• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.02a
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• pp.345-350
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• 2000

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.221-227
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• 2019

One of the important requirements for the application of reduced activation ferritic/martensitic steel is to retain proper mechanical properties in irradiation and high temperature conditions. In order to simulate the impact toughness with the effect of temperature and irradiation, a simulation model based on energy balance method consisted of crack initiation, plastic propagation and cleavage propagation stages was established. The effect of temperature on impact toughness was analyzed by the model and the trend of the simulation results was basicly consistent with the previous experimental results of CLAM steels. The load-displacement curve was simulated to express the low temperature ductile-brittle transition. The effect of grain size and inclusion was analyzed by the model, which was consistent with classical experiment results. The transgranular-intergranular transformation in brittle materials was also simulated.

• Advances in aircraft and spacecraft science
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• v.9 no.5
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• pp.367-375
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• 2022

Modeling the properties of complex alloys such as nickel superalloys is an extremely challenging scientific and engineering task. The model should take into account a large number of uncorrelated factors, for many of which information may be missing or vague. The individual contribution of one or another chemical element out of a dozen possible ligants cannot be determined by traditional methods. Moreover, there are no general analytical models describing the influence of elements on the characteristics of alloys. Artificial neural networks are one of the few statistical modeling tools that can account for many implicit correlations and establish correspondences that cannot be identified by other more familiar mathematical methods. However, such networks require careful tuning to achieve high performance, which is time-consuming. Data preprocessing can make model training much easier and faster. This article focuses on combining physics-based deep network configuration and input data engineering to simulate the solvus temperature of nickel superalloys. The used deep artificial neural network shows good simulation results. Thus, this method of numerical simulation can be easily applied to such problems.

• KIEE International Transactions on Power Engineering
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• v.5A no.2
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• pp.159-170
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• 2005

This paper presents the design and development of a scaled down physical model for power Distribution Automation (DA) system simulation. The developed DA system simulator is useful in providing hands-on experience to utility engineers / managers to familiarize with the DA system and gain confidence in managing the power distribution system from the computer aided distribution control center. The distribution automation system simulator can be effectively used to carry out further research work in this area. This also helps the undergraduate and graduate students to understands the power distribution automation technology in the laboratory environment. The developed DA simulator has become an integral part of a distribution automation lab in the Electrical Engineering Department at Indian Institute of Technology Kanpur in India.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.4
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• pp.371-378
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• 2011

In this paper, the wavelet denoising techniques using thresholding method are applied to the low cost micro electromechanical system (MEMS)-global positioning system(GPS) integrated system. This was done to improve the navigation performance. The low cost MEMS signals can be distorted with conventional pre-filtering method such as low-pass filtering method. However, wavelet denoising techniques using thresholding method do not distort the rapidly-changing signals. They can reduce the signal noise. This paper verified the improvement of the navigation performance compared to the conventional pre-filtering by simulation and experiment.

• IE interfaces
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• v.8 no.3
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• pp.61-73
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• 1995

As the level of maunfacturing system automation increases, the issues of modeling and simulation of AMS(Automated Manufacturing System) are becoming more important. Proposed in this paper is the JR-Net(Job Resource relation-Net) modeling framework which naturally mimics the process of designing an AMS by FA(Factory Automation) engineers. Its main purpose is to provide a modeling tool which facilitate modeling work of AMS for FA engineers unfamiliar with simulation modeling. The proposed modeling scheme is based on the extensive observation that typical AMSs are built from the set of 'standard' components(or catalog items). As an application of the proposed model, two real examples of FMS('G7'FMS model plant, RPI FMS) are modeled by JR-Net, and in case of FMS model plant, a simulation program development procedure using JR-Net modeling results is explained. Finally, simulation result of FMS model plant is analyzed.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.2
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• pp.89-94
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• 2001

This paper presents an approach to leak detection and location of gas pipelines based on a strong tracking filter(STF). The STF has strong robustness against model uncertainties, which will deteriorate the performance of the extended Kalman filter. Hence, much faster and more accurate leak detection and location has been obtained. Computer simulation results demonstrate the effective-ness of the proposed approach.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.320-326
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• 2008

This paper studies the problem of fault estimation using adaptive fault diagnosis observer. A fast adaptive fault estimation (FAFE) approximator is proposed to improve the rapidity of fault estimation. Then based on linear matrix inequality (LMI) technique, a feasible algorithm is explored to solve the designed parameters. Furthermore, an extension to sensor fault case is investigated. Finally, simulation results are presented to illustrate the efficiency of the proposed FAFE methodology.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1113-1118
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• 2004

This paper presents the dynamic analysis method for an electromechanical system. The engineer has at his disposal a variety of software simulation tools. However, difficulties arise when the study of the behavior of complex electromechanical systems in combination with coupling element is required. Typical examples of such systems are machines for factory automation, home automation, and office automation. Dynamic systems analysis packages or electronic systems analysis packages offer the restrictive to simulate these mixed systems such electromechanical product. Electronic circuit analysis algorithm is easily incorporated into a multi-body dynamics analysis algorithm. The governing equation of electronic circuit is formulated as a differential algebraic equation form including both electrical and mechanical variables and is simultaneously solved in every time step. This analysis method clearly demonstrates the application potential for mixed electromechanical simulation.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.575-584
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• 2016

Considering the randomness and uncertainty of wind power, a reliability model of WTGs is established based on the combination of the Weibull distribution and the Markov chain. To analyze the failure mode quickly, we use the switch-section partitioning method. After defining the first-level load zone node, we can obtain the supply power sets of the first-level load zone nodes with each WTG. Based on the supply sets, we propose the dynamic division strategy of island operation. By adopting the fault analysis method with the attributes defined in the switch-section, we evaluate the reliability of the distribution network with WTGs using a sequential Monte Carlo simulation method. Finally, using the IEEE RBTS Bus6 test system, we demonstrate the efficacy of the proposed model and method by comparing different schemes to access the WTGs.