The scope of this course is an optimal design for Engineering Design. This course is composed of three parts. The first one
lectures on modeling and computational principles of an optimal design. Several optimization methods are described in the
second topics including CAX technologies. The last one exercises optimization and presentation for a pasta bridge competition.
To acquire the thinking process, the theory, and methods of optimal design which combined CAE and optimization technologies
- Can translate a design problem into optimization problems
- Can understand optimization methodologies
- Can apply an optimization algorithm
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1． | Orientation and interview of your study plans | Writing up your study plan related to an optimal design | 60minutes |
| 2． | Translating design problem into optimization problems | The brush up about a linear programming method | 120minutes |
| 3． | Translating constraint conditions into penalty functions | The brush up about translation of a design problem | 120minutes |
| 4． | Definition of optimal design for pasta bridge competition | Checking the specification for pasta bridge competition | 120minutes |
| The definition of optimization problem for pasta bridge competition | 240minutes | ||
| 5． | Presentation and discussion for pasta bridge definitions | Making of the presentation document | 120minutes |
| 6． | Basic algorithms derived from optimality conditions—Gradient method | Seeing about Gradient method and SLP | 60minutes |
| 7． | Non-linear optimization algorithm—SQP method | Seeing about SQP method | 60minutes |
| Reporting HJ method as a direct algorithm | 120minutes | ||
| 8． | Soft computing method for Multi-peak problems—SA method | Seeing about SA | 90minutes |
| 9． | Evolutional algorithm for Multi-peak problems—GA method | Seeing about GA | 90minutes |
| 10． | Approximation method for optimal design—RSM | Seeing about RSM | 90minutes |
| 11． | Optimal design for pasta bridge competition (definition step) | The brush up about definition of the optimization problem with constraint functions | 120minutes |
| Creating your optimization algorithm | 240minutes | ||
| 12． | Optimal design for paste bridge competition (optimization step) | The brush up about optimization approach to use | 120minutes |
| Creating your optimization algorithm | 240minutes | ||
| 13． | Optimal design for paste bridge competition (validation step) | Applying your optimization algorithm to Pasta Bridge design problem, and estimation of optimization result | 240minutes |
| Making Pasta Bridge | 180minutes | ||
| 14． | Presentation and discussion for your optimal designs | Making Pasta Bridge | 120minutes |
| Making final presentation material | 120minutes | ||
| Total. | - | - | 2670minutes |
| Problem definition | HJ method report | Presentation material | Optimal design solution | Total. | |
|---|---|---|---|---|---|
| 1. | 25% | 25% | |||
| 2. | 25% | 25% | |||
| 3. | 25% | 25% | 50% | ||
| 4. | 0% | ||||
| Total. | 25% | 25% | 25% | 25% | - |
Depending the design review of optimization definition (25%), HJ method report (25%), final presentation (25%), and optimal
design solution (25%). If proposed optimal design, satisfied the design specification for pasta bridge competition, is performed
by using your optimization method systematically, and also the HJ report can describe the reason clearly, those outcomes will
be evaluated as 80%.
K. Kawamo, M. Yokoyama and H. Hasegawa, Fundamentals and Applications of Optimization Theory (in Japanese) (2000), Corona
Publishing Co. LTD.
| Work experience | Work experience and relevance to the course content if applicatable |
|---|---|
| Applicatable | To perform syllabus planning based on experience and needs of our company period, and setting an exercise problem to obtain CAE and optimization technical ability. |
Last modified : Thu Mar 21 15:32:35 JST 2019