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 | Lecture Notes |
| 2 | Graphical Solution Procedure | Lecture Notes |
| 3 | Steepest-Descent Method | Lecture Notes |
| 4 | Newton’s Method | Lecture Notes |
| 5 | Branch and Bound Method | Lecture Notes |
| 6 | Evolutionary Algorithms | Lecture Notes |
| 7 | Evolutionary Algorithms | Lecture Notes |
| 8 | Evolutionary Algorithms | Lecture Notes |
| 9 | Sizing Optimization | Lecture Notes |
| 10 | Geometry Optimization | Lecture Notes |
| 11 | Topology Optimization | Lecture Notes |
| 12 | Sensitivity Analysis Techniques | Lecture Notes |
| 13 | Multiobjective Structural Optimization | Lecture Notes |
| 14 | Multi-objective Structural Optimization | Lecture Notes |
| 15 | Practical Applications | |
| 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 | Engineering Knowledge: Knowledge of mathematics, science, fundamental engineering, computational sciences, and related engineering disciplines; the ability to apply this knowledge to solve complex engineering problems. | |||||
| 2 | Problem Analysis: The ability to identify, formulate, and analyze complex engineering problems using fundamental scientific, mathematical, and engineering knowledge, considering the relevant UN Sustainable Development Goals. | |||||
| 3 | Engineering Design: The ability to design creative solutions to complex engineering problems; the ability to design complex systems, processes, devices, or products to meet current and future requirements, considering realistic constraints and conditions. | |||||
| 4 | Techniques and Tool Usage: The ability to select and use appropriate techniques, resources, and modern engineering and computing tools, including estimation and modeling, for the analysis and solution of complex engineering problems, while being aware of their limitations. | |||||
| 5 | Research and Investigation: The ability to use research methods, including literature review, designing experiments, conducting experiments, collecting data, analyzing and interpreting results, to investigate complex engineering problems. | |||||
| 6 | Global Impact of Engineering Applications: Information about the impacts of engineering applications on society, health and safety, the economy, sustainability and the environment within the framework of the UN Sustainable Development Goals; awareness of the legal consequences of engineering solutions. | X | ||||
| 7 | Engineering Ethics: Knowledge of ethical responsibility and adherence to engineering professional principles; awareness of impartiality, lack of discrimination, and inclusivity. | |||||
| 8 | Individual and Teamwork: The ability to work effectively individually and as a team member or leader in interdisciplinary and multidisciplinary teams (face-to-face, on-line, or hybrid). | |||||
| 9 | Oral and Written Communication: The ability to communicate effectively orally and in writing on technical topics, considering the diverse differences of the target audience (education, language, profession, etc.). | |||||
| 10 | Project Management: Knowledge of business practices such as project management and economic feasibility analysis; awareness of entrepreneurship and innovation. | |||||
| 11 | Lifelong Learning: The ability to learn independently and continuously, adapt to new and emerging technologies, and think critically about technological change. | |||||
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 | ||