ECTS - Structural Optimization
Structural Optimization (CE423) Course Detail
| Course Name | Course Code | Season | Lecture Hours | Application Hours | Lab Hours | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| Structural Optimization | CE423 | Area Elective | 3 | 0 | 0 | 3 | 6 |
| Pre-requisite Course(s) |
|---|
| CE321 |
| Course Language | English |
|---|---|
| Course Type | Elective Courses |
| 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 | Gains adequate knowledge in mathematics, science, and relevant engineering disciplines and acquires the ability to use theoretical and applied knowledge in these fields to solve complex engineering problems. | |||||
| 2 | Gains the ability to identify, formulate, and solve complex engineering problems and the ability to select and apply appropriate analysis and modeling methods for this purpose. | |||||
| 3 | Gains the ability to design a complex system, process, device, or product under realistic constraints and conditions to meet specific requirements and to apply modern design methods for this purpose. | |||||
| 4 | Gains the ability to select and use modern techniques and tools necessary for the analysis and solution of complex engineering problems encountered in engineering applications and the ability to use information technologies effectively. | |||||
| 5 | Gains the ability to design experiments, conduct experiments, collect data, analyze results, and interpret findings for investigating complex engineering problems or discipline specific research questions. | |||||
| 6 | Gains the ability to work effectively in intra-disciplinary and multi-disciplinary teams and the ability to work individually. | |||||
| 7 | Gains the ability to communicate effectively in written and oral form, acquires proficiency in at least one foreign language, the ability to write effective reports and understand written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. | |||||
| 8 | Gains awareness of the need for lifelong learning and the ability to access information, follow developments in science and technology, and to continue to educate him/herself | |||||
| 9 | Gains knowledge about behaviour in accordance with ethical principles, professional and ethical responsibility and standards used in engineering applications | |||||
| 10 | Gains knowledge about business practices such as project management, risk management, and change management and develops awareness of entrepreneurship, innovation, and sustainable development. | |||||
| 11 | Gains 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 | ||