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. 2022/23, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
• Progettazione e fabbricazione additiva per applicazioni aerospaziali. A.A. 2023/24, INGEGNERIA AEROSPAZIALE. Collaboratore del corso
• Strutture aeronautiche. A.A. 2022/23, INGEGNERIA AEROSPAZIALE. Collaboratore del corso

• Iannotti, Pierluigi (2025)
  Development and Assessment of Structural Theories Using Machine Learning Techniques. relatore: PETROLO, MARCO; ZAPPINO, ENRICO; , 37. XXXVII Ciclo, P.: 179
  Doctoral Thesis
• Petrolo, M.; Pagani, A.; Candita, G.; Iannotti, P.; Carrera, E. (2025)
  Assessment of multi-fidelity structural theories for dynamic analyses using machine learning. In: ASME 2025 Aerospace Structures, Structural Dynamics, and Materials Conference SSDM2025, Houston, 5-7 May 2025
  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.; 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)
• 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.; 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)
• Petrolo, M.; Iannotti, P. (2023)
  Best Theory Diagrams for Laminated Composite Shells Based on Failure Indexes. In: AEROTECNICA MISSILI & SPAZIO, vol. 102, pp. 199-218. ISSN 2524-6968
  Contributo su Rivista
• Petrolo, M.; Iannotti, P.; Pagani, A.; Carrera, E. (2023)
  Derivation of Best Theory Diagrams through the use of Failure Indexes. In: AIAA SCITECH 2023 Forum, National Harbor, 23-27 January 2023
  Contributo in Atti di Convegno (Proceeding)
• Petrolo, M.; Iannotti, P.; Trombini, M.; Melis, M. (2023)
  Global-local modeling of composite structures through node-dependent kinematics and convolutional neural networks. In: ICCS26 - 26th International Conference on Composite Structures & MECHCOMP8 - 8th International Conference on Mechanics of Composites, Porto, 27-30 June 2023
  Contributo in Atti di Convegno (Proceeding)
• Petrolo, M.; Iannotti, P. (2023)
  Best kinematics for shell finite elements using convolutional neural networks. In: MECHANICS OF ADVANCED MATERIALS AND STRUCTURES, vol. 30, pp. 1106-1116. ISSN 1537-6532
  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)
• Petrolo, M.; Iannotti, P.; Pagani, A.; Carrera, E. (2022)
  On the accuracy and efficiency of convolutional neural networks for element-wise refinement of FEM models. In: ASME 2022 International Mechanical Engineering Congress and Exposition IMECE2022, Columbus, Ohio, 30 October 2022 - 3 November 2022
  Contributo in Atti di Convegno (Proceeding)
• Petrolo, M.; Pagani, A.; Iannotti, P.; Carrera, E. (2022)
  Local Refinement of Structural Kinematics for Failure Onset Analysis via Neural Networks. In: 15th World Congress on Computational Mechanics (WCCM-XV) and 8th Asian Pacific Congress on Computational Mechanics (APCOM-VIII), Yokohama, 31/07/2022 - 05/08/2022. ISBN: 978-84-123222-8-6
  Contributo in Atti di Convegno (Proceeding)
• Carrera, E.; Iannotti, P.; Pagani, A.; Petrolo, M. (2022)
  Advanced finite elements and neural networks for scaled models. In: 9th International Symposium on Scale Modeling, Napoli, 2-4 March 2022
  Contributo in Atti di Convegno (Proceeding)