• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.751-755
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• 1995

It become more difficult to anticipate the performance of fluid power systems as the number of components increases because of nonlinearrities inherent in hydraulic components. In this situation, the computer simulation technique can be an effective tool in the analysis and design of fluid power systems. In this paper, simulation results are presented for dynamic characteriatics of a knuckle crane. Simple models for hydraulic components and relatively detailed motion equations for attachments are used. the simulation reaults are very close to those of experiments. The simulation is performed using a simulation package developed with object-oriented method. This package provides the encironment that user can construct desirct desired circuits form the component library, checks the continuity and compatibility conditions automatically and executes simulation

• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.1974-1982
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• 2020

Numerical prediction of fission product plateout and circulating coolant activities under normal operating conditions is crucial in the design of a high temperature gas-cooled reactor (HTGR). The results are used for the maintenance and repair of the components as well as the safety analysis regarding early source terms under loss of coolant accident scenarios. In this work, a new computer code named POSCA (Plate-Out Surface and Circulating Activities) was developed based on a one-dimensional model to evaluate fission product plateout and circulating coolant activities within the primary circuit of a HTGR. The verification and validation of study for the POSCA code was done using available analytical results and two in-pile experiments (i.e., OGL-1 and VAMPYR-1). The results of the POSCA calculations show that POSCA is able to simulate plateout and circulating coolant activities in a HTGR with fast computation and reasonable accuracy.

• Journal of Power Electronics
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• v.13 no.6
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• pp.975-984
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• 2013

This paper proposes a robust optimal nonlinear control with an observer to reject the offset errors of position tracking for surface mounted permanent magnet synchronous motors. We provide the control method to reject offset errors and load torque for designing field oriented control (FOC) based the alternating current (AC) frame. The proposed method consists of a torque generator, a commutation scheme, an electrical controller, and a load torque observer. The mechanical controller is designed to compensate for load torque and the offset error and generate the desired torque. The commutation scheme is proposed to create the desired currents for the desired torque. The electrical controller is developed to guarantee the desired currents. The observer is designed to estimate both the velocity and the load torque. In order to obtain the robustness to parameter uncertainties and a gain tuning guide, the linear quadratic regulator method is applied to the proposed method. The closed-loop stability is proven. A detailed process for the FOC design and an analysis of the control methods based on the AC frame are presented. The performance of the proposed method was validated via experiments. The proposed method obtains the FOC based on the AC frame. Furthermore, the position tracking performance of the proposed method is superior to that of the conventional method.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.219-224
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• 2017

This paper is to introduce an application of face recognition algorithm in parallel. We have experiments of 25 images with different motions and simulated the image recognitions; grouping of the image vectors, image normalization, calculating average image vectors, etc. We also discuss an analysis of the related eigen-image vectors and a parallel algorithm. To develop the parallel algorithm, we propose a new type of initial matrices for eigenvalue problem. If A is a symmetric matrix, initial matrices for eigen value problem are investigated: the "optimal" one, which minimize ${\parallel}C-A{\parallel}_F$ and the "super optimal", which minimize ${\parallel}I-C^{-1}A{\parallel}_F$. In this paper, we present a general new approach to the design of an initial matrices to solving eigenvalue problem based on the new optimal investigating C with preserving the characteristic of the given matrix A. Fast all resulting can be inverted via fast transform algorithms with O(N log N) operations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.9
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• pp.1422-1428
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• 2004

In this paper, computer simulation model of handrail band including pulley-driving system is developed to calculate handrail slippage. This handrail simulation model is validated with test result within operating range and used to predict its slippage behavior with respect to variation of 4 different design parameters considering the applicability into the real handrail system. Based upon this parameter study, optimal condition for handrail slippage improvement is proposed without time-consuming and costly experiments of the real handrail system. And then performance improvement of handrail slippage complied with safety code is achieved after applying the optimal condition into the real handrail band system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.89-100
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• 1987

In this paper, we present the effect of buffer storage capacity un two-stage transfer lines in such a way as to introduce the production rate to be reduced which is called a Slowed Down(SD) state. A Markov model is used to establish a formulation for the analysis of the delays associated with the stage to be starved or blocked. Operating policies are proposed by analyzing the effect of the decision variables such as the production rates, the failure rates, buffer capacities and SD rates through computer simulation experiments.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.199-202
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• 2005

In this paper, the six sigma scheme is employed together with the rigid-viscoplastic finite element method to obtain the optimal metal flow lines in hot press forging. In general, the six sigma process is consisted of following five steps : define, measure, analyze, improve and control. Each step Is investigated in detail to meet customer's requirements through improvement of product quality. A forging simulator, AFDEX-2D, is used for analysis of the metal flow lines of a multi-stage hot forging process under various conditions of major factors, determined at each step of the six sigma process. The analyzed results are examined in order to reveal the effects of major factors on the metal flow lines and the formed shapes. The effects are used to find an optimal process and the optimal process with die is devised and tested. The comparison between required metal flow lines and experiments shows that the approach is effective for optimal process in hot forging design considering metal flow lines.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.8
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• pp.989-996
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• 2010

Statistical regression and/or interpolation models have been used for data analysis and response prediction using the results of the physical experiments and/or computer simulations in structural engineering fields. These models have been employed during the last decade to develop a variety of design methodologies. However, these models only handled responses with respect to space variables such as size and shape of structures and cannot handle time-variant dynamic responses, i.e. response varying with time. In this research, statistical space-time metamodels based on multiple response approach that can handle responses with respect to both space variables and a time variable are proposed. Regression and interpolation models such as the response surface model (RSM) and kriging model were developed for handling time-variant dynamic responses of structural engineering. We evaluate the accuracies of the responses predicted by the two statistical space-time metamodels by comparing them with the responses obtained by the physical experiments and/or computer simulations.

• International Journal of Computer Science & Network Security
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• v.24 no.9
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• pp.30-40
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• 2024

Building an accurate 3-D spatial road network model has become an active area of research now-a-days that profess to be a new paradigm in developing Smart roads and intelligent transportation system (ITS) which will help the public and private road impresario for better road mobility and eco-routing so that better road traffic, less carbon emission and road safety may be ensured. Dealing with such a large scale 3-D road network data poses challenges in getting accurate elevation information of a road network to better estimate the CO₂ emission and accurate routing for the vehicles in Internet of Vehicle (IoV) scenario. Clustering and regression techniques are found suitable in discovering the missing elevation information in 3-D spatial road network dataset for some points in the road network which is envisaged of helping the public a better eco-routing experience. Further, recently Explainable Artificial Intelligence (xAI) draws attention of the researchers to better interprete, transparent and comprehensible, thus enabling to design efficient choice based models choices depending upon users requirements. The 3-D road network dataset, comprising of spatial attributes (longitude, latitude, altitude) of North Jutland, Denmark, collected from publicly available UCI repositories is preprocessed through feature engineering and scaling to ensure optimal accuracy for clustering and regression tasks. K-Means clustering and regression using Support Vector Machine (SVM) with radial basis function (RBF) kernel are employed for 3-D road network analysis. Silhouette scores and number of clusters are chosen for measuring cluster quality whereas error metric such as MAE ( Mean Absolute Error) and RMSE (Root Mean Square Error) are considered for evaluating the regression method. To have better interpretability of the Clustering and regression models, SHAP (Shapley Additive Explanations), a powerful xAI technique is employed in this research. From extensive experiments , it is observed that SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions SHAP analysis validated the importance of latitude and altitude in predicting longitude, particularly in the four-cluster setup, providing critical insights into model behavior and feature contributions with an accuracy of 97.22% and strong performance metrics across all classes having MAE of 0.0346, and MSE of 0.0018. On the other hand, the ten-cluster setup, while faster in SHAP analysis, presented challenges in interpretability due to increased clustering complexity. Hence, K-Means clustering with K=4 and SVM hybrid models demonstrated superior performance and interpretability, highlighting the importance of careful cluster selection to balance model complexity and predictive accuracy.

• Journal of the Korea Computer Industry Society
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• v.6 no.3
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• pp.559-566
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• 2005

ALTIBASE is the relational main memory DBMS that enables us to develop the high performance and fault tolerant applications. It guarantees the short and predictable execution time as well as the basic functionality of conventional disk-based DBMS. We present the overview of system architecture and the performance analysis with respect to the various design choices. The assorted experiments are performed under the various environments. The results of TPC-H and Wisconsin benchmark tests are described. We illustrate the various performance comparisons under the various index mechanisms, the replication models, the transaction durabilities, and the application structures. A performance study shows the ALTIBASE system can be applied to the wide area of industrial DBMS fields.