IANNOTTI, PIERLUIGI

IANNOTTI, PIERLUIGI  

Dipartimento di Ingegneria Meccanica e Aerospaziale  

030471  

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Citazione Data di pubblicazione Autori File
A machine learning approach to evaluate the influence of higher-order generalized variables on shell free vibrations / Petrolo, M.; Iannotti, P.; Trombini, M.; Pagani, A.; Carrera, E.. - In: JOURNAL OF SOUND AND VIBRATION. - ISSN 0022-460X. - ELETTRONICO. - 575:(2024). [10.1016/j.jsv.2024.118255] 1-gen-2024 M. PetroloP. IannottiM. TrombiniA. PaganiE. Carrera PITPC_JSV_2024.pdf
Best kinematics for shell finite elements using convolutional neural networks / Petrolo, M.; Iannotti, P.. - In: MECHANICS OF ADVANCED MATERIALS AND STRUCTURES. - ISSN 1537-6532. - ELETTRONICO. - 30:5(2023), pp. 1106-1116. [10.1080/15376494.2022.2111009] 1-gen-2023 M. PetroloP. Iannotti PI_MAMS_2022_revised.pdfPI_MAMS_2023.pdf
Best Theory Diagrams for Laminated Composite Shells Based on Failure Indexes / Petrolo, M.; Iannotti, P.. - In: AEROTECNICA MISSILI & SPAZIO. - ISSN 2524-6968. - ELETTRONICO. - 102:(2023), pp. 199-218. [10.1007/s42496-023-00158-5] 1-gen-2023 M. PetroloP. Iannotti PI_ATMS_2023.pdf
Derivation of Best Theory Diagrams through the use of Failure Indexes / Petrolo, M.; Iannotti, P.; Pagani, A.; Carrera, E.. - ELETTRONICO. - (2023). (Intervento presentato al convegno AIAA SCITECH 2023 Forum tenutosi a National Harbor nel 23-27 January 2023) [10.2514/6.2023-0592]. 1-gen-2023 M. PetroloP. IannottiA. PaganiE. Carrera 6.2023-0592.pdf
Global-local modeling of composite structures through node-dependent kinematics and convolutional neural networks / Petrolo, M.; Iannotti, P.; Trombini, M.; Melis, M.. - (2023). (Intervento presentato al convegno ICCS26 - 26th International Conference on Composite Structures & MECHCOMP8 - 8th International Conference on Mechanics of Composites tenutosi a Porto nel 27-30 June 2023). 1-gen-2023 M. PetroloP. IannottiM. Trombini + ICCS26_proceedings_020723.pdf
Refinement of Structural Theories for Composite Shells through Convolutional Neural Networks / Petrolo, M.; Iannotti, P.; Trombini, M.; Melis, M.. - (2023). (Intervento presentato al convegno 27th Congress of the Italian Association of Aeronautics and Astronautics, AIDAA 2023 tenutosi a Padova nel 4-7 September 2023). 1-gen-2023 M. PetroloP. IannottiM. Trombini + PITM_AIDAA2023_Paper.pdf
Advanced finite elements and neural networks for scaled models / Carrera, E.; Iannotti, P.; Pagani, A.; Petrolo, M.. - ELETTRONICO. - (2022). (Intervento presentato al convegno 9th International Symposium on Scale Modeling tenutosi a Napoli nel 2-4 March 2022). 1-gen-2022 E. CarreraP. IannottiA. PaganiM. Petrolo CARRER_abs.pdf
Local Refinement of Structural Kinematics for Failure Onset Analysis via Neural Networks / Petrolo, M.; Pagani, A.; Iannotti, P.; Carrera, E.. - ELETTRONICO. - (2022). (Intervento presentato al convegno 15th World Congress on Computational Mechanics (WCCM-XV) and 8th Asian Pacific Congress on Computational Mechanics (APCOM-VIII) tenutosi a Yokohama nel 31/07/2022 - 05/08/2022). 1-gen-2022 M. PetroloA. PaganiP. IannottiE. Carrera PPIC_WCCM2022.pdf
On the accuracy and efficiency of convolutional neural networks for element-wise refinement of FEM models / Petrolo, M.; Iannotti, P.; Pagani, A.; Carrera, E.. - ELETTRONICO. - (2022). (Intervento presentato al convegno ASME 2022 International Mechanical Engineering Congress and Exposition IMECE2022 tenutosi a Columbus, Ohio nel 30 October 2022 - 3 November 2022). 1-gen-2022 M. PetroloP. IannottiA. PaganiE. Carrera -