Michele Marconcini

Associate Professor

Università degli Studi di Napoli Federico II

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Articles (14)

Collaborators (5)

Roberto Pacciani

Associate Professor

Università degli Studi di Roma La Sapienza

Giacomo Bruno Azzurro Persico

Associate Professor (Professore Associato)

Politecnico di Milano

Karsten Knobloch

Deutsches Zentrum für Luft- und Raumfahrt

Lorenzo Pinelli

Assistant Professor

University of Florence

Paolo Savio

Michele Marconcini

Research Interests

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Articles (14)

Collaborators (5)

Roberto Pacciani

Giacomo Bruno Azzurro Persico

Karsten Knobloch

Lorenzo Pinelli

Paolo Savio

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Michele Marconcini

Research Interests

Explore related searches

Contact this professor

Articles (14)

A Data-Driven Approach for Generalizing the Laminar Kinetic Energy Model for Separation and Bypass Transition in Low- and High-Pressure Turbines

Improvements in the Prediction of Steady and Unsteady Transition and Mixing in Low-Pressure Turbines by Means of Machine-Learnt Closures

Improving Aeromechanical Performance of Compressor Rotor Blisk with Topology Optimization

The Impact of the Off-Design Conditions on the Entropy Wave Interaction With a High-Pressure Turbine Stage

The Effects of Swirling Flows in Entropy Wave Convection Through High-Pressure Turbine Stage

Validation of an Analytical Model for the Acoustic Impedance Eduction of Multi-Cavity Resonant Liners by a High-Fidelity LES Approach

Multi-Point Surrogate-Based Approach for Assessing Impacts of Geometric Variations on Centrifugal Compressor Performance

Predicting the Impact of Compressor Flexibility Improvements on Heavy-Duty Gas Turbines for Minimum and Base Load Conditions

Effect of clocking on entropy noise generation within an aeronautical high pressure turbine stage

Retrofittable Solutions Capability for Gas Turbine Compressors

Accelerating legacy applications with spatial computing devices

Analysis of Measured and Predicted Turbine Maps From Start-Up to Design Point

An AI-Based Fast Design Method for New Centrifugal Compressor Families

Assessment of Machine-Learned Turbulence Models Trained for Improved Wake-Mixing in Low-Pressure Turbine Flows

Collaborators (5)

Roberto Pacciani

Giacomo Bruno Azzurro Persico

Karsten Knobloch

Lorenzo Pinelli

Paolo Savio

How do I reach out?

Meet Kite AI