1-20 of 74
Time series
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Predicting Gas Turbine NOx Emissions With Machine Learning

Available to Purchase

Harrison Eller, Sanjana Singh, Sumit Soni
Proc. ASME. GT2024, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A015, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-127627
https://doi.org/10.1115/GT2024-127627
View Paper titled, Predicting Gas Turbine NOx Emissions With Machine Learning
Open the PDF for Predicting Gas Turbine NOx Emissions With Machine Learning in another window
Topics: Emissions, Gas turbines, Machine learning, Nitrogen oxides, Deep neural networks, Artificial neural networks, Carbon monoxide, Combustion, Errors, Monitoring systems
Proceedings Papers

Low Data Prognostic Model for Rolling Element Bearing Remaining Useful Life

Available to Purchase

Edoardo Gheller, Sivachakaravarthy Natarajan, Abyjith Pazhoor, Steven Chatterton, Andrea Vania, Paolo Pennacchi
Proc. ASME. GT2024, Volume 4: Controls, Diagnostics, and Instrumentation, V004T05A035, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-127841
https://doi.org/10.1115/GT2024-127841
View Paper titled, Low Data Prognostic Model for Rolling Element Bearing Remaining Useful Life
Open the PDF for Low Data Prognostic Model for Rolling Element Bearing Remaining Useful Life in another window
Topics: Rolling bearings, Service life (Equipment), Bearings, Failure, Algorithms, Damage, Maintenance, Delays, Filters, Gas turbines
Proceedings Papers

Techno-Economic Analysis of Emerging Energy Storage Technologies for a Microgrid

Available to Purchase

Joshua Schmitt, Douglas Hofer, Owen Pryor, George Khawly, Fernando Karg Bulnes, Aaron McClung
Proc. ASME. GT2024, Volume 6: Education; Electric Power; Energy Storage; Fans and Blowers, V006T09A017, June 24–28, 2024
Publisher: American Society of Mechanical Engineers
Paper No: GT2024-129215
https://doi.org/10.1115/GT2024-129215
View Paper titled, Techno-Economic Analysis of Emerging Energy Storage Technologies for a Microgrid
Open the PDF for Techno-Economic Analysis of Emerging Energy Storage Technologies for a Microgrid in another window
Topics: Economics , Energy storage, Microgrids, Storage, Carbon capture and storage, Energy generation, Generators, Batteries, Carbon neutrality, Cycles
Proceedings Papers

Performance Characterization of a Small-Scale Pumped Thermal Energy Storage System

Available to Purchase

Natalie R. Smith, Joshua Just, Jeremy Johnson, Fernando Karg-Bulnes
Proc. ASME. GT2023, Volume 6: Education; Electric Power; Energy Storage; Fans and Blowers, V006T09A012, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-104232
https://doi.org/10.1115/GT2023-104232
View Paper titled, Performance Characterization of a Small-Scale Pumped Thermal Energy Storage System
Open the PDF for Performance Characterization of a Small-Scale Pumped Thermal Energy Storage System in another window
Topics: Energy storage, Heat, Performance characterization, Thermal energy storage, Steady state, Transients (Dynamics), Cycles, Heat engines, Heat exchangers, Heat losses
Proceedings Papers

Application of Machine Learning for Prediction of Turbofan’s Airflow

Available to Purchase

Sara Rejeb, Catherine Duveau, Tabea Rebafka
Proc. ASME. GT2023, Volume 1: Aircraft Engine, V001T01A026, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-103015
https://doi.org/10.1115/GT2023-103015
View Paper titled, Application of Machine Learning for Prediction of Turbofan’s Airflow
Open the PDF for Application of Machine Learning for Prediction of Turbofan’s Airflow in another window
Topics: Air flow, Blades, Machine learning, Time series
Proceedings Papers

The Effect of Ignition Procedure on Flashback of Hydrogen-Enriched Flames

Available to Purchase

Tarik Yahou, Thierry Schuller, James R. Dawson
Proc. ASME. GT2023, Volume 3A: Combustion, Fuels, and Emissions, V03AT04A039, June 26–30, 2023
Publisher: American Society of Mechanical Engineers
Paper No: GT2023-101785
https://doi.org/10.1115/GT2023-101785
View Paper titled, The Effect of Ignition Procedure on Flashback of Hydrogen-Enriched Flames
Open the PDF for The Effect of Ignition Procedure on Flashback of Hydrogen-Enriched Flames in another window
Topics: Flames, Hydrogen, Ignition, Fuels, Pressure, Methane, Dynamics (Mechanics), Flow (Dynamics), Chemiluminescence, Combustion
Proceedings Papers

Modeling of Inviscid Flow Shock Formation in a Wedge-Shaped Domain Using a Physics-Informed Neural Network-Based Partial Differential Equation Solver

Available to Purchase

Ryno Laubscher, Pieter Rousseau, Chris Meyer
Proc. ASME. GT2022, Volume 10C: Turbomachinery — Design Methods and CFD Modeling for Turbomachinery; Ducts, Noise, and Component Interactions, V10CT32A020, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-81768
https://doi.org/10.1115/GT2022-81768
View Paper titled, Modeling of Inviscid Flow Shock Formation in a Wedge-Shaped Domain Using a Physics-Informed Neural Network-Based Partial Differential Equation Solver
Open the PDF for Modeling of Inviscid Flow Shock Formation in a Wedge-Shaped Domain Using a Physics-Informed Neural Network-Based Partial Differential Equation Solver in another window
Topics: Artificial neural networks, Computational fluid dynamics, Inviscid flow, Modeling, Partial differential equations, Physics, Shock (Mechanics), Wedges, Architecture, Equations of state
Proceedings Papers

Effect of Counter- and Co-Swirl on Low-Frequency Combustion Instabilities of Jet A-1 Spray Flames

Available to Purchase

Byeonguk Ahn, Kyu Tae Kim
Proc. ASME. GT2022, Volume 3A: Combustion, Fuels, and Emissions, V03AT04A012, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-79706
https://doi.org/10.1115/GT2022-79706
View Paper titled, Effect of Counter- and Co-Swirl on Low-Frequency Combustion Instabilities of Jet A-1 Spray Flames
Open the PDF for Effect of Counter- and Co-Swirl on Low-Frequency Combustion Instabilities of Jet A-1 Spray Flames in another window
Topics: Combustion, Flames, Sprays, Pressure, Diffusion flames, Flow (Dynamics), Heat, Oscillations, Atmospheric pressure, Combustion chambers
Proceedings Papers

From Pressure Time Series Data to Flame Transfer Functions: A Framework for Perfectly-Premixed Swirling Flames

Available to Purchase

Abdulla Ghani, Alp Albayrak
Proc. ASME. GT2022, Volume 3B: Combustion, Fuels, and Emissions, V03BT04A058, June 13–17, 2022
Publisher: American Society of Mechanical Engineers
Paper No: GT2022-84357
https://doi.org/10.1115/GT2022-84357
View Paper titled, From Pressure Time Series Data to Flame Transfer Functions: A Framework for Perfectly-Premixed Swirling Flames
Open the PDF for From Pressure Time Series Data to Flame Transfer Functions: A Framework for Perfectly-Premixed Swirling Flames in another window
Topics: Flames, Pressure, Swirling flow, Time series, Transfer functions, Optimization, Combustion, Turbulence, Acoustics, Combustion chambers
Proceedings Papers

Prediction of Gas Turbine Trip: a Novel Methodology Based on Random Forest Models

Available to Purchase

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Fabio Ceschini, Giovanni Bechini, Giuseppe Cota, Fabrizio Riguzzi
Proc. ASME. GT2021, Volume 8: Oil and Gas Applications; Steam Turbine, V008T20A005, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58916
https://doi.org/10.1115/GT2021-58916
View Paper titled, Prediction of Gas Turbine Trip: a Novel Methodology Based on Random Forest Models
Open the PDF for Prediction of Gas Turbine Trip: a Novel Methodology Based on Random Forest Models in another window
Topics: Gas turbines, Machine learning, Case studies, Data mining, Image segmentation, Natural, scientific and engineering processes and practices, Profitability, Sensors, Service life (Equipment), Time series
Proceedings Papers

Data Selection and Feature Engineering for the Application of Machine Learning to the Prediction of Gas Turbine Trip

Available to Purchase

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Fabio Ceschini, Giovanni Bechini, Giuseppe Cota, Fabrizio Riguzzi
Proc. ASME. GT2021, Volume 8: Oil and Gas Applications; Steam Turbine, V008T20A004, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58914
https://doi.org/10.1115/GT2021-58914
View Paper titled, Data Selection and Feature Engineering for the Application of Machine Learning to the Prediction of Gas Turbine Trip
Open the PDF for Data Selection and Feature Engineering for the Application of Machine Learning to the Prediction of Gas Turbine Trip in another window
Topics: Gas turbines, Machine learning, Algorithms, Damage, Fourier transforms, Peak load, Performance, Reliability, Service life (Equipment), Stress
Proceedings Papers

Delay Identification in Thermoacoustics

Available to Purchase

F. Gant, G. Ghirardo, A. Cuquel, M. R. Bothien
Proc. ASME. GT2021, Volume 3A: Combustion, Fuels, and Emissions, V03AT04A024, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58903
https://doi.org/10.1115/GT2021-58903
View Paper titled, Delay Identification in Thermoacoustics
Open the PDF for Delay Identification in Thermoacoustics in another window
Topics: Delays, Thermoacoustics, Flames, Noise (Sound), Acoustics, Combustion, Time series, Damping, Dynamics (Mechanics), Engineering simulation
Proceedings Papers

Detection of Machinery Failure Signs From Big Time-Series Data Obtained by Flow Simulation of Intermediate-Pressure Steam Turbines

Available to Purchase

Kazuhiko Komatsu, Hironori Miyazawa, Cheng Yiran, Masayuki Sato, Takashi Furusawa, Satoru Yamamoto, Hiroaki Kobayashi
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A002, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-58698
https://doi.org/10.1115/GT2021-58698
View Paper titled, Detection of Machinery Failure Signs From Big Time-Series Data Obtained by Flow Simulation of Intermediate-Pressure Steam Turbines
Open the PDF for Detection of Machinery Failure Signs From Big Time-Series Data Obtained by Flow Simulation of Intermediate-Pressure Steam Turbines in another window
Topics: Failure, Flow simulation, Machinery, Pressure, Steam turbines, Time series
Proceedings Papers

Prediction Enhancement of Machine Learning Using Time Series Modeling in Gas Turbines

Available to Purchase

Vipul Goyal, Mengyu Xu, Jayanta Kapat, Ladislav Vesely
Proc. ASME. GT2021, Volume 4: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage; Education; Electric Power, V004T09A004, June 7–11, 2021
Publisher: American Society of Mechanical Engineers
Paper No: GT2021-59082
https://doi.org/10.1115/GT2021-59082
View Paper titled, Prediction Enhancement of Machine Learning Using Time Series Modeling in Gas Turbines
Open the PDF for Prediction Enhancement of Machine Learning Using Time Series Modeling in Gas Turbines in another window
Topics: Blades, Combustion, Combustion systems, Cooling systems, Flow (Dynamics), Fuels, Gas turbines, Machine learning, Modeling, Power stations
Proceedings Papers

Structured Methodology for Clustering Gas Turbine Transients by Means of Multi-Variate Time Series

Available to Purchase

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Ceschini, Giovanni Bechini, Giuseppe Cota, Fabrizio Riguzzi
Proc. ASME. GT2020, Volume 9: Oil and Gas Applications; Organic Rankine Cycle Power Systems; Steam Turbine, V009T21A005, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-14751
https://doi.org/10.1115/GT2020-14751
View Paper titled, Structured Methodology for Clustering Gas Turbine Transients by Means of Multi-Variate Time Series
Open the PDF for Structured Methodology for Clustering Gas Turbine Transients by Means of Multi-Variate Time Series in another window
Topics: Gas turbines, Time series, Transients (Dynamics), Algorithms, Case studies, Damage, Data mining, Databases, Engines, Reliability
Proceedings Papers

Recuperator Performance Assessment in Humidified Micro Gas Turbine Applications Using Experimental Data Extended With Preliminary Support Vector Regression Model Analysis

Available to Purchase

Ward De Paepe, Alessio Pappa, Diederik Coppitters, Marina Montero Carrerro, Panagiotis Tsirikoglou, Francesco Contino
Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T06A028, September 21–25, 2020
Publisher: American Society of Mechanical Engineers
Paper No: GT2020-15634
https://doi.org/10.1115/GT2020-15634
View Paper titled, Recuperator Performance Assessment in Humidified Micro Gas Turbine Applications Using Experimental Data Extended With Preliminary Support Vector Regression Model Analysis
Open the PDF for Recuperator Performance Assessment in Humidified Micro Gas Turbine Applications Using Experimental Data Extended With Preliminary Support Vector Regression Model Analysis in another window
Topics: Micro gas turbines, Support vector machines, Cycles, Flow (Dynamics), Modeling, Combined heat and power, Electromagnetic scattering, Compressors, Distributed power generation, Exhaust systems
Proceedings Papers

Use of Vector Autoregressive Model for Anomaly Detection in Utility Gas Turbines

Available to Purchase

Vipul Goyal, Mengyu Xu, Jayanta Kapat
Proc. ASME. GT2019, Volume 3: Coal, Biomass, Hydrogen, and Alternative Fuels; Cycle Innovations; Electric Power; Industrial and Cogeneration; Organic Rankine Cycle Power Systems, V003T08A004, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-90995
https://doi.org/10.1115/GT2019-90995
View Paper titled, Use of Vector Autoregressive Model for Anomaly Detection in Utility Gas Turbines
Open the PDF for Use of Vector Autoregressive Model for Anomaly Detection in Utility Gas Turbines in another window
Topics: Gas turbines, Time series, Combined cycles, Modeling, Power stations, Steam turbines, Turbines
Proceedings Papers

Prediction of Premixed Flame Dynamics Using LES With Tabulated Chemistry and Eulerian Stochastic Fields

Available to Purchase

Alexander Avdonin, Alireza Javareshkian, Wolfgang Polifke
Proc. ASME. GT2019, Volume 4A: Combustion, Fuels, and Emissions, V04AT04A004, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-90140
https://doi.org/10.1115/GT2019-90140
View Paper titled, Prediction of Premixed Flame Dynamics Using LES With Tabulated Chemistry and Eulerian Stochastic Fields
Open the PDF for Prediction of Premixed Flame Dynamics Using LES With Tabulated Chemistry and Eulerian Stochastic Fields in another window
Topics: Chemistry, Dynamics (Mechanics), Flames, Combustion, Enthalpy, Turbulence, Computation, Excitation, Heat, Heat losses
Proceedings Papers

Anomaly Detection in Gas Turbine Time Series by Means of Bayesian Hierarchical Models

Available to Purchase

Enzo Losi, Mauro Venturini, Lucrezia Manservigi, Giuseppe Fabio Ceschini, Giovanni Bechini
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T27A006, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-90057
https://doi.org/10.1115/GT2019-90057
View Paper titled, Anomaly Detection in Gas Turbine Time Series by Means of Bayesian Hierarchical Models
Open the PDF for Anomaly Detection in Gas Turbine Time Series by Means of Bayesian Hierarchical Models in another window
Topics: Gas turbines, Time series, Sensors
Proceedings Papers

A Prognostics and Health Management Framework for Wind

Available to Purchase

Shuangwen Sheng, Yi Guo
Proc. ASME. GT2019, Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy, V009T48A013, June 17–21, 2019
Publisher: American Society of Mechanical Engineers
Paper No: GT2019-91533
https://doi.org/10.1115/GT2019-91533
View Paper titled, A Prognostics and Health Management Framework for Wind
Open the PDF for A Prognostics and Health Management Framework for Wind in another window
Topics: Failure, Probability, Service life (Equipment), Wind, Wind turbines, Mechanical drives, Bearings, Failure mechanisms, Maintenance, Physics