Biblio

Found 265 results
Author [ Keyword(Desc)] Type Year
Filters: Author is Michele Marconcini  [Clear All Filters]
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High Lift
Marconcini M, Rubechini F, Pacciani R, Arnone A, Bertini F.  2012.  Redesign of High-Lift Low Pressure Turbine Airfoils For Low Speed Testing. ASME Journal of Turbomachinery. 134(5):051017.
Pacciani R, Marconcini M, Arnone A, Bertini F.  2011.  An Assessment of the Laminar Kinetic Energy Concept for the Prediction of High-Lift, Low-Reynolds Number Cascade Flows. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy. 225(7):995-1003.
winner of 2011 SAGE Best Paper Award (JPE) http://pia.sagepub.com/cgi/collection/2011
Pacciani R, Marconcini M, Fadai-Ghotbi A, Lardeau S, Leschziner MA.  2011.  Calculation of High-Lift Cascades in Low Pressure Turbine Conditions Using a Three-Equation Model. ASME Journal of Turbomachinery. 133(3):031016.
Pacciani R, Marconcini M, Arnone A, Bertini F.  2012.  URANS Analysis of Wake-Induced Effects in High-Lift, Low Reynolds Number Cascade Flows. ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. 8: Turbomachinery, Parts A, B, and C:1521-1530.
ASME paper GT2012-69479.
Pacciani R, Marconcini M, Arnone A, Bertini F.  2014.  Predicting High-Lift Low-Pressure Turbine Cascades Flows Using Transition-Sensitive Turbulence Closures. ASME Journal of Turbomachinery. 136(5):051007.
High-performance computing
Savio P, Scionti A, Vitali G, Viviani P, Vercellino C, Terzo O, Nguyen H-N, Magarielli D, Spano E, Marconcini M et al..  2023.  Accelerating Legacy Applications with Spatial Computing Devices. Journal of Supercomputing. 79:7461–7483.
Hill Chart
Arnone A, Marconcini M, Rubechini F, Schneider A, Alba G.  2009.  Kaplan Turbine Performance Prediction Using CFD: an Artificial Neural Network Approach. HYDRO 2009 Conference Proceedings.
Lyon, France, 26-28 October 2009, paper n.263
HP turbine
Burberi C, Ghignoni E, Pinelli L, Marconcini M.  2018.  Numerical Analysis of Direct and Indirect Noise Produced by a High Pressure Turbine Stage. ATI 2018 - 73rd Conference of the Italian Thermal Machines Engineering Association. Energy Procedia 148:130-137.
hydrogen
Bandini A, Bettini C, Peruzzi L, Caretta M, Canelli C, Marconcini M, Pinelli L, Arnone A.  2024.  Targeting Full-Hydrogen Operation on Industrial-Scale Gas Turbines: Impact of Unconventional Fuels on Turbine Module Performance and Aeromechanics. ASME Turbo Expo 2024 Turbomachinery Technical Conference and Exposition. Volume 12B: Turbomachinery:V12BT30A043.
GT2024-128743 (accepted for publication on ASME Journal of Turbomachinery)
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
Kacker-Okapuu
Bertini F, Ampellio E, Marconcini M, Giovannini M.  2013.  A Critical Numerical Review of Loss Correlation Models and Smith Diagram for Modern Low Pressure Turbine Stages. ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. 6B: Turbomachinery:V06BT37A018-;14pages.
ASME paper GT2013-94849
Kaplan Turbine
Arnone A, Marconcini M, Rubechini F, Schneider A, Alba G.  2009.  Kaplan Turbine Performance Prediction Using CFD: an Artificial Neural Network Approach. HYDRO 2009 Conference Proceedings.
Lyon, France, 26-28 October 2009, paper n.263

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