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Modeling of Turbojet and Gas Turbine Engine for Minimal Environmental Impact

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "I2: Energy and Combustion Science".

Deadline for manuscript submissions: closed (21 March 2023) | Viewed by 5042

Special Issue Editor


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Guest Editor
Department of Aeronautical, Faculty of Engineering, Sathyabama Institute of Science and Technology, Chennai, India
Interests: aerodynamics; renewable energy; aircraft design; microgas turbine engines

Special Issue Information

Dear Colleagues,

Pollutant emissions from the aviation industry are of greatest concern for the environment. Due to the massive development of air traffic, the harmful pollutants (NOx, CO, SOx and HC) emitted by gas turbine and other turbo engines are dramatically increasing every day. In general, aviation engines impact local air quality and the global climate. By modifying the engine with optimum materials and combustor design, the possibility of a reduction in the formation of the carbon is viable. Over a few years, novel technologies in the aviation industry have reduced the emission of greenhouse gases by 50% by implementing advanced materials and combustion chambers. Using conventional combustors results in an improper air–fuel mixture ratio and leads to a higher local temperature in the combustor, which results in increased formation of NO and soot.  On the other hand, the utilization of biofuel for aviation is a promising option for meeting global energy needs without any collateral damage to the environment. The addition of biofuel to gas turbine engines results in effective thrust production with less formation of carbon than fossil fuels. Furthermore, the dispersion of nanoparticles in biofuel blends can realize higher thrust production with minimal damage to the environment. The intention of this Special Issue is to invite quality research and review articles on the design, development and simulation of gas turbine and turbojet engines.  

Dr. Manigandan Sekar
Guest Editor

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Keywords

  • experimental and numerical analysis of combustors
  • combustion chamber design
  • high-temperature materials and coatings
  • advanced fuel technology: biofuel, hydrogen and electricity
  • microgas turbine engines
  • exergetic performance of gas turbine engines
  • machine learning and other analytical approaches in engine design
  • assessment of risk in gas turbine engine modeling
  • prediction of emissions from aviation jets
  • unmanned ariel vehicles

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Published Papers (2 papers)

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Research

19 pages, 7609 KiB  
Article
Aerothermal Performance and Soot Emissions of Reacting Flow in a Micro-Gas Turbine Combustor
by Heyu Wang and Kai Hong Luo
Energies 2023, 16(7), 2947; https://doi.org/10.3390/en16072947 - 23 Mar 2023
Cited by 1 | Viewed by 2187
Abstract
Micro-gas turbines are used for power generation and propulsion in unmanned aerial vehicles. Despite the growing demand for electric engines in a world striving for a net zero carbon footprint, combustion gas turbines will continue to play a critical role. Hence, there is [...] Read more.
Micro-gas turbines are used for power generation and propulsion in unmanned aerial vehicles. Despite the growing demand for electric engines in a world striving for a net zero carbon footprint, combustion gas turbines will continue to play a critical role. Hence, there is a need for improved micro-gas turbines that can meet stringent environmental regulations. This paper is the first part of a comprehensive study focused on understanding the fundamental performance and emission characteristics of a micro-gas turbine model, with the aim of finding ways to enhance its operation. The study used a multidisciplinary CFD model to simulate the reacting flow in the combustion chamber and validated the results against experimental data and throughflow simulations. The present work is one of the few work that attempts to address both the aerothermal performance and emissions of the gas turbine. The findings highlight that parameters such as non-uniform outlet pressure, fuel-to-air ratio, and fuel injection velocity can greatly influence the performance and emissions of the micro-gas turbine. These parameters can affect the combustion efficiency, the formation of hot spots at the combustor–turbine interface, and the soot emissions. The results provide valuable insights for optimizing the performance and reducing the emissions of micro-gas turbines and serve as a foundation for further research into the interaction between the combustor and the turbine. Full article
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22 pages, 2359 KiB  
Article
Extreme Learning Machine-Based Diagnostics for Component Degradation in a Microturbine
by Nicola Menga, Akhila Mothakani, Maria Grazia De Giorgi, Radoslaw Przysowa and Antonio Ficarella
Energies 2022, 15(19), 7304; https://doi.org/10.3390/en15197304 - 4 Oct 2022
Cited by 12 | Viewed by 1996
Abstract
Micro turbojets are used for propelling radio-controlled aircraft, aerial targets, and personal air vehicles. When compared to full-scale engines, they are characterized by relatively low efficiency and durability. In this context, the degraded performance of gas path components could lead to an unacceptable [...] Read more.
Micro turbojets are used for propelling radio-controlled aircraft, aerial targets, and personal air vehicles. When compared to full-scale engines, they are characterized by relatively low efficiency and durability. In this context, the degraded performance of gas path components could lead to an unacceptable reduction in the overall engine performance. In this work, a data-driven model based on a conventional artificial neural network (ANN) and an extreme learning machine (ELM) was used for estimating the performance degradation of the micro turbojet. The training datasets containing the performance data of the engine with degraded components were generated using the validated GSP model and the Monte Carlo approach. In particular, compressor and turbine performance degradation were simulated for three different flight regimes. It was confirmed that component degradation had a similar impact in flight than at sea level. Finally, the datasets were used in the training and testing process of the ELM algorithm with four different input vectors. Two vectors had an extensive number of virtual sensors, and the other two were reduced to just fuel flow and exhaust gas temperature. Even with the small number of sensors, the high prediction accuracy of ELM was maintained for takeoff and cruise but was slightly worse for variable flight conditions. Full article
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