• Advances in nano research
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• v.3 no.3
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• pp.143-168
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• 2015

Initiation of crack and its growth simulation requires accurate model of traction - separation law. Accurate modeling of traction-separation law remains always a great challenge. Atomistic simulations based prediction has great potential in arriving at accurate traction-separation law. The present paper is aimed at establishing a method to address the above problem. A method for traction-separation law prediction via utilizing atomistic simulations data has been proposed. In this direction, firstly, a simpler approach of common neighbor analysis (CNA) for the prediction of crack growth has been proposed and results have been compared with previously used approach of threshold potential energy. Next, a scheme for prediction of crack speed has been demonstrated based on the stable crack growth criteria. Also, an algorithm has been proposed that utilizes a variable relaxation time period for the computation of crack growth, accurate stress behavior, and traction-separation atomistic law. An understanding has been established for the generation of smoother traction-separation law (including the effect of free surface) from a huge amount of raw atomistic data. A new curve fit has also been proposed for predicting traction-separation data generated from the molecular dynamics simulations. The proposed traction-separation law has also been compared with the polynomial and exponential model used earlier for the prediction of traction-separation law for the bulk materials.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.940-946
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• 2012

This paper proposes a method to predict maximum traction for unmanned robots on rough terrain in order to improve traversability. For a traction prediction, we use a friction-slip model based on modified Brixius model derived empirically in terramechanics which is a function of mobility number $B_n$ and slip ratio S. A friction-slip model includes characteristics of various rough terrains where robots are operated such as soil, sandy soil and grass-covered soil. Using a friction-slip model, we build a prediction model for terrain parameters on which we can know maximum static friction and optimal slip with respect to mobility number $B_n$. In this paper, Mobility number $B_n$ is estimated by modified Willoughby Sinkage model which is a function of sinkage z and slip ratio S. Therefore, if sinkage z and slip ratio are measured once by sensors such as a laser sensor and a velocity sensor, then mobility number $B_n$ is estimated and maximum traction is predicted through a prediction model for terrain parameters. Estimation results for maximum traction are shown on simulation using MATLAB. Prediction Performance for maximum traction of various terrains is evaluated as high accuracy by analyzing estimation errors.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.297-304
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• 2009

This study was conducted to investigate the adequacy of the representative empirical models which are developed for predicting the tractive performance of the tractor operating in various soil conditions. Four representative empirical models which are widely used in the traction prediction of tractor were selected through literature review. Four models were Wismer-Luth, Brixius, Dwyer and Hernandez model, which were empirical traction models of a single wheel. The efficacy of four models were confirmed via comparison of the tractions of tractor predicted using the four models with those measured from traction tests which were conducted for two different driving type (2WD and 4WD) of the tractor on two different soil conditions. The results showed that tractions predicted by Brixius' model, especially for slip range under 20% which the operating efficiency of a tractor is very high, were well consistent with the ones measured from traction test better than the tractions predicted by models which are proposed by Wismer-Luth, Dwyer and Hernandez.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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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.

• Journal of Biosystems Engineering
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• v.9 no.2
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• pp.19-26
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• 1984

This study intended to develop the prediction models of the traction and field performance of two-wheel tractors by using the principles which were applied for predicting those of the four-wheel tractors. The traction model developed in this study consists of the net traction coefficient, rolling resistance coefficient and traction efficiency, Which are expressed as functions of both wheel numeric and slip. A computer program on the field performance of two-wheel tractors is also developed to predict the drawbar horsepower, traction force, traction efficiency, rotational speed of engine and engine horsepower if the characteristics of the engine performance and operational condition of the two-wheel tractor are known. Based on the developed models, the conditions of basic variables to maximize the field performance were analyzed so as to assess the existing two-wheel tractor.

• Journal of Drive and Control
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• v.20 no.1
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• pp.16-26
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• 2023

Although the upland field area of Korea is high as 44.8%, the platform optimized for the upland field is insufficient. It is necessary to develop an optimized platform for the upland field because the upland field environment is an irregular environment with many slopes. In addition, due to the characteristic of agricultural operations, the traction power and torque of the platform have to be sufficient. Therefore, in this study, a simulation model that can predict the traction power and driving torque of a crawler-type platform for the upland field was developed and validated using the specifications of the crawler platform. The simulation model was developed using Amesim (19.1, Siemens, Germany). The development of the model was conducted using the specifications of the platform. A measurement system was developed to validate the simulation model. The traction power data of the simulation model was validated with the traction force and vehicle speed. The driving torque data of the simulation model was validated with the torque of the sprocket on the crawler system. As a result of the analysis, the error between measurement and simulation results occurred within 10%, and it was determined that the traction power and driving torque prediction of the crawler platform using this model was possible.

• Tribology and Lubricants
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• v.14 no.1
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• pp.85-93
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• 1998

The Bair & Winer's limiting shear stress rheological model is incorporated into the Reynolds equation to successfully predict the traction and film thickness for an isothermal line contact using the primary rheological properties. The modified WLF viscosity model and Barus viscosity model are also adapted for the realistic prediction of EHD tractional behavior. The influences of the limiting shear stress and slide-roll ratio on the pressure spike, film thickness, distribution of shear stress and nonlinear variation of traction are examined. A good agreement between the disc machine experiments and numerical traction prediction has been established. The film thickness due to non-Newtonian effects does not deviate significantly from the fdm thicknesss with Newtonian lubricant.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.763-766
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• 2000

In this paper, stator form-winding sample coils based on silicone resin and polyimide were made for fault prediction and reliability estimation on the 200 Class insulation system of traction motors. The complex accelerative degradation was performed by periods during 10 cycles, which was composed of thermal stress, fast rising surge voltage, vibration, water immersion and overvoltage applying. After aging of 10 cycles, condition diagnosis test such as insulation resistance & polarization index, capacitance & dielectric loss and partial discharge properties were investigated in the temperature range of 20∼160$^{\circ}C$. Relationship among condition diagnosis test was analyzed to find an dominative degradation factor and an insulation state at end-life point.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.653-659
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• 2015

The aim of this study is to develop a technique for the accelerated life test of the capacitor in a propulsion control device of a traction inverter used for a high-speed train. Using this technique, the accelerated life test can possibly estimate the life cycle of a capacitor under various temperature conditions and irregularly applied voltage. The accelerated life test is conducted for the capacitor of the traction inverter. The common proceedings of this test are selection of failure mechanism, determination of accelerated stress, range determination of the accelerated stress, determination of the test condition, and distribution and determination of the sample. From this result, the continuous applied voltage was not considered for the acceleration factors anymore. Therefore, the final result having an acceleration factor of 9.4 (= 13,626/1,445) was observed. Furthermore, the life-shortening acceleration effect for the irregular applied voltage condition can be applied to various situations.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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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.