Advances in plasma-assisted ignition and combustion for combustors of aerospace engines

M Li, Z Wang, R Xu, X Zhang, Z Chen… - Aerospace Science and …, 2021 - Elsevier
The improvement of the ignition and combustion performance of aerospace engines under
extreme conditions such as high altitude, low temperature, low pressure, and high speed is …

A review on the corrosion and fatigue failure of gas turbines

L Fathyunes, MA Mohtadi-Bonab - Metals, 2023 - mdpi.com
Since gas turbines are used in airplanes, ship engines and power plants, they play a
significant role in providing sustainable energy. Turbines are designed for a certain lifetime …

A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels

S Fan, Y Wang, S Cao, B Zhao, T Sun, P Liu - Energy, 2022 - Elsevier
Uneven dust accumulation can significantly influence the thermal balance between different
regions of photovoltaic (PV) panels, leading to a sharp decrease in power generation …

Exergoeconomic machine-learning method of integrating a thermochemical Cu–Cl cycle in a multigeneration combined cycle gas turbine for hydrogen production

D Strušnik, J Avsec - International Journal of Hydrogen Energy, 2022 - Elsevier
Integrating new technologies into existing thermal energy systems enables
multigenerational production of energy sources with high efficiency. The advantages of …

Diagnostics using a physics-based engine model in aero gas turbine engine verification tests

S Kim, JH Im, M Kim, J Kim, YI Kim - Aerospace Science and Technology, 2023 - Elsevier
In the present study, the application of a diagnostic method using a physics-based model is
proposed during engine verification testing. A physics-based engine model is constructed …

Use of artificial neural networks to predict fuel consumption on the basis of technical parameters of vehicles

J Ziółkowski, M Oszczypała, J Małachowski… - Energies, 2021 - mdpi.com
This publication presents a multi-faceted analysis of the fuel consumption of motor vehicles
and the way human impacts the environment, with a particular emphasis on the passenger …

Performance prediction and design optimization of turbine blade profile with deep learning method

Q Du, Y Li, L Yang, T Liu, D Zhang, Y Xie - Energy, 2022 - Elsevier
Aerodynamic design optimization of the blade profile is a critical approach to improve
performance of turbomachinery. This paper aims to achieve the performance prediction with …

Machine learning based approach for forecasting emission parameters of mixed flow turbofan engine at high power modes

H Aygun, OO Dursun, S Toraman - Energy, 2023 - Elsevier
To predict aircraft emissions from their own features has become more important as the
usage field of aviation engines is extended to different sectors for different purposes. In the …

Long short-term memory network-based normal pattern group for fault detection of three-shaft marine gas turbine

M Bai, J Liu, Y Ma, X Zhao, Z Long, D Yu - Energies, 2020 - mdpi.com
Fault detection and diagnosis can improve safety and reliability of gas turbines. Current
studies on gas turbine fault detection and diagnosis mainly focus on the case of abundant …

A time-series turbofan engine successive fault diagnosis under both steady-state and dynamic conditions

YZ Chen, E Tsoutsanis, C Wang, LF Gou - Energy, 2023 - Elsevier
In recent years there has been a growing interest in gas turbine fault diagnosis, especially
under dynamic conditions, due to the evolving operating profile of gas turbines and the need …