IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v135y2014icp572-585.html

A component map tuning method for performance prediction and diagnostics of gas turbine compressors

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Soleimani, Mohammadjavad & Irani, Fatemeh Negar & Yadegar, Meysam & Meskin, Nader, 2025. "Comprehensive review of gas turbine fault diagnostic strategies," Applied Energy, Elsevier, vol. 401(PC).
  2. Cheng, Xianda & Zheng, Haoran & Yang, Qian & Zheng, Peiying & Dong, Wei, 2023. "Surrogate model-based real-time gas path fault diagnosis for gas turbines under transient conditions," Energy, Elsevier, vol. 278(PA).
  3. Duan, Jiandong & Fan, Shaogui & An, Quntao & Sun, Li & Wang, Guanglin, 2017. "A comparison of micro gas turbine operation modes for optimal efficiency based on a nonlinear model," Energy, Elsevier, vol. 134(C), pages 400-411.
  4. Han, Jaeyoung & Yu, Sangseok & Yi, Sun, 2017. "Adaptive control for robust air flow management in an automotive fuel cell system," Applied Energy, Elsevier, vol. 190(C), pages 73-83.
  5. Kim, Jeong Ho & Kim, Tong Seop, 2019. "A new approach to generate turbine map data in the sub-idle operation regime of gas turbines," Energy, Elsevier, vol. 173(C), pages 772-784.
  6. Son, Seongmin & Jeong, Yongju & Cho, Seong Kuk & Lee, Jeong Ik, 2020. "Development of supercritical CO2 turbomachinery off-design model using 1D mean-line method and Deep Neural Network," Applied Energy, Elsevier, vol. 263(C).
  7. Tsoutsanis, Elias & Meskin, Nader, 2017. "Derivative-driven window-based regression method for gas turbine performance prognostics," Energy, Elsevier, vol. 128(C), pages 302-311.
  8. Mo, Huadong & Sansavini, Giovanni, 2019. "Impact of aging and performance degradation on the operational costs of distributed generation systems," Renewable Energy, Elsevier, vol. 143(C), pages 426-439.
  9. Kiaee, Mehrdad & Tousi, A.M., 2021. "Vector-based deterioration index for gas turbine gas-path prognostics modeling framework," Energy, Elsevier, vol. 216(C).
  10. Binbin Yan & Minghui Hu & Kun Feng & Zhinong Jiang, 2021. "Enhanced Component Analytical Solution for Performance Adaptation and Diagnostics of Gas Turbines," Energies, MDPI, vol. 14(14), pages 1-20, July.
  11. Huang, Qinni & Gu, Xiwen & Zhang, Hongwei & Sun, Jiahao & Yang, Shixi, 2025. "An adaptive performance map generation method through shape feature fusion for the gas turbine compressor," Energy, Elsevier, vol. 320(C).
  12. Wang, Yuqi & Liu, Tianyuan & Meng, Yue & Zhang, Di & Xie, Yonghui, 2022. "Integrated optimization for design and operation of turbomachinery in a solar-based Brayton cycle based on deep learning techniques," Energy, Elsevier, vol. 252(C).
  13. Kang, Do Won & Kim, Tong Seop, 2018. "Model-based performance diagnostics of heavy-duty gas turbines using compressor map adaptation," Applied Energy, Elsevier, vol. 212(C), pages 1345-1359.
  14. Kim, Sangjo, 2021. "A new performance adaptation method for aero gas turbine engines based on large amounts of measured data," Energy, Elsevier, vol. 221(C).
  15. Kim, Sangjo & Kim, Kuisoon & Son, Changmin, 2020. "A new transient performance adaptation method for an aero gas turbine engine," Energy, Elsevier, vol. 193(C).
  16. Liao, Zengbu & Zhan, Keyi & Zhao, Hang & Deng, Yuntao & Geng, Jia & Chen, Xuefeng & Song, Zhiping, 2024. "Addressing class-imbalanced learning in real-time aero-engine gas-path fault diagnosis via feature filtering and mapping," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
  17. Tahan, Mohammadreza & Tsoutsanis, Elias & Muhammad, Masdi & Abdul Karim, Z.A., 2017. "Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review," Applied Energy, Elsevier, vol. 198(C), pages 122-144.
  18. Chen, Yu-Zhi & Zhang, Wei-Gang & Tsoutsanis, Elias & Zhao, Junjie & Tam, Ivan C.K. & Gou, Lin-Feng, 2025. "An advanced performance-based method for soft and abrupt fault diagnosis of industrial gas turbines," Energy, Elsevier, vol. 321(C).
  19. Ma, Yujia & Liu, Jinfu & Zhu, Linhai & Li, Qi & Guo, Yaqiong & Liu, Huanpeng & Yu, Daren, 2022. "Multi-objective performance optimization and control for gas turbine Part-load operation Energy-saving and NOx emission reduction," Applied Energy, Elsevier, vol. 320(C).
  20. Likun Ren & Haiqin Qin & Zhenbo Xie & Jing Xie & Bianjiang Li, 2022. "A Thermodynamics-Oriented and Neural Network-Based Hybrid Model for Military Turbofan Engines," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
  21. Tsoutsanis, Elias & Meskin, Nader & Benammar, Mohieddine & Khorasani, Khashayar, 2016. "A dynamic prognosis scheme for flexible operation of gas turbines," Applied Energy, Elsevier, vol. 164(C), pages 686-701.
  22. Cody Allen & Mauricio Oliveira, 2022. "A Minimal Cardinality Solution to Fitting Sawtooth Piecewise-Linear Functions," Journal of Optimization Theory and Applications, Springer, vol. 192(3), pages 930-959, March.
  23. Xu, Maojun & Liu, Jinxin & Li, Ming & Geng, Jia & Wu, Yun & Song, Zhiping, 2022. "Improved hybrid modeling method with input and output self-tuning for gas turbine engine," Energy, Elsevier, vol. 238(PA).
  24. Son, In Woo & Jeong, Yongju & Son, Seongmin & Park, Jung Hwan & Lee, Jeong Ik, 2022. "Techno-economic evaluation of solar-nuclear hybrid system for isolated grid," Applied Energy, Elsevier, vol. 306(PA).
  25. Chen, Yu-Zhi & Zhao, Xu-Dong & Xiang, Heng-Chao & Tsoutsanis, Elias, 2021. "A sequential model-based approach for gas turbine performance diagnostics," Energy, Elsevier, vol. 220(C).
  26. Jin, Zexi & Liu, Jinxin & Xu, Maojun & Wang, Kang & Zhao, Hang & Song, Zhiping, 2026. "Improving the reliability of aero-engine control system via virtual sensor-assisted fault-tolerant control," Reliability Engineering and System Safety, Elsevier, vol. 266(PA).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.