Biblio

Found 35 results
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Artificial Neural Networks
Checcucci M, Sazzini F, Marconcini M, Arnone A, Coneri M, De Franco L, Toselli M.  2011.  Assessment of a Neural-Network-Based Optimization Tool: a Low Specific-Speed Impeller Application. International Journal of Rotating Machinery. 2011:1-11.
Agnolucci A, Marconcini M, Arnone A, Toni L, Grimaldi A, Giachi M.  2021.  Centrifugal Compressor Stage Efficiency and Rotor Stiffness Augmentation via Artificial Neural Networks. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 2D: Turbomachinery: Radial Turbomachinery Aerodynamics
ASME paper GT2021-59998
Compressors
Agnolucci A, Marconcini M, Arnone A, Toni L, Grimaldi A, Giachi M.  2021.  Centrifugal Compressor Stage Efficiency and Rotor Stiffness Augmentation via Artificial Neural Networks. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 2D: Turbomachinery: Radial Turbomachinery Aerodynamics
ASME paper GT2021-59998
computational methods
Pinelli L, Poli F, Arnone A, Guérin S, Holewa A, Aparicio JRFernán, Puente R, Torzo D, Favre C, Gaetani P et al..  2015.  On the Numerical Evaluation of Tone Noise Emissions Generated by a Turbine Stage: an In-Depth Comparison Among Different Computational Methods. ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. 2B: Turbomachinery
ASME paper GT2015-42376
Contra-Rotating Turbine
Pinelli L, Poli F, Marconcini M, Arnone A, Schipani C, Spano E, Torzo D.  2011.  A Linearized Method for Tone Noise Generation and Propagation Analysis in a Multistage Contra-Rotating Turbine. 9th European Turbomachinery Conference (ETC9). :1253–1263.
Istanbul, Turkey, 21-25 March 2011
Design
Burberi C, Michelassi V, Scotti Del Greco A, Lorusso S, Tapinassi L, Marconcini M, Pacciani R.  2020.  Validation of Steady and Unsteady CFD Strategies in the Design of Axial Compressors for Gas Turbine Engines. Aerospace Science and Technology. 107:106307.
Agnolucci A, Marconcini M, Arnone A, Toni L, Grimaldi A, Giachi M.  2021.  Centrifugal Compressor Stage Efficiency and Rotor Stiffness Augmentation via Artificial Neural Networks. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 2D: Turbomachinery: Radial Turbomachinery Aerodynamics
ASME paper GT2021-59998
Diffusers
Agnolucci A, Marconcini M, Arnone A, Toni L, Grimaldi A, Giachi M.  2021.  Centrifugal Compressor Stage Efficiency and Rotor Stiffness Augmentation via Artificial Neural Networks. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 2D: Turbomachinery: Radial Turbomachinery Aerodynamics
ASME paper GT2021-59998
Impellers
Agnolucci A, Marconcini M, Arnone A, Toni L, Grimaldi A, Giachi M.  2021.  Centrifugal Compressor Stage Efficiency and Rotor Stiffness Augmentation via Artificial Neural Networks. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 2D: Turbomachinery: Radial Turbomachinery Aerodynamics
ASME paper GT2021-59998
LPT
Pinelli L, Poli F, Di Grazia E, Arnone A, Torzo D.  2013.  A Comprehensive Numerical Study of Tone Noise Emissions in a Multistage Cold Flow Rig. 19th AIAA/CEAS Aeroacoustics Conference (34th AIAA Aeroacoustics Conference), 27-29 May.
AIAA paper 2013-2104
Noise Propagation
Pinelli L, Poli F, Marconcini M, Arnone A, Schipani C, Spano E, Torzo D.  2011.  A Linearized Method for Tone Noise Generation and Propagation Analysis in a Multistage Contra-Rotating Turbine. 9th European Turbomachinery Conference (ETC9). :1253–1263.
Istanbul, Turkey, 21-25 March 2011
Optimization
Checcucci M, Sazzini F, Marconcini M, Arnone A, Coneri M, De Franco L, Toselli M.  2011.  Assessment of a Neural-Network-Based Optimization Tool: a Low Specific-Speed Impeller Application. International Journal of Rotating Machinery. 2011:1-11.
Agnolucci A, Marconcini M, Arnone A, Toni L, Grimaldi A, Giachi M.  2021.  Centrifugal Compressor Stage Efficiency and Rotor Stiffness Augmentation via Artificial Neural Networks. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 2D: Turbomachinery: Radial Turbomachinery Aerodynamics
ASME paper GT2021-59998

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