• Title/Summary/Keyword: Estimation Methodology

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Effects of Uncertain Spatial Data Representation on Multi-source Data Fusion: A Case Study for Landslide Hazard Mapping

  • Park No-Wook;Chi Kwang-Hoon;Kwon Byung-Doo
    • Korean Journal of Remote Sensing
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    • v.21 no.5
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    • pp.393-404
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    • 2005
  • As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

A Study on Prediction of Temperature and Humidity for Estimation of Cooling Load (냉방부하 추정을 위한 온도와 습도 예측에 관한 연구)

  • Yoo, Seong-Yeon;Lee, Je-Myo;Han, Kyou-Hyun;Han, Seung-Ho
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.19 no.5
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    • pp.394-402
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    • 2007
  • To estimate the cooling load for the following day, outdoor temperature and humidity are needed in hourly base. But the meteorological administration forecasts only maximum and minimum temperature. New methodology is proposed for predicting hourly outdoor temperature and humidity by using the forecasted maximum and minimum temperature. The correlations for normalized outdoor temperature and specific humidity has been derived from the weather data for five years from 2001 to 2005 at Seoul, Daejeon and Pusan. The correlations for normalized temperature are independent of date, while the correlations for specific humidity are linearly dependent on date. The predicted results show fairly good agreement with the measured data. The prediction program is also developed for hourly outdoor dry bulb temperature, specific humidity, dew point, relative humidity, enthalpy and specific volume.

Environmental Noise Prediction using Scale Model: A Measurement Methodology

  • Kim, Tae-Min;Han, Jae-Hyun;Kim, Jeung-Tae
    • International Journal of Railway
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    • v.4 no.2
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    • pp.42-49
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    • 2011
  • Today, rolling stock has become a fast and convenient mode of transportation and has witnessed increased demand. But the speed improvement has resulted in increased aerodynamic noise and therefore residential districts near the railroad tracks are exposed to ever increasing noise level. A study on methodologies for measuring and appraising rolling stock's environmental noise has therefore become an important area of endeavor. In the case of the environmental noise, there are no changes in tone so prediction can be made by reducing areas around the railway. The present study explores estimation of the noise around the railway using scale model, and the source of the noise has been investigated as well. The scale model of rolling stock will have to be able to measure high frequency noise and it is required to be generated in a short amount of time. Since popping a balloon or firing a gun fits this requirement the present study analyzed the characteristics of these two different noise sources. Measurement was made in a large vacant lot and the reflection due to the ground was also examined. The method proposed here can be used in the future for predicting the environmental noise of railway vehicles.

Modeling Alignment Experiment Errors for Improved Computer-Aided Alignment

  • Kim, Yunjong;Yang, Ho-Soon;Song, Jae-Bong;Kim, Sug-Whan;Lee, Yun-Woo
    • Journal of the Optical Society of Korea
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    • v.17 no.6
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    • pp.525-532
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    • 2013
  • Contrary to the academic interests of other existing studies elsewhere, this study deals with how the alignment algorithms such as sensitivity or Differential Wavefront Sampling (DWS) can be better used under effects from field, compensator positioning and environmental errors unavoidable from the shop-floor alignment work. First, the influences of aforementioned errors to the alignment state estimation was investigated with the algorithms. The environmental error was then found to be the dominant factor influencing the alignment state prediction accuracy. Having understood such relationship between the distorted system wavefront caused by the error sources and the alignment state prediction, we used it for simulated and experimental alignment runs for Infrared Optical System (IROS). The difference between trial alignment runs and experiment was quite close, independent of alignment methods; 6 nm rms for sensitivity method and 13 nm rms for DWS. This demonstrates the practical usefulness and importance of the prior error analysis using the alignment algorithms before the actual alignment runs begin. The error analysis methodology, its application to the actual alignment of IROS and their results are described together with their implications.

Cohort-based evacuation time estimation using TSIS-CORSIM

  • Park, Sunghyun;Sohn, Seokwoo;Jae, Moosung
    • Nuclear Engineering and Technology
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    • v.53 no.6
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    • pp.1979-1990
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    • 2021
  • Evacuation Time Estimate (ETE) can provide decision-makers with a likelihood to implement evacuation of a population with radiation exposure risk by a nuclear power plant. Thus, the ETE is essential for developing an emergency response preparedness. However, studies on ETE have not been conducted adequately in Korea to date. In this study, different cohorts were selected based on assumptions. Existing local data were collected to construct a multi-model network by TSIS-CORSIM code. Furthermore, several links were aggregated to make simple calculations, and post-processing was conducted for dealing with the stochastic property of TSIS-CORSIM. The average speed of each cohort was calculated by the link aggregation and post-processing, and the evacuation time was estimated. As a result, the average cohort-based evacuation time was estimated as 2.4-6.8 h, and the average clearance time from ten simulations in 26 km was calculated as 27.3 h. Through this study, uncertainty factors to ETE results, such as classifying cohorts, degree of model complexity, traffic volume outside of the network, were identified. Various studies related to these factors will be needed to improve ETE's methodology and obtain the reliability of ETE results.

Economic-based approach for predicting optimal water pipe renewal period based on risk and failure rate

  • Kim, Kibum;Seo, Jeewon;Hyung, Jinseok;Kim, Taehyeon;Kim, Jaehag;Koo, Jayong
    • Environmental Engineering Research
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    • v.24 no.1
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    • pp.63-73
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    • 2019
  • This study suggests a method for calculating the benefits of water pipe renewal based on an estimate of the water supply suspension risk. The proposed method based on five benefit items is more direct and specific than other benefit estimation methods. In addition, a methodology evaluating the economics of pipe renewal based on pipe failure rate is proposed for estimating the optimal renewal point from an economic perspective. By estimating the optimal renewal period based on a yearly benefit cost ratio per pipe in a case study area, it was possible to draft an optimal renewal plan for the subject region from an economic perspective. Compared with other methodologies, a reasonable optimal renewal period was derived from an economic point of view. The result of this study may be used to develop future water pipe renewal plans. Moreover, the proposed methodologies and results derived from this study can be applied to asset management plans.

Fragility assessment for electric cabinet in nuclear power plant using response surface methodology

  • Tran, Thanh-Tuan;Cao, Anh-Tuan;Nguyen, Thi-Hong-Xuyen;Kim, Dookie
    • Nuclear Engineering and Technology
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    • v.51 no.3
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    • pp.894-903
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    • 2019
  • An approach for collapse risk assessment is proposed to evaluate the vulnerability of electric cabinet in nuclear power plants. The lognormal approaches, namely maximum likelihood estimation and linear regression, are introduced to establish the fragility curves. These two fragility analyses are applied for the numerical models of cabinets considering various boundary conditions, which are expressed by representing restrained and anchored models at the base. The models have been built and verified using the system identification (SI) technique. The fundamental frequency of the electric cabinet is sensitive because of many attached devices. To bypass this complex problem, the average spectral acceleration $S_{\bar{a}}$ in the range of period that cover the first mode period is chosen as an intensity measure on the fragility function. The nonlinear time history analyses for cabinet are conducted using a suite of 40 ground motions. The obtained curves with different approaches are compared, and the variability of risk assessment is evaluated for restrained and anchored models. The fragility curves obtained for anchored model are found to be closer each other, compared to the fragility curves for restrained model. It is also found that the support boundary conditions played a significant role in acceleration response of cabinet.

Evaluation of nuclear material accountability by the probability of detection for loss of Pu (LOPu) scenarios in pyroprocessing

  • Woo, Seung Min;Chirayath, Sunil S.
    • Nuclear Engineering and Technology
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    • v.51 no.1
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    • pp.198-206
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    • 2019
  • A new methodology to analyze the nuclear material accountability for pyroprocessing system is developed. The $Pu-to-^{244}Cm$ ratio quantification is one of the methods for Pu accountancy in pyroprocessing. However, an uncertainty in the $Pu-to-^{244}Cm$ ratio due to the non-uniform composition in used fuel assemblies can affect the accountancy of Pu. A random variable, LOPu, is developed to analyze the probability of detection for Pu diversion of hypothetical scenarios at a pyroprocessing facility considering the uncertainty in $Pu-to-^{244}Cm$ ratio estimation. The analysis is carried out by the hypothesis testing and the event tree method. The probability of detection for diversion of 8 kg Pu is found to be less than 95% if a large size granule consisting of small size particles gets sampled for measurements. To increase the probability of detection more than 95%, first, a new Material Balance Area (MBA) structure consisting of more number of Key Measurement Points (KMPs) is designed. This multiple KMP-measurement for the MBA shows the probability of detection for 8 kg Pu diversion is greater than 96%. Increasing the granule sample number from one to ten also shows the probability of detection is greater than 95% in the most ranges for granule and powder sizes.

Buckling Strength Increment of Curved Panels Due to Rotational Stiffness of Closed-Section Ribs Under Uniaxial Compression

  • Andico, Arriane Nicole P.;Park, Yong-Myung;Choi, Byung H.
    • International journal of steel structures
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    • v.18 no.4
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    • pp.1363-1372
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    • 2018
  • Recently, there have been studies about the increasing effect on the local plate buckling strength of flat plates when longitudinally stiffened with closed-section ribs and an approximate solution to quantitatively estimate these effects were suggested for flat plates. Since there are few studies to utilize such increasing effect on curved panels and a proper design method is not proposed, thus, this study aims to numerically evaluate such effect due to the rotational stiffness of closed-section ribs on curved panels and to propose an approximate method for estimating the buckling strength. Three-dimensional finite element models were set up using a general structural analysis program ABAQUS and a series of parametric numerical analyses were conducted in order to examine the variation of buckling stresses along with the rotational stiffness of closed-section ribs. By using a methodology that combine the strength increment factor due to the restraining effect by closed-section ribs and the buckling coefficient of the panel curvature, the approximate solutions for the estimation of buckling strength were suggested. The validity of the proposed methods was verified through a comparative study with the numerical analysis results.

Bayesian and maximum likelihood estimations from exponentiated log-logistic distribution based on progressive type-II censoring under balanced loss functions

  • Chung, Younshik;Oh, Yeongju
    • Communications for Statistical Applications and Methods
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    • v.28 no.5
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    • pp.425-445
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    • 2021
  • A generalization of the log-logistic (LL) distribution called exponentiated log-logistic (ELL) distribution on lines of exponentiated Weibull distribution is considered. In this paper, based on progressive type-II censored samples, we have derived the maximum likelihood estimators and Bayes estimators for three parameters, the survival function and hazard function of the ELL distribution. Then, under the balanced squared error loss (BSEL) and the balanced linex loss (BLEL) functions, their corresponding Bayes estimators are obtained using Lindley's approximation (see Jung and Chung, 2018; Lindley, 1980), Tierney-Kadane approximation (see Tierney and Kadane, 1986) and Markov Chain Monte Carlo methods (see Hastings, 1970; Gelfand and Smith, 1990). Here, to check the convergence of MCMC chains, the Gelman and Rubin diagnostic (see Gelman and Rubin, 1992; Brooks and Gelman, 1997) was used. On the basis of their risks, the performances of their Bayes estimators are compared with maximum likelihood estimators in the simulation studies. In this paper, research supports the conclusion that ELL distribution is an efficient distribution to modeling data in the analysis of survival data. On top of that, Bayes estimators under various loss functions are useful for many estimation problems.