• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.116-121
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• 2001

Prediction of the top(service) speeds of high-speed trains and configuration design to trainset of them has been studied using the neural network system The traction system. The traction system of high-speed trains is composed of transformers, motor blocks, and traction motors of which locations and number in the trainset formation should be determine in the early stage of train conceptural design. Components of the traction system are the heaviest parts in a train so that it gives strong influence to the top speeds of high-speed trains. Prediction of the top speeds has been performed mainly with data associated with the traction system based on the frequently used neural network system-backpropagation. The neural network has been trained with the data of the high-speed trains such as TGV, ICE, and Shinkanse. Configuration design of the trainset determines the number of trains motor cars, traction motors, weights and power of trains. Configuration results from the neural network are more accurate if neural networks is trained with data of the same type of trains will be designed.

• 한국CDE학회논문집
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• 제8권4호
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• pp.222-230
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• 2003

Artificial intelligence has been used in the configuration design stage of high-speed train. The traction system of a high-speed train is composed of transformers, motor blocks, and traction motors of which locations and number in the trainset should be determined in the early stage of the train conceptual design. Components of the traction system are heavy parts in the train, so it gives strong influence to the top speeds and overall train configuration of high-speed trains. Top speeds have been predicted using the neural network with the associated data of the traction system. The neural networks have been learned with data sets of many commercially operated high-speed trains, and the predicted results have been compared with the actual values. The configuration design of the train set of a high-speed train determines the basic specification of the train and layout of the traction system. The neural networks is a useful design tool when there is not sufficient data for the configuration design and we need to use the existing data of other train for the prediction of trainset in development.

• 한국철도학회:학술대회논문집
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• 한국철도학회 1999년도 추계학술대회 논문집
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• pp.172-180
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• 1999

The major subject of this paper is to develop the concept fur a Korea high speed train system and recommend to train configuration. High speed train configurations are basically concerned traction power(train configurations with concentrated; CPT or distributed Power system: DPT) and train design(single car as compared with articulated bogies). The result of configuration, a advantages and disadvantaged were necessitated by different train configurations; -distributed underfloor power have an increased length for the seats by 15% as compared with the concentrated power trait - articulated trainsets are characterised by less of number of bogies and reduced values of mass, train resistance, noise and vibration. from the result, the optimized train concept combining high seat capacity per train length with low weight and train resistance is 400m long, single -floor train composed of two symmetrically arranged half trainsets. Therefore, at this work recommended distributed train system However, the final decision of Korea high speed train configuration was concentrated power train and articulated bogie system. The configuration of trainset was 20cars included 2 power cars, 4 motorized cars and 14 trailer cars.

• 한국전산유체공학회지
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• 제19권1호
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• pp.41-46
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• 2014

The aerodynamic drag of high-speed train has been calculated and the effect of bogie side fairing on the aerodynamic drag has been investigated. Computational Fluid Dynamics (CFD) simulation based on steady-state 3 dimensional Navier-Stokes equation has been conducted employing FLUENT 12 and the aerodynamic model of HEMU-430x, the Korean next generation high-speed train under development has been built using GAMBIT 2.4.6. Three types of bogie side fairing configuration, the proto-type without fairing, half-covered fairing to avoid the interference with the bogie frame and full-covered fairing have been adopted to the train model to compare the drag reduction effects of the bogie side fairing configurations and the numerical results yields that the bogie side fairing can reduce the aerodynamic drag of the 6-car trainset up to 7.8%. The aerodynamic drag coefficient of each vehicle as well as the flow structures around the bogie system have also been examined to analyze the reason and mechanism of the drag reduction by bogie side fairing.