FORTRAN is used as a numerical and scientific computing language. The main objective of the lab work is to understand FORTRAN language using which we solve simple numerical problems and compare different methodologies. Through this project we make use of various functions of FORTRAN and solve a FDM simple heat equation problem applying different conditions viz. Dirichlet and Von Neumann. The given problems are solved analytically then built and compiled using a free integrated development environment called CODE::BLOCKS [1] which is an open source platform for FORTRAN and C.
Thermochemical study of Energy associated with reactions using python.Nagesh NARASIMHA PRASAD
Thermochemistry deals with the study of the energy and heat associated with chemical reactions or physical transformations. With numerous products and reactants it’s a very complex phenomenon to analyse and sometimes even impossible to obtain accurate results analytically. Using a programming language to solve or compute such complex problems gives reliable results. CANTERA is an open source tool based on python programming language which can be used to solve chemical, thermodynamics processes. We make use of CANTERA in this project to obtain chemical composition of products and compare it with analytical solutions and also to calculate flame temperature, enthalpy etc.
vFORTRAN is used as a numerical and scientific computing language. The main objective of the lab work is to understand FORTRAN language using which we solve simple numerical problems and compare different methodologies. Through this project we make use of various functions of FORTRAN and solve a simple projectile problem and also LAPACK library to solve a tridiagonal matrix problem. We use DGESV and DGTSV functions to make it possible. The given problems are built and compiled using a free integrated development environment called CODE::BLOCKS [1] which is an open source platform for FORTRAN and C.
Thermochemical study of Energy associated with reactions using python.Nagesh NARASIMHA PRASAD
Thermochemistry deals with the study of the energy and heat associated with chemical reactions or physical transformations. With numerous products and reactants it’s a very complex phenomenon to analyse and sometimes even impossible to obtain accurate results analytically. Using a programming language to solve or compute such complex problems gives reliable results. CANTERA is an open source tool based on python programming language which can be used to solve chemical, thermodynamics processes. We make use of CANTERA in this project to obtain chemical composition of products and compare it with analytical solutions and also to calculate flame temperature, enthalpy etc.
vFORTRAN is used as a numerical and scientific computing language. The main objective of the lab work is to understand FORTRAN language using which we solve simple numerical problems and compare different methodologies. Through this project we make use of various functions of FORTRAN and solve a simple projectile problem and also LAPACK library to solve a tridiagonal matrix problem. We use DGESV and DGTSV functions to make it possible. The given problems are built and compiled using a free integrated development environment called CODE::BLOCKS [1] which is an open source platform for FORTRAN and C.
NUMERICAL METHODS IN STEADY STATE, 1D and 2D HEAT CONDUCTION- Part-IItmuliya
This file contains slides on NUMERICAL METHODS IN STEADY STATE 1D and 2D HEAT CONDUCTION – Part-II.
The slides were prepared while teaching Heat Transfer course to the M.Tech. students in Mechanical Engineering Dept. of St. Joseph Engineering College, Vamanjoor, Mangalore, India, during Sept. – Dec. 2010.
Contents: Methods of solving a system of simultaneous, algebraic equations - 1D steady state conduction in cylindrical and spherical systems - 2D steady state conduction in cartesian coordinates - Problems
Numerical Solution of Diffusion Equation by Finite Difference Methodiosrjce
IOSR Journal of Mathematics(IOSR-JM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Novel Space-time Discontinuous Galerkin Method for Solving of One-dimension...TELKOMNIKA JOURNAL
In this paper we propose a high-order space-time discontinuous Galerkin (STDG) method for
solving of one-dimensional electromagnetic wave propagations in homogeneous medium. The STDG
method uses finite element Discontinuous Galerkin discretizations in spatial and temporal domain
simultaneously with high order piecewise Jacobi polynomial as the basis functions. The algebraic
equations are solved using Block Gauss-Seidel iteratively in each time step. The STDG method is
unconditionally stable, so the CFL number can be chosen arbitrarily. Numerical examples show that the
proposed STDG method is of exponentially accuracy in time.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Some Mixed Quadrature Rules for Approximate Evaluation of Real Cauchy Princip...IJERD Editor
In this paper some mixed quadrature rules have been constructed for numerical integration of real
Cauchy principal value integrals and their asymptotic error estimates have been derived. The numerical
verification of the rules has been done by considering some standard Cauchy principal value integrals.
Numerical Methods in Mechanical Engineering - Final ProjectStasik Nemirovsky
Final Project for the class of "Numerical Methods in Mechanical Engineering" - MECH 309.
In this project, various engineering problems were analyzed and solved using advanced numerical approximation methods and MATLAB software.
NUMERICAL METHODS IN STEADY STATE, 1D and 2D HEAT CONDUCTION- Part-IItmuliya
This file contains slides on NUMERICAL METHODS IN STEADY STATE 1D and 2D HEAT CONDUCTION – Part-II.
The slides were prepared while teaching Heat Transfer course to the M.Tech. students in Mechanical Engineering Dept. of St. Joseph Engineering College, Vamanjoor, Mangalore, India, during Sept. – Dec. 2010.
Contents: Methods of solving a system of simultaneous, algebraic equations - 1D steady state conduction in cylindrical and spherical systems - 2D steady state conduction in cartesian coordinates - Problems
Numerical Solution of Diffusion Equation by Finite Difference Methodiosrjce
IOSR Journal of Mathematics(IOSR-JM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mathemetics and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mathematics. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
A Novel Space-time Discontinuous Galerkin Method for Solving of One-dimension...TELKOMNIKA JOURNAL
In this paper we propose a high-order space-time discontinuous Galerkin (STDG) method for
solving of one-dimensional electromagnetic wave propagations in homogeneous medium. The STDG
method uses finite element Discontinuous Galerkin discretizations in spatial and temporal domain
simultaneously with high order piecewise Jacobi polynomial as the basis functions. The algebraic
equations are solved using Block Gauss-Seidel iteratively in each time step. The STDG method is
unconditionally stable, so the CFL number can be chosen arbitrarily. Numerical examples show that the
proposed STDG method is of exponentially accuracy in time.
International Journal of Mathematics and Statistics Invention (IJMSI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJMSI publishes research articles and reviews within the whole field Mathematics and Statistics, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Some Mixed Quadrature Rules for Approximate Evaluation of Real Cauchy Princip...IJERD Editor
In this paper some mixed quadrature rules have been constructed for numerical integration of real
Cauchy principal value integrals and their asymptotic error estimates have been derived. The numerical
verification of the rules has been done by considering some standard Cauchy principal value integrals.
Numerical Methods in Mechanical Engineering - Final ProjectStasik Nemirovsky
Final Project for the class of "Numerical Methods in Mechanical Engineering" - MECH 309.
In this project, various engineering problems were analyzed and solved using advanced numerical approximation methods and MATLAB software.
Finite Volume Method Advanced Numerical Analysis by Md.Al-AminMd. Al-Amin
Finite Volume Method Advanced Numerical Analysis by Md.Al-Amin
Imam Hasan Al-Amin, professionally known as MD Al-Amin, He was born on December 25th, 1999, and brought up in Pirojpur. He is a Bangladeshi entrepreneur and mathematician. He graduated from Khulna University, Khulna, Bangladesh also Bangladesh University of Engineering and Technology(BUET) in mathematics. He is the co-founder and CEO of Juhod Shop-যুহদ শপ, which is mainly an online shop in Bangladesh. Here, you can buy products online with a few clicks or convenient phone calls. Also, he is the founder and CEO of Juhod IT-Care, a full-service digital media agency that partners with clients to boost their personal and business outcomes. His expertise in marketing has allowed him to help a number of businesses increase their revenue by tremendous amounts. From childhood, he wanted to do something different that would be fruitful for mankind. He started working as a vocal artist when he was only 18 years old.
390 Guided Projects
Guided Project 31: Cooling coffee
Topics and skills: Derivatives, exponential functions
Imagine pouring a cup of hot coffee and letting it cool at room temperature. How does the temperature of the
coffee decrease in time? How long must you wait until the coffee is cool enough to drink? When should you
add an ounce of cold milk to the coffee to accelerate the cooling as much as possible?
A fairly accurate model to describe the temperature changes in a conducting object is Newton’s Law of
Cooling. Suppose that at time t ≥ 0 an object has a temperature of T(t). The Law of Cooling says that the rate at
which the temperature of the object increases or decreases is given by
( ( ) ) , (1)
dT
k T t A
dt
= − −
where A is the ambient (surrounding) temperature and k > 0 is a constant called the conductivity (which is a
property of the cooling object). Newton’s Law of Cooling assumes that the cooling body has a uniform
temperature throughout its interior. This is not strictly accurate, as a cooling body loses heat through its surface.
1. Explain in words what equation (1) means. Specifically, in terms of T and A, when is 0
dT
dt
> and when is
0
dT
dt
< ? For the case of hot coffee cooling to room temperature, which case do you expect to see?
2. Verify by substitution that the solution to equation (1) subject to the initial condition T(0) = T0 is
0( ) ( ) . (2)
ktT t A T A e−= + −
3. Before graphing the temperature function, use equation (2) to evaluate T(0) and limt→∞ T(t). Are these the
values you expect?
4. Consider the case of a cup of hot coffee cooling with an ambient room temperature of A = 60◦ F and the
initial temperature of the coffee is T0 = 200
◦ F. Use a graphing utility to plot the temperature function for
k = 0.3, 0.2, 0.1, and 0.05. Comment on how the curves change with k. Do larger values of k produce faster
or slower rates of temperature change?
5. For the values of A and T0 in Step 4, estimate the value of k that describes the case in which the coffee
cools to 100 degrees in 10 minutes.
Here is an interesting question. Suppose you want to cool your hot coffee to 100◦ F as quickly as possible.
Suppose also that you have one ounce of cold milk with a temperature of 40◦ F that you can add to the
cooling coffee at any time. When should you add the milk to cool the coffee to 100◦ F as quickly as
possible?
6. We need to make an assumption about the effect of cold milk on the temperature of the coffee. A
reasonable assumption is that when milk is added to coffee, the temperature of the coffee immediately
decreases to the average of the coffee temperature and the milk temperature, where the average is weighted
by the volumes. So if we add 1 ounce of milk with temperature Tm to 8 ounces of coffee with temperature
T, the temperature of the mixture will be
1 8 8
. (3)
1 8 9
m m
new
T T T T
T
⋅ .
390 Guided Projects
Guided Project 31: Cooling coffee
Topics and skills: Derivatives, exponential functions
Imagine pouring a cup of hot coffee and letting it cool at room temperature. How does the temperature of the
coffee decrease in time? How long must you wait until the coffee is cool enough to drink? When should you
add an ounce of cold milk to the coffee to accelerate the cooling as much as possible?
A fairly accurate model to describe the temperature changes in a conducting object is Newton’s Law of
Cooling. Suppose that at time t ≥ 0 an object has a temperature of T(t). The Law of Cooling says that the rate at
which the temperature of the object increases or decreases is given by
( ( ) ) , (1)
dT
k T t A
dt
= − −
where A is the ambient (surrounding) temperature and k > 0 is a constant called the conductivity (which is a
property of the cooling object). Newton’s Law of Cooling assumes that the cooling body has a uniform
temperature throughout its interior. This is not strictly accurate, as a cooling body loses heat through its surface.
1. Explain in words what equation (1) means. Specifically, in terms of T and A, when is 0
dT
dt
> and when is
0
dT
dt
< ? For the case of hot coffee cooling to room temperature, which case do you expect to see?
2. Verify by substitution that the solution to equation (1) subject to the initial condition T(0) = T0 is
0( ) ( ) . (2)
ktT t A T A e−= + −
3. Before graphing the temperature function, use equation (2) to evaluate T(0) and limt→∞ T(t). Are these the
values you expect?
4. Consider the case of a cup of hot coffee cooling with an ambient room temperature of A = 60◦ F and the
initial temperature of the coffee is T0 = 200
◦ F. Use a graphing utility to plot the temperature function for
k = 0.3, 0.2, 0.1, and 0.05. Comment on how the curves change with k. Do larger values of k produce faster
or slower rates of temperature change?
5. For the values of A and T0 in Step 4, estimate the value of k that describes the case in which the coffee
cools to 100 degrees in 10 minutes.
Here is an interesting question. Suppose you want to cool your hot coffee to 100◦ F as quickly as possible.
Suppose also that you have one ounce of cold milk with a temperature of 40◦ F that you can add to the
cooling coffee at any time. When should you add the milk to cool the coffee to 100◦ F as quickly as
possible?
6. We need to make an assumption about the effect of cold milk on the temperature of the coffee. A
reasonable assumption is that when milk is added to coffee, the temperature of the coffee immediately
decreases to the average of the coffee temperature and the milk temperature, where the average is weighted
by the volumes. So if we add 1 ounce of milk with temperature Tm to 8 ounces of coffee with temperature
T, the temperature of the mixture will be
1 8 8
. (3)
1 8 9
m m
new
T T T T
T
⋅ .
Different analytical and numerical methods are commonly used to solve transient heat conduction problems. In this problem, the use of Alternating Direct Implicit scheme (ADI) was adopted to solve temperature variation within an infinitesimal long bar of a square cross-section. The bottom right quadrant of the square cross-section of the bar was selected. The surface of the bar was maintained at constant temperature and temperature variation within the bar was evaluated within a time frame. The Laplace equation governing the 2-dimesional heat conduction was solved by iterative schemes as a result of the time variation. The modelled problem using COMSOL-MULTIPHYSICS software validated the result of the ADI analysis. On comparing the Modelled results from COMSOL MULTIPHYSICS and the results from ADI iterative scheme graphically, there was an high level of agreement between both results.
Temperature Distribution in a ground section of a double-pipe system in a dis...Paolo Fornaseri
Our analysis concerns the distribution network of a suburb in the city of Turin.
We analyzed the thermal needs, the network layout and many other engineering problems regarding
the distribution of heat.
In the following report we are going to analyze the simplified model of a couple of buried ducts,
conveying the fluid used for thermal needs in the houses.
We analyzed the thermal distribution in the pipeline, in particular we focused on a section of the
ground, in which the water passes through the double-pipe system, namely return and supply pipe.
We used the fundamental heat equation (conduction) and the subsequent numerical discretization, in
the transient and in the steady state.
To this aim, we made some simplifications in order to apply our mathematical model.
To demonstrate the effect of cross sectional area on the heat rate.
To measure the temperature distribution for unsteady state conduction of heat through the uniform plane wall and the wall of the thick cylinder.
The experiment demonstrates heat conduction in radial conduction models It
allows us to obtain experimentally the coefficient of thermal conductivity of some unknown materials and in this way, to understand the factors and parameters that affect the rates of heat transfer.
To understand the use of the Fourier Rate Equation in determining the rate of heat flow for of energy through the wall of a cylinder (radial energy flow).
To use the equation to determine the constant of proportionality (the thermal conductivity, k) of the disk material.
To observe unsteady conduction of heat
Formal expansion method for solving an electrical circuit modelTELKOMNIKA JOURNAL
We investigate the validity of the formal expansion method for solving a second order ordinary differential equation raised from an electrical circuit problem. The formal expansion method approximates the exact solution using a series of solutions. An approximate formal expansion solution is a truncated version of this series. In this paper, we confirm using simulations that the approximate formal expansion solution is valid for a specific interval of domain of the free variable. The accuracy of the formal expansion approximation is guaranteed on the time-scale 1.
Similar to Projectwork on different boundary conditions in FDM. (20)
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Final project report on grocery store management system..pdf
Projectwork on different boundary conditions in FDM.
1. Numerical Methods Lab Work 2
By
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh
Submitted to
KOZHANOVA Ksenia
2. ABSTRACT
FORTRAN is used as a numerical and scientific computing language. The main objective
of the lab work is to understand FORTRAN language using which we solve simple
numerical problems and compare different methodologies. Through this project we make
use of various functions of FORTRAN and solve a FDM simple heat equation problem
applying different conditions viz. Dirichlet and Von Neumann. The given problems are
solved analytically then built and compiled using a free integrated development
environment called CODE::BLOCKS [1] which is an open source platform for FORTRAN
and C.
3. CONTENTS:
List of figures.
1. A simple heat flow experiment using 1D Heat Equation. 1
2. Finite Difference Explicit Method. 2
3. Finite Difference Implicit Method. 9
CONCLUSION 11
REFERENCE 12
4. LIST OF FIGURES.
Fig 1: Rod considered for the problem.
Dirichlet Boundary,
Fig 2: Temperature variation at each node of c value 0.25
Fig 3: Temperature variation at each node of C value 0.49
Fig 4: Temperature variation at each node of C value 0.51
Fig 5: Temperature variation at each node of C value 0.75
Von Neumann Boundary,
Fig 6: Temperature variation at each node of C value 0.25
Fig 7: Temperature variation at each node of C value 0.49
Fig 8: Temperature variation at each node of C value 0.55
Fig 9: Temperature variation at each node of C value 0.75
5. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 1 | P a g e
1. A simple heat flow experiment using 1D Heat Equation.
A Copper rod of length L = 1m and diameter is 1 cm with lateral sides insulated is subjected to
external temperature T0, until the temperature of the rod reaches T0. At time t=0, the ends of the rod
are subjected to T1 and T2 temperature with the given boundary conditions solve the heat equation
and write in non-dimensional form.
Fig 1: Rod considered for the problem.
Initial and boundary conditions,
T (0, x) = T0 = 400 Initial
T(t,0) = T1 = 300 Dirichlet condition
T (t, L) = T2 = 500 Dirichlet condition
𝜌𝐶 𝑝
𝜕𝑇
𝜕𝑡
+
𝜕
𝜕𝑥
(−𝜆
𝜕𝑇
𝜕𝑥
) = 0 ………….(1)
Where,
𝝆 is Density (kg/m3
)
Cp is the Heat capacity
𝝀 is the conductivity.
Assuming 𝜆 as constant equation 1 can be written as,
𝜕𝑇
𝜕𝑡
= 𝛼
𝜕2 𝑇
𝜕𝑥2 ……………..(2)
Where,
𝛼 =
𝜆
𝜌𝐶 𝑝
Non Dimensionalization of the equation,
𝑇̃ = T
𝑥̃ = x
𝑡̃ = t
6. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 2 | P a g e
𝜕𝑇̃
𝜕𝑡̃
=
𝜕2
𝑇̃
𝜕𝑥̃2
2. Finite Difference Explicit Method:
Using second order centered difference for space derivative and simple first order forward
difference for time derivative. The scheme results in,
𝜕 = T (t + 𝛥𝑡) - T (t)
𝜕𝑡 𝛥𝑡
Using the above scheme,
∂T
∂t
=
Tj
k+1
−Tj
k
∆t
.………………... (3)
Substituting the equation no. 3,
𝜕2 𝑇
𝜕𝑥2 =
𝑇𝑗+1
𝑘
−2𝑇𝑗
𝑘
+𝑇𝑗−1
𝑘
(∆𝑥)2 …………. (4)
Using the equation no. 3 and 4,
𝑇𝑗
𝑘+1
− 𝑇𝑗
𝑘
=
∆𝑡
∆𝑥2 (𝑇𝑗+1
𝑘
− 2𝑇𝑗
𝑘
+ 𝑇𝑗−1
𝑘
) ………. (5)
Considering,
𝑐 =
∆𝑡
∆𝑥2
This equation helps in finding the temperature evolution at different stages,
𝑻𝒋
𝒌+𝟏
= 𝒄. 𝑻𝒋−𝟏
𝒌
+ (𝟏 − 𝟐𝒄)𝑻𝒋
𝒌
+ 𝒄. 𝑻𝒋+𝟏
𝒌
Discretizing Boundary conditions:
Boundary conditions and initial conditions for the problem is given for two cases. Imposed
temperature in the two ends of the rod,
T(1,t)=300 indicating 𝑻 𝟏
𝒌
= 𝟑𝟎𝟎
T(L,t)=500 indicating 𝑻 𝑵
𝒌
= 𝟓𝟎𝟎
7. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 3 | P a g e
The initial condition is T(x, 1) = 400 indicating 𝑇𝑗
1
= 400
Applying the boundary conditions in the obtained equation 5 with j varying from 2 to N-1
𝑇𝑗
𝑘+1
= 𝑐𝑇𝑗−1
𝑘
+ (1 − 2𝑐)𝑇𝑗
𝑘
+ 𝑐𝑇𝑗+1
𝑘
The equation for the second node can be written as,
𝑇2
𝑘+1
= 𝑐𝑇1
𝑘
+ (1 − 2𝑐)𝑇2
𝑘
+ 𝑐𝑇3
𝑘
𝑇2
𝑘+1
= 300𝑐 + (1 − 2𝑐)𝑇2
𝑘
+ 𝑐𝑇3
𝑘
The equation for the last but one node can be written as,
𝑇 𝑁−1
𝑘+1
= 𝑐𝑇 𝑁−2
𝑘
+ (1 − 2𝑐)𝑇 𝑁−1
𝑘
+ 𝑐𝑇 𝑁
𝑘
𝑇 𝑁−1
𝑘+1
= 𝑐𝑇 𝑁−2
𝑘
+ (1 − 2𝑐)𝑇 𝑁−1
𝑘
+ 500𝑐
Writing the system of equations in the matrix form:
𝑻 𝒌+𝟏
= 𝑨𝑻 𝒌
+ 𝑩
(
𝑇1
𝑘+1
⋮
𝑇 𝑁
𝑘+1
) = [
1 − 2𝑐 𝑐 0
𝑐 ⋱ ⋱
0 ⋱ 1 − 2𝑐
] (
𝑇1
𝑘
⋮
𝑇 𝑁
𝑘
) + [
300
⋮
500
]
Here (1-2c) occupies the main diagonal and c the lower and upper diagonal. B is the boundary
condition matrix with only two entries at the extreme nodes and the other values are 0.
By applying the derived equation into program graphs for temperature values as function of time for
different length divisions can be obtained.
8. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 4 | P a g e
Fig 2: Temperature variation at each node of c value 0.25
Fig 3: Temperature variation at each node of C value 0.49
As shown in the graphs 1 and 2 the temperature at each node after some amount of time converges
showing that it gains equilibrium. This is considered true only when c value is less than 0.5 which is
evident from the graph 3 and 4. As c increased to 0.5, the system became marginally stable. The
reason of referring the system has been deduced from unstable solutions where c takes a value above
0.5.
290
340
390
440
490
-0.15 0.05 0.25 0.45 0.65 0.85 1.05
Temparature(K)
LENGTH (L)
C = 0.25
270
320
370
420
470
-0.15 0.05 0.25 0.45 0.65 0.85 1.05
Temperature(K)
LENGTH (L)
C = 0.49
9. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 5 | P a g e
Fig 4: Temperature variation at each node of C value 0.51
Fig 5: Temperature variation at each node of C value 0.75
For values of c > 0.5, the system becomes unstable. The resulting graphs are varying and dissimilar
when compared to graphs of stable system. Oscillations in temperature curves can be seen as time
progress occurs, which indicates instability in the system. In c = 0.75, instabilities begin to start
earlier which say that as c is increased further, oscillations occur rapidly.
Von Neumann Boundary condition:
Imposed temperature on one end of the rod and a flux on another end of the rod,
T (1, t) = 300 indicating,
-2E+30
-1.5E+30
-1E+30
-5E+29
0
5E+29
1E+30
1.5E+30
2E+30
-0.15 0.05 0.25 0.45 0.65 0.85 1.05
Temperature(K)
LENGTH (L)
C = 0.51
-4E+38
-3E+38
-2E+38
-1E+38
0
1E+38
2E+38
3E+38
4E+38
-0.15 0.05 0.25 0.45 0.65 0.85 1.05
Temperature(K)
LENGTH (L)
C = 0.75
10. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 6 | P a g e
𝑇1
𝑘
= 300 𝑎𝑛𝑑
𝜕𝑇( 𝑡, 𝐿)
𝜕𝑥
= 50
This temperature is maintained at all time in this problem. The initial condition is same as the
previous case given by T(x, 1) = 400 indicating 𝑇𝑗
1
= 400
Applying the boundary conditions in the obtained with j varying from 2 to N-1:
𝑇𝑗
𝑘+1
= 𝑐𝑇𝑗−1
𝑘
+ (1 − 2𝑐)𝑇𝑗
𝑘
+ 𝑐𝑇𝑗+1
𝑘
The equation for the second node is same as the previous case:
𝑇2
𝑘+1
= 300𝑐 + (1 − 2𝑐)𝑇2
𝑘
+ 𝑐𝑇3
𝑘
The equation for the second last node using the Von Neumann boundary condition:
𝜕𝑇(𝑡, 𝐿)
𝜕𝑥
= 50
Is expressed using backward scheme as follows:
𝑇 𝑁
𝑘
= 50𝛥𝑥 + 𝑇 𝑁−1
𝑘
We get the final equation as∶
𝑇 𝑁−1
𝑘+1
= 𝑐𝑇 𝑁−2
𝑘
+ (1 − 2𝑐)𝑇2
𝑘
+ 50𝛥𝑥 + 𝑇 𝑁−1
𝑘
Applying center difference scheme to the boundary conditions we get,
𝜕𝑇
𝜕𝑥
=
𝑇𝑛+1
𝑘
− 𝑇𝑛−1
𝑘
2∆𝑥
= 50
Where 𝑇𝑛+1
𝑘
= 100 × ∆𝑥 + 𝑇𝑛−1
𝑘
is a ghost node that updates the values of Tn in the
equation.
By applying the derived equation into program graphs for temperature values as function of time for
different length divisions can be obtained.
11. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 7 | P a g e
Fig 6: Temperature variation at each node of C value 0.25
Fig 7: Temperature variation at each node of C value 0.49
290
310
330
350
370
390
410
430
0 0.2 0.4 0.6 0.8 1
Temperature(K)
LENGTH (L)
C = 0.25
290
310
330
350
370
390
410
430
0 0.2 0.4 0.6 0.8 1
Temperature(K)
LENGTH (L)
C = 0.49
12. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 8 | P a g e
Fig 8: Temperature variation at each node of C value 0.55
Fig 9: Temperature variation at each node of C value 0.75
From the obtained graphs, it can be seen that the effect of the Von Neumann boundary condition on
right end of the bar is observed from the plots. The temperature value at this end is drastically
decreased comparing with that of Dirichlet boundary condition. It can be observed that the solution
of temperature variation for von Neumann condition takes more time to intersect compared to
Dirichlet. From the stability point of view, for values of c > 0.5, oscillations occur with increasing
time resulting in instability.
-2.5E+38
-2E+38
-1.5E+38
-1E+38
-5E+37
0
5E+37
1E+38
1.5E+38
2E+38
2.5E+38
-0.15 0.05 0.25 0.45 0.65 0.85 1.05
Temperature(K)
LENGTH (L)
C = 0.55
-3E+15
-2E+15
-1E+15
0
1E+15
2E+15
3E+15
-0.15 0.05 0.25 0.45 0.65 0.85 1.05
Temperature(K)
LENGTH (L)
C = 0.75
13. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 9 | P a g e
3. Finite difference implicit method:
In this method, the forward difference scheme is applied for time derivative and center second
difference scheme is applied for space derivative for the next time step as follows.
𝜕𝑇
𝜕𝑡
=
𝑇𝑗
𝑘+1
− 𝑇𝑗
𝑘
∆𝑡
𝜕2
𝑇
𝜕𝑥2
=
𝑇𝑗+1
𝑘+1
− 2𝑇𝑗
𝑘+1
+ 𝑇𝑗−1
𝑘+1
(∆𝑥)2
Substituting the above equations in the equation no. 1, and considering,
𝑐 =
∆𝑡
(∆𝑥)2,
The following equation is obtained,
𝑻(𝒌) = −𝒄. 𝑻𝒋−𝟏
𝒌+𝟏
+ (𝟏 + 𝟐𝒄)𝑻𝒋
𝒌+𝟏
− 𝒄. 𝑻𝒋+𝟏
𝒌+𝟏
……………(6)
The following boundary conditions are applied to the above stated equation. Boundary conditions
and initial conditions for the problem is given for two cases. Imposed temperature in the two ends
of the beam,
T(1,t)=300 indicating 𝑻 𝟏
𝒌
= 𝟑𝟎𝟎
T(L,t)=500 indicating 𝑻 𝑵
𝒌
= 𝟓𝟎𝟎
This temperature is maintained at all times for this problem. The initial condition is T(x, 1) =400
indicating 𝑻𝒋
𝟏
= 𝟒𝟎𝟎
Applying the boundary conditions in the obtained equation 6 with j varying from 2 to N-1
𝑇𝑗
𝑘
= −𝑐𝑇𝑗−1
𝑘+1
+ (1 + 2𝑐)𝑇𝑗
𝑘+1
− 𝑐𝑇𝑗+1
𝑘+1
The equation for the second node can be written as,
𝑇2
𝑘
= −𝑐𝑇1
𝑘+1
+ (1 + 2𝑐)𝑇2
𝑘+1
+ 𝑐𝑇3
𝑘+1
14. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 10 | P a g e
The equation for the last but one nod can be written as,
𝑇 𝑁−1
𝑘
= −𝑐𝑇 𝑁−1
𝑘+1
+ (1 + 2𝑐)𝑇 𝑁
𝑘+1
− 𝑐𝑇 𝑁+1
𝑘+1
This temperature is maintained at all times for this problem. The initial condition is same as the
previous one given by T(x, 1) = 400 indicating,
𝑇𝑗
1
= 400
Applying the boundary conditions in the obtained equation with j varying from 2 to N-1
𝑇𝑗
𝑘
= −𝑐𝑇𝑗−1
𝑘+1
+ (1 + 2𝑐)𝑇𝑗
𝑘+1
− 𝑐𝑇𝑗+1
𝑘+1
Writing the system of equation in the matrix form
𝐴. 𝑇 𝑘+1
= 𝑇 𝑘
+ 𝐵
[
1 + 2𝑐 −𝑐 0
−𝑐 ⋱ ⋱
0 ⋱ 1 + 2𝑐
] (
𝑇1
𝑘+1
⋮
𝑇 𝑁
𝑘+1
) = (
𝑇1
𝑘
⋮
𝑇 𝑁
𝑘
) + [
300
⋮
500
]
Where A is tridiagonal matrix with 1+2c as the main diagonal and -c as the lower and upper diagonal.
B is the boundary condition matrix with only two entries at the extreme nodes and the other values
being 0.
15. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 11 | P a g e
CONCLUSION
Altogether in this lab work we used finite difference method to solve a heat equation and apply the
same to a rod which is heated from one end. Here application of two different boundary conditions
is done viz. Dirichlet and Von Neumann through which we solve the given problem. This task helped
in understanding application of FDM on heat equation analysis and also made us familiarize with
different boundary conditions. The implicit mode of solving is done analytically by which we obtain
the matrix form of the given problem as written in the report. In order to execute the program for
implicit it is required to make use of DGESV function which is not submitted in this lab work. We
tried programming the code where we got few errors which we were unable to rectify.
16. Numerical Methods Lab work 2
PENKULINTI Sai Sreenivas & NARASIMHA PRASAD Nagesh 12 | P a g e
REFERENCES
1. Team CODE::BLOCKS, http://www.codeblocks.org/downloads/26
Version 17.12, Dated 30 Dec 2017.
2. Tutorials Point – Fortran Tutorials, https://www.tutorialspoint.com/fortran/index.htm
3. Stanford education - Learn Fortran, https://web.stanford.edu/class/me200c/tutorial_90/
4. Moodle ENSMA – Numerical Methods Links, https://moodle.ensma.fr/course/
5. https://en.wikipedia.org/wiki/Talk%3ANeumann_boundary_condition for Vonn Neumann
condition.
6. https://en.wikipedia.org/wiki/Nondimensionalization for non dimensionalization.