Multidisciplinary Design Optimization

Introduction to the theory and practice of multidisciplinary design optimization of mechanical structures. 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? Fundamentals of mathematical optimization algorithms used to solve such tasks in practice are presented and their interaction with model-based simulation of the structure's behavior is explained. The learning content of the lecture will be implemented on simplified but still practical examples in the computer exercises.

After participating in the course Multidisciplinary Design Optimisation, students are able to understand model-based design tasks as optimization tasks, have
become familiar with the mathematical principles and solution algorithms essential for practical application and have practiced the implementation of model-based optimization task on the computer. The students learn the importance of the procedure and the form of the conversion of practical model-based design tasks into mathematical optimization tasks as well as the selection and application of suitable solution algorithms and to master them in first approaches. In addition, students gain insight into current research in the field of multidisciplinary design optimization and the challenges of implementing the theory from the lecture in practice.

None (basic studies in mechanical engineering sufficient)

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.

Lecture, presentation, tablet with beamer, online teaching materials, computer exercises.

Papalambros, P. Y., Wilde, D.J.: Principles of Optimal Design: Modeling and Computation, 3rd Edition, Cambridge University Press, 2017

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, 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.