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      FACULTY OF ENGINEERING

      Department of Mechatronics Engineering

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      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
      • Öğr. Gör. Dr. Musa Özgün Güleç
      Course Lecturer(s)
      • Öğr. Gör. Dr. Musa Özgün Güleç
      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
      1Define an optimization problem with the objective function and related constraints (equality and/or inequality) in the standard form.2x
      2Solve constrained and/or unconstrained optimization problems using analytical methods and graphical approaches. 1.6x
      3Solve linear optimization problems with linear programming method. 1.6x
      4Determine the numerical solution of a constrained and/or unconstrained optimization problem using conventional search techniques using MATLAB/Octave (or other tools and programming languages).1.4x
      5Solve an optimization problem using modern search techniques / evolutionary algorithms. 1.4x
      Course Description This course will cover the place and importance of optimization in engineering, basic definitions and facts about optimization problems, analytical and graphical solutions to linear, nonlinear, constrained, and unconstrained optimization problems, and solutions to optimization problems using conventional and modern/evolutionary search techniques.
      Related Sustainable Development Goals

       



      Course Category

      Core Courses
      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 optimization, its place in engineering, basic definitions, and facts. Textbook 1: Chapter 1
      2 Analytical solutions of unconstrained optimization problems Textbook 1: Chapter 4
      3 Analytical solutions of equality constrained optimization problems Textbook 1: Chapter 4
      4 Analytical solutions of inequality constrained optimization problems Textbook 1: Chapter 4
      5 Solving optimization problems with the graphical method. Textbook 1: Chapter 3
      6 Convex problems Textbook 1: Chapter 4
      7 Linear Programming Textbook 1: Chapter 8
      8 Midterm Exam
      9 Conventional numerical methods for one-dimensional optimization problems Textbook 2: Chapter 5
      10 Conventional numerical methods for one-dimensional optimization problems Textbook 2: Chapter 5
      11 Conventional numerical methods for multidimensional optimization problems Textbook 2: Chapter 6
      12 Conventional numerical methods for multidimensional optimization problems Textbook 2: Chapter 6
      13 Solving optimization problems via evolutionary algorithms Textbook 2: Chapter 13
      14 Solving optimization problems via evolutionary algorithms Textbook 2: Chapter 13
      15 Course review
      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.
      Suggested Readings/Materials

      Numerical Methods for Engineers. Seventh Edition, McGraw-Hill, 2018. ISBN 978-0-07-339796-2

       

      EVALUATION SYSTEM

      Semester Activities Number Weigthing LO 1 LO 2 LO 3 LO 4 LO 5
      Participation
      Laboratory / Application
      Field Work
      Quizzes / Studio Critiques
      1
      15
      XX
      Portfolio
      Homework / Assignments
      1
      15
      XX
      Presentation / Jury
      Project
      Seminar / Workshop
      Oral Exams
      Midterm
      1
      30
      XXX
      Final Exam
      1
      40
      XXXXX
      Total
      33222

      Weighting of Semester Activities on the Final Grade
      3
      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
      2
      28
      Field Work
      0
      Quizzes / Studio Critiques
      1
      22
      22
      Portfolio
      0
      Homework / Assignments
      1
      22
      22
      Presentation / Jury
      0
      Project
      0
      Seminar / Workshop
      0
      Oral Exam
      0
      Midterms
      1
      26
      26
      Final Exam
      1
      34
      34
          Total
      180

       

      COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

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

      To have knowledge in Mathematics, science, physics knowledge based on mathematics; mathematics with multiple variables, differential equations, statistics, optimization and linear algebra; to be able to use theoretical and applied knowledge in complex engineering problems

      -
      -
      -
      -
      -
      2

      To be able to identify, define, formulate, and solve complex mechatronics engineering problems; to be able to select and apply appropriate analysis and modeling methods for this purpose.

      -
      -
      -
      X
      -
      3

      To be able to design a complex electromechanical system, process, device or product with sensor, actuator, control, hardware, and software to meet specific requirements under realistic constraints and conditions; to be able to apply modern design methods for this purpose.

      -
      -
      -
      -
      -
      4

      To be able to develop, select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in Mechatronics Engineering applications; to be able to use information technologies effectively.

      -
      -
      -
      X
      -
      5

      To be able to design, conduct experiments, collect data, analyze and interpret results for investigating Mechatronics Engineering problems.

      -
      -
      -
      -
      -
      6

      To be able to work effectively in Mechatronics Engineering disciplinary and multidisciplinary teams; to be able to work individually.

      -
      -
      -
      -
      -
      7

      To be able to communicate effectively in Turkish, both in oral and written forms; 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; information on standards used 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

      Using a foreign language, he collects information about Mechatronics Engineering and communicates with his colleagues. ("European Language Portfolio Global Scale", Level B1)

      -
      -
      -
      -
      -
      12

      To be able to use the second foreign language at intermediate level.

      -
      -
      -
      -
      -
      13

      To recognize the need for lifelong learning; to be able to access information; to be able to follow developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Mechatronics Engineering.

      -
      -
      -
      -
      -

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


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