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Journal Articles

Physics-Informed Deep Learning-Based Proof-of-Concept Study of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery

Karthik Reddy Lyathakula, Sevki Cesmeci, Matthew DeMond, Mohammad Fuad Hassan, Hanping Xu, Jing Tang
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. December 2023, 145(12): 121705.
Paper No: JERT-23-1075
https://doi.org/10.1115/1.4063326
Published Online: September 29, 2023
View Article titled, Physics-Informed Deep Learning-Based Proof-of-Concept Study of a Novel Elastohydrodynamic Seal for Supercritical CO 2 Turbomachinery
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Topics: Clearances (Engineering), Design, Flow (Dynamics), Leakage, Physics, Pressure, Rotors, Supercritical carbon dioxide, Turbomachinery, Sealing (Process)
Journal Articles

Analysis of Turbomachinery Losses in sCO 2 Brayton Power Blocks

Lakshminarayanan Seshadri, Pramod Kumar, Abdul Nassar, Gaurav Giri
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. November 2022, 144(11): 112101.
Paper No: JERT-21-2020
https://doi.org/10.1115/1.4054133
Published Online: April 11, 2022
View Article titled, Analysis of Turbomachinery Losses in sCO 2 Brayton Power Blocks
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Topics: Cycles, Turbomachinery, Pressure, Compressors, Turbines
Includes: Supplementary data
Journal Articles

Identifying the Market Scenarios for Supercritical CO 2 Power Cycles

Mohamed Noaman, Omar Awad, Tatiana Morosuk, George Tsatsaronis, Søren Salomo
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. May 2022, 144(5): 050906.
Paper No: JERT-21-1292
https://doi.org/10.1115/1.4052543
Published Online: October 18, 2021
View Article titled, Identifying the Market Scenarios for Supercritical CO 2 Power Cycles
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Topics: Cycles, Energy generation, Supercritical carbon dioxide, Thermodynamic power cycles, Turbomachinery, Renewable energy, Power stations, Technology management
Journal Articles

Using Machine Learning Tools to Predict Compressor Stall

Samuel M. Hipple, Harry Bonilla-Alvarado, Paolo Pezzini, Lawrence Shadle, Kenneth M. Bryden
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. July 2020, 142(7): 070915.
Paper No: JERT-19-1798
https://doi.org/10.1115/1.4046458
Published Online: April 8, 2020
View Article titled, Using Machine Learning Tools to Predict Compressor Stall
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Topics: Compressors, Machine learning, Surges, Turbines, Turbomachinery, Stall inception, Regression models, Gas turbines, Artificial neural networks
Journal Articles

Dynamic Modeling and Fuel Consumption Potential of an Intercooled Regenerative Reheat Gas Turbine Auxiliary Power Unit on Series Hybrid Electric Vehicle

Wissam Bou Nader, Florent Breque, Youssef Mazloum, Clément Dumand, Maroun Nemer
Journal: Journal of Energy Resources Technology
Publisher: ASME
Article Type: Research Papers
J. Energy Resour. Technol. January 2020, 142(1): 012203.
Paper No: JERT-18-1901
https://doi.org/10.1115/1.4044366
Published Online: September 3, 2019
View Article titled, Dynamic Modeling and Fuel Consumption Potential of an Intercooled Regenerative Reheat Gas Turbine Auxiliary Power Unit on Series Hybrid Electric Vehicle
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Topics: Dynamic modeling, Fuel consumption, Temperature, Transients (Dynamics), Turbomachinery, Vehicles, Gas turbines, Dynamic models, Hybrid electric vehicles, Simulation