• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.197-202
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• 1999

Electric arc furnaces (EAFs) use bulk electrical energy to create heat in metal refining industries. The electric arc process is a main cause of the degradation of the electric power quality such as voltage flicker due to the interaction of the high demand currents of the load with the supply system impedance. The stochastic models have described the aperiodic physical phenomena of EAFs. An alternative approach is to include deterministic chaos in the characterization of the arc currents. In this parer, a chaotic approach to such modeling is described and justified. At the same time, a DLL(Dynamic Link Library) module, which is a FORTRAN interface with TACS (Transient Analysis of Control Systems), is developed to implement the chaotic load model in the Electromagnetic Transients Program (EMTP). The details of the module and the results of tests performed on the module to verify the model and to illustrate its capabilities are presented in this paper.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.204-208
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• 2018

Comparison of different optimizer performance in photovoltaic power modeling using artificial neural deep learning techniques is described in this paper. Six different deep learning optimizers are tested for Long-Short-Term Memory networks in this study. The optimizers are namely Adam, Stochastic Gradient Descent, Root Mean Square Propagation, Adaptive Gradient, and some variants such as Adamax and Nadam. For comparing the optimization techniques, high and low fluctuated photovoltaic power output are examined and the power output is real data obtained from the site at Mokpo university. Using Python Keras version, we have developed the prediction program for the performance evaluation of the optimizations. The prediction error results of each optimizer in both high and low power cases shows that the Adam has better performance compared to the other optimizers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.4
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• pp.875-886
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• 1994

This study is to develop an advanced storm runoff analysis program which takes geomorphological characteristics of watershed into consideration in determining model parameters. Basic concept of storm runoff modelling is based upon the kinematic wave theory. And numerical solution is obtained by the characteristic curve method. The storm runoff analysis program developed by this study is composed of multiple equivalent roughness sub-basins, each of which has two equivalent catchments on both side of a stream. Because it is based upon the stream-order of the Strahler system, the equivalent catchment-stream network reflects the stochastic geomorphological characteristics in the model parameter. Applicability and reliability of the storm runoff analysis program is evidenced by model calibration and verification process utilizing geographical and hydrological data of the Bocheong-river area which is a representative watershed of IHP projects in Korea. This study will hopefully contribute to hydrological calculation essentially required to understand water quality effect caused by regional development.

• Korean Journal of Veterinary Research
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• v.49 no.2
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• pp.149-155
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• 2009

The objective of this study was to analyze data from the planned national serological monitoring program for Aujeszky's disease (AD) using a simulation model to evaluate probable outcomes expected in the sample derived from the simulated herds at predefined within-herd prevalence and herd prevalence. Additionally, prevalence at animal- and herd-level estimated by the stochastic simulation model based on the distributions of the proportion of infected herds and test-positive animals was compared with those of data from a national serological survey in 2006, in which 106,762 fattening pigs from 5,325 herds were tested for AD using a commercial ELISA kit. A fixed value of 95% was used for test sensitivity, and the specificity was modeled with a minimum, most likely and maximum of 95, 97 and 99%, respectively. The within-herd prevalence and herd prevalence was modeled using Pert and Triang distributions, respectively with a minimum, most likely and maximum point values. In all calculations, population size of 1,000 was used due to lack of representative information. The mean number of infected herds and true test-positives was estimated to be 27 herds (median = 25; 95% percentile 44) and 214 pigs (median = 196; 95% percentile 423), respectively. When testing 20 pigs (mean of 2006 survey) in each herd, there was a 3.3% probability that the potential for false-positive reactions due to less than 100% specificity of the ELISA test would be detected. It was found that the model showed prevalence of 0.21% (99% percentile 0.50%) and 0.5% (99% percentile 0.99%) at animal- and herd-level, respectively. These rates were much similar to data from the 2006 survey (0.62% versus 0.83%). The overall mean herd-level sensitivity of the 2006 survey for fattening pigs was 99.9%, with only a 0.2% probability of failing to detect at least one infected herd.

• Journal of Korea Water Resources Association
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• v.33 no.3
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• pp.365-374
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• 2000

This paper is to present the determination of the optimal Joss rate parameters and urnt bydrographs from the observed single rainfall-runoff event using optimization models coupled with a stochastic technique for the global solution. Two kinds of the linear program models are formulated to derive the optimal unit hydrographs and loss rate parameters for gaged basins; one mimmizes the summation of the absolute residual between predlCted and observed runoff ordinates and the other, the maximum absolute residuaL Multistart algorithm which is one or stochastic techniques for the global optimum is adopted to perturb the parameters of the loss rate equations. Multistart efficiently searches the feasIble region to identify the global optimlUll for loss rate parameters, which yields the optimal loss rate parameters and unit hydrograph for Kostiakov's, Plulip's, and Horton's equation. The unique unit hydrograph ordinates for a gIven rainfall-runoff event iS exclusrvely obtained WIth $\Phi$ index, but unit hydrograph ordinates depend upon the parameters [or each loss rate equations. The parameters of Green-Ampt's are determined through a trial and error method. In this paper the single rainfall-nmoff event observed from a watershed is considered to test the proposed method. The optimal unit hydrograph herein found has smaller deviations than the ones reported previously by other researchers.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.10
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• pp.1558-1565
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• 2004

It is important to determine supporting locations for structural stability when a structure is loaded with non-uniform load or supporting locations as well as the number of the supporting structures are restricted by the problem of space. Moreover, the supporting location optimization of complex structure in real world is frequently faced with discontinuous design space. Therefore, the traditional optimization methods based on derivative are not suitable Whereas, Genetic Algorithm (CA) based on stochastic search technique is a very robust and general method. The KSTAR in-vessel control coil installed in vacuum vessel is loaded with non- uniform electro-magnetic load and supporting locations are restricted by the problem of space. This paper shows the supporting location optimization for structural stability of the in-vessel control coil. Optimization has been performed by means of a developed program. It consists of a Finite Element Analysis interfaced with a Genetic Algorithm. In addition, this paper presents an algorithm to find an optimum solution in discontinuous space using continuous design variables.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2220-2226
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• 2018

Electric vehicles (EVs) are significant resources for demand response (DR). Thus, it is essential for EV aggregators to quantitatively evaluate their capability for DR. In this paper, a concept of dynamic equivalent battery (DEB) is proposed as a metric for evaluating the DR performance using EVs. The DEB is the available virtual battery for DR. The capacity of DEB is determined from stochastic calculation while satisfying the charging requirements of each EV, and it varies also with time. Further, a new indicator based on the DEB and time-varying electricity prices, named as value of DEB (VoDEB), is introduced to quantify the value of DEB coupled with the electricity prices. The effectiveness of the DEB and the VoDEB as metrics for the DR performance of EVs is verified with the simulations, where the difference of charging cost reduction between direct charging and optimized bidding methods is used to express the DR performance. The simulation results show that the proposed metrics accord well with the DR performance of an EV fleet. Thus, an EV aggregator may utilize the proposed concepts of DEB and VoDEB for designing an incentive scheme to EV users, who participate in a DR program.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.5
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• pp.125-139
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• 1996

This study was performed to provide the design method for soil structure which guarantees proper safety with uncertainty of soil parameters. For this purpose, the effect of uncertainty of soil parameters for slope stability was analyzed by Bishop's simplified method and Monte Carlo simulation(MC). And reliability analysis program, RESFEM, was developed by combining elastic theory, MC, FEM, SFEM, and reliability, which can consider uncertainty of soil parameters. For factor of safety(FS) 1.0 and 1.2 by Bishop's simplified method, the probability of failure(Pf) was analyzed with varying coefficient of variation(c.o.v.) of soil parameters. The Pf increased as c.o.v. of soil parameters increased. This implies that FS is not the absolute index of slope safety, and even if FS is same, it has different Pf according to c.o.v. of soil parameters. The RESFEM was able to express the Pf at each element in slope quantitatively according to uncertainty of soil parameters. The variation of Pf with uncertainty of soil parameters was analyzed by RESFEM, and it was shown that the Pf increased as the c.o.v. of soil parameters increased.

• Steel and Composite Structures
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• v.37 no.1
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• pp.1-14
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• 2020

Composite beams with corrugated steel webs represent a new innovative system which has emerged in the past decade for medium span in the construction technology. The use of composite beams with corrugated steel webs results in a range of benefits, including flexible spaces and reduced foundation costs in the construction technology. The thin corrugated web affords a significant weight reduction of these beams, compared with hot-rolled or welded ones. In the current research, an optimal designed I-girder beam with corrugated web has been proposed to improve the structural performance of continuous composite girder under bending moment. The experimental program has been conducted for six simply supported composite beams with different loading conditions. The tested specimens are designed by using one of the stochastic techniques called hunting search algorithm. In the optimization process, besides the thickness of concrete slab and studs, corrugated web properties are considered as design variables. The design constraints are respectively implemented from Eurocode 3, BS-8110 and DIN 18-800 Teil-1. The last part of the study focuses on performing a numerical study on composite beams by utilizing finite element analysis and the bending behavior of steel girders with corrugated webs experimentally and numerically verified the results. A nonlinear analysis was carried out using the finite element software ANSYS on the composite beams which were modelled using the elements ten-node high order quadrilateral type.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1322-1327
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• 2003

It is important to determine supporting locations for structural stability of a structure under non-uniform load in space interfered by other parts. In this case, There are many local optima with discontinuous design space. Therefore, The traditional optimization methods based on derivative are not suitable. Whereas, Genetic algorithm(GA) based on stochastic search technique is a very robust and general method. This paper has been presented to determine supporting locations of the vertical supports for reducing stress of the KSTAR(Korea super Superconducting Tokamak Advanced Research) IVCC(In-vessel control coil) under non-uniform electromagnetic load and space interfered by other parts using genetic algorithm. For this study, we develop a program combining finite element analysis with a genetic algorithm to perform structural analysis of IVCC. In addition, this paper presents a technique to perform optimization with FEM when design variables are trapped in an incongruent design space.