Biblio

Found 481 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 
Navier–Stokes
Cavazzini A, Campobasso MS, Marconcini M, Pacciani R, Arnone A.  2019.  Harmonic balance Navier-Stokes analysis of tidal stream turbine wave loads. Recent Advances in CFD for Wind and​ Tidal Offshore Turbines. :pp37-49.
multistage
Batisti M, Marconcini M, Agnolucci A, Belardini E, Grimaldi A, Toni L, Valente R, Arnone A.  2025.  Experimental and Numerical Rotating Stall Investigation of a Multistage Centrifugal Compressor. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 12: Turbomachinery:V012T35A009.
GT2025-153766. Published on ASME J. Eng. Gas Turbine. Power
multi-stage LPT
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A.  2025.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 1: Computational Opportunities and Methodology. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery:V011T32A014.
GT2025-152583. Recommended for publication on ASME J. Turbomach.
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A, Spano E, Bertini F.  2025.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 2: Effect of Reynolds Number on Different Blade Geometries. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery:V011T32A024.
GT2025-153512. Recommended for publication on ASME J. Turbomach.
multi-row effects
Pinelli L, Vienni D, Tapinassi L, Michelassi V, Burberi C, Lorusso S, Ignesti M, Marconcini M.  2024.  Understanding the Aerodynamic Damping Behavior of an Axial Compressor Rotor for Industrial Applications. ASME Turbo Expo 2024 Turbomachinery Technical Conference and Exposition. Volume 10A: Structures and Dynamics:V10AT21A016.
GT2024-128729
multi-fidelity
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A.  2025.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 1: Computational Opportunities and Methodology. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery:V011T32A014.
GT2025-152583. Recommended for publication on ASME J. Turbomach.
Rosenzweig M, Kozul M, Sandberg R, Giannini G, Pacciani R, Marconcini M, Arnone A, Spano E, Bertini F.  2025.  Numerical Design of Experiments for Repeating Low-Pressure Turbine Stages Part 2: Effect of Reynolds Number on Different Blade Geometries. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery:V011T32A024.
GT2025-153512. Recommended for publication on ASME J. Turbomach.
Modeling
Cozzi L, Rubechini F, Arnone A, Schneider A, Astrua P.  2019.  Improving Steady CFD to Capture the Effects of Radial Mixing in Axial Compressors. ASME Turbo Expo 2019. Volume 2C: Turbomachinery:V02CT41A016.
ASME paper GT2019-90363
Maceli N, Arcangeli L, Arnone A.  2021.  Two Phase Flow CFD Modeling of a Steam Turbine Low Pressure Section: Comparison With Data and Correlations. ASME Turbo Expo 2021 Turbomachinery Technical Conference and Exposition. 8: Oil and Gas Applications; Steam Turbine
ASME paper GT2021-59645
mistuning
Biagiotti S, Pinelli L, Poli F, Vanti F, Pacciani R.  2018.  Numerical Study of Flutter Stabilization in Low Pressure Turbine Rotor with Intentional Mistuning. ATI 2018 - 73rd Conference of the Italian Thermal Machines Engineering Association.. Energy Procedia 148:98-105.
meta-model
Checcucci M, Schneider A, Marconcini M, Rubechini F, Arnone A, De Franco L, Coneri M.  2015.  A Novel Approach to Parametric Design of Centrifugal Pumps for a Wide Range of Specific Speeds. 12th International Symposium on Experimental and Computational Aerothermodynamics of Internal Flows.
paper n.121
machine learning; multi-objective optimization; low pressure turbine; transition; turbulence modeling
Akolekar H, Waschkowski F, Zhao Y, Pacciani R, Sandberg R.  2021.  Transition Modeling for Low Pressure Turbines Using Computational Fluid Dynamics Driven Machine Learning. Energies. 14(15):4680.
Machine Learning
Pela A, Marconcini M, Arnone A, Agnolucci A, Belardini E, Valente R, Grimaldi A, Toni L.  2025.  Convolutional Neural Network Approach for Impeller Blade Loading Inference. 1st International Symposium on AI and Fluid Mechanics (AIFLUIDs).
LS-89
Castelli N, Bacci T, Giuntini S, Pacciani R, Andreini A.  2025.  Numerical Prediction of the Heat Loads on a Turbine Vane Test Case. ASME Turbo Expo 2025 Turbomachinery Technical Conference and Exposition. 11: Turbomachinery
LPT
Arnone A, Marconcini M, Pacciani R, Spano E.  1999.  Numerical Prediction of Wake–Induced Transition in a Low Pressure Turbine. 14th ISABE Symposium.
September 5–10, Florence, Italy, ISABE paper 99–058

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