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A general methodology for performance prediction of pumps-as-turbines using Artificial Neural Networks

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Cited by:

  1. Huican Luo & Peijian Zhou & Lingfeng Shu & Jiegang Mou & Haisheng Zheng & Chenglong Jiang & Yantian Wang, 2022. "Energy Performance Curves Prediction of Centrifugal Pumps Based on Constrained PSO-SVR Model," Energies, MDPI, vol. 15(9), pages 1-19, May.
  2. Ping, Xu & Yang, Fubin & Zhang, Hongguang & Zhang, Jian & Zhang, Wujie & Song, Gege, 2021. "Introducing machine learning and hybrid algorithm for prediction and optimization of multistage centrifugal pump in an ORC system," Energy, Elsevier, vol. 222(C).
  3. Kim, Sangjo & Kim, Kuisoon & Son, Changmin, 2020. "Transient system simulation for an aircraft engine using a data-driven model," Energy, Elsevier, vol. 196(C).
  4. Pugliese, Francesco & Fontana, Nicola & Marini, Gustavo & Giugni, Maurizio, 2021. "Experimental assessment of the impact of number of stages on vertical axis multi-stage centrifugal PATs," Renewable Energy, Elsevier, vol. 178(C), pages 891-903.
  5. Balacco, Gabriella & Fiorese, Gaetano Daniele & Alfio, Maria Rosaria & Totaro, Vincenzo & Binetti, Mario & Torresi, Marco & Stefanizzi, Michele, 2023. "PaT-ID: A tool for the selection of the optimal pump as turbine for a water distribution network," Energy, Elsevier, vol. 282(C).
  6. Telikani, Akbar & Rossi, Mosé & Khajehali, Naghmeh & Renzi, Massimiliano, 2023. "Pumps-as-Turbines’ (PaTs) performance prediction improvement using evolutionary artificial neural networks," Applied Energy, Elsevier, vol. 330(PA).
  7. Wang, Yuqi & Du, Qiuwan & Li, Yunzhu & Zhang, Di & Xie, Yonghui, 2022. "Field reconstruction and off-design performance prediction of turbomachinery in energy systems based on deep learning techniques," Energy, Elsevier, vol. 238(PB).
  8. Stefanizzi, M. & Filannino, D. & Capurso, T. & Camporeale, S.M. & Torresi, M., 2023. "Optimal hydraulic energy harvesting strategy for PaT installation in Water Distribution Networks," Applied Energy, Elsevier, vol. 344(C).
  9. Maria Castorino, Giulia Anna & Manservigi, Lucrezia & Barbarelli, Silvio & Losi, Enzo & Venturini, Mauro, 2023. "Development and validation of a comprehensive methodology for predicting PAT performance curves," Energy, Elsevier, vol. 274(C).
  10. Jiang, Chiju & Zhang, Weihao & Li, Ya & Li, Lele & Wang, Yufan & Huang, Dongming, 2023. "Multi-scale Pix2Pix network for high-fidelity prediction of adiabatic cooling effectiveness in turbine cascade," Energy, Elsevier, vol. 265(C).
  11. Lin, Tong & Li, Xiaojun & Zhu, Zuchao & Xie, Jing & Li, Yi & Yang, Hui, 2021. "Application of enstrophy dissipation to analyze energy loss in a centrifugal pump as turbine," Renewable Energy, Elsevier, vol. 163(C), pages 41-55.
  12. Chacón, Miguel Crespo & Rodríguez Díaz, Juan Antonio & Morillo, Jorge García & McNabola, Aonghus, 2021. "Evaluation of the design and performance of a micro hydropower plant in a pressurised irrigation network: Real world application at farm-level in Southern Spain," Renewable Energy, Elsevier, vol. 169(C), pages 1106-1120.
  13. Gabriella Balacco, 2018. "Performance Prediction of a Pump as Turbine: Sensitivity Analysis Based on Artificial Neural Networks and Evolutionary Polynomial Regression," Energies, MDPI, vol. 11(12), pages 1-17, December.
  14. Kandi, Ali & Moghimi, Mahdi & Tahani, Mojtaba & Derakhshan, Shahram, 2021. "Optimization of pump selection for running as turbine and performance analysis within the regulation schemes," Energy, Elsevier, vol. 217(C).
  15. Zhang, Yiming & Li, Jingxiang & Fei, Liangyu & Feng, Zhiyan & Gao, Jingzhou & Yan, Wenpeng & Zhao, Shengdun, 2023. "Operational performance estimation of vehicle electric coolant pump based on the ISSA-BP neural network," Energy, Elsevier, vol. 268(C).
  16. Li, Jinxing & Liu, Tianyuan & Zhu, Guangya & Li, Yunzhu & Xie, Yonghui, 2023. "Uncertainty quantification and aerodynamic robust optimization of turbomachinery based on graph learning methods," Energy, Elsevier, vol. 273(C).
  17. Renzi, Massimiliano & Rudolf, Pavel & Štefan, David & Nigro, Alessandra & Rossi, Mosè, 2019. "Installation of an axial Pump-as-Turbine (PaT) in a wastewater sewer of an oil refinery: A case study," Applied Energy, Elsevier, vol. 250(C), pages 665-676.
  18. Du, Qiuwan & Yang, Like & Li, Liangliang & Liu, Tianyuan & Zhang, Di & Xie, Yonghui, 2022. "Aerodynamic design and optimization of blade end wall profile of turbomachinery based on series convolutional neural network," Energy, Elsevier, vol. 244(PA).
  19. Leguizamón, Sebastián & Avellan, François, 2020. "Computational parametric analysis of the design of cross-flow turbines under constraints," Renewable Energy, Elsevier, vol. 159(C), pages 300-311.
  20. Chen, Zhihuan & Yuan, Xiaohui & Yuan, Yanbin & Lei, Xiaohui & Zhang, Binqiao, 2019. "Parameter estimation of fuzzy sliding mode controller for hydraulic turbine regulating system based on HICA algorithm," Renewable Energy, Elsevier, vol. 133(C), pages 551-565.
  21. Ávila, Carlos Andrés Macías & Sánchez-Romero, Francisco-Javier & López-Jiménez, P. Amparo & Pérez-Sánchez, Modesto, 2021. "Optimization tool to improve the management of the leakages and recovered energy in irrigation water systems," Agricultural Water Management, Elsevier, vol. 258(C).
  22. Diamantis Karakatsanis & Nicolaos Theodossiou, 2022. "Smart Hydropower Water Distribution Networks, Use of Artificial Intelligence Methods and Metaheuristic Algorithms to Generate Energy from Existing Water Supply Networks," Energies, MDPI, vol. 15(14), pages 1-21, July.
  23. Crespo Chacón, Miguel & Rodríguez Díaz, Juan Antonio & García Morillo, Jorge & McNabola, Aonghus, 2020. "Hydropower energy recovery in irrigation networks: Validation of a methodology for flow prediction and pump as turbine selection," Renewable Energy, Elsevier, vol. 147(P1), pages 1728-1738.
  24. Venturini, Mauro & Manservigi, Lucrezia & Alvisi, Stefano & Simani, Silvio, 2018. "Development of a physics-based model to predict the performance of pumps as turbines," Applied Energy, Elsevier, vol. 231(C), pages 343-354.
  25. Tahani, Mojtaba & Kandi, Ali & Moghimi, Mahdi & Houreh, Shahram Derakhshan, 2020. "Rotational speed variation assessment of centrifugal pump-as-turbine as an energy utilization device under water distribution network condition," Energy, Elsevier, vol. 213(C).
  26. Rossi, Mosè & Nigro, Alessandra & Renzi, Massimiliano, 2019. "Experimental and numerical assessment of a methodology for performance prediction of Pumps-as-Turbines (PaTs) operating in off-design conditions," Applied Energy, Elsevier, vol. 248(C), pages 555-566.
  27. Binama, Maxime & Su, Wen-Tao & Cai, Wei-Hua & Li, Xiao-Bin & Muhirwa, Alexis & Li, Biao & Bisengimana, Emmanuel, 2019. "Blade trailing edge position influencing pump as turbine (PAT) pressure field under part-load conditions," Renewable Energy, Elsevier, vol. 136(C), pages 33-47.
  28. Stefanizzi, Michele & Capurso, Tommaso & Balacco, Gabriella & Binetti, Mario & Camporeale, Sergio Mario & Torresi, Marco, 2020. "Selection, control and techno-economic feasibility of Pumps as Turbines in Water Distribution Networks," Renewable Energy, Elsevier, vol. 162(C), pages 1292-1306.
  29. Renzi, Massimiliano & Nigro, Alessandra & Rossi, Mosè, 2020. "A methodology to forecast the main non-dimensional performance parameters of pumps-as-turbines (PaTs) operating at Best Efficiency Point (BEP)," Renewable Energy, Elsevier, vol. 160(C), pages 16-25.
  30. Jacopo Carlo Alberizzi & Massimiliano Renzi & Maurizio Righetti & Giuseppe Roberto Pisaturo & Mosè Rossi, 2019. "Speed and Pressure Controls of Pumps-as-Turbines Installed in Branch of Water-Distribution Network Subjected to Highly Variable Flow Rates," Energies, MDPI, vol. 12(24), pages 1-18, December.
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