• Proceedings of the KSR Conference
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• 1999.11a
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• pp.566-573
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• 1999

This paper is the result of sensitivity analysis of derailment with respect to the selected suspension elements for the rail vehicle. Derailment phenominon has been explained by the derailment quotient. Thus, the sensitivity of derailment is suggested by a response surface model(RSM) which is a functional relationship between derailment quotient and characteristics of suspension elements. To summarize generation of RSM, we can introduce the procedure of sensitivity analysis as follows. First, to form a RSM, a experiment is performed by a dynamic analysis code, VAMPIRE according to a kind of the design of experiments(DOE). Second, RSM is constructed to a 1$\^$st/ order polynomial and then main effect fators are screened through the stepwise regression. Finally, we can see the sensitivity level through the RSM which only consists of the main effect factors and is expressed by the liner, interaction and quadratic effect terms.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.7
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• pp.542-549
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of given design variables and chance them to get a bettor design. Even though commercial simulation codes are used, the computational time and cost remains non-trivial. Therefore, malty researchers have used a mesa model made by sampling data through simulation. In this paper, four mesa-models for each index group such as ride comfort, derailment Quotient, unloading radio and stability index, are constructed by use of neural network. After these meta models are constructed, multi-objective optimization are achieved by using the differential evolution. This paper shows that the optimization of design variables using the neural network model is very efficient to solve the complex optimization Problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.717-724
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• 2017

To improve the running safety of a tram operating on a concrete embedded track, a bogie, the core system of the tram, was developed and fabricated. After it was integrated with the prototype car body, a short distance track with a sharp curve and steep gradient was constructed for the test operation. A formula to check the interference of the wheel flange with the track during running was proposed. Based on the results provided by the formula, the track was designed. Another simple formula was derived to estimate the derailment quotient and the wheel unloading ratio. During running on the track, the acceleration of the car body was measured and the interface status between the wheel and the track was monitored by a video system. According to the results calculated by these simple formulas, the derailment quotient and wheel unloading ratio were estimated to be within the safety criteria. In the actual test, no derailment occurred and the measured acceleration satisfied the criteria. Also, there was no interference between the wheel and track. The video monitoring results showed no signs of derailment, such as the climbing of the wheel. The pinion in the center showed good running safety, contacting smoothly with the rack. The measurements of environmental noise proved that the criteria were satisfied.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.151-154
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• 2007

THE DOMESTIC AND FOREIGN OF THE COUNTRY RAILROAD ACCIDENT ANALYSIS IT LED FROM THE PAPER WHICH IT SEES AND IT ANALYZED A TRAIN COLLISION/DERAILED ACCIDENT RISK FIXED QUANTITY. THE TRAIN ACCIDENT OCCURS DIRECT AND LATENT DAMAGE. IT CLASSIFIES THE ACCIDENT WHICH 5 YEAR FOR OCCURS RECENTLY DOMESTIC AND FOREIGN OF THE COUNTRY WITH A TYPE FROM THE RESEARCH WHICH IT SEES. IT TRIED TO ANALYZE THE DAMAGE SIZE AGAINST A TRAIN COLLISION/DERAILED ACCIDENT WITH DANGEROUS QUOTIENT.

• Journal of the Korean Society for Railway
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• v.17 no.1
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• pp.28-34
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• 2014

In this paper, a concept design of a rail type ultra-high-speed train is proposed and its dynamic characteristics are analyzed. Instead of the existing solid axle, a new type bogie system and independently rotating wheels are applied in the proposed train. In order to analyze the dynamic characteristics, a multibody dynamic model of a vehicle is developed and the basic validity is verified by eigenvalue analysis. Also, it is shown that the critical speed is improved in comparison to that of existing high-speed train model HEMU-430X. Finally, through 7000R curved track driving analysis at a speed of 550 km/h, the lateral force of the wheels and the derailment quotient are estimated and the applicability of the new concept railway vehicle is confirmed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.6
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• pp.461-468
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)＝f($\chi$)＋$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1086-1092
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• 2002

Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of a given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a mega model that has a regression model made by sampling data through simulation. In this paper, the neural network is used a mega model that have twenty-nine design variables and forty-six responses. After this mega model is constructed, multi-objective optimal solutions are achieved by using the differential evolution. This paper shows that this optimization method using the neural network and the differential evolution is a very efficient tool to solve the complex optimization problem.