Ph.D. candidate in Ingegneria Meccanica , 37th cycle (2021-2024)
Department of Mechanical and Aerospace Engineering (DIMEAS)
Profile
PhD
Thesis title
Advanced Numerical Models and Optimization for the Analysis of Structures Made of Innovative Materials
Tutors
Teaching
Teachings
Master of Science
- Sperimentazione su strutture aerospaziali/Tecnologie aerospaziali (modulo di Tecnologie aerospaziali). A.A. 2023/24, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
- Progettazione e fabbricazione additiva per applicazioni aerospaziali. A.A. 2023/24, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
- Progettazione e fabbricazione additiva per applicazioni aerospaziali. A.A. 2022/23, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
- Strutture aeronautiche. A.A. 2022/23, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
Publications
Latest publications View all publications in Porto@Iris
- Petrolo, M.; Pagani, A.; Carrera, E.; Iannotti, P.; Candita, G. (2024)
Synergistic Use of CUF and Machine Learning for Structural Mechanics Problems. In: Fourth International Congress on Mechanics of Advanced Materials and Structures - ICMAMS, Bengaluru, India, 11-13 December 2024
Contributo in Atti di Convegno (Proceeding) - Petrolo, M.; Iannotti, P.; Pagani, A.; Carrera, E. (2024)
Selection of beam, plate, and shell theories using an axiomatic/asymptotic method and neural networks. In: ASME 2024 Aerospace Structures, Structural Dynamics, and Materials Conference SSDM2024 April 29 - May 1, 2024, Renton, Washington, Renton, WA, USA, 29 April - 1 May 2024
Contributo in Atti di Convegno (Proceeding) - Iannotti, P. (2024)
Selection of best beam theories based on natural frequencies and dynamic response obtained through mode superposition method. In: IV Aerospace PhD-Days, Scopello, Italy, 6-9th of May 2024, pp. 5-9
Contributo in Atti di Convegno (Proceeding) - Petrolo, M.; Iannotti, P.; Trombini, M.; Pagani, A.; Carrera, E. (2024)
A machine learning approach to evaluate the influence of higher-order generalized variables on shell free vibrations. In: JOURNAL OF SOUND AND VIBRATION, vol. 575. ISSN 0022-460X
Contributo su Rivista - Petrolo, M.; Iannotti, P.; Trombini, M.; Melis, M. (2023)
Refinement of Structural Theories for Composite Shells through Convolutional Neural Networks. In: 27th Congress of the Italian Association of Aeronautics and Astronautics, AIDAA 2023, Padova, 4-7 September 2023
Contributo in Atti di Convegno (Proceeding)