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1-11 of 11
Keywords: machine learning
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Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. April 2025, 147(4): 041024.
Paper No: GTP-24-1545
Published Online: November 5, 2024
...Md Abir Hossain; Calvin M. Stewart This study explored the application of black box machine learning (ML) to build high throughput models that predict the creep response of Ni-based Alloy 617. Black box ML refers to highly complex machine learning algorithms that generate outputs from inputs...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. January 2025, 147(1): 011021.
Paper No: GTP-24-1404
Published Online: September 19, 2024
...Tihomir Varchev; Jürgen Mathes; Christian Koch; Stephan Staudacher A machine learning-based approach is presented, which allows to detect persistent engine faults after a single flight. It utilizes transient in-flight measurements and a transient engine model. The time series of the residuals...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. November 2024, 146(11): 111008.
Paper No: GTP-23-1519
Published Online: July 20, 2024
... sufficient data of eroded cases for predictive analysis is challenging. Therefore, this paper proposes a blade erosion prediction method using numerical simulation and machine learning. Pressure data of several blade erosion cases are collected from the numerical turbine simulation. The machine learning...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. August 2024, 146(8): 081014.
Paper No: GTP-23-1619
Published Online: February 26, 2024
...-mail: chris.hill@ansys.com e-mail: florian.menter@ansys.com e-mail: saurabh.patwardhan@ansys.com e-mail: ishan.verma@ansys.com 24 10 2023 06 12 2023 26 02 2024 turbulence modeling machine learning neural networks gas turbine combustion swirling flows...
Journal Articles
Ashish Sutar, Anandvinod Dalmiya, Manaf Sheyyab, Hadis Anahideh, Eric K. Mayhew, Kenneth Brezinsky, Patrick T. Lynch
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. July 2024, 146(7): 071009.
Paper No: GTP-23-1518
Published Online: February 8, 2024
... to operate. Over the last decade, there have been advances in the development of chemometric models, which use machine learning to correlate infrared spectra of fuels to fuel properties like DCN, density, and C/H ratio, among many others. These techniques have certain advantages over the ASTM methods...
Journal Articles
Axial Compressor Map Generation Leveraging Autonomous Self-Training Artificial Intelligence. Phase 2
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2024, 146(3): 031024.
Paper No: GTP-23-1376
Published Online: January 4, 2024
... are described. The approach for autonomous selection of the architectures and hyperparameters of Machine Learning (ML) models is explained. The uncertainty quantification techniques are considered. The developed ML-powered methods for compressor geometry prediction are discussed. The ML models' accuracy values...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. May 2024, 146(5): 051013.
Paper No: GTP-23-1360
Published Online: December 20, 2023
... in a specific configuration that enabled sharp images to be acquired at these extreme conditions. The collected images were processed using a purposely developed and trained machine learning (ML) algorithm to detect and characterize the droplets' evaporation regime. The results revealed different evaporation...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. July 2023, 145(7): 071010.
Paper No: GTP-23-1007
Published Online: May 25, 2023
.... Traditional methods of testing and optimizing the performances of IC engine are complex, time-consuming, and expensive. This has led the researchers to shift their focus to faster and computationally feasible techniques like soft computing (SC) and machine learning (ML) algorithms, which predict the optimum...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. April 2023, 145(4): 041015.
Paper No: GTP-22-1451
Published Online: December 13, 2022
...-driven approach for tackling the computational overhead of injector simulations, whereby the transient injection profiles are emulated for a side-oriented, single-hole diesel injector using a Bayesian machine-learning framework. First, an interpretable Bayesian learning strategy was employed...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. January 2023, 145(1): 011001.
Paper No: GTP-22-1328
Published Online: October 19, 2022
... analysis. e-mail: m.burlaka@softinway.com e-mail: l.moroz@softinway.com 11 07 2022 11 08 2022 19 10 2022 axial compressor performance map machine learning artificial neural network compressor vanes' angles optimization Stennis Space Center 10.13039/100006205...
Journal Articles
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. November 2019, 141(11): 111023.
Paper No: GTP-19-1338
Published Online: October 23, 2019
...Michael T. Tong With the rise in big data and analytics, machine learning is transforming many industries. It is being increasingly employed to solve a wide range of complex problems, producing autonomous systems that support human decision-making. For the aircraft engine industry, machine learning...