Page 1 | Search Results | J. Turbomach.

1-6 of 6

Sort by

Sort Order Select

Journal Articles

A Data-Driven Method for the Derivation of Explicit Algebraic Reynolds Stress Models Applied to the Wake Losses of Low-Pressure Turbine Cascades

Johannes Deutsch, Nima Fard Afshar, Stefan Henninger, Peter Jeschke

Publisher: ASME

J. Turbomach. June 2025, 147(6): 061007.

Paper No: TURBO-24-1188

https://doi.org/10.1115/1.4067032

Published Online: November 22, 2024

View Article titled, A Data-Driven Method for the Derivation of Explicit Algebraic Reynolds Stress Models Applied to the Wake Losses of Low-Pressure Turbine Cascades

Topics: Kinetic energy, Optimization, Pressure, Reynolds stress, Simulation, Turbines, Turbulence, Wakes, Reynolds-averaged Navier–Stokes equations, Tensors

Journal Articles

Machine Learning for the Development of Data-Driven Turbulence Closures in Coolant Systems

James Hammond, Francesco Montomoli, Marco Pietropaoli, Richard D. Sandberg, Vittorio Michelassi

Publisher: ASME

J. Turbomach. August 2022, 144(8): 081003.

Paper No: TURBO-20-1174

https://doi.org/10.1115/1.4053533

Published Online: March 3, 2022

View Article titled, Machine Learning for the Development of Data-Driven Turbulence Closures in Coolant Systems

Topics: Anisotropy, Design, Errors, Flow (Dynamics), Geometry, Heat transfer, Reynolds-averaged Navier–Stokes equations, Tensors, Testing, Turbulence

Journal Articles

Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot

R. D. Sandberg, R. Tan, J. Weatheritt, A. Ooi, A. Haghiri, V. Michelassi, G. Laskowski

Publisher: ASME

J. Turbomach. October 2018, 140(10): 101008.

Paper No: TURBO-18-1202

https://doi.org/10.1115/1.4041268

Published Online: September 28, 2018

View Article titled, Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot

Topics: Anisotropy, Heat flux, Large eddy simulation, Reynolds-averaged Navier–Stokes equations, Scalars, Stress, Tensors, Turbulence, Eddies (Fluid dynamics), Algebra

Journal Articles

Affordable Uncertainty Quantification for Industrial Problems: Application to Aero-Engine Fans

Tiziano Ghisu, Shahrokh Shahpar

Publisher: ASME

J. Turbomach. May 2018, 140(6): 061005.

Paper No: TURBO-17-1198

https://doi.org/10.1115/1.4038982

Published Online: April 27, 2018

View Article titled, Affordable Uncertainty Quantification for Industrial Problems: Application to Aero-Engine Fans

Topics: Blades, Design, Geometry, Polynomials, Pressure, Uncertainty, Uncertainty quantification, Fans, Chaos, Flow (Dynamics)

Journal Articles

Education Committee Best Paper of 1995 Award: Methods of Classical Mechanics Applied to Turbulence Stresses in a Tip Leakage Vortex

J. G. Moore, S. A. Schorn, J. Moore

Publisher: ASME

J. Turbomach. October 1996, 118(4): 622–629.

https://doi.org/10.1115/1.2840917

Published Online: October 1, 1996

View Article titled, Education Committee Best Paper of 1995 Award: Methods of Classical Mechanics Applied to Turbulence Stresses in a Tip Leakage Vortex

Topics: Classical mechanics, Education, Leakage, Stress, Turbulence, Vortices, Stress tensors, Approximation, Cascades (Fluid dynamics), Tensors

Journal Articles

An Inverse (Design) Problem Solution Method for the Blade Cascade Flow on Streamsurface of Revolution

Naixing Chen, Fengxian Zhang, Weihong Li

Publisher: ASME

J. Turbomach. October 1986, 108(2): 194–199.

https://doi.org/10.1115/1.3262037

Published Online: October 1, 1986

View Article titled, An Inverse (Design) Problem Solution Method for the Blade Cascade Flow on Streamsurface of Revolution

Topics: Blades, Design, Flow (Dynamics), Tensors, Pressure, Suction, Cascades (Fluid dynamics), Aerodynamics, Computational methods, Differential equations

Journal citation

NARROW

A Data-Driven Method for the Derivation of Explicit Algebraic Reynolds Stress Models Applied to the Wake Losses of Low-Pressure Turbine Cascades

Machine Learning for the Development of Data-Driven Turbulence Closures in Coolant Systems

Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot

Affordable Uncertainty Quantification for Industrial Problems: Application to Aero-Engine Fans

Education Committee Best Paper of 1995 Award: Methods of Classical Mechanics Applied to Turbulence Stresses in a Tip Leakage Vortex

An Inverse (Design) Problem Solution Method for the Blade Cascade Flow on Streamsurface of Revolution

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

Opportunities

A Data-Driven Method for the Derivation of Explicit Algebraic Reynolds Stress Models Applied to the Wake Losses of Low-Pressure Turbine Cascades

Machine Learning for the Development of Data-Driven Turbulence Closures in Coolant Systems

Applying Machine Learnt Explicit Algebraic Stress and Scalar Flux Models to a Fundamental Trailing Edge Slot

Affordable Uncertainty Quantification for Industrial Problems: Application to Aero-Engine Fans

Education Committee Best Paper of 1995 Award: Methods of Classical Mechanics Applied to Turbulence Stresses in a Tip Leakage Vortex

An Inverse (Design) Problem Solution Method for the Blade Cascade Flow on Streamsurface of Revolution

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

Opportunities

This Feature Is Available To Subscribers Only