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J. V. Taylor
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Journal Articles

Student Research Projects With Industrial Impact

S. D. Grimshaw, C. J. Clark, J. V. Taylor, R. Spataro
Journal: Journal of Engineering for Gas Turbines and Power
Article Type: Research-Article
J. Eng. Gas Turbines Power. June 2022, 144(6): 061008.
Paper No: GTP-21-1496
DOI: https://doi.org/10.1115/1.4053708
Published Online: March 29, 2022
View Article titled, Student Research Projects With Industrial Impact
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Topics: Students, Collaboration, Design
Proceedings Papers

Student Research Projects With Industrial Impact

S. D. Grimshaw, C. J. Clark, J. V. Taylor, R. Spataro
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T08A003, June 7–11, 2021
Paper No: GT2021-58948
DOI: https://doi.org/10.1115/GT2021-58948
View Paper titled, Student Research Projects With Industrial Impact
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Topics: Students, Collaboration, Design, Undergraduate research, Aerospace industry, Career development, Compressors, Cycles, Ducts, Engines
Journal Articles

Super Aggressive S-Ducts for Air Breathing Rocket Engines

J. V. Taylor, F. Flanagan, A. Dunlop, S. D. Grimshaw, R. J. Miller
Journal: Journal of Turbomachinery
Article Type: Research Papers
J. Turbomach. June 2021, 143(6): 061015.
Paper No: TURBO-20-1317
DOI: https://doi.org/10.1115/1.4050596
Published Online: April 27, 2021
View Article titled, Super Aggressive S-Ducts for Air Breathing Rocket Engines
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Topics: Design, Ducts, Flow (Dynamics), Struts (Engineering), Blades, Computational fluid dynamics
Proceedings Papers

Super Aggressive S-Ducts for Air Breathing Rocket Engines

J. V. Taylor, F. Flanagan, A. Dunlop, S. D. Grimshaw, R. J. Miller
Proc. ASME. GT2020, Volume 2D: Turbomachinery, V02DT36A014, September 21–25, 2020
Paper No: GT2020-14927
DOI: https://doi.org/10.1115/GT2020-14927
View Paper titled, Super Aggressive S-Ducts for Air Breathing Rocket Engines
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Topics: Ducts, Rocket engines, Design, Aerospace industry, Compressors, Computational fluid dynamics, Flow (Dynamics), Gas turbines, Blades, Corners (Structural elements)
Journal Articles

Predicting the Operability of Damaged Compressors Using Machine Learning

J. V. Taylor, B. Conduit, A. Dickens, C. Hall, M. Hillel, R. J. Miller
Journal: Journal of Turbomachinery
Article Type: Research Papers
J. Turbomach. May 2020, 142(5): 051010.
Paper No: TURBO-19-1281
DOI: https://doi.org/10.1115/1.4046658
Published Online: April 30, 2020
View Article titled, Predicting the Operability of Damaged Compressors Using Machine Learning
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Topics: Artificial neural networks, Blades, Compressors, Damage, Machine learning, Pressure, Parametrization
Proceedings Papers

Predicting the Operability of Damaged Compressors Using Machine Learning

J. V. Taylor, B. Conduit, A. Dickens, C. Hall, M. Hillel, R. J. Miller
Proc. ASME. GT2019, Volume 2A: Turbomachinery, V02AT39A027, June 17–21, 2019
Paper No: GT2019-91339
DOI: https://doi.org/10.1115/GT2019-91339
View Paper titled, Predicting the Operability of Damaged Compressors Using Machine Learning
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Topics: Compressors, Machine learning, Aerospace industry, Testing, Blades, Damage, Uncertainty
Proceedings Papers

Fast Settling Millimetre-Scale Five-Hole Probes

S. D. Grimshaw, J. V. Taylor
Proc. ASME. GT2016, Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A014, June 13–17, 2016
Paper No: GT2016-56628
DOI: https://doi.org/10.1115/GT2016-56628
View Paper titled, Fast Settling Millimetre-Scale Five-Hole Probes
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Topics: Probes, Design, Geometry, Blades, Modeling, Pressure, Shear (Mechanics), Tubing, Wakes