• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.684-701
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• 2016

The Gaussian process model (GPM) is a flexible surrogate model that can be used for nonparametric regression for multivariate problems. A unique feature of the GPM is that a prediction variance is automatically provided with the regression function. In this paper, we estimate the safety margin of a nuclear power plant by performing regression on the output of best-estimate simulations of a large-break loss-of-coolant accident with sampling of safety system configuration, sequence timing, technical specifications, and thermal hydraulic parameter uncertainties. The key aspect of our approach is that the GPM regression is only performed on the dominant input variables, the safety injection flow rate and the delay time for AC powered pumps to start representing sequence timing uncertainty, providing a predictive model for the peak clad temperature during a reflood phase. Other uncertainties are interpreted as contributors to the measurement noise of the code output and are implicitly treated in the GPM in the noise variance term, providing local uncertainty bounds for the peak clad temperature. We discuss the applicability of the foregoing method to reduce the use of conservative assumptions in best estimate plus uncertainty (BEPU) and Level 1 probabilistic safety assessment (PSA) success criteria definitions while dealing with a large number of uncertainties.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.639-645
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• 2013

The aim of the study is to investigate the method to estimate a storage life of propelling charge on the decrease of muzzle velocity by stochastic gamma process model. It is required to establish criterion for state failure to estimate the storage life and it is defined in this paper as a muzzle velocity difference between reference value and maximum allowable standard deviation multiplied by 6. The relationship between storage time and muzzle velocity is investigated by nonlinear regression analysis. The stochastic gamma process model is used to estimated the state distribution and the life distribution for storage time for 155mm propelling charge KM4A2 because the regression analysis is a deterministic method and it can't describe the distribution of life for storage time.

• Journal of Distribution Science
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• v.11 no.12
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• pp.5-11
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• 2013

Purpose - The purpose of this study was to construct a turnover estimation model by investigating research by Park et al. (2006) on the market area of domestic distribution. The study investigated distribution by using a new tool for the turnover estimation technique. This study developed and discussed the turnover estimation technique of Park et al. (2006), applying it to a large-scale retailer in "D"city that was suitable for on-the-spot distribution. It constructed the new model in accordance with test procedures keeping to this retail business location, to apply its procedures to a specific situation and improve the turn over estimation process. Further, it investigated the analysis and procedures of existing turnover estimation cases to provide problems and alternatives for turnover estimation for a large-scale retailer in "D"city. Finally, it also discussed problems and scope for further research. Research design, data, and methodology - This study was conducted on the basis of "virtue" studies. In other words, it took into account the special quality of the structure of Korea's trade zones. The researcher sought to verify a sale estimate model for use in a distribution industry's location. The main purpose was to enable the sale estimate model (that is, the individual model's presentation) to be practically used in real situations in Korea by supplementing processes and variables. Results - The sale estimate model is constructed, first, by conducting a data survey of the general trading area. Second, staying within the city's census of company operating areas, the city's total consumption expenditure is derived by applying the large-scale store index. Third, the probability of shopping is investigated. Fourth, the scale of sales is estimated using the process of singularity. The correct details need to be verified for the model construction and the new model will need to be a distinct sale estimate model, with this being a special quality for business conditions. This will need to be a subsequent research task. Conclusions - The study investigated, tested, and supplemented the turnover estimation model of Park et al. (2006) in a market area in South Korea. Supplementation of some procedures and variables could provide a turnover estimation model in South Korea that would be an independent model. The turnover estimation model is applied, first, by undertaking an investigation of the market area. Second, a census of the intercity market area is carried out to estimate the total consumption of the specific city. Consumption is estimated by applying indexes of large-scale retailers. Third, an investigation is undertaken on the probability of shopping. Fourth, the scale of turnover is estimated. Further studies should investigate each department as well as direct and indirect variables. The turnover estimation model should be tested to construct new models depending on the type of region and business. In-depth and careful discussion by researchers is also needed. An upgraded turnover estimation model could be developed for Korea's on-the-spot distribution.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.10 s.181
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• pp.2581-2588
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• 2000

In previous studies, the dynamic resistance, which was calculated by the process variables measured at the electrode of the welding machine, and the electrode displacement were used for quality exa mination. However, in-process usage of such systems is not effective in systems that include a welding gun attached to a robot. In order to overcome such problems, we obtained and used the process variables from the welding machine timer. This would allow us to estimate real time in -process weld quality. For quality estimation, the features were extracted as factors from the primary dynamic resistance patterns, which were measured in t he welding machine timer. The relationship between the indexes and nugget size of the welds was observed through the regression analysis. Using the analyzed factors, a regression model that could estimate nugget diameter was developed. Two regression equations of the model were suggested depending on the factors, and it was showed that the model developed by stepwise method was effective one for weld quality estimation. The developed estimation model was in good linearity with the nugget diameter obtained through the experimentation.

• Bulletin of the Korean Mathematical Society
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• v.39 no.4
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• pp.705-714
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• 2002

We consider a jump-diffusion model generated by a Levy process for an asset price. We present an error estimate for the option prices between the jump-diffusion model and the Black-scholes model when the former converges weakly to the latter.

• Computers and Concrete
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• v.25 no.5
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• pp.433-445
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• 2020

A method is proposed in this paper to estimate the workability of self-compacting concrete (SCC) in different mixing conditions with different mixers and mixing volumes by recording the mixing process based on deep learning (DL). The SCC mixing videos were transformed into a series of image sequences to fit the DL model to predict the SF and VF values of SCC, with four groups in total and approximately thirty thousand image sequence samples. The workability of three groups SCC whose mixing conditions were learned by the DL model, was estimated. One additionally collected group of the SCC whose mixing condition was not learned, was also predicted. The results indicate that whether the SCC mixing condition is included in the training set and learned by the model, the trained model can estimate SCC with different workability effectively at the same time. Our goal to estimate SCC workability in different mixing conditions is achieved.

• Journal of Information Technology Applications and Management
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• v.21 no.4
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• pp.225-245
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• 2014

ICT based convergence application is one of the most prevalent industrial issue these days. Despite of criticalness and potential economic opportunities of the ICT based convergence, theoretical research to analyze the feasibility and estimate the economic impact of the application is rather limited. This paper is intended to fill this research gap. In this respect, we develop theoretical framework to quantitatively estimate the differential benefits of convergent applications, which necessarily include underling ICT technology's contribution attributes extractions, and resulting value increments engendered from user's process effectiveness when ICT based service application is adopted. The research model to assess the differential value of the ICT based service application is developed, grounded on theoretical framework of TPC (Technology-to-performance chain) and contingency fit theories. Scenario based survey method is adopted, and SmartPLS 2.0. is used for statistical analysis of the structural equation model using 312 questionnaire. Valid statistical results are presented to provide useful insight.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.32-42
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• 2006

This study aims at establishing a technique for sailing yachts model tests with sailing condition. It is very important to estimate a ship's potential speed performance before building a real ship. Several methods are used to estimate a ship's potential speed performance such as using parent ship data, standard vessel chart and model test. Model test is the most precise among these options. In korea. model testing is widely used with general vessels but not with sailing yachts. Because sailing yachts are propelled with heeling and leeway. using the wind. another method is needed to estimate their speed. The new model test. which is different from tests for upright general vessels, is in a great demand. In this paper. we describe a test method for the sailing yacht model test. based on Masuyama's equation of motion. And we describe choosing scale ratio. production process and materials of the model. Also. various ways of measuring instruments. attaching jigs and adjusting calibration are described so that they can be utilized as useful data for model testing.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1173-1177
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• 2015

This paper deals with estimating the acid concentration of pickling process using the Volterra inputs. To estimate the acid concentration, the whole pickling process is represented by the grey box model consists of the white box dealing with known system and the black box dealing with unknown system. Because there is a possibility of nonlinear term in the unknown system, the Volterra series are used to estimate the acid concentration. For the white box modeling, the acid tank solution level and concentration equations are used, and for the black box modeling, the acid concentration is estimated using the Volterra Least Mean Squares (LMS) algorithm and Least Squares (LS) algorithm. The LMS algorithm has the advantage of the simple structure and the low computation, and the LS algorithm has the advantage of lowest error. The simulation results compared to the measured data are included.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.165-168
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• 1996

In this paper, we propose a design method of PID adaptive controller based on frequency domain analysis. The method is based on the estimation of a nonparametric process model in the frequency domain and the determination of the PID controller parameters by achieving partial model matching so as to minimize a performance function concerning to relative model error between the loop transfer function of the control system and the desired system. In the design method the process is represented only by a discrete set of points on the Nyquist curve of the process. Therefore it is not necessary to estimate a full order parameterized process model.