The educational objective of the course is to provide students with the knowledge for managing the design of complex engineering systems.
- Knowledge and understanding: At the end of the course, the student will have to know the methodologies with which to tackle multidisciplinary design problems in a systematic way.
- Ability to apply knowledge and understanding: The student must be able to solve a complex and multidisciplinary design case using numerical technologies based on optimization.
- Making judgements: The student must be able to identify the best design methodologies through optimization
- Communication skills: The student must be able to describe what he has learned with language properties.
- Learning skills: The student must be able to interpret and use technologies for the design of complex engineering systems.

Corse of Numerical Methods for Enginering Design

The course intends to give the skills for the management of complex projects in a multidisciplinary field.
Starting from the concept of MDO (Multi Disciplinary Optimization), the methodologies studied during the course of Foundations and Methods for design will be revisited with particular regard to the interaction between different disciplines within the design phase of complex systems.

Lecturer's notes

The course aims to offer advanced numerical and management methods for design in a multi-disciplinary field (Knowledge and understanding).
Starting from the concept of CAO (Computer Aided Optimization), the course will deepen the methodologies of Project Management in the Multi-Disciplinary field, observing both the methodologies of management of vertical teams on single engineering disciplines and the most advanced numerical methodologies for the search for optimal solutions.
The course is mainly structured on three thematic areas: concept of multi-disciplinary optimization, computerized and team management, in-depth study of numerical methods of CAO.

The exercises, carried out with the help of industrial software, are aimed at a design study agreed with working groups of 2 or 3 students (Applied knowledge and understanding and Autonomy of judgment and Communication skills).


Thematic areas:
- MDO (Multi Disciplinary Optimization)
- Process MDO
- Mudules in MDO;
- Teams and data management in MDO
- Collaborative and multi level optimization
- Self Organizing Maps
- Algorthm Particle Swarm
- Topologic Optimization
- Adjoint method
- Polynomial Chaos
- Multi fidelity

Classical lectures plus team work for the design project.

Oral examination and discussion of the team work project

This course explores topics closely related to one or more goals of the United Nations 2030 Agenda for Sustainable Development (SDGs)