• Journal of the Korean Society for Heat Treatment
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• v.13 no.4
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• pp.259-264
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• 2000

In this study, we quantitatively measure the ion ranges of arsenic with energies ranging from 10 KeV to 100 KeV, implanted at $3^{\circ}$, $9^{\circ}$ $15^{\circ}$ the (100) plane, and the damage created during ion implantation. To obtain detailed information of ion range and damage distributions in low energy region where elastic collisions dominate the slowing down process, molecular dynamics computer simulation was performed and compared to the existing results. The effects of implant energy and degree on damage generation are present. The number of vacancy were calculated from the deposited energy using Kinchin-Pease equation. In the energy range 10 keV-100 keV, simulations show that the number of Frenckel pairs produced by As-ion bimbardment is 9 and incident angle dependence of the vacancy was the same but defects were distributed at different depth.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.8
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• pp.68-74
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• 1998

The neural network predictiv econtroller (NNPC) is proposed for the attempt to mimic the function of brain that forecasts the future. It consists of two loops, one is for the prediction of output (NNP:neural network predictor) and the other one is for control the plant(NNC: neural network controller). The output of NNC makes the control input of plant, which is followed by the variation of both plant error and predictin error. The NNP forecasts the future output based upon the current control input and the estimated control output. The input and the output data of a system and a new method using evolution strategy are used to train the NNP. A two-step NNPC is applied to control the temeprature in boiler systems. It was compared with PI controller and auto-tuning PID controller. The computer simulaton and experimental results show that the proposed method has better performances than the other method.

• Journal of IKEEE
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• v.22 no.1
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• pp.6-13
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• 2018

To develop highly dependable CPS, M&S(modeling and simulation) is very important. It is not easy to model any CPS whole system in a single simulation tool because each simulation tool is optimized for modeling each different part of the CPS. The FMI is the standard for M&S between different simulation tools. The DDS is a communication middleware suitable for large-scale real-time data transmission. In this paper, we proposed FMI based CPS real-time distributed simulaton framework using DDS. To evaluate the performance of the proposed framework, we performed distributed simulation using IEEE HLA/RTI and OMG DDS middleware and measured and compared the execution time of the entire simulation. From the simulation results, we can confirm that the simulation execution time using DDS is at least 1.14 times faster compared to execution time using HLA/RTI.