[HTML][HTML] Soft computing investigation of stand-alone gas turbine and hybrid gas turbine–solid oxide fuel cell systems via artificial intelligence and multi-objective grey …

A Hasanzadeh, A Chitsaz, A Ghasemi, P Mojaver… - Energy Reports, 2022 - Elsevier
Despite of huge effort performed in the literature encompassing the concept of hybrid solid
oxide fuel cell–gas turbine (SOFC-GT), the economic and environmental superiority of this …

Transient temperature fields of the tank vehicle with various parameters using deep learning method

F Zhu, J Chen, D Ren, Y Han - Applied Thermal Engineering, 2023 - Elsevier
Calculation of transient temperature fields is widely used in engineering application and is
also very crucial. Nevertheless, the existing methods for the prediction of complex transient …

Thermal radiation correction formula of the scaling criteria for film cooling of turbine blades

H Li, M Wang, R You, S Liu - Energy, 2023 - Elsevier
Adiabatic effectiveness (η) is the most important parameter for evaluating film cooling
capacity. For turbine blades, it is usually based on the scaling criteria to achieve the …

Predicting the energy and exergy performance of F135 PW100 turbofan engine via deep learning approach

M Sabzehali, AH Rabiee, M Alibeigi… - Energy Conversion and …, 2022 - Elsevier
In the present study, the effects of flight-Mach number, flight altitude, fuel types, and intake
air temperature on thrust specific fuel consumption, thrust, intake air mass flow rate, thermal …

Multi-fidelity graph neural network for flow field data fusion of turbomachinery

J Li, Y Li, T Liu, D Zhang, Y Xie - Energy, 2023 - Elsevier
Efficient and accurate prediction of the flow field in turbomachinery is vital for tasks such as
optimization and off-design modeling. Deep learning methods offer inspiring tools for flow …

Study on the film superposition method for dense multirow film Hole layouts

F Zhang, C Liu, L Ye, Y Ran, T Zhou, H Yan - Energy, 2024 - Elsevier
The film superposition method is an important tool in the design of film cooling structures.
The method can quickly predict the temperature at the film cooling surface and reduce the …

A Review of Machine Learning Methods in Turbine Cooling Optimization

L Xu, S Jin, W Ye, Y Li, J Gao - Energies, 2024 - mdpi.com
In the current design work, turbine performance requirements are getting higher and higher,
and turbine blade design needs multiple rounds of iterative optimization. Three-dimensional …

Fast performance prediction and field reconstruction of gas turbine using supervised graph learning approaches

J Li, Y Wang, Z Qiu, D Zhang, Y Xie - Aerospace Science and Technology, 2023 - Elsevier
Accurately and rapidly predicting the multi-conditions characteristics of turbines is
fundamental for realizing efficient energy conversion and optimal layout schemes. Based on …

Numerical Study on Cooling Performance of a Steam-Cooled Blade Based on Response Surface Method

Z Zhao, L Xi, J Gao, L Xu, Y Li - Applied Sciences, 2023 - mdpi.com
In order to investigate the cooling mechanism of the turbine blade and to enrich and
supplement the experimental study of the blade, a numerical study of a steam-cooled blade …

Numerical study on cooling characteristics of turbine blade based on laminated cooling configuration with clapboards

Z Chen, X Chen, XF Yang, B Yu, B Wang, J Zhu… - Energy, 2024 - Elsevier
The double-wall configuration, characterized by its notable overall cooling effectiveness,
serves as a pivotal reference configuration in the design of next-generation turbine blades …