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Multidisciplinary Design Optimization

MW0085
Mechanical Engineering

About this course

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.

Learning outcomes

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.

Examination

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.

Course requirements

None (basic studies in mechanical engineering sufficient)

Resources

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

Activities

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.

Additional information

  • Credits
    ECTS 5
  • Contact hours per week
    2
  • Instructors
    Nicola Barthelmes, Horst Baier, Erich Wehrle, Johannes Achleitner, Rilian Shao, Sebastian Rötzer, Lukas Krischer, Ögmundur Petersson, Bernhard Sauerer, Tanut Ungwattanapanit, Mirko Hornung, Eduardo Rodrigues Della Noce, Systemadministrator, Tobias Wanninger, Andela Babaja, Markus Zimmermann, Jintin Frank, Akhil Sathuluri
  • Mode of instruction
    Hybrid
If anything remains unclear, please check the FAQ of TUM (Germany).

Offering(s)

  • Start date

    25 April 2025

    • Ends
      25 July 2025
    • Term *
      Summer 2025
    • Instruction language
    • Register between
      6 Jan - 20 Jan 2025
    Enrolment starts in 11 days
These offerings are valid for students of TalTech (Estonia)