¯nitesimal volume of °uid with a measurable mass and containing a large
number of molecules.
1.1 Fluid particle kinematics
Fluid kinematics is the study of the particles motion without considering the forces that
cause the motion. It describes the time evolution of particles properties (position, velocity,
acceleration, density, pressure, temperature, etc) during the motion as function of time and
space position.
1.1.1 Particle position vector
Consider a Cartesian reference system with origin O and an orthonormal basis (i1; i2; i3).
For any °uid particle, the vector position is denoted by x(t) and is function of time t :
x(t) = x1(t)i1 + x2(t)i2 + x3(t)i3 (1.1)
with x1(t); x2(t); x3(t) are the position coordinates.
In the following we will use the so-called Einstein's notation convention, i.e. when an index
is repeated in a mathematical expression that means a summation over the repeated index.
For example, equation (1.1) can be rewritten in a more compact form as
x(t) = x1(t)i1 + x2(t)i2 + x3(t)i3 =
X
k
xkik ´ xkik:
4. 2 1 Introduction
1.1.2 Particle velocity and acceleration vectors
Consider a °uid particle at time t. During a small time duration ¢t, the vector position
becomes x(t + ¢t) and the displacement vector of the particle is
¢x = x(t + ¢t) ¡ x(t):
x3
x1
O
i1
Particle at time t + ¢t
x2
Particle at time t
x(t + ¢t)
x(t)
i3
i2
Vector displacement after ¢t
¢x = x(t + ¢t) ¡ x(t)
Fig. 1.1. Particle position vector
The particle velocity vector is de¯ned as the rate of change of the vector position :
u(t) = lim
¢t!0
¢x
¢t
= dx
dt
(1.2)
The particle acceleration vector is de¯ned as the rate of change of the velocity vector :
a(t) = lim
¢t!0
¢u
¢t
= du
dt
= d2x
dt2 (1.3)
1.1.3 Lagrangian and Eulerian Kinematic Descriptions
To de¯ne the velocity and acceleration vectors, we need actually to specify or to identify
which particle is under study. One convenient way is to label each particle by its position » at a
certain initial time t0. Then the motion of the whole °uid can be described by two independent
5. 1.1 Fluid particle kinematics 3
variables » and t. For a particle with label », equation x = x(»; t) gives the particle trajectory
or patheline. The velocity and acceleration vectors are then given more precisely by
u(»; t) =
·
@x(»; t)
@t
¸
»
; (1.4)
and
a(»; t) =
·
@u(»; t)
@t
¸
»
: (1.5)
The use of the independent variables » and t is called the Lagrangian or the material
description. Another description very often used in °uid kinematics is to use as independent
variables x and t. That is, we are interested to describe the motion of the particle which passes
at a ¯xed position x in space and at the time instant t. This description is called the Eulerian
kinematic description and is very often used in Fluid Mechanics. Solving equation » = »(x; t)
gives the labels of all particles that occupied the ¯xed position x. The velocity and acceleration
vectors can now be described as functions of x and t,
u(x; t) = u(x(»; t); t) (1.6)
and
a(x; t) = a(x(»; t); t) (1.7)
1.1.4 Material derivative
In the following we will obtain the derivative with respect to time when using the Eulerian
description. Consider ¯rst a scalar material property µ(x; t) such as pressure or temperature.
The rate of change of this property felt by the particle labeled by » as it moves is de¯ned by
Dµ
Dt
´
·
dµ(x(»; t); t)
dt
¸
»
: (1.8)
Using the di®erentiation chain rule, equation (1.8) is developed into
Dµ
Dt
=
·
@µ(x; t)
@t
¸
t
+ @µ
@x1
@x1(»; t)
@t
+ @µ
@x2
@x2(»; t)
@t
+ @µ
@x3
@x3(»; t)
@t
: (1.9)
The ¯rst term on the right hand side of equation (1.9) is the rate of change of the property
µ at the ¯xed position x. This term is called the local derivative, and is non zero when, for
instance, the boundary conditions of the °uid domain change in time. The other terms in (1.9)
give the rate of change when the particle moves from x to x + ¢x. It is called the convective
derivative. In fact the terms @xk
@t
are the velocity components uk which convect or transport
the material property. The convective derivative is non zero when, for instance, there is a
variation in the domain geometry that causes a spatial variation @µ
@xk
. An illustration of the
6. 4 1 Introduction
Lateral boundary heated in
a non uniform manner
Incomming flow with
time varying
temperature
Temperature measurement
A(x1) x1
x1 = 0
u1(x1; t)
£(0; t)
£(x1; t)
x1
Fig. 1.2. An illustration for temperature material derivative measurement
local and convective rate of change is given in ¯gure (1.2). A °uid °ows in a duct with a variable
cross section A(x). For simplicity, we assume that the °ow is unidirectional with velocity u1.
The incoming °uid has a time dependent temperature µ(0; t), that is the boundary condition
at the inlet is time varying. A thermometer is placed at a ¯xed position x1. By taking two
successive temperature observations µ(x1; t) and µ(x1; t + ¢t) in a small time interval ¢t we
can indirectly measure the local temperature derivative, i.e.
·
@µ(x1; t)
@t
¸
x1
¼
µ(x1; t + ¢t) ¡ µ(x1; t)
¢t
:
Another thermometer is placed at a close position x1 + ¢x1, so that the rate of temperature
change observed by the particle in its travel of the distance ¢x1 (with ¢x1 ¼ u1(x1; t)¢t) can
be approximated by
u1(x1; t) µ(x1 + ¢x1; t) ¡ µ(x1; t)
¢x1
:
The temperature gradient can be caused by heating the lateral boundary in a nonuniform
manner. Thus the material derivative of the particle passing at position x1 at time t can be
indirectly measured without actually moving the thermometer with this particle. Therefore,
only the °ow ¯eld u1(x1; t) and the temperature ¯eld µ(x1; t) have to be measured at di®erent
time intervals to be able to compute the material derivative.
Using indicial notation, the material derivative can be rewritten as
Dµ
Dt
(x; t) = @µ(x; t)
@t
+ uk
@µ
@xk
(1.10)
Equation (1.10) can also be written in a matrix form as
7. 1.1 Fluid particle kinematics 5
Dµ
Dt
= @µ(x; t)
@t
+ [u1; u2; u3] ¢
8>>>>>>>>>>><
>>>>>>>>>>>:
@µ
@x1
@µ
@x2
@µ
@x3
9>>>>>>>>>>>=
>>>>>>>>>>>;
; (1.11)
or
Dµ
Dt
= @µ(x; t)
@t
+ [u1; u2; u3] ¢
8>>>>>>>>>>><
>>>>>>>>>>>:
@
@x1
@
@x2
@
@x3
9>>>>>>>>>>>=
>>>>>>>>>>>;
µ (1.12)
or in a more compact form, using tensorial notation, as
Dµ
Dt
= @µ(x; t)
@t
+ (u ¢ r)µ: (1.13)
Now, we consider the expression of the rate of change in the Eulerian description of a
material vector property £ = µkik (Here, we use Eisntein's notation). Since the operator D()
Dt
is linear then
D£
Dt
= Dµk
Dt
ik + µk
Dik
Dt
(1.14)
If the reference frame is chosen ¯xed then there is no change in its basis vectors as the °uid
particles move, i.e. Dik
Dt
= 0, therefore
D£
Dt
= Dµk
Dt
ik: (1.15)
The expression of the particle acceleration in the Eulerian description can be found by
taking £ as the velocity vector. The kth acceleration component is obtained as
ak(x; t) = Duk
Dt
= @uk(x; t)
@t
+ (u ¢ r)uk = @uk
@t
+ ui
@uk
@xi
; (1.16)
and the acceleration vector is then written using tensorial notation as
8. 6 1 Introduction
a(x; t) = Du(x; t)
Dt
= @u(x; t)
@t
+ (u ¢ r)u: (1.17)
The ¯rst term on the right hand side of equation (1.17) represents the local acceleration. The
last term represents the convective acceleration which is nonlinear since a product of u by its
gradient appears.
1.1.5 Pathlines and streamlines
The pathline is de¯ned by the successive positions occupied by the particle ». If the ve-
locity ¯eld u(x; t) is known then the pathline can be obtained by solving for x the following
di®erential equation :
dx
dt
= u(x; t): (1.18)
The streamlines are de¯ned as the lines tangent to the velocity vector. Any vector displacement
Streamline
Pathline
Particule position at time
u(x; t)
t
x(»; t)
Fig. 1.3. Figure 1.3. Pathline and streamline
dx along the streamlines is parallel to the velocity vector :
dx £ u = 0; (1.19)
which can be developed in the orthonnormal basis as
¯¯¯¯¯¯
dx1 u1 i1
dx2 u2 i2
dx3 u3 i3
¯¯¯¯¯¯
= (u3dx2 ¡ u2dx3)i1 + (u1dx3 ¡ u3dx1)i2 + (u2dx1 ¡ u1dx2)i3 = 0 (1.20)
This leads to solving a set of di®erential equations :
dx1
u1
= dx2
u2
= dx3
u3
: (1.21)
Example 1.1 : Steady °ow in a convergent duct
An incompressible °uid °ows in a duct having a convergent cross section A(x1) = A0
1 + x1
l
,
9. 1.1 Fluid particle kinematics 7
with l a positive constant. The velocity at the inlet section x = 0 is u0. Calculate the velocity
and the acceleration in the Eulerian and Lagragian descriptions.
"
Ax
10. 0
u u
x 0 x
Fig. 1.4. Flow in a convergent duct
Solution
Since the °ow is assumed one-dimensional u = (u1; 0; 0). The °uid is also assumed incompres-
sible so that the °ow rate (see chapter 2) is constant, i.e. u1(x1)A(x1) ³
= const = u0A0. Hence,
we get the velocity in the Eulerian description as u1(x1) = u0
1 + x1
l
´
. As the °ow is time
independent (steady °ow), the local acceleration is zero @u1
@t = 0. The convective acceleration
is calculated as
u1(x1)@u1
@x1
= u0u1(x1)=l:
Let »1 be the initial position of the °uid particle. The particle patheline is expressed by the
function x1(»1; t) and is calculated by solving
·
@x1
@t
¸
»1
= u1:
Inserting the expression of u1(x1) and using a separation of variables, we get u0dt = dx1
1 + x1
l
.
Integrating the left hand side from 0 to t and the right hand side from »1 to x1 leads to
u0t = l ln
0
B@1 + x1
l
1 + »1
l
1
CA
:
The pathline function is then described by
x1(»1; t) = l
0
B@
(1 + »1
l
Ã
u0t
)e
l
!
¡ 1
1
CA
:
11. 8 1 Introduction
On the other hand, given a ¯xed position x1 we can also obtain the Lagrangian variable
»1(x1; t) of the particles passing by x1. Hence,
»1(x1; t) = l
0
@(1 + x1
l
)e
(
¡u0t
l
)
¡ 1
1
A:
The velocity in the Lagrangian description is de¯ned by u1(»; t) =
·
@x1
@t
¸
»1
and thus by a
simple di®erentiation we obtain
u1(»1; t) = u0(1 + »1
l
)e( u0t
l
):
Since (1 + »1
l
)e
(
u0t
l
) = 1 + x1
l
we can verify that the we obtain the same result for the velocity
in the Lagranian and Eulerian descriptions.
The Lagrangian description of the acceleration is
a1(»1; t) =
·
@u1
@t
¸
»1
= u20
l
(1 + »1
l
)e( u0t
l
):
Example 1.2 : Unsteady °ow in a convergent duct
Repeat example (1.1) with a time dependent boundary condition u1(0; t) = u0(t) = Ue¡®t
with U and ® positive constants.
Solution
The velocity ¯eld is time dependent because of the time varying nature of the in°ow. As before,
invoking the principle of mass conservation ³
for an incompressible °uid the velocity at any
space position is obtained u1(x1; t) = u0(t)
1 + x1
l
´
. The local and convective accelerations
are respectively @u1(x; t)
@t
= ¡®Ue¡®t
³
1 + x1
l
´
and u0(t)u1(x1; t)=l.
Again, we obtain the particle pathline by solving the di®erential equation
·
@x1
@t
¸
»1
= u1(x1; t):
Using the method of separation of variables, we obtain the pathline equation
x1(t) = l
µ
(1 + »1
l
¶
;
)ef(t) ¡ 1
with
f(t) = ¡
U
l®
³
e(¡®t) ¡ 1
´
= ln
0
B@
1 + x1
l
1 + »1
l
1
CA
:
12. 1.1 Fluid particle kinematics 9
The Lagrangian variable at time t corresponding to a ¯xed spatial position is
»1(x1; t) = l
³
(1 + x1
l
)e¡f(t) ¡ 1
´
:
The velocity in the Lagrangian description is u1(»; t) =
·
@x1
@t
¸
»1
= lf0(t)(1 + 1
l
)ef(t), which
can be veri¯ed to be equal to Ue¡®t(1 + x1
l
) = u1(x1; t). When the velocity u1(»; t) is di®eren-
tiated with respect to time this gives the acceleration a1(»; t) in the Lagrangian description.
Example 1.3 : Steady two-dimensional °ow close to a stagnation point
The motion of a °uid is described by its velocity ¯eld given in the Eulerian description by :
u = ®(x1;¡x2)
with ® a positive constant.
a) Determine the velocity ¯eld and acceleration in the Lagrangian and Eulerian descriptions.
Find the pathline equation of a particle which occupied position » = (»1; »2) at time 0.
b) Find the streamline equation of a particle which occupied position x at time t.
Solution
a) The velocity components in the Eulerian description are : u1 = ®x1 and u2 = ¡®x2. As a
result, the acceleration components are determined using equation (1.16), a1(x; t) = ®2x1 and
a2(x; t) = ®2x2.
The pathline di®erential equations are :
ui(x; t) =
·
@xi
@t
¸
»
:
By integration, we obtain the pathline equations :
x1(»; t) = »1 exp(®t)
and
x2(»; t) = »2 exp(¡®t):
In these equations t represents the curve parameter of the pathline, and »i are the paramete-
rized families. By eliminating the curve parameter t,
t = (
1
®
) ln(x1
»1
) = ¡(
1
®
) ln(x2
»2
)
we obtain the explicit form of the pathline equation
x2 = »1»2
x1
;
which de¯nes a family of hyperboles.
The velocity components in the Lagrangian description are u1(»; t) = ®»1 exp(®t) and
u2(»; t) = ¡®»2 exp(¡®t). The acceleration components in the Lagrangian description are
13. 10 1 Introduction
a1(»; t) = ®2»1 exp(®t) and a2(»; t) = ®2»2 exp(¡®t).
b)The streamline di®erential equations are given by equation (1.21) which leads in the case of
a two-dimensional °ow to solving the di®erential equation
@x2
@x1
= u2
u1
:
Inserting the expression of the velocity components we obtain
@x2
@x1
= ¡
x2
x1
:
And by integration, we obtain x2 = C1C2
1
x1
with C1 and C2 two constants of integration.
Therefore, the streamlines de¯ne families of hyperboles identical to those de¯ned by the path-
lines.
Example 1.4 : Material derivative in cylindrical coordinates
a) Develop the divergence r ¢ v of the vector v using cylindrical coordinates (r; µ; z) and the
polar orthonormal basis (er; eµ; ez).
b) Derive the material derivative for a scalar function T in cylindrical coordinates.
c) Derive the material derivative for a vector function v in cylindrical coordinates.
Solution
a)Recall that the Cartesian basis vectors are related to the basis vectors (er; eµ; ez) by :
i1 = cos µ er ¡ sin µ eµ;
i2 = sin µ er + cos µ eµ;
i3 = ez:
The velocity in the cylindrical system is :
u = urer + uµeµ + uzez
The unit vectors er and eµ vary with the angle. We have the following relations @er
@µ
= eµ
and @eµ
@µ
= ¡er.
The gradient operator in cylindrical polar coordinates can be veri¯ed as (do it as an exer-
cise) :
r = er
@
@r
+ eµ
1
r
@
@µ
+ ez
@
@z
:
Let consider a vector v = vrer + vµeµ + vzez. The divergence is de¯ned as the scalar product
of the gradient vector with the vector v. Thus,
r¢v = (er
@
@r
+eµ
1
r
@
@µ
+ez
@
@z
)¢(vrer+vµeµ+vzez) = @vr
@r
+eµ
1
r
µ
vr
¢
@er
@µ
+ @vµ
@µ
eµ + vµ
@eµ
@µ
¶
+@vz
@z
14. 1.1 Fluid particle kinematics 11
=)
r ¢ v = @vr
@r
+ vr
r
+
1
r
@vµ
@µ
+ @vz
@z
:
b)The material derivative of a function T(r; µ; z; t) is obtained as :
DT
Dt
= @T
@t
+ @T
@r
@r
@t
+ @T
@µ
@µ
@t
+ @T
@z
@z
@t
:
The velocity components in the polar system are ur = @r
@t
, uµ = r
@µ
@t
and uz = @z
@t
. Then, the
material derivative in cylindrical coordinates is :
DT
Dt
= @T
@t
+ ur
@T
@r
+ uµ
r
@T
@µ
+ uz
@T
@z
:
It can be veri¯ed that the convection operator is given in cylindrical coordinates by
u ¢ r = (urer + uµeµ + uzez) ¢ (er
@
@r
+ eµ
1
r
@
@µ
+ ez
@
@z
:) = ur
@
@r
+ uµ
r
@
@µ
+ uz
@T
@z
:
Therefore, the material derivative can be written as
DT
Dt
= @T
@t
+ (u ¢ r)T
which is the same tensorial expression as in the Cartesian coordinates system.
c)The material derivative for a vector ¯eld v(r; µ; z; t) = vrer + vµeµ + vzez is obtained as
Dv
Dt
= Dvr
Dt
er + vr
Der
Dt
+ Dvµ
Dt
eµ + vµ
Deµ
Dt
+ Dvz
Dt
ez + vz
Dez
Dt
:
Noting that
Der
Dt
= @er
@µ
@µ
@t
= uµ
r
eµ
Deµ
Dt
= @eµ
@µ
@µ
@t
= ¡
uµ
r
er
then
Dv
Dt
=
µ
Dvr
Dt
¡
vµuµ
r
¶
er +
µ
Dvµ
Dt
+ vruµ
r
¶
eµ + Dvz
Dt
ez:
If we replace v by the velocity then the acceleration a has in cylindrical coordinates system
the components :
ar = Dur
Dt
¡
2
r
uµ
= @ur
@t
+ (u ¢ r)ur ¡
2
r
uµ
;
aµ = Duµ
Dt
+ uµur
r
= @uµ
@t
+ (u ¢ r)uµ + uµur
r
15. 12 1 Introduction
and
az = Duz
Dt
= @uz
@t
+ (u ¢ r)uz:
Example 1.5 : Material derivative in natural coordinates
a) The unit tangent vector to the pathline is :
¡!¿
=
dx
dx
and its unit normal vector in the two dimensional space is
n = R
d¡!¿
ds
with s the coordinate in the direction of ¡!¿
and n is the coordinate in the direction of n. (¡!¿
; n)
de¯ne a local orthonormal basis. Derive the acceleration components on this basis.
Solution
The velocity components on the local basis are u¿ and un = 0. The material derivative of the
velocity is
Du
Dt
= Du
Dt
¡!¿
+ u
D¡!¿
dt
Now we develop the following terms :
Du(s; n; t)
Dt
= @u
@t
+ u
@u
@s
+ un
@u
@n
;
and
D¡!¿
Dt
= u
R
n:
Since un = 0 and @un
@s = 0 then
Du
Dt
= @u
@t
+ u
@u
@s
:
It follows that the acceleration in the local basis is
Du
Dt
= (@u
@t
+ u
@u
@s
)¡!¿
+ u2
R
n:
1.2 Velocity gradients and Deformations
1.2.1 Linear Deformations
The simplest motion that a °uid particle can undergo is translation. Consider a small °uid
element with a brick shape. The edges lengths are in¯nitesimal and are denoted by ±x1, ±x2
and ±x3. The original volume is ±# = ±x1±x2±x3.
16. 1.2 Velocity gradients and Deformations 13
B C C’
O A A’
±x2
u1
u1 +
@u1
@x1
±x1
±x1
@u1
@x1
±x1
u1 +
@u1
@x1
±x1
u1
@u1
@x1
±x1
Fig. 1.5. Linear deformation for a °uid element
Let us ¯rst analyze the e®ect of a translation motion in the i1 direction.
Particularly, we are interested to study the deformations as the °uid element moves during
a small time interval ±t. The edge OB is translated into O0B0 by the velocity component u1 and
the edge AC is translated into A0C0 by the velocity component u1(x1 + ±x1) ¼ u1 + @u1
@x1
±x1.
Because of this velocity di®erence, edges' OA and BC lengths are changed by @u1
@x1
±x1±t.
Therefore, the particle deforms and its volume changes by ±# = @u1
@x1
±x1±x2±x3±t. The rate at
which the original volume is changing per unit volume is
lim
±t!0
1
±#
±#
±t
= lim
±t!0
@u1
@x1
±x1±x2±x3±t
±x1±x2±x3±t
= @u1
@x1
(1.22)
When there is no velocity gradient, the °uid element undergoes a pure translation without
deformation.
The total rate of change of the °uid particle volume per unit volume for a three-dimensional
translation can be readily obtained
lim
±t!0
1
±#
±#
±t
= @u1
@x1
+ @u2
@x2
+ @u3
@x3
= @uk
@xk
= r:u = div(u) (1.23)
The velocity gradient components @uk
@xk
are responsible for the volumetric dilatation. The
other components of the velocity gradient (i.e., @ui
@xk
for i6= k) cause rotations and angular
deformations. By de¯nition an incompressible °uid has no volumetric dilation therefore in this
case div(u) = 0.
1.2.2 Angular deformation
For illustration, we will consider motion in the x1¡x2 plane. The velocity gradient compo-
nents that cause rotation and angular deformation are illustrated in ¯gure ?. During a small
17. 14 1 Introduction
B C
±x2
O A
±x1
u2 +
@u2
@x1
±x1
u1 +
@u1
@x2
±x2
u1
u2
Fig. 1.6. Velocity components responsible for angular rotation and deformation
µ
@u1
@x2
±x2
B C
O
C’
B’
A’
A
±x2
U1 ±x1
U2
µ
@u2
@x1
±x1
¶
±® ±t
±¯
¶
±t
Fig. 1.7. Angular rotation and deformation for a °uid element
time interval ±t, edges OA and OB will rotate to O0A0 and O0B0 by angles ±® and ±¯. A
positive rotation is by convention counterclockwise. The angular velocity of edge OA is
!0A = lim
±t!0
±®
±t
(1.24)
For small angles :
±® ¼ tan(±®) =
@u2
@x1
±x1±t
±x1
= @u2
@x1
±t (1.25)
and (1.24) becomes
!0A = lim
±t!0
±®
±t
= @u2
@x1
(1.26)
Similarly, the angular velocity of edge OB is
!0B = ¡ lim
±t!0
±¯
±t
= ¡
@u1
@x2
(1.27)
The rotation of the °uid element about the x3 axis is de¯ned as the average of the angular
velocities !0A and !0B, it follows that
18. 1.2 Velocity gradients and Deformations 15
!3 = !0A + !0B
2
=
1
2
µ
@u2
@x1
¡
@u1
@x2
¶
(1.28)
The angular velocities about the other axis !1 and !2 can be obtained using a similar analysis,
and they are respectively
!1 =
1
2
µ
@u3
@x2
¡
@u2
@x3
¶
and !2 =
1
2
µ
@u1
@x3
¡
@u3
@x1
¶
(1.29)
The three angular velocities !1, !2 and !3 de¯ne the rotation vector ! as
! = !1i1 + !2i2 + !3i3 (1.30)
This vector represents actually half of the curl of the velocity vector,
! =
1
2curl(u) (1.31)
since by de¯nition of the vector operator r £ u
curl(u = r £ u =
¯¯¯¯¯¯¯
i1 i2 i3
@
@
@x1
@x2
@
@x3
u1 u2 u3
¯¯¯¯¯¯¯
= 2! (1.32)
To eliminate the factor 1=2, the vorticity is de¯ned as twice the rotation vector
³ = 2! = r £ u: (1.33)
It can be concluded at this point that the divergence of the velocity represents the linear
deformations while the curl represents rotations. On the other hand, there are also angular
deformations associated with the cross derivatives as can be observed from ¯gure (1.7). The
change in the original right angle formed by the edges OA and OB is a shearing deformation
±°12 = ±® + ±¯
where it is considered positive if the original right angle is decreased. The rate of angular
deformation (or shearing strain) is
°_12 = lim
±t!0
±°12
±t
= lim
±t!0
2
664
@u2
@x1
±t + @u1
@x2
±t
±t
3
775
= @u2
@x1
+ @u1
@x2
(1.34)
If @u2
@x1
= ¡
@u1
@x2
, the angular deformation is zero and this corresponds to a pure rotation. Using
a similar analysis, the other two rate shearing strains in the planes x1 ¡ x3 and x2 ¡ x3 can
be obtained and are respectively
°_13 = @u3
@x1
+ @u1
@x3
and °_23 = @u3
@x2
+ @u2
@x3
: (1.35)
19. 16 1 Introduction
1.2.3 Tensors in Fluid Kinematics
It follows from the previous section that the spatial derivatives of the velocity ¯eld de¯ne
three di®erent tensors :
¤ The velocity gradient :
F =
2
666664
@u1
@x1
@u1
@x2
@u1
@x3
@u2
@x1
@u2
@x2
@u2
@x3
@u3
@x1
@u3
@x2
@u3
@x3
3
777775
= ruT : (1.36)
¤ The rate of strain (or rate of deformation) :
D =
2
4
²11 ²12 ²13
²21 ²22 ²23
²31 ²32 ²33
3
5 =
F + FT
2
=
(ru + (ru)T )
2
(1.37)
where
²kl =
1
2
(@uk
@xl
+ @ul
@xk
) (1.38)
{ The strain tensor is symmetric and detailed more clearly as follows :
D =
2
666664
@u1
@x1
1
2
(@u1
@x2
+ @u2
@x1
)
1
2
(@u1
@x3
+ @u3
@x1
)
1
2
(@u2
@x1
+ @u1
@x2
) @u2
@x2
1
2
(@u2
@x3
+ @u3
@x2
)
1
2
(@u3
@x1
+ @u1
@x3
)
1
2
(@u3
@x2
+ @u2
@x3
) @u3
@x3
3
777775
(1.39)
{ ²kk = @uk
@xk
= tr(D) is the volumetric deformation.
{ 2²kl = °_kl is the rate of angular deformation.
¤ The spin tensor :
S = F ¡ D =
F ¡ FT
2
(1.40)
is the antisymmetric part of the velocity gradient and is detailed as follows
20. 1.2 Velocity gradients and Deformations 17
S =
2
666664
0
1
2
(@u1
@x2
¡
@u2
@x1
)
1
2
(@u1
@x3
¡
@u3
@x1
)
1
2
(@u2
@x1
¡
@u1
@x2
) 0
1
2
(@u2
@x3
¡
@u3
@x2
)
1
2
(@u3
@x1
¡
@u1
@x3
)
1
2
(@u3
@x2
¡
@u2
@x3
) 0
3
777775
=
2
4
0 ¡!3 !2
!3 0 ¡!1
¡!2 !1 0
3
5 (1.41)
{ Using index notation, the components of the above tensors can be written in a compact
form as follows :
Fij = @ui
@xj
(1.42)
Dij = Fij + Fji
2
=
1
2
( @ui
@xj
+ @uj
@xi
) (1.43)
Sij = Fij ¡ Fji
2
=
1
2
( @ui
@xj
¡
@uj
@xi
) (1.44)
Remark : The velocity ¯eld in the vicinity of a °uid particle at position x can be completely
described if the velocity gradient tensor is known. Using Taylor's expansion, the velocity at a
close position x + dx is approximated at the ¯rst order by
u(x + dx; t) = u(x; t) + ruT ¢ dx (1.45)
since the velocity gradient tensor is decomposed into a symmetric and an antisymmetric part
then
u(x + dx; t) = u(x; t) + S ¢ dx + D ¢ dx (1.46)
Furthermore, it can be easily veri¯ed that
S ¢ dx = ! £ dx
The motion of a °uid element located at position x with length dx and aligned along vector
dx can be decomposed into a pure translation by velocity u(x; t), a pure rotation at velocity
!, and deformations (linear and angular) at a rate D ¢ dx.
Example 1.6 : Deformations for a shearing °ow
Consider a simple two dimensional °ow whose velocity is given by
u1 = ax2
and
u2 = 0:
21. 18 1 Introduction
Derive all related tensors and give an interpretation for the °uid motion.
Solution
The velocity gradient tensor is readily obtained
ruT =
·
0 a
0 0
¸
:
Its symmetric and antisymmetric parts are respectively
D =
1
2
·
0 a
a 0
¸
and
S =
1
2
·
0 a
¡a 0
¸
:
The rotation vector has one non zero component
!3 = ¡
a
2 ;
hence the °ow is rotational. It can be seen that a square element translates horizontally by a
velocity u1 while its vertical edges rotate clockwise by an angle
d¯ = adt
so that its rate of rotation is a. The volume of the °uid element is unchanged, but the diagonal
line will rotate clockwise at the rate ¡1
2a. On the other hand, the angle originally at ¼
2 is
reduced by an angle adt, which shows that the °uid element is sheared at the rate °_ = a.
Example 1.7 : Deformations for a stagnation °ow
Consider a simple two dimensional °ow whose velocity is given by
u1 = ax1
and
u2 = ¡ax2:
Derive all related tensors and give an interpretation for the °uid motion.
Solution
The velocity gradient tensor is readily obtained
ruT =
·
a 0
0 ¡a
¸
:
Since it is a symmetric tensor then its symmetric and antisymmetric parts are respectively
22. 1.2 Velocity gradients and Deformations 19
D = ruT
and
S = 0:
Since S = 0, the °ow is irrotational. The sum of the diagonal coe±cients of the deformation
tensor is zero, therefore the volumetric dilatation is zero (in other words the °ow is incompres-
sible). From ¯gure ( ) we can see that the °uid element can be decomposed into a translation
motion by the velocity vector u and a relative motion which causes deformations whose velo-
city is ( @u1
@x1
dx1; @u2
@x2
dx2) = (adx1;¡adx2). The angle variations d¯ and d® are zero. This shows
that the °uid elements does not rotate and has no shearing. It has only linear deformations
(for a positive value of a, it corresponds to an expansion in the horizontal direction and a
compression in the vertical one).
Example 1.8 : Rate of change of material line
Consider a material line element dx with length ds, i.e. ds2 = dx ¢ dx and l = ( dx
ds ). Show that
the rate of extension or stretching of the element de¯ned by 1
ds
D(ds)
Dt is given by
1
ds
D(ds)
Dt
= l ¢ D ¢ l = li²ij lj : (1.47)
Solution
First of all, one can verify the following identities (proof left as an exercise) :
1
ds
D(ds)
Dt
=
1
2ds2
D(ds2)
Dt
;
D(dx)
Dt
= du;
and for any antisymmetric tensor W and any vector v one has
v ¢W¢ v = 0:
Using these relations (prove them as an exercise) one gets :
1
2ds2
D(ds2)
Dt
=
1
ds2 dx ¢ du:
Using equation (1.45), we have du = ru ¢ dx.
We denote by l the unit vector parallel to dx, that is : l = ( dx
ds ): It follows that
1
ds
D(ds)
Dt
= l ¢ ru ¢ l:
Since the velocity gradient tensor can be decomposed into a symmetric and an antisymmetric
parts :
23. 20 1 Introduction
1
ds
D(ds)
Dt
= l ¢ (D + S) ¢ l:
Since the spin tensor S is antisymmetric, the product l ¢ S ¢ l is zero. We can conclude that,
1
ds
D(ds)
Dt
= l ¢ D ¢ l = li²ij lj : (1.48)
Equation (1.48) gives an interpretation of the coe±cients of the strain tensor. If the material
element is parallel to a basis vector, for instance i1, then 1
ds
D(ds)
Dt = l ¢ D ¢ l = ²11. Therefore,
the diagonal elements of D represents the stretching of the material element parallel to the
axes.
Example 1.9 : Rate of change of the angle between material vectors
Consider two material line elements a and b. Initially these vectors make a right angle. Show
that the rate of change of the angle is :
D(µ)
Dt µ=¼2
= ¡2a ¢ D ¢ b
1.3 Problems
1.1. Measurements of a one dimensional velocity ¯eld give the following results :
Time x=0m x=10m x=20m
t=0s v=0m/s v=0m/s v=0m/s
t=1s v=1m/s v=1.2m/s v=1.4m/s
t=2s v=1.7m/s v=1.8m/s v=1.9m/s
t=3s v=2.1m/s v=2.15m/s v=2.2m/s
Calculate the acceleration at t = 1s and x = 10m .
1.2. Consider the velocity components : u = x2 ¡ y2 et v = ¡2xy. Calculate the divergence
and vorticity.
1.3. Consider the velocity ¯eld whose components are : u1 = a(x1 + x2)
u2 = a(x1 ¡ x2)
u3 = w with a, w are constants. Determine the divergence , vorticity and the pathlines.
1.4. Consider the velocity ¯eld : 8
:
u1 = bx2
u2 = bx1
u3 = 0
9=
;
et
8
:
u1 = ¡bx2
u2 = bx1
u3 = 0
9= ;
Is the °ow incompressible ?. Is it rotational ?.
1.5. Consider the velocity ¯eld v=(u,À) with u = cx + 2!y + y0 et À = cy + À0. Compute the
vorticity and the strain tensor.
24. 1.3 Problems 21
1.6. Consider the velocity ¯eld u = ax2 + by and v = ¡2axy + ct. Is the °ow incompressible ?
Determine the streamlines.
1.7. Verify the following relations :
{ a) div(Áv) = Ádiv(v) + vgrad(Á)
{ b) div(u £ v) = v:curl(u) ¡ u:curl(v)
{ c) (¿ : rv) = r(¿v) ¡ vr¿ with A : B =
P
i
P
j AijBij
1.8. { Find the expanded forms of the quantities :
(u:r)u
(ru):u
¾:u
div((ru):u)
{ Show that the magnitude of the vorticity vector is :
j³j2 = @ui
@xj
( @ui
@xj
¡
@uj
@xi
)
1.9. Show that the vorticity vector in cylindrical coordinates is given by :
curlu = r £ u = (
1
r
@uz
@µ
¡
@uµ
@r
)er + (@ur
@z
¡
@uz
@r
)eµ + (
1
r
(@(ruµ)
@r
¡
@ur
@µ
))ez
Calculate the vorticity for the following velocity ¯eld (°uid in solid rotation) : u = uµ(r)eµ
where uµ(r) = !r