ECTS - Structural Optimization
Structural Optimization (CE423) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Structural Optimization | CE423 | 3 | 0 | 0 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| CE 321 Structural Analysis |
| Course Language | English |
|---|---|
| Course Type | N/A |
| Course Level | Bachelor’s Degree (First Cycle) |
| Mode of Delivery | Face To Face |
| Learning and Teaching Strategies | Lecture, Discussion, Question and Answer, Problem Solving. |
| Course Lecturer(s) |
|
| Course Objectives | The objective of this course is to introduce basic concepts of structural optimization. Different types of structural optimization problems will be formulated and solved using various optimization techniques. This course aims to enable the students to use and implement different algorithms for structural optimization. |
| Course Learning Outcomes |
The students who succeeded in this course;
|
| Course Content | Formulation of structural optimization problems, graphical solution procedure, sizing, geometry, and topology optimization, steepest-descent method, Newton?s method, branch and bound method, multi-objective structural optimization, evolutionary algorithms, sensitivity analysis techniques, and practical applications. |
Weekly Subjects and Releated Preparation Studies
| Week | Subjects | Preparation |
|---|---|---|
| 1 | Formulation of Structural Optimization Problems | |
| 2 | Graphical Solution Procedure | |
| 3 | Steepest-Descent Method | |
| 4 | Newton’s Method | |
| 5 | Branch and Bound Method | |
| 6 | Evolutionary Algorithms | |
| 7 | Evolutionary Algorithms | |
| 8 | Evolutionary Algorithms | |
| 9 | Sizing Optimization | |
| 10 | Geometry Optimization | |
| 11 | Topology Optimization | |
| 12 | Sensitivity Analysis Techniques | |
| 13 | Multiobjective Structural Optimization | |
| 14 | Practical Applications | |
| 15 | Final Exam Period | |
| 16 | Final Exam Period |
Sources
| Other Sources | 1. Arora, J.S., Introduction to Optimum Design, Third Edition, Elsevier Academic Press, 2012. |
|---|
Evaluation System
| Requirements | Number | Percentage of Grade |
|---|---|---|
| Attendance/Participation | - | - |
| Laboratory | - | - |
| Application | - | - |
| Field Work | - | - |
| Special Course Internship | - | - |
| Quizzes/Studio Critics | - | - |
| Homework Assignments | - | - |
| Presentation | - | - |
| Project | 1 | 30 |
| Report | - | - |
| Seminar | - | - |
| Midterms Exams/Midterms Jury | 1 | 30 |
| Final Exam/Final Jury | 1 | 40 |
| Toplam | 3 | 100 |
| Percentage of Semester Work | 60 |
|---|---|
| Percentage of Final Work | 40 |
| Total | 100 |
Course Category
| Core Courses | X |
|---|---|
| Major Area Courses | |
| Supportive Courses | |
| Media and Managment Skills Courses | |
| Transferable Skill Courses |
The Relation Between Course Learning Competencies and Program Qualifications
| # | Program Qualifications / Competencies | Level of Contribution | ||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in the solution of complex engineering problems. | |||||
| 2 | Ability to formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose. | |||||
| 3 | Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. | |||||
| 4 | Ability to select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. | |||||
| 5 | Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions. | |||||
| 6 | Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. | |||||
| 7 | Ability to communicate effectively, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Awareness of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. | |||||
| 9 | Knowledge on behavior according ethical principles, professional and ethical responsibility and standards used in engineering practices. | |||||
| 10 | Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. | |||||
| 11 | Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions. | X | ||||
ECTS/Workload Table
| Activities | Number | Duration (Hours) | Total Workload |
|---|---|---|---|
| Course Hours (Including Exam Week: 16 x Total Hours) | 16 | 3 | 48 |
| Laboratory | |||
| Application | |||
| Special Course Internship | |||
| Field Work | |||
| Study Hours Out of Class | 14 | 3 | 42 |
| Presentation/Seminar Prepration | |||
| Project | 1 | 32 | 32 |
| Report | |||
| Homework Assignments | |||
| Quizzes/Studio Critics | |||
| Prepration of Midterm Exams/Midterm Jury | 1 | 13 | 13 |
| Prepration of Final Exams/Final Jury | 1 | 15 | 15 |
| Total Workload | 150 | ||