- Docente responsabile
- LUCA LOMAZZI
- CCS proponenti
- Ingegneria Aerospaziale
- CFU
- 4
- Ore in presenza
- 60
- Prerequisiti
- Basic knowledge of structural engineering and introductory programming skills in MATLAB or similar languages are required.
Before the in-person sessions, online learning materials will be made available and short live sessions will be held online to provide fundamental concepts on numerical simulations, machine learning techniques, and dynamic loading conditions, in order to align the background level of all participants. - N° max studenti
- 8
- Criteri di selezione
- Priority will be given to PhD candidates (any specialization) and students enrolled in Mechanical Engineering or Aeronautical/Space Engineering programmes.
Candidates must include a 'Motivational Letter' text box in the PiA application form. If possible, the letter should not exceed 4,500 characters, including spaces. - Parole chiave:
- Artificial Intelligence, Deep Learning, Structural Design, numerical simulations
- Tag
- Computer science, Engineering, Artificial intelligence, Materials, Structures
Descrizione dell'iniziativa
Deep Learning–Driven Design under Dynamic Loads
Course description
This blended intensive course provides MSc and early-stage PhD students with the knowledge and tools to design lightweight structures capable of withstanding highly dynamic loads. The activity combines physical understanding of dynamic behavior and Fluid–Structure Interaction (FSI) with Deep Learning (DL) techniques for surrogate modeling and structural design. Students will learn how to (i) quantify the influence of FSI on shock-loaded structures and (ii) generate lattice-based metamaterials optimized for energy absorption.
Teaching methods and tools
The course adopts a flipped and challenge-based learning approach. Students first complete online micro-lectures and short live sessions to build a common background in Finite Element simulations, deep learning, and dynamic material behavior.
A five-day in-person session at Politecnico di Milano includes focused international lectures, hands-on workshops, and a team challenge involving data-driven structural design and rapid prototyping of lattice metamaterials using 3D printing.
A two-day follow-up seminar series at NTNU features international keynotes on AI and metamaterials, AI and blast loading, and PhD short talks from both institutions, fostering cross-university collaboration. All sessions are also streamed online.
Innovative aspects
The initiative promotes innovation through:
- Integration of physics-based and AI-driven modeling approaches.
- Application of DL to both FSI surrogate modeling and lattice structures design.
- Hands-on making sessions for physical validation.
- International co-teaching and peer learning between students from different universities.
Assessment criteria
Evaluation is based on:
- Participation and engagement (20%)
- Team challenge: technical pitch and report (50%)
- Follow-up activities: short scientific reflection and discussion contribution (30%)
For further information on the Learning Objectives, please refer to the attached document.
Periodo di svolgimento
dal April 2026 a June 2026
Calendario
Sessione Online
Quattro sessioni online di due ore ciascuna, da erogare prima dell'inizio del corso: 7/04, 9/04, 14/04, 16/04: dalle ore 14.00 alle 16.00
Sessione a Milano
Tutti i giorni da lunedì 20/04/2026 a venerdì 24/04/2026. La sessione sarà dalle 09:00 alle 18:00
Sessione a Trondheim
Giugno 23-24 - dalle 09:00 alle 16:00