Mr Shahin Alipour Bonab
- Research Assistant (Autonomous Systems & Connectivity)
- Student IT Helpdesk Assistant (Business Relationship Management)
email:
Shahin.AlipourBonab@glasgow.ac.uk
pronouns:
He/him/his
Publications
2024
Alipour Bonab, S. , Waite, T., Song, W. , Flynn, D. and Yazdani-Asrami, M. (2024) Machine learning-powered performance monitoring of proton exchange membrane water electrolyzers for enhancing green hydrogen production as a sustainable fuel for aviation industry. Energy Reports, 12, pp. 2270-2282. (doi: 10.1016/j.egyr.2024.08.028)
Alipour Bonab, S. and Yazdani-Asrami, M. (2024) Artificial intelligence-based model to predict the heat transfer coefficient in flow boiling of liquid hydrogen as fuel and cryogenic coolant in future hydrogen-powered cryo-electric aviation. Fuel, 381(A), 133323. (doi: 10.1016/j.fuel.2024.133323)
Alipour Bonab, S. and Yazdani-Asrami, M. (2024) Investigation on the heat transfer estimation of subcooled liquid hydrogen for transportation applications using intelligent technique. International Journal of Hydrogen Energy, 84, pp. 468-479. (doi: 10.1016/j.ijhydene.2024.08.257)
Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2024) Enhancing the predictive modeling of n-value surfaces in various high temperature superconducting materials using a feed-forward deep neural network technique. Crystals, 14(7), 619. (doi: 10.3390/cryst14070619)
Alipour Bonab, S. , Xing, Y., Russo, G., Fabbri, M., Morandi, A., Bernstein, P., Noudem, J. and Yazdani-Asrami, M. (2024) Estimation of magnetic levitation and lateral forces in MgB2 superconducting bulks with various dimensional sizes using artificial intelligence techniques. Superconductor Science and Technology, (doi: 10.1088/1361-6668/ad4e77) (Early Online Publication)
Alipour Bonab, S. , Russo, G., Morandi, A. and Yazdani-Asrami, M. (2024) A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes. Machine Learning: Science and Technology, (doi: 10.1088/2632-2153/ad45b1) (Early Online Publication)
Alipour Bonab, S. , Sadeghi, A. and Yazdani-Asrami, M. (2024) Artificial Intelligence-based surrogate model for computation of the electric field of high voltage transmission line ceramic insulator with Corona ring. World Journal of Engineering, (doi: 10.1108/WJE-11-2023-0478) (Early Online Publication)
Sadeghi, A., Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2024) Intelligent estimation of critical current degradation in HTS tapes under repetitive overcurrent cycling for cryo-electric transportation applications. Materials Today Physics, 42, 101365. (doi: 10.1016/j.mtphys.2024.101365)
Sadeghi, A., Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2024) Short circuit analysis of a fault-tolerant current-limiting high temperature superconducting transformer in a power system in presence of distributed generations. Superconductivity, 9, 100085. (doi: 10.1016/j.supcon.2024.100085)
2023
Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2023) A new intelligent estimation method based on the Cascade Forward Neural Network for the Electric and Magnetic fields in the vicinity of the High Voltage Overhead Transmission Lines. Applied Sciences, 13(20), 11180. (doi: 10.3390/app132011180)
Articles
Alipour Bonab, S. , Waite, T., Song, W. , Flynn, D. and Yazdani-Asrami, M. (2024) Machine learning-powered performance monitoring of proton exchange membrane water electrolyzers for enhancing green hydrogen production as a sustainable fuel for aviation industry. Energy Reports, 12, pp. 2270-2282. (doi: 10.1016/j.egyr.2024.08.028)
Alipour Bonab, S. and Yazdani-Asrami, M. (2024) Artificial intelligence-based model to predict the heat transfer coefficient in flow boiling of liquid hydrogen as fuel and cryogenic coolant in future hydrogen-powered cryo-electric aviation. Fuel, 381(A), 133323. (doi: 10.1016/j.fuel.2024.133323)
Alipour Bonab, S. and Yazdani-Asrami, M. (2024) Investigation on the heat transfer estimation of subcooled liquid hydrogen for transportation applications using intelligent technique. International Journal of Hydrogen Energy, 84, pp. 468-479. (doi: 10.1016/j.ijhydene.2024.08.257)
Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2024) Enhancing the predictive modeling of n-value surfaces in various high temperature superconducting materials using a feed-forward deep neural network technique. Crystals, 14(7), 619. (doi: 10.3390/cryst14070619)
Alipour Bonab, S. , Xing, Y., Russo, G., Fabbri, M., Morandi, A., Bernstein, P., Noudem, J. and Yazdani-Asrami, M. (2024) Estimation of magnetic levitation and lateral forces in MgB2 superconducting bulks with various dimensional sizes using artificial intelligence techniques. Superconductor Science and Technology, (doi: 10.1088/1361-6668/ad4e77) (Early Online Publication)
Alipour Bonab, S. , Russo, G., Morandi, A. and Yazdani-Asrami, M. (2024) A comprehensive machine learning-based investigation for the index-value prediction of 2G HTS coated conductor tapes. Machine Learning: Science and Technology, (doi: 10.1088/2632-2153/ad45b1) (Early Online Publication)
Alipour Bonab, S. , Sadeghi, A. and Yazdani-Asrami, M. (2024) Artificial Intelligence-based surrogate model for computation of the electric field of high voltage transmission line ceramic insulator with Corona ring. World Journal of Engineering, (doi: 10.1108/WJE-11-2023-0478) (Early Online Publication)
Sadeghi, A., Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2024) Intelligent estimation of critical current degradation in HTS tapes under repetitive overcurrent cycling for cryo-electric transportation applications. Materials Today Physics, 42, 101365. (doi: 10.1016/j.mtphys.2024.101365)
Sadeghi, A., Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2024) Short circuit analysis of a fault-tolerant current-limiting high temperature superconducting transformer in a power system in presence of distributed generations. Superconductivity, 9, 100085. (doi: 10.1016/j.supcon.2024.100085)
Alipour Bonab, S. , Song, W. and Yazdani-Asrami, M. (2023) A new intelligent estimation method based on the Cascade Forward Neural Network for the Electric and Magnetic fields in the vicinity of the High Voltage Overhead Transmission Lines. Applied Sciences, 13(20), 11180. (doi: 10.3390/app132011180)