• 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.

• 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.

• 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 Korean Society for Railway
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• v.2 no.2
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• pp.6-12
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• 1999

In this study, the most important suspension characteristics of railway vehicle, such as primary and secondary stiffness, are optimized to maximize ride qualify. Critical speed, secondary suspension stroke oil tangent track and derailment coefficient on the maximum curvature, are selected as the performance constraints. Piecewise linear curving model is used to evaluate derailment coefficient where it is assumed that wheel/rail contacts occurs at tread or at idealized flange. The combined design procedure is used to optimize above design variables at the same time.

• 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 Materials Research Society of Korea Conference
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• 2003.11a
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• pp.40-40
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• 2003

최근 나노기술의 발달과 더불어 나노재료에 대한 특성평가 요구가 높아지고 있고, 따라서 나노스케일에서 재료의 기계적 거동을 분석할 수 있는 나노인덴테이션 기법이 심도있게 연구되고 있다. 본 연구에서는 나노인덴테이션, 주사탐침현미경(SPM), 투과전자현미경(TEM) 기법을 이용하여 여러가지 재료의 탄성 소성 변형 거동과 팝인/괍아웃 현상을 조사하고 해석하였다. 나노인덴테이션 기법으로는 50 마이크로뉴턴 (5 mg) 이하의 매우 작은 하중 하에서는 접촉 응력조건이라도 인장시험에서 관찰되는 영구변형이 제로인 완전탄성 변형 거동을 관찰할 수 있었다. 또한, 50-250 마이크로 뉴턴의 하중 범위에서 재료는 탄성변형 이후에 갑작스런 항복거동과 더불어 수십-수백 나노미터를 미끌어지듯 변형하는 팝인(pop-in), 또는 탈선(excursion) 현상을 관찰할 수 있었다. 이 현상은 하중을 가하는 동안에 여러 번 발생하였으며 재료의 표면상태와 전위밀도와 밀접한 상관관계를 보였다. 반복 압입 시험에서는 전형적인 가공경화 현상으로 항복점이 높아지고 새로운 항복점 이후에야 다시 팝인 발생함을 보였다. 한편, 하중을 가할 때 발생하는 팝인과는 달리 하중을 제거할 때 급격히 회복하는 팝아웃 현상 또한 관찰되었다.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.2
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• pp.162-167
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• 2017

The chevron rubber spring is used for subway vehicle as a primary suspension. Generally, the primary suspension has an influence to the running performance and not so much effect on the ride comfort in railway vehicle. But the stiffness of chevron spring is harder and harder as time goes on because of rubber characteristics. Therefore the dynamic characteristics such as ride comfort and derailment coefficient should be reviewed according to the stiffness variation of chevron rubber spring. In this paper the effect of chevron rubber spring on dynamic characteristics was studied by considering multi-body dynamics of railway vehicle on one straight line and seven curved lines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.1
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• pp.609-617
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• 2017

Railways are one of the safest and most important transportation systems in the world. On the other hand, due to the increasing complexity of the railway system and the running distance of rail vehicles, railway accidents occur continuously every year. In particular, in the case of high-speed trains and freight trains, if the function of the axle bearing is lost due to abnormal overheating of the axle box bearing, the load on the axle becomes uneven. Therefore, abnormal overheating in the train axle box bearings can cause serious accidents or derailments. For this purpose, a Hot Box Detector (HBD) was installed in the track side of a high speed line to detect abnormal overheating. This paper proposes an EWMA technique-based axle temperature monitoring method to detect abnormal overheating quickly and efficiently. A statistical design of the proposed method was also performed. The proposed method has better performance compared to the current method in the case of abnormal overheating and the performance is improved by approximately 170% at the maximum.