Gas Turbine Propulsion for High-Speed Railcars

1967 ◽  
Author(s):  
P. B. Garner ◽  
W. L. Hull
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
High Speed ◽  
Long Island ◽  
Experimental Tests ◽  
Propulsion System ◽  
Drive System ◽  
Market Potential ◽  
Demonstration Program ◽  
Gas Turbine Power Plant

Experimental tests of a turbine-powered, self-propelled, high-speed railcar are presently being conducted on a section of the Long Island Railroad. This paper describes the railcar, the unique gas turbine power plant and mechanical drive system, and the expected railcar performance. The objectives of the demonstration program, the merits of the selected turbomechanical drive system, and the market potential for production turbine-powered railcars are discussed. A summary of test experience to date and a preview of propulsion-system innovations that may be tested in follow-on programs are presented.

scholarly journals The Performance of Gas Turbine Power Plant Using 5% Biodiesel & 95% High Speed Diesel

2019 ◽  
Vol 6 (3) ◽  
pp. 229-233
Author(s):  
Mujammil Asdhiyoga Rahmanta ◽  
◽  
Tiva Winahayu Dwi Hapsari ◽  
Bernaded Oka Anggraini
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
High Speed ◽  
High Speed Diesel ◽  
Gas Turbine Power Plant

scholarly journals A Proper Shape of the Trailing Edge Modification to Solve a Housing Damage Problem in a Gas Turbine Power Plant

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 705
Author(s):  
Thodsaphon Jansaengsuk ◽  
Mongkol Kaewbumrung ◽  
Wutthikrai Busayaporn ◽  
Jatuporn Thongsri
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Structural Dynamics ◽  
Pressure Ratio ◽  
Equivalent Stress ◽  
Total Deformation ◽  
Trailing Edge ◽  
Housing Damage ◽  
The Difference ◽  
Gas Turbine Power Plant

To solve the housing damage problem of a fractured compressor blade (CB) caused by an impact on the inner casing of a gas turbine in the seventh stage (from 15 stages), modifications of the trailing edge (TE) of the CB have been proposed, namely 6.5 mm curved cutting and a combination of 4 mm straight cutting with 6.5 mm curved cutting. The simulation results of the modifications in both aerodynamics variables Cl and Cd and the pressure ratio, including structural dynamics such as a normalized power spectrum, frequency, total deformation, equivalent stress, and the safety factor, found that 6.5 mm curved cutting could deliver the aerodynamics and structural dynamics similar to the original CB. This result also overcomes the previous work that proposed 5.0 mm straight cutting. This work also indicates that the operation of a CB gives uneven pressure and temperature, which get higher in the TE area. The slightly modified CB can present the difference in the properties of both the aerodynamics and the structural dynamics. Therefore, any modifications of the TE should be investigated for both properties simultaneously. Finally, the results from this work can be very useful information for the modification of the CB in the housing damage problem of the other rotating types of machinery in a gas turbine power plant.

Thermal performance of gas turbine power plant based on exergy analysis

2017 ◽  
Vol 115 ◽  
pp. 977-985 ◽  
Author(s):  
Thamir K. Ibrahim ◽  
Firdaus Basrawi ◽  
Omar I. Awad ◽  
Ahmed N. Abdullah ◽  
G. Najafi ◽  
...  
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Thermal Performance ◽  
Exergy Analysis ◽  
Gas Turbine Power Plant

Combustion Tuning for a Gas Turbine Power Plant Using Data-Driven and Machine Learning Approach

2021 ◽  
Vol 143 (3) ◽  
Author(s):  
Suhui Li ◽  
Huaxin Zhu ◽  
Min Zhu ◽  
Gang Zhao ◽  
Xiaofeng Wei
Keyword(s):  
Machine Learning ◽  
Power Plant ◽  
Gas Turbine ◽  
Operating Conditions ◽  
Data Driven ◽  
Ann Model ◽  
Promising Alternative ◽  
Combustion Performance ◽  
Wide Range ◽  
Gas Turbine Power Plant

Abstract Conventional physics-based or experimental-based approaches for gas turbine combustion tuning are time consuming and cost intensive. Recent advances in data analytics provide an alternative method. In this paper, we present a cross-disciplinary study on the combustion tuning of an F-class gas turbine that combines machine learning with physics understanding. An artificial-neural-network-based (ANN) model is developed to predict the combustion performance (outputs), including NOx emissions, combustion dynamics, combustor vibrational acceleration, and turbine exhaust temperature. The inputs of the ANN model are identified by analyzing the key operating variables that impact the combustion performance, such as the pilot and the premixed fuel flow, and the inlet guide vane angle. The ANN model is trained by field data from an F-class gas turbine power plant. The trained model is able to describe the combustion performance at an acceptable accuracy in a wide range of operating conditions. In combination with the genetic algorithm, the model is applied to optimize the combustion performance of the gas turbine. Results demonstrate that the data-driven method offers a promising alternative for combustion tuning at a low cost and fast turn-around.

Analysis of Exergy and Energy Variation of Gas Turbine Power Plant in Taza-Iraq

2021 ◽  
Vol 9 (2) ◽  
pp. 35
Author(s):  
Anmmar Mahmoud Anmmar ◽  
Ahmed Hasan Ahmed ◽  
Obed M. Ali
Keyword(s):  
Power Plant ◽  
Gas Turbine ◽  
Energy Variation ◽  
Gas Turbine Power Plant
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