İzmir Ekonomi Üniversitesi
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  • FACULTY OF ENGINEERING

    Department of Mechanical Engineering

    FENG 346 | Course Introduction and Application Information

    Course Name
    Numerical Methods for Engineers II
    Code
    Semester
    Theory
    (hour/week)
    Application/Lab
    (hour/week)
    Local Credits
    ECTS
    FENG 346
    Spring
    3
    0
    3
    6

    Prerequisites
      FENG 345 To get a grade of at least FD
    Course Language
    English
    Course Type
    Required
    Course Level
    First Cycle
    Mode of Delivery -
    Teaching Methods and Techniques of the Course Problem Solving
    Lecture / Presentation
    National Occupation Classification -
    Course Coordinator
    Course Lecturer(s)
    Assistant(s) -
    Course Objectives The course objectives are to provide the central ideas behind algorithms for the numerical solution of differentiable optimization problems by presenting key methods for both unconstrained and constrained optimization, as well as providing theoretical justification as to why they succeed. Additionally, it is aimed to teach the computational tools available to solving optimization problems on computers once a mathematical formulation has been found.
    Learning Outcomes
    #
    Content
    PC Sub
    * Contribution Level
    1
    2
    3
    4
    5
    1Formulate an optimization problem in the standard format with the objective function and the related constraints(equality and/or inequality)
    2Find the optimum point of an optimization problem by using graphical techniques
    3Perform analytical calculations to write the optimality conditions of optimization problems(constrained and unconstrained).
    4Solve constrained and unconstrained optimization problems either analytically or by using MATLAB/Octave(or other tools and programming languages)
    5Solve linear programming problems
    6Solve basic parabolic and elliptic partial differential equations by using finite difference methods
    Course Description In this course, the following topics will be covered, with a special focus on practical applications: the importance of optimization, basic definition and facts on optimization problems, theory of linear programming, nonlinear programming (constrained and unconstrained optimization problems), numerical methods for constrained and unconstrained problems, numerical solution of partial differential(elliptic and parabolic) equations.

     



    Course Category

    Core Courses
    X
    Major Area Courses
    Supportive Courses
    Media and Management Skills Courses
    Transferable Skill Courses

     

    WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

    Week Subjects Related Preparation Learning Outcome
    1 Introduction to Partial Differential Equations Textbook 3: Chapter 28
    2 Finite Difference Method: Simple Implicit and Explicit Finite Difference Schemes and Numerical Stability Textbook 3: Chapter 29, 30
    3 Finite Difference: Elliptic Equations Textbook 3: Chapter 29
    4 Finite Difference: Parabolic Equations Textbook 3: Chapter 30
    5 Optimization concept and historical perspective, basic concepts in optimization process. Textbook 1: Chapter 1 Textbook 2: Chapter 1
    6 Optimum Design Problem Formulation Textbook 1: Chapter 2
    7 Graphical Solution Method and Basic Optimization Concepts Textbook 1: Chapter 3
    8 Midterm Exam
    9 Optimum Design Concepts: Optimality Conditions Textbook 1: Chapter 4
    10 Optimum Design Concepts: Optimality Conditions Textbook 1: Chapter 4
    11 Numerical Methods for Unconstrained Optimization Textbook 1: Chapter 10
    12 Numerical Methods for Constrained Optimization Textbook 1: Chapter 12
    13 Linear Programming Textbook 1: Chapter 8
    14 Linear Programming Textbook 1: Chapter 8
    15 Review of the semester
    16 Final

     

    Course Notes/Textbooks
    1. Jasbir Singh Arora. Introduction to Optimum Design. 4th Edition, Academic Press, 2016. ISBN 978-0-12-800806-5
    2. Engineering Optimization: Theory and Practice, S. S. Rao, John Wiley and Sons Inc, ISBN 978-0-470-18352-6.
    3. Steven, C. Chapra. Numerical Methods for Engineers. Seventh Edition, McGraw-Hill, 2018. ISBN 978-0-07-339796-2
    4. John A. Trangenstein, Numerical Solution of Elliptic and Parabolic Partial Differential Equations, Cambridge University Press, 2013
    5. K. W. Morton, D. F. Mayers, Numerical Solution of Partial Differential Equations, Second Edition, Cambridge University Press, 2005
    Suggested Readings/Materials
    1.  P. Venkataraman, Applied Optimization with MATLAB Programming, John Wiley & Sons, Inc., 2009, ISBN: 978-0-470-08488-5
    2. Numerical Analysis by Timothy Sauer, 2006, Pearson;
    3. Numerical Methods for Engineers and Scientists: An Introduction with Applications using MATLAB by Gilat and Subramaniam, Wiley.

     

    EVALUATION SYSTEM

    Semester Activities Number Weigthing LO 1 LO 2 LO 3 LO 4 LO 5 LO 6
    Participation
    Laboratory / Application
    Field Work
    Quizzes / Studio Critiques
    Portfolio
    Homework / Assignments
    1
    40
    Presentation / Jury
    Project
    Seminar / Workshop
    Oral Exams
    Midterm
    1
    20
    Final Exam
    1
    40
    Total

    Weighting of Semester Activities on the Final Grade
    2
    60
    Weighting of End-of-Semester Activities on the Final Grade
    1
    40
    Total

    ECTS / WORKLOAD TABLE

    Semester Activities Number Duration (Hours) Workload
    Theoretical Course Hours
    (Including exam week: 16 x total hours)
    16
    3
    48
    Laboratory / Application Hours
    (Including exam week: '.16.' x total hours)
    16
    0
    Study Hours Out of Class
    14
    3
    42
    Field Work
    0
    Quizzes / Studio Critiques
    0
    Portfolio
    0
    Homework / Assignments
    7
    8
    56
    Presentation / Jury
    0
    Project
    0
    Seminar / Workshop
    0
    Oral Exam
    0
    Midterms
    1
    14
    14
    Final Exam
    1
    20
    20
        Total
    180

     

    COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

    #
    PC Sub Program Competencies/Outcomes
    * Contribution Level
    1
    2
    3
    4
    5
    1

    To have adequate knowledge in Mathematics, Mathematics based physics, statistics and linear algebra and Mechanical Engineering; to be able to use theoretical and applied information in these areas on complex engineering problems.

    -
    -
    -
    X
    -
    2

    To be able to identify, define, formulate, and solve complex Mechanical Engineering problems; to be able to select and apply proper analysis and modeling methods for this purpose.

    -
    -
    -
    X
    -
    3

    To be able to design a thermal and mechanical system, process, device or product under realistic constraints and conditions, in such a way as to meet the requirements; to be able to apply modern design methods for this purpose.

    X
    -
    -
    -
    -
    4

    To be able to devise, select, and use modern techniques and tools needed for analysis and solution of complex problems in engineering applications.

    -
    -
    X
    -
    -
    5

    To be able to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or Mechanical Engineering research topics.

    -
    -
    -
    -
    -
    6

    To be able to work efficiently in Mechanical Engineering disciplinary and multi-disciplinary teams; to be able to work individually.

    -
    -
    -
    -
    -
    7

    To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively, to be able to give and receive clear and comprehensible instructions.

    -
    -
    -
    -
    -
    8

    To have knowledge about global and social impact of engineering practices on health, environment, and safety; to have knowledge about contemporary issues as they pertain to engineering; to be aware of the legal ramifications of engineering solutions.

    -
    -
    -
    -
    -
    9

    To be aware of ethical behavior, professional and ethical responsibility; to have knowledge about standards utilized in engineering applications.

    -
    -
    -
    -
    -
    10

    To have knowledge about industrial practices such as project management, risk management, and change management; to have awareness of entrepreneurship and innovation; to have knowledge about sustainable development.

    -
    -
    -
    -
    -
    11

    To be able to collect data in the area of Mechanical Engineering, and to be able to communicate with colleagues in a foreign language.

    -
    -
    -
    -
    -
    12

    To be able to speak a second foreign language at a medium level of fluency efficiently.

    -
    -
    -
    -
    -
    13

    To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Mechanical Engineering.

    -
    -
    -
    -
    -

    *1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

     


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