Course syllabus
Course-PM
PPU191 Engineering design and optimization lp1 HT20 (7.5 hp). The course is offered by the Department of Industrial and Materials Science
Course purpose
The course aims at integrating traditional design methodologies with concepts and techniques of modern optimization theory and practice. With the approach and instilled knowledge, the students are expected to create design solutions that are creative and have better performance than traditional conservative methods. Furthermore, the course aims to:
- Demonstrate a selection of different tools and methods for optimization of mechanical products and structures
- Design for improvement of components in products and mechanical systems by bridging detailed design and creative side of the design process in a systematic way
- Demonstrate the iterative nature of the development chain including modeling-analysis-test
- Use and familiarize students with modern CAE tools
- Incorporate material selection as a part of the product development process
Learning objectives
- Master the complete development chain including modeling-analyses-test-evaluation
- Identify areas for improvement in a product design
- Identify and choose appropriate material alternatives based on product requirements
- Apply previously-learned design methods and tools to practical problems
- Create appropriate simulation models of the design problem
- Use Computer-Aided Engineering (CAE) tools to design and simulate product performance
- Apply previous knowledge in mathematics and mechanics to formulate and solve optimization problems.
- Formulate design optimization problems based on project or product requirements
- Apply numerical optimization techniques and computer tools to solve optimization problems
- Assessing the advantages, and disadvantages of different based algorithms based on the optimization problem
- Interpret optimization results for design decision making (e.g., material selection, geometry, manufacturing, production)
- Create CAE drawings for use with three-dimensional printing tools
- Understand the possibilities and limitations of different manufacturing techniques when it comes to optimal design, such as obtained with topology optimization
- Create and Iterate on design solutions to continually improve a product's design and performance
- Communicate design solutions, including rationales for a given choice, advantages, and disadvantages over alternatives
Prerequisites
- CAD
- Machine Elements, Applied Mechanics, or similar
- FEM
- Programming (Matlab)
- Material science
- Manufacturing technology
- Mechanics
- Solid mechanics
Course evaluation committee
MPAUT nymax@student.chalmers.se Max Nylund
MPPDE honkala@student.chalmers.se Albin Andersson Honkala
MPPDE thimj@student.chalmers.se Thim Johansson
MPAUT rahis@student.chalmers.se Simon Tsobanoglou
MPPDE simwas@student.chalmers.se Simon Wassenius
Schedule
Course design
Lectures: The course is divided into 16 lectures over the course of 8 weeks. Project assignments will reinforce the lecture material through design tasks that reflect the content of the lectures leading up to them. The lecture topics are as follows:
Lecture | Topic(s) | Lecturer(s) |
1 | Course intro & general engineering approach | GA |
2 | Applied mechanics 1 | HJ |
3 | Introduction to optimization | GA |
4 | Modelling | GA |
5 | Optimization algorithms & tools 1 | GA |
6 | Optimization algorithms & tools 2 | GA |
7 | Applied mechanics 2 | HJ |
8 | Material selection in Design | CP |
9 | Optimization algorithms & tools 3 | GA |
10 | Concept & Embodiment Design | GA |
11 | Multi-obj. Optimization & trade-off analysis | GA |
12 | Additive manufacturing | EH |
13 | Quality & uncertainty management | GA |
14 | Multi Syst. Optimization (MSO) | KB |
15 | Applied mechanics 3 | HJ |
16 | Course recap | GA |
Guest Lectures: Three guest lectures from the industry are scheduled and will be held online. Mandatory to attend and reflect on two out of three guest lectures.
X1 – Topology optimization in automotive, Harald Hasselblad, VCC
X2 – Optimization in practice, Petter Andersson, GKN
X3 – COMSOL Multiphysics, Johan Potrus/Björn Bragée COMSOL
Workshops - Flipped classroom -There will be scheduled workshops to reinforce concepts and introduce software from the lectures under supervision. Some of the workshops will be used for supervision and are therefore intentionally left blank in the schedule.
- Applied Optimization - Ansys
- Optimization using MATLAB
- Metamodeling –DoE – The Helicopter I+II
- Material Selection with CES
- MOO using MATLAB
- Robustness and Reliability using MATLAB
- Optimization Examples
Project Assignments: There will be three project assignments throughout the course focusing on the later stages of design. In the assignments, students will work in groups of two (pairs). To achieve positive cross-over effects, students in a group should be enrolled in different MSc programs.
PA 1 - The Cantilever Challenge
Design, build and test a cantilever beam over two iterations ending with a live competition. Who will achieve the highest performance and win the challenge?
PA 2 – Materials selection and design optimization
Optimization of a bicycle frame considering material selection and embodiment of a design
PA 3 – MOO - Multi-Objective Optimization
Design, simulation, and optimization of a multidisciplinary system using Multi-Objective Optimization
Changes made since the last occasion
The lecture format of the core lectures has been changed to include more interactive discussions. The course format is a hybrid course (Online and Physical). One lecture has been changed out - Composites and is replaced by Optimizatization Algorithm III. Additional workshop for robustness and reliability is added.
Course literature
The main literature in the course is the Principle of optimal design, which is available at Chalmers Store
- Papalambros & Wilde: Principles of Optimal Design, 3nd Edition. 2000 ISBN 0-521-62727-3
Additional sources include:
- Christensen & Klarbring: An Introduction to Structural Optimization, 2009. Available as an e-book through Chalmers library
- Bendsoe & Sigmund: Topology Optimization: Theory, Methods, and Applications, 2004. Available as an e-book through Chalmers library
- Selected research articles - provided on Canvas
Location
Lectures will primarily be held in both virtual and physical setup (See Zoom link on Canvas). Workshops and computer exercises will usually be located in SB-D409 (Arch.), ES62, 63 (Edit) and SAL A (Vasa). Some lectures and workshops will change location due to the feasibility of the activity. Such changes will be communicated via Canvas, during lectures as well as via email.
Examination form
The examination is based on four parts
- Written final exam (Grade 5, 4, 3, Fail): One written examination, covering all the theory and material from the lectures, guest lectures, recommended readings and workshops.
- Midterm exam (bonus points for the exam) - Online in Canvas
- Three approved assignments (Pass/Fail)
- Attended compulsory guest lectures and write a short reflection (bonus points for the exam).
Each assignment is graded on a scale of (not passed/passed). The projects will be worth 3 credits (1,1,1) of the student’s individual course grade, and the exams will be worth 4.5 credits. Bonus credits from the midterm exam and Guest Lecture (if such is given) are valid for the first regular examination. If students are not able to attend and review two out of three compulsory guest lectures, a complimentary review will be assigned.
Contact details
The organization of the course is as follows:
Dr. Gauti Asbjörnsson
Examiner, lecturer
gauti@chalmers.se
Kanishk Bhadani
Course Supervisor
kanishk@chalmers.se
Vasanth Kumar
Course administration & supervisor
kumarva@chalmers.se
Dr. Håkan Johansson
Lecturer
hakan.johansson@chalmers.se
Prof. Christer Persson
Lecturer
christer.persson@chalmers.se
Prof. Eduard Hryha
Lecturer
hryha@chalmers.se
Dr. Harald Hasselblad, VCC
Guest lecturer
harald.hasselblad@volvocars.com
Petter Andersson, GKN
Guest lecturer
petter.andersson@gknaerospace.com
Johan Potrus, Comsol
Guest lecturer
johan.potrus@comsol.se
Course summary:
Date | Details | Due |
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