Schlieren visualization of micro gas turbine exhaust plume with different shapes of nozzle

Choi, Seong Man; Lee, Jeong Seok; Myong, R.S.; Jo, Ha Na; Kim, Jae Won

doi:10.1007/s12650-020-00648-9

Cited by 9 publications

(3 citation statements)

References 10 publications

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“…The intercooling cycle gas turbine is to install an intercooler between the low-pressure compressor and the high-pressure compressor to reduce the compression power consumption of the high-pressure compressor by reducing the gas temperature. The HP coal-fired generator set of indirect cooling cycle machine is two-stage cooling, with simple structure and high unit efficiency [9][10].…”

Section: Intercooled (Regenerative) Cycle Gas Turbinementioning

confidence: 99%

Dynamic Performance Analysis of Gas Turbine with Intermediate Cooling and Regenerative Based on Neural Network Algorithm

2022

KME

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Gas turbine is one of the most important large-scale equipment power plants at present, which has been widely used in the industrial field. Mechanical performance test is a very important parameter for gas turbine. Neural network algorithm can play a great role in system data processing and monitoring. Therefore, in order to observe the dynamic performance of gas turbine, neural network is used to study the data changes related to intermediate cooling and regeneration of gas turbine. This paper mainly uses the experimental method to compare, control the variable of pressure ratio, and analyze its dynamic performance through computer group efficiency, fuel consumption rate and the quality of carbon dioxide and oxygen. The experimental results show that, under rated load, the unit operates with variable pressure ratio. When the pressure ratio is less than 11, if efficiency is required, the unit power can be kept basically constant by changing the fuel quality.

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Section: Intercooled (Regenerative) Cycle Gas Turbinementioning

confidence: 99%

Dynamic Performance Analysis of Gas Turbine with Intermediate Cooling and Regenerative Based on Neural Network Algorithm

2022

KME

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“…Due to their high propulsive efficiency, turbofan engines are currently the most popular propulsion system for different civil or military aircrafts (Benzakein 2014;Choi et al 2020). The transonic rotor of a fan is one of the main components of a turbofan engine.…”

Section: Introductionmentioning

confidence: 99%

Design of an Axial Transonic Rotor by Modified Spanwise Loading Distribution

2021

JAFM

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Improving the aerodynamic performance of the transonic fan in a turbofan engine can be beneficial for both the fuel consumption and maneuverability of an airplane. Deep insight into the supersonic aerodynamics is needed for the simultaneous improvement of all operating parameters of a transonic rotor, including the pressure ratio, efficiency, and surge margin. A design method was developed for an axial transonic rotor by using a combination of radial equilibrium theory, the free vortex method, and a distributed span-wise diffusion factor. The loading distribution obtained by this method was the highest in the hub section and gradually decreased in the tip section. To evaluate the method, a transonic rotor was designed using the geometric parameters and operating conditions of NASA rotor 67. A code was developed to determine a geometry for the new rotor and to modify it. The code was coupled with a RANS flow solver for 3D modification of the new designed rotor. Only standard multi-and double-circular arc airfoils were applied in different radial sections of the new rotor with no blade profile optimization. The results of the RANS equations solution for the new designed rotor showed 1.5% higher efficiency, 3% higher pressure ratio, and more than 1.5 times larger operating range in comparison to NASA rotor 67. The new designed method seems to be an efficient approach that not only improved the efficiency and pressure ratio but also increased the operating range of an axial transonic rotor.

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“…EGR can effectively reduce NOx emissions [3][4]. Some scholars use data based machine learning algorithms to predict the carbon load of DPF in passenger car diesel engines [5][6]. Therefore, in the environment of low-carbon development, it is necessary to study the diesel engine exhaust gas recirculation technology based on machine learning in the industrial field.…”

Section: Introductionmentioning

confidence: 99%

Diesel Engine Exhaust Gas Recirculation Technology Based on Machine Learning

2021

KME

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Recycling technology has the characteristics of high efficiency, recyclability and reuse. At the same time, it can be widely used in industrial production as an environment-friendly technology. At present, the waste gas treatment methods adopted in China mainly include mechanical (heat treatment) or chemical methods. These methods do great harm to the environment. In order to improve the environmental protection of diesel engines, this paper intends to study the application of machine learning in exhaust gas recirculation technology, and propose the method of exhaust gas recirculation technology. This paper mainly uses the experimental method of EGR scheme design and changes the variables to compare the data difference to realize the research on the influence of internal EGR on emission performance and combustion characteristics. The experimental results show that the NOx emissions of the internal EGR scheme are lower than 10/g•h-1 at 2200r/min and 10% load conditions. The internal exhaust gas recirculation technology has great potential to improve the harmful exhaust gas and total fuel emissions of diesel engines.

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Schlieren visualization of micro gas turbine exhaust plume with different shapes of nozzle

Cited by 9 publications

References 10 publications

Dynamic Performance Analysis of Gas Turbine with Intermediate Cooling and Regenerative Based on Neural Network Algorithm

Dynamic Performance Analysis of Gas Turbine with Intermediate Cooling and Regenerative Based on Neural Network Algorithm

Design of an Axial Transonic Rotor by Modified Spanwise Loading Distribution

Diesel Engine Exhaust Gas Recirculation Technology Based on Machine Learning

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