MULTIDIMENSIONAL HEAT TRANSFER  This equation governs the Cartesian, temperature distribution for a three-dimensional unsteady, heat transfer problem.

Slides:



Advertisements
Similar presentations
Computational Modeling for Engineering MECN 6040
Advertisements

Basic law of heat conduction --Fourier’s Law Degree Celsius.
Heat Transfer Chapter 2.
CHE/ME 109 Heat Transfer in Electronics LECTURE 6 – ONE DIMENSIONAL CONDUTION SOLUTIONS.
Finite Element Method (FEM) Different from the finite difference method (FDM) described earlier, the FEM introduces approximated solutions of the variables.
Chapter 2: Steady-State One-Dimensional Heat Conduction
By S Ziaei-Rad Mechanical Engineering Department, IUT.
Chapter 3 Steady-State Conduction Multiple Dimensions
Copyright 2001, J.E. Akin. All rights reserved. CAD and Finite Element Analysis Most ME CAD applications require a FEA in one or more areas: –Stress Analysis.
CHE/ME 109 Heat Transfer in Electronics LECTURE 12 – MULTI- DIMENSIONAL NUMERICAL MODELS.
CHE/ME 109 Heat Transfer in Electronics LECTURE 10 – SPECIFIC TRANSIENT CONDUCTION MODELS.
CHE/ME 109 Heat Transfer in Electronics LECTURE 11 – ONE DIMENSIONAL NUMERICAL MODELS.
CHE/ME 109 Heat Transfer in Electronics LECTURE 8 – SPECIFIC CONDUCTION MODELS.
Solutions of the Conduction Equation P M V Subbarao Associate Professor Mechanical Engineering Department IIT Delhi An Idea Generates More Mathematics….
Partial differential equations Function depends on two or more independent variables This is a very simple one - there are many more complicated ones.
Types of Governing equations
CHAPTER 8 APPROXIMATE SOLUTIONS THE INTEGRAL METHOD
Chapter 5 NUMERICAL METHODS IN HEAT CONDUCTION
Two-Dimensional Conduction: Flux Plots and Shape Factors
Chapter 4 TRANSIENT HEAT CONDUCTION
Chapter 2 HEAT CONDUCTION EQUATION
Numerical Methods Due to the increasing complexities encountered in the development of modern technology, analytical solutions usually are not available.
CHAPTER 7 NON-LINEAR CONDUCTION PROBLEMS
ITERATIVE TECHNIQUES FOR SOLVING NON-LINEAR SYSTEMS (AND LINEAR SYSTEMS)
Tutorial 5: Numerical methods - buildings Q1. Identify three principal differences between a response function method and a numerical method when both.
Elliptic Partial Differential Equations - Introduction
Chapter 2 HEAT CONDUCTION EQUATION
Multidimensional Heat Transfer This equation governs the Cartesian, temperature distribution for a three-dimensional unsteady, heat transfer problem involving.
PAT328, Section 3, March 2001MAR120, Lecture 4, March 2001S16-1MAR120, Section 16, December 2001 SECTION 16 HEAT TRANSFER ANALYSIS.
Two-Dimensional Conduction: Finite-Difference Equations and Solutions
Module 4 Multi-Dimensional Steady State Heat Conduction.
Chapter 5: Numerical Methods in Heat Transfer
One-Dimensional Steady-State Conduction
HOT PLATE CONDUCTION NUMERICAL SOLVER AND VISUALIZER Kurt Hinkle and Ivan Yorgason.
Transient Conduction: Finite-Difference Equations and Solutions Chapter 5 Section 5.9  
Boundary Value Problems l Up to this point we have solved differential equations that have all of their initial conditions specified. l There is another.
Silesian University of Technology in Gliwice Inverse approach for identification of the shrinkage gap thermal resistance in continuous casting of metals.
TRANSIENT CONDUCTION Lumped Thermal Capacitance Method Analytical Method: Separation of Variables Semi-Infinite Solid: Similarity Solution Numerical Method:
MECN 3500 Inter - Bayamon Lecture 9 Numerical Methods for Engineering MECN 3500 Professor: Dr. Omar E. Meza Castillo
HEAT CONDUCTION EQUATION
HEAT TRANSFER FINITE ELEMENT FORMULATION
Finite Element Methods and Crack Growth Simulations Materials Simulations Physics 681, Spring 1999 David (Chuin-Shan) Chen Postdoc, Cornell Fracture Group.
Unsteady State Heat Conduction
Heat flux through the wall
Copyright © The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 Chapter 27.
Chapter 2: Heat Conduction Equation
Shape Factor Example 2 The shape factor can be modeled as a thermal resistance where Rt=1/kS. Therefore, it can be integrated into the electrical circuit.
Finite-Difference Solutions Part 2
Linear Systems Numerical Methods. 2 Jacobi Iterative Method Choose an initial guess (i.e. all zeros) and Iterate until the equality is satisfied. No guarantee.
Shape Factor Example The shape factor can be modeled as thermal resistance as R t =1/kS, Therefore, it can be integrated with the electric circuit analog.
ERT 216 HEAT & MASS TRANSFER Sem 2/ Dr Akmal Hadi Ma’ Radzi School of Bioprocess Engineering University Malaysia Perlis.
FINITE DIFFERENCE In numerical analysis, two different approaches are commonly used: The finite difference and the finite element methods. In heat transfer.
HEAT TRANSFER Problems with FEM solution
The Finite Element Approach to Thermal Analysis Appendix A.
Part 8 - Chapter 29.
differential equations of heat transfer
Fourier’s Law and the Heat Equation
FEM : Finite Element Method 2017.
Spatial Effects QUESTION: When can we neglect the temperature variation inside a solid? We can do that if the heat transfer via conduction inside the solid.
PDEs and Examples of Phenomena Modeled
Materials Science & Engineering University of Michigan
Chapter 27.
Numerical Examples Example: Find the system of finite difference equations for the following problem. Steady state heat conduction through a plane wall.
Numerical Method (Special Cases)
Numerical Method (Special Cases)
Numerical Analysis Lecture13.
What is Fin? Fin is an extended surface, added onto a surface of a structure to enhance the rate of heat transfer from the structure. Example: The fins.
Steady-State Heat Transfer (Initial notes are designed by Dr
Home assignment #3 (1) (Total 3 problems) Due: 12 November 2018
Presentation transcript:

MULTIDIMENSIONAL HEAT TRANSFER  This equation governs the Cartesian, temperature distribution for a three-dimensional unsteady, heat transfer problem involving heat generation.  For steady state  /  t = 0  No generation  To solve for the full equation, it requires a total of six boundary conditions: two for each direction. Only one initial condition is needed to account for the transient behavior.

Two-Dimensional, Steady State Case There are three approaches to solve this equation:  Numerical Method: Finite difference or finite element schemes, usually will be solved using computers.  Graphical Method: Limited use. However, the conduction shape factor concept derived under this concept can be useful for specific configurations. (see Table 4.1 for selected configurations)  Analytical Method: The mathematical equation can be solved using techniques like the method of separation of variables. (refer to handout)

Conduction Shape Factor  This approach applied to 2-D conduction involving two isothermal surfaces, with all other surfaces being adiabatic. The heat transfer from one surface (at a temperature T 1 ) to the other surface (at T 2 ) can be expressed as: q=Sk(T 1 -T 2 ) where k is the thermal conductivity of the solid and S is the conduction shape factor.  The shape factor can be related to the thermal resistance: q=Sk(T 1 - T 2 )=(T 1 -T 2 )/(1/kS)= (T 1 -T 2 )/R t where R t = 1/(kS)  1-D heat transfer can use shape factor also. Ex: Heat transfer inside a plane wall of thickness L is q=kA(  T/L), S=A/L  Common shape factors for selected configurations can be found in most textbooks, as also illustrated in Table 4.1.

Example Example: A 10 cm OD uninsulated pipe carries steam from the power plant across campus. Find the heat loss if the pipe is buried 1 m in the ground is the ground surface temperature is 50 ºC. Assume a thermal conductivity of the sandy soil as k = 0.52 w/m K. z=1 m T2T2 T1T1

The shape factor for long cylinders is found in Table 4.1 as Case 2, with L >> D: S = 2  L/ln(4  z/D) Where z = depth at which pipe is buried. S = 2  1  m/ln(40) = 1.7 m Then q' = (1.7  m)(0.52 W/m  K)(100 o C - 50 o C) q' = 44.2 W

Numerical Methods  Due to the increasing complexities encountered in the development of modern technology, analytical solutions usually are not available. For these problems, numerical solutions obtained using high-speed computer are very useful, especially when the geometry of the object of interest is irregular, or the boundary conditions are nonlinear. In numerical analysis, three different approaches are commonly used: the finite difference, the finite volume and the finite element methods. In heat transfer problems, the finite difference and finite volume methods are used more often. Because of its simplicity in implementation, the finite difference method will be discussed here in more detail.

Numerical Methods (contd…)  The finite difference method involves:  Establish nodal networks  Derive finite difference approximations for the governing equation at both interior and exterior nodal points  Develop a system of simultaneous algebraic nodal equations  Solve the system of equations using numerical schemes

The Nodal Networks  The basic idea is to subdivide the area of interest into sub- volumes with the distance between adjacent nodes by  x and  y as shown. If the distance between points is small enough, the differential equation can be approximated locally by a set of finite difference equations. Each node now represents a small region where the nodal temperature is a measure of the average temperature of the region.

The Nodal Networks (contd…) xx m,n m,n+1 m,n-1 m+1, n m-1,n yy m-½,n intermediate points m+½,n x=m  x, y=n  y Example

Finite Difference Approximation

Finite Difference Approximation (contd...)

A System of Algebraic Equations  The nodal equations derived previously are valid for all interior points satisfying the steady state, no generation heat equation. For each node, there is one such equation. For example: for nodal point m=3, n=4, the equation is T 2,4 + T 4,4 + T 3,3 + T 3,5 - 4T 3,4 =0 T 3,4 =(1/4)(T 2,4 + T 4,4 + T 3,3 + T 3,5 )  Nodal relation table for exterior nodes (boundary conditions) can be found in standard heat transfer textbooks (Table 4.2 in this presentation).  Derive one equation for each nodal point (including both interior and exterior points) in the system of interest. The result is a system of N algebraic equations for a total of N nodal points.

Matrix Form A total of N algebraic equations for the N nodal points and the system can be expressed as a matrix formulation: [A][T]=[C]

Numerical Solutions  Matrix form: [A][T]=[C]. From linear algebra: [A] -1 [A][T]=[A] -1 [C], [T]=[A] -1 [C] where [A] -1 is the inverse of matrix [A]. [T] is the solution vector.  Matrix inversion requires cumbersome numerical computations and is not efficient if the order of the matrix is high (>10)

Numerical Solutions (contd…)  Gauss elimination method and other matrix solvers are usually available in many numerical solution package. For example, “Numerical Recipes” by Cambridge University Press or their web source at  For high order matrix, iterative methods are usually more efficient. The famous Jacobi & Gauss-Seidel iteration methods will be introduced in the following.

Iteration Replace (k) by (k-1) for the Jacobi iteration

Iteration (contd…)  (k) - specify the level of the iteration, (k-1) means the present level and (k) represents the new level.  An initial guess (k=0) is needed to start the iteration.  By substituting iterated values at (k-1) into the equation, the new values at iteration (k) can be estimated  The iteration will be stopped when max  Ti (k) -Ti (k-1) , where  specifies a predetermined value of acceptable error