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Proceedings Papers

Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

Proc. ASME. GT2022, Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications, V007T19A003, June 13–17, 2022

Paper No: GT2022-80552

DOI: https://doi.org/10.1115/GT2022-80552

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Topics: Modeling, Optimization, Transportation systems, Pipelines, Compressors, Flow (Dynamics), Gas compressors, Hydrogen, Natural gas, Renewable energy

Journal Articles

Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

Cody W. Allen

J. Eng. Gas Turbines Power. October 2022, 144(10): 101014.

Paper No: GTP-22-1401

DOI: https://doi.org/10.1115/1.4055358

Published Online: September 12, 2022

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Topics: Compressors, Optimization, Pipelines, Flow (Dynamics), Turbines

Proceedings Papers

Anomaly Detection for Large Fleets of Industrial Equipment: Utilizing Machine Learning With Applications to Power Plant Monitoring

Cody W. Allen, Chad Holcomb, Maurício de Oliveira

Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T05A016, June 7–11, 2021

Paper No: GT2021-60116

DOI: https://doi.org/10.1115/GT2021-60116

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Topics: Machine learning, Power stations, Machinery, Gas turbines, Algorithms, Errors, Failure, Model development, Neural network models, Reliability

Proceedings Papers

Axial Compressor Fouling and its Effect on Gas Turbine Fuel Consumption and Emissions

Cody W. Allen, Purushotham Balaji, Maurício de Oliveira

Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A030, September 21–25, 2020

Paper No: GT2020-16089

DOI: https://doi.org/10.1115/GT2020-16089

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Topics: Compressors, Emissions, Fuel consumption, Gas turbines, Fuels, Flow (Dynamics), Carbon dioxide, Foundry coatings, Simulation, Blades

Journal Articles

Estimating Recoverable Performance Degradation Rates and Optimizing Maintenance Scheduling

Cody W. Allen, Chad M. Holcomb, Maurício de Oliveira

J. Eng. Gas Turbines Power. January 2019, 141(1): 011032.

Paper No: GTP-18-1322

DOI: https://doi.org/10.1115/1.4041004

Published Online: November 14, 2018

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Topics: Maintenance, Optimization

Proceedings Papers

Estimating Recoverable Performance Degradation Rates and Optimizing Maintenance Scheduling

Cody W. Allen, Chad M. Holcomb, Mauricio de Oliveira

Proc. ASME. GT2018, Volume 6: Ceramics; Controls, Diagnostics, and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A004, June 11–15, 2018

Paper No: GT2018-75267

DOI: https://doi.org/10.1115/GT2018-75267

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Topics: Maintenance, Algorithms, Compressors, Gas turbines, Optimization, Blades, Cooling, Heat exchangers, Simulation, Statistical distributions

Proceedings Papers

Gas Turbine Machinery Diagnostics: A Brief Review and a Sample Application

Cody W. Allen, Chad M. Holcomb, Mauricio de Oliveira

Proc. ASME. GT2017, Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A028, June 26–30, 2017

Paper No: GT2017-64755

DOI: https://doi.org/10.1115/GT2017-64755

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Topics: Gas turbines, Machinery, Algorithms, Machine learning, Engines, Turbines, Artificial neural networks, Computational methods, Engineering standards, Fuels

Proceedings Papers

Fault Detection Using Reduced Rank Linear Engine Models

Cody W. Allen, Chad M. Holcomb, Mauricio de Oliveira

Proc. ASME. GT2016, Volume 6: Ceramics; Controls, Diagnostics and Instrumentation; Education; Manufacturing Materials and Metallurgy, V006T05A024, June 13–17, 2016

Paper No: GT2016-57916

DOI: https://doi.org/10.1115/GT2016-57916

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Topics: Design, Engines, Errors, Flaw detection, Gas turbines, Physics, Sensors

Journal citation

NARROW

Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

Modeling Power Constraints Using Maps and Field Data in Optimization Problems for Gas Transportation Systems

Anomaly Detection for Large Fleets of Industrial Equipment: Utilizing Machine Learning With Applications to Power Plant Monitoring

Axial Compressor Fouling and its Effect on Gas Turbine Fuel Consumption and Emissions

Estimating Recoverable Performance Degradation Rates and Optimizing Maintenance Scheduling

Estimating Recoverable Performance Degradation Rates and Optimizing Maintenance Scheduling

Gas Turbine Machinery Diagnostics: A Brief Review and a Sample Application

Fault Detection Using Reduced Rank Linear Engine Models

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