• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.59-62
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• 1991

This paper describes an effective algorithm for evaluating the reliability indices and calculating the production cost for generation system with thermal, hydro and pumped storage plants. Using the Energy Invariance property, this algorithm doesn't need deconvolution process which gives large burden in computing time. In order to consider an adaptable load model, we consider the system load with forecasting uncertainty. The proposed algorithm is applied to the KEPCO system and its result shows high accuracy and less computing time.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.5
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• pp.47-62
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• 2020

Rice paddy accounts for approximately 52.5% of all farmlands in South Korea, and it is closely related to the water environment. Climate change is expected to affect not only agricultural productivity also the water and the nutrient circulation. Therefore this study was aimed to evaluate changes of nitrogen load from rice paddy considering climate change scenario uncertainty. APEX-Paddy model which reflect rice paddy environment by modifying APEX (Agricultural Policy and Environmental eXtender) model was used. Using the AIMS (APCC Integrated Modeling Solution) offered by the APEC Climate Center, bias correction was conducted for 9 GCMs using non-parametric quantile mapping. Bias corrected climate change scenarios were applied to the APEX-Paddy model. The changes and uncertainty in runoff and nitrogen load were evaluated using multi-model ensemble. Paddy runoff showed a change of 23.1% for RCP4.5 scenario and 45.5% for RCP8.5 scenario compared the 2085s (2071 to 2100) against the base period (1976 to 2005). The nitrogen load was found to be increased as 43.9% for RCP4.5 scenario and 76.0% for RCP8.5 scenario. The uncertainty analysis showed that the annual standard deviation of nitrogen loads increased in the future, and the maximum entropy indicated an increasing tendency. And Duncan's analysis showed significant differences among GCMs as the future progressed. The result of this study seems to be used as a basis for mid- and long-term policies for water resources and water system environment considering climate change.

• Composites Research
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• v.21 no.1
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• pp.30-39
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• 2008

In this paper, a parallel micro genetic algorithm was utilized in the optimal design of composite structures instead of a conventional genetic algorithm(SGA). Micro genetic algorithm searches the optimal design variables with only 5 individuals. The diversities from the nominal convergence and the re-initialization processes make micro genetic algorithm to find out the optimums with such a small population size. Two different composite structure optimization problems were proposed to confirm the efficiency of micro genetic algorithm compared with SGA. The results showed that micro genetic algorithm can get the solutions of the same level of SGA while reducing the calculation costs up to 70% of SGA. The composite laminated structure optimization under the load uncertainty was conducted using micro genetic algorithm. The result revealed that the design variables regarding the load uncertainty are less sensitive to load variation than that of fixed applied load. From the above-mentioned results, we confirmed micro genetic algorithm as a optimization method of composite structures is efficient.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2395-2406
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• 2023

To study the influence of parameter uncertainty in small pressurized water reactor (SPWR) once-through steam generator (OTSG), the nonlinear mathematical model of the SPWR is firstly established. Including the reactor core model, the OTSG model and the pressurizer model. Secondly, a control strategy that both the reactor core coolant average temperature and the secondary-side outlet pressure of the OTSG are constant is adopted. Then, the uncertainty quantification method is established based on Latin hypercube sampling and statistical method. On this basis, the quantitative platform for parameter uncertainty of the OTSG is developed. Finally, taking the uncertainty in primary-side flowrate of the OTSG as an example, the platform application work is carried out under the variable load in SPWR and step disturbance of secondary-side flowrate of the OTSG. The results show that the maximum uncertainty in the critical output parameters is acceptable for SPWR.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.3
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• pp.88-98
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• 2000

In this paper, a robust controller using $H_{\infty}$ control theory has been designed for the load frequency control of interconnected 2-area power system. The main advantage of the proposed $H_{\infty}$ controller is that uncertainties of power system can be included at the stage of controller design. Representation of uncertainties is modeled by multiplicative uncertainly. In the mixed sensitivity problems, disturbance attenuation and uncertainty of the system is treated simultaneously. The robust stability and the performance of model uncertainties are represented by frequency weighted transfer function. The design of load frequency controller for each area was based on state-space approach. The comparative computer simulation results for the proposed controller and the conventional techniques such as the optimal control and the PID one were analyzed at the additions of various disturbances. Their deviation magnitude of frequency and tie line power flow at each area were mainly evaluated. Also the testing results of robustness for the cases that the perturbations of the all parameters of power system were amounted to about 20% were introduced. It was approved that the resultant performances of the proposed $H_{\infty}$ controller with mixed sensitivity were more robust and stable than the one of conventional controllers.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.20-28
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• 2008

This paper proposes a method for solving distribution system planning problems taking into account demand uncertainty and geographical information. The proposed method can automatically select appropriate location and size of a substation, routing of feeders, and appropriate sizes of conductors while satisfying constraints, e.g. voltage drop and thermal limit. The demand uncertainty representing load growth is modeled by fuzzy numbers. Feeder routing is determined with consideration of existing infrastructure, e.g. streets and canals. The method integrates planner's experience and process optimization to achieve an appropriate practical solution. The proposed method has been tested with an actual distribution system, from which the results indicate that it can provide satisfactory plans.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.1-20
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• 2009

The present contribution addresses uncertainty quantification and uncertainty propagation in structural mechanics using stochastic analysis. Presently available procedures to describe uncertainties in load and resistance within a suitable mathematical framework are shortly addressed. Monte Carlo methods are proposed for studying the variability in the structural properties and for their propagation to the response. The general applicability and versatility of Monte Carlo Simulation is demonstrated in the context with computational models that have been developed for deterministic structural analysis. After discussing Direct Monte Carlo Simulation for the assessment of the response variability, some recently developed advanced Monte Carlo methods applied for reliability assessment are described, such as Importance Sampling for linear uncertain structures subjected to Gaussian loading, Line Sampling in linear dynamics and Subset simulation. The numerical example demonstrates the applicability of Line Sampling to general linear uncertain FE systems under Gaussian distributed excitation.

• Earthquakes and Structures
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• v.6 no.1
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• pp.19-43
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• 2014

A risk assessment framework for evaluating building structures is implemented in this study. This framework allows considering sources of uncertainty both on structural capacity and seismic demand. In particular randomness on seismic load, incident angle, material properties, floor mass and structural damping are considered; in addition the choice of fibre modelling versus plastic hinge model is also considered as a source of uncertainty. The main objective of this work is to study the contribution of these sources of uncertainty on the fragilities of steel and steel-reinforced concrete composite 3D building structures. The fragility curves are expressed in the form of a two-parameter lognormal distribution where vertical statistics in conjunction with metaheuristic optimization are implemented for calculating the two parameters.

• Journal of Power Electronics
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• v.12 no.4
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• pp.538-547
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• 2012

This paper presents two different robust controllers for boost converters with two stages in a cascade. The first robust controller is monovariable; that is, the duty-cycle is the same for the two switches. The monovariable controller ensures that some prescribed constraints on pole placement and control effort are met, and optimizes the load disturbance rejection, while takes into account the uncertainty in certain parameters. The first controller is then compared with a multivariable robust controller; that is, with independent duty cycles in each switch. The multivariable controller takes into account the same uncertainty, constraints and optimization function. The comparison shows that the multivariable controller performs better at the expense of a slightly more complex implementation; that is, the multivariable controller provides a better rejection of the load disturbance. The paper also describes simulations and experimental results that are in perfect agreement with theoretical derivations.

• Journal of the Korean Society of Safety
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• v.16 no.4
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• pp.160-167
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• 2001

Cracking in connote structures is one of the main issues of structural design next to ensuring the load-bearing capacity. Thermal analysis is used to prevent thermal mucking, but concrete properties are uncertain variable, and analysis results have uncertainty, too. In this study, sensitivity analysis is performed to investigate the effect of conductivity, specific heal and pouring temperature. The results show that lower conductivity and higher specific heat increase the maximum temperature and maximum tensile stress. The structure with internal restraint is mostly influenced by the change of conductivity and specific heat.