|Language of instruction
After participating in the Multidisciplinary Design Optimization module, students are able to: • understand model-based design tasks as optimization problems; • understand the mathematical principles and optimization algorithms that are essential for use in practice; • select and apply suitable solution algorithms for a given problem; • convert practical model-based design tasks into mathematical optimization tasks; • make a practical implementation of an algorithm and solve a model-based optimization task on the computer; • recognize current research in the field of multidisciplinary optimization.
Introduction to the theory and practice of multidisciplinary design optimization, with examples from different fields of engineering, such as structural mechanics. We aim to answers questions such as: - How can classical design tasks of the engineer be formulated as mathematical optimization tasks and how are they solved using mathematical optimization algorithms? - What characterizes an optimal design and how must the modeling of the design task be formulated in order to find this optimum efficiently? - What is an admissible design and how can it be ensured that the optimization process returns only physically meaningful valid designs? - How can one deal with multiple design goals, which may have conflicts between each other, and multiple disciplines, all of which may influence one another? Fundamentals of mathematical optimization algorithms used to solve such tasks in practice are presented and their interaction with model-based simulation is explained. The learning content of the lecture will be implemented on simplified but still practical examples in the computer exercises.
Basic mathematical and engineering knowledge from basic studies
Teaching and learning methods
The module consists of a lecture and an exercise. In the lecture, the theoretical foundations of Multidisciplinary Design Optimization are taught using lecture, presentation and writing down on tablet PC. Students will be provided with all lecture materials online. In the lecture, the contents are taught, also by means of examples. In the exercises, the contents are deepened and the practical implementation of the theory from the lecture is made comprehensible by means of computer exercises. With this, the students learn to precisely state optimization problems, analytically and computationally solve them and deal with multiple objectives and disciplines.
The module examination takes the form of a written exam (90 min). Said exam is composed of a variety of questions, including multiple choice, calculation questions, and open qualitative questions. Through these tasks, students demonstrate that they understand the main topics of the lecture, such as how to formulate clear optimization problem statements, how optimization algorithms work, and the challenges involved in design optimization with multiple objectives and disciplines. A non-programmable calculator and a one-sided, handwritten DIN-A4 sheet are permitted as aids.
Papalambros, P. Y., Wilde, D.J.: Principles of Optimal Design: Modeling and Computation, 3rd Edition, Cambridge University Press, 2017
|Language of instruction
schedule to be announced in the first lecture