Biblio

Found 407 results
Author [ Keyword(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
LKE
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.
Laminar-turbulent multi-mode transition
Pacciani R, Fang Y, Metti L, Marconcini M, Sandberg RD.  2024.  A Reformulation of the Laminar Kinetic Energy Model to Enable Multi-Mode Transition Predictions.. Flow, Turbulence and Combustion. s10494-024-00590-y
Laminar kinetic energy
Pacciani R, Fang Y, Metti L, Marconcini M, Sandberg RD.  2024.  A Reformulation of the Laminar Kinetic Energy Model to Enable Multi-Mode Transition Predictions.. Flow, Turbulence and Combustion. s10494-024-00590-y
Kaplan Turbine
Arnone A, Pacciani R, Gebendinger M, Francini S.  1994.  Numerical Characterization of a Kaplan Turbine Using a Three-Dimensional Viscous Solver. Modelling, Testing & Monitoring for Hydro Powerplants Meeting, Hydropower & Dams.
Budapest, Hungary, July
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
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
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
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)
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.
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
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.

Pages