Research outputs
Selected research outputs
- Aleatory uncertainty quantification based on multi-fidelity deep neural networks (Journal article - 2024)
- Investigation of Compressor Cascade Flow Using Physics-Informed Neural Networks with Adaptive Learning Strategy (Journal article - 2024)
- High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks (Journal article - 2023)
- Windage Torque Reduction in Low-Pressure Turbine Cavities Part I: Concept Design and Numerical Investigations (Journal article - 2024)
- High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multi-Fidelity Deep Neural Networks (Conference Paper - 2023)
- Investigation of endwall effect on transitional flow inside compressor cascade passage at low Reynolds number (Journal article - 2021)
- Physical Mechanisms Investigation of Sharkskin-Inspired Compressor Cascade Based on Large Eddy Simulations (Journal article - 2021)
- Effect of Nonuniform Tip Clearance on the Performance of Transonic Axial Compressors (Journal article - 2018)
- Review of design optimization methods for turbomachinery aerodynamics (Journal article - 2017)
- Blade-end treatment for axial compressors based on optimization method (Journal article - 2017)
2025
Physics-Guided Graph Neural Networks: Numerical Investigation of High-Pressure Turbine Flow
Li, Z., & Montomoli, F. (2025). Physics-Guided Graph Neural Networks: Numerical Investigation of High-Pressure Turbine Flow. Journal of Turbomachinery, 147(12). doi:10.1115/1.4068832
Machine Learning-based regional cooling demand prediction with Optimized dataset partitioning
Zhang, M., Li, Z., & Yu, Z. (2025). Machine Learning-based regional cooling demand prediction with Optimized dataset partitioning. ENERGY AND BUILDINGS, 344. doi:10.1016/j.enbuild.2025.116004
Control of Shroud Leakage Loss and Windage Torque in a Low-Pressure Turbine Stage
Christodoulou, L., Li, Z., Ambrose, S., Jefferson-Loveday, R., Jackson, R., Lock, G., . . . Scobie, J. (2025). Control of Shroud Leakage Loss and Windage Torque in a Low-Pressure Turbine Stage. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 147(4). doi:10.1115/1.4066816
Optimization of Pin Fins Using Computational Fluid Dynamics and Machine Learning
Sarosi, R., Montomoli, F., Li, Z., & Agarwal, R. K. (2024). Optimization of Pin Fins Using Computational Fluid Dynamics and Machine Learning. Journal of Thermophysics and Heat Transfer, 1-13. doi:10.2514/1.t6984
2024
Physics Guided Graph Neural Networks (PG-GNNs): Numerical Investigation of High-Pressure Turbine Flow
Li, Z., & Montomoli, F. (2024). Physics Guided Graph Neural Networks (PG-GNNs): Numerical Investigation of High-Pressure Turbine Flow. In Volume 12D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery. American Society of Mechanical Engineers. doi:10.1115/gt2024-123649
Windage Torque Reduction in Low-Pressure Turbine Cavities Part I: Concept Design and Numerical Investigations
Li, Z., Christodoulou, L., Jefferson-Loveday, R., Ambrose, S., Jackson, R., Lock, G. D., . . . Scobie, J. A. (2024). Windage Torque Reduction in Low-Pressure Turbine Cavities Part I: Concept Design and Numerical Investigations. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 146(6). doi:10.1115/1.4064224
Windage Torque Reduction in Low-Pressure Turbine Cavities Part II: Experimental and Numerical Results
Jackson, R. W., Li, Z., Christodoulou, L., Ambrose, S., Sangan, C. M., Jefferson-Loveday, R., . . . Scobie, J. A. (2024). Windage Torque Reduction in Low-Pressure Turbine Cavities Part II: Experimental and Numerical Results. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 146(6). doi:10.1115/1.4063876
Aleatory uncertainty quantification based on multi-fidelity deep neural networks
Li, Z., & Montomoli, F. (2024). Aleatory uncertainty quantification based on multi-fidelity deep neural networks. RELIABILITY ENGINEERING & SYSTEM SAFETY, 245. doi:10.1016/j.ress.2024.109975
Investigation of Compressor Cascade Flow Using Physics-Informed Neural Networks with Adaptive Learning Strategy
Li, Z., Montomoli, F., & Sharma, S. (2024). Investigation of Compressor Cascade Flow Using Physics-Informed Neural Networks with Adaptive Learning Strategy. AIAA JOURNAL, 62(4), 1400-1410. doi:10.2514/1.J063562
2023
High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks
Li, Z., Montomoli, F., Casari, N., & Pinelli, M. (2023). High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multifidelity Deep Neural Networks. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 145(11). doi:10.1115/1.4063391
Influence of swirl and ingress on windage losses in a low-pressure turbine stator-well cavity
Jackson, R., Christodoulou, L., Li, Z., Sangan, C. M., Ambrose, S., Jefferson-Loveday, R., . . . Scobie, J. A. (2023). Influence of swirl and ingress on windage losses in a low-pressure turbine stator-well cavity. EXPERIMENTS IN FLUIDS, 64(11). doi:10.1007/s00348-023-03715-7
High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multi-Fidelity Deep Neural Networks
Li, Z., Montomoli, F., Casari, N., & Pinelli, M. (2023). High-Dimensional Uncertainty Quantification of High-Pressure Turbine Vane Based on Multi-Fidelity Deep Neural Networks. In Volume 13D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery. American Society of Mechanical Engineers. doi:10.1115/gt2023-101698
Windage Torque Reduction in Low-Pressure Turbine Cavities - Part 1: Concept Design and Numerical Investigations
Li, Z., Christodoulou, L., Jefferson-Loveday, R., Ambrose, S., Jackson, R., Lock, G. D., . . . Scobie, J. A. (2023). Windage Torque Reduction in Low-Pressure Turbine Cavities - Part 1: Concept Design and Numerical Investigations. In Volume 13B: Turbomachinery — Axial Flow Turbine Aerodynamics. American Society of Mechanical Engineers. doi:10.1115/gt2023-103532
Windage Torque Reduction in Low-Pressure Turbine Cavities Part 2: Experimental and Numerical Results
Jackson, R., Lock, G. D., Sangan, C. M., Scobie, J. A., Li, Z., Christodoulou, L., . . . Ambrose, S. (2023). Windage Torque Reduction in Low-Pressure Turbine Cavities Part 2: Experimental and Numerical Results. In Volume 13B: Turbomachinery — Axial Flow Turbine Aerodynamics. American Society of Mechanical Engineers. doi:10.1115/gt2023-102311
2022
Numerical Simulations and Design Optimization of Compressor Cascade Flow Using One Equation and Wray-Agarwal Turbulence Model
Li, Z., & Agarwal, R. K. (2022). Numerical Simulations and Design Optimization of Compressor Cascade Flow Using One Equation and Wray-Agarwal Turbulence Model. INTERNATIONAL JOURNAL OF COMPUTATIONAL FLUID DYNAMICS, 36(8), 705-718. doi:10.1080/10618562.2023.2187050
2021
Investigation of endwall effect on transitional flow inside compressor cascade passage at low Reynolds number
Li, Z., & Agarwal, R. K. (2021). Investigation of endwall effect on transitional flow inside compressor cascade passage at low Reynolds number. PHYSICS OF FLUIDS, 33(11). doi:10.1063/5.0069254
Physical Mechanisms Investigation of Sharkskin-Inspired Compressor Cascade Based on Large Eddy Simulations
Li, Z., Jin, Y., Du, J., Zhang, H., & Nie, C. (2021). Physical Mechanisms Investigation of Sharkskin-Inspired Compressor Cascade Based on Large Eddy Simulations. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 143(6). doi:10.1115/1.4050147
A study of fan-distortion interaction within the fan rotor
Li, Z., Du, J., Zhang, Q., Ji, G., & Zhang, H. (2021). A study of fan-distortion interaction within the fan rotor. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART A-JOURNAL OF POWER AND ENERGY, 235(2), 185-201. doi:10.1177/0957650920920044
2020
Design optimization of axial slot casing treatment in a highly-loaded mixed-flow compressor
Ba, D., Zhang, Q., Du, J., Li, Z., Zhang, H., & Nie, C. (2020). Design optimization of axial slot casing treatment in a highly-loaded mixed-flow compressor. AEROSPACE SCIENCE AND TECHNOLOGY, 107. doi:10.1016/j.ast.2020.106262
Physical Mechanisms Investigation of Sharkskin-Inspired Compressor Cascade Based on Large Eddy Simulations
Li, Z., Du, J., & Zhang, H. (2020). Physical Mechanisms Investigation of Sharkskin-Inspired Compressor Cascade Based on Large Eddy Simulations. In Volume 2A: Turbomachinery. American Society of Mechanical Engineers. doi:10.1115/gt2020-15209
2019
Entropy Generation Analysis in a Mixed-Flow Compressor with Casing Treatment
Zhang, Q., Du, J., Li, Z., Li, J., & Zhang, H. (2019). Entropy Generation Analysis in a Mixed-Flow Compressor with Casing Treatment. JOURNAL OF THERMAL SCIENCE, 28(5), 915-928. doi:10.1007/s11630-019-1206-5
Performance enhancement of industrial high loaded gas compressor using Coanda jet flap
Du, J., Li, Y., Li, Z., Li, J., Wang, Z., & Zhang, H. (2019). Performance enhancement of industrial high loaded gas compressor using Coanda jet flap. ENERGY, 172, 618-629. doi:10.1016/j.energy.2019.01.163
Improving Aerodynamic Performance of a Highly Loaded Compressor Based on Coanda Jet Flap
Du, J., Li, Y., Li, Z., Li, J., Wang, Z., & Zhang, H. (2019). Improving Aerodynamic Performance of a Highly Loaded Compressor Based on Coanda Jet Flap. In Volume 2A: Turbomachinery. American Society of Mechanical Engineers. doi:10.1115/gt2019-91552
2018
Optimization of rough transonic axial compressor
Li, Z., & Liu, Y. (2018). Optimization of rough transonic axial compressor. AEROSPACE SCIENCE AND TECHNOLOGY, 78, 12-25. doi:10.1016/j.ast.2018.03.031
Robust Optimization Design of Single-Stage Transonic Axial Compressor Considering the Manufacturing Uncertainties
Li, Z., Liu, Y., & Agarwal, R. K. (2018). Robust Optimization Design of Single-Stage Transonic Axial Compressor Considering the Manufacturing Uncertainties. In Volume 2D: Turbomachinery. American Society of Mechanical Engineers. doi:10.1115/gt2018-75415
Effect of Nonuniform Tip Clearance on the Performance of Transonic Axial Compressors
Li, Z., Liu, Y., Ji, L., & Agarwal, R. K. (2018). Effect of Nonuniform Tip Clearance on the Performance of Transonic Axial Compressors. JOURNAL OF PROPULSION AND POWER, 34(3), 808-818. doi:10.2514/1.B36617
Uncertainty Quantification of Geometric and Flow Variables Affecting the Performance of a Transonic Axial Compressor
Li, Z., Liu, Y., & Agarwal, R. K. (2018). Uncertainty Quantification of Geometric and Flow Variables Affecting the Performance of a Transonic Axial Compressor. In 2018 AIAA Aerospace Sciences Meeting. American Institute of Aeronautics and Astronautics. doi:10.2514/6.2018-0068
2017
Review of design optimization methods for turbomachinery aerodynamics
Li, Z., & Zheng, X. (2017). Review of design optimization methods for turbomachinery aerodynamics. PROGRESS IN AEROSPACE SCIENCES, 93, 1-23. doi:10.1016/j.paerosci.2017.05.003
Effect of end-wall roughness on performance of transonic axial compressor
Li, Z., & Liu, Y. (2017). Effect of end-wall roughness on performance of transonic axial compressor. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 231(7), 1213-1224. doi:10.1177/0954410016650910
Blade-end treatment for axial compressors based on optimization method
Li, Z., & Liu, Y. (2017). Blade-end treatment for axial compressors based on optimization method. ENERGY, 126, 217-230. doi:10.1016/j.energy.2017.03.021
Blade-end treatment to improve the performance of axial compressors: An overview
Zheng, X., & Li, Z. (2017). Blade-end treatment to improve the performance of axial compressors: An overview. PROGRESS IN AEROSPACE SCIENCES, 88, 1-14. doi:10.1016/j.paerosci.2016.09.001
2016
The effect of end wall boundary layer on matching and corresponding flow control technique for multistage axial compressor
Li, Z., Zheng, X., Liu, Y., Li, Q., & Ji, B. (2016). The effect of end wall boundary layer on matching and corresponding flow control technique for multistage axial compressor. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 230(12), 2179-2194. doi:10.1177/0954410015621928