• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.629-634
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• 2016

In this study, we investigated the effect of factors that influence the measurement of smoke density using synthetic rubber flooring. The characteristics of rolling stock in an enclosed environment can cause enormous loss of life by smoke inhalation during fires inside passenger cars. The amount of smoke generation from interior materials for rolling stock is strictly restricted domestically and in other countries. Precise measurement of smoke density is therefore required to assess the fire performance of interior materials. Major factors that influence the measurement of smoke density include the uniformity of the specimen, the variations in conditions and instruments, and the operational and maintenance environment of the instruments. The contribution of factors was analyzed by estimating the uncertainty to investigate the contribution ratios of the major factors. The results show a contribution ratio of about 86% for the variation from the measurement of light transmission using a photomultiplier tube. Thus, this factor was the most representative for the measurement of smoke density. The contribution ratio of the other factors was low at about 11%, including irradiant flux conditions (${\pm}0.5 kW/m^2$) and the influence of the operational and maintenance environment of the instrument. These results were obtained using specimens with high uniformity.

• Journal of the Korean Geotechnical Society
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• v.18 no.2
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• pp.51-64
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• 2002

Observational results of ground movement during the construction were very different from those predicted during the analysis of design step because of the uncertainty of the numerical analysis modelling, the soil parameter, and the condition of a construction field, etc., however accurately numerical analysis method was applied for prediction of ground movement per the excavation step. Therefore, the management system through the construction field measurement should be achieved for grasping the situation during the excavation. Until now, the measurement system restricted by 'Absolute Value Management system'analyzing only the stability of present step has been executed. So, it was difficult to expect the prediction of ground movement fur the next excavation step. In this situation, this study developed 'The Management system TOMAS-EXCAV'consisted of 'Absolute value management system'analyzing the stability of present step and 'Prediction management system'expecting the ground movement of next excavation step and analyzing the stability of next excavation step by 'Back Analysis'. TOMAS-EXCAV could be applied to all the uncertainty of earth retaining structures analysis by connecting 'Forward analysis program'and 'Back analysis program'and optimizing the main design variables using SQP-MMFD optimization method through measurement results. The applicability of TOMAS-EXCAV was confirmed by back analysis selecting two earth retains construction fields.

• Plant Journal
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• v.17 no.4
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• pp.53-60
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• 2021

The purpose of this study was to develop a portable vibration analyzer that is effective for acquiring and analyzing vibration data of rotating equipment of a power plant and a domestic vibration monitoring system manufacturer Nada Co., Ltd. The hardware of the developed portable vibration analyzer minimizes measurement errors by calibrating the measured values obtained through measurement uncertainty for calibration of the measuring devices in the system, and is composed of a signal processing device with high resolution through high speed data processing. The software structure implements a variety of vibration plots to execute a detailed analysis program, and applies algorithms to measure and remove noise caused by disturbances while operating a rotating machine. The developed product contributed greatly to increase the user's mobility and performance, as well as to reduce the purchase cost due to localization.

• Analytical Science and Technology
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• v.21 no.6
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• pp.502-509
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• 2008

An ID LC/MS (isotope dilution liquid chromatography/mass spectrometry) was used as a primary method for the quantitative analysis of cholesterol in human serum. The separation of cholesterol was carried out by Thermo ODS hypersil $C^{18}$ column. The mobile phase was 100% methanol, and flow rate was $0.3m{\ell}/min$. Cholesterol and cholesterol-$3,4-13C_2$ were monitored at m/z 369.4 and 371.3, which correspond to $[M-H_2O+H]^+$ respectively. In order to verify the measurement method, NIST SRM 909b was analyzed. The results agreed well with certified values within uncertainty. The four kinds of serum certified reference material were prepared and certified. The repeatabilities of measurement were ranged from 0.1 to 0.8% (RSD), which were relatively good. The reproducibility between independent measurement run was below 0.24% (RSD). The expanded uncertainty was about 1.43% within the 95% confidence interval.

• Current Research on Agriculture and Life Sciences
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• v.31 no.2
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• pp.113-123
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• 2013

The carbon-offset mechanism based on forest management has been recognized as a meaningful tool to sequestrate carbons already existing in the atmosphere. Thus, with an emphasis on the forest-originated carbon-offset mechanism, the accurate measurement of the carbon stock in forests has become important, as carbon credits should be issued proportionally with forest carbon stocks. Various remote sensing techniques have already been developed for measuring forest carbon stocks. Yet, despite the efficiency of remote sensing techniques, the final accuracy of their carbon stock estimations is disputable. Therefore, minimizing the uncertainty embedded in the application of remote sensing techniques is important to prevent questions over the carbon stock evaluation for issuing carbon credits. Accordingly, this study reviews the overall procedures of carbon stock evaluation-related remote sensing techniques and identifies the problematic technical issues when measuring the carbon stock. The procedures are sub-divided into four stages: the characteristics of the remote sensing sensor, data preparation, data analysis, and evaluation. Depending on the choice of technique, there are many disputable issues in each stage, resulting in quite different results for the final carbon stock evaluation. Thus, the establishment of detailed standards for each stageis urgently needed. From a policy-making perspective, the top priority should be given to establishinga standard sampling technique and enhancing the statistical analysis tools.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3563-3579
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• 2021

Measured decay heat data of light water reactor (LWR) spent nuclear fuel (SNF) assemblies are adopted to train machine learning (ML) models. The measured data is available for fuel assemblies irradiated in commercial reactors operated in the United States and Sweden. The data comes from calorimetric measurements of discharged pressurized water reactor (PWR) and boiling water reactor (BWR) fuel assemblies. 91 and 171 measurements of PWR and BWR assembly decay heat data are used, respectively. Due to the small size of the measurement dataset, we propose: (i) to use the method of multiple runs (ii) to generate and use synthetic data, as large dataset which has similar statistical characteristics as the original dataset. Three ML models are developed based on Gaussian process (GP), support vector machines (SVM) and neural networks (NN), with four inputs including the fuel assembly averaged enrichment, assembly averaged burnup, initial heavy metal mass, and cooling time after discharge. The outcomes of this work are (i) development of ML models which predict LWR fuel assembly decay heat from the four inputs (ii) generation and application of synthetic data which improves the performance of the ML models (iii) uncertainty analysis of the ML models and their predictions.

• Geomechanics and Engineering
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• v.24 no.3
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• pp.281-293
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• 2021

Uncertainties in geomechanical input parameters which mainly related to inappropriate data acquisition and estimation due to lack of sufficient calibration information, have led wellbore instability not yet to be fully understood or addressed. This paper demonstrates a workflow of employing Quantitative Risk Assessment technique, considering these uncertainties in terms of rock properties, pore pressure and in-situ stresses to makes it possible to survey not just the likelihood of accomplishing a desired level of wellbore stability at a specific mud pressure, but also the influence of the uncertainty in each input parameter on the wellbore stability. This probabilistic methodology in conjunction with Monte Carlo numerical modeling techniques was applied to a case study of a well. The response surfaces analysis provides a measure of the effects of uncertainties in each input parameter on the predicted mud pressure from three widely used failure criteria, thereby provides a key measurement for data acquisition in the future wells to reduce the uncertainty. The results pointed out that the mud pressure is tremendously sensitive to UCS and SHmax which emphasize the significance of reliable determinations of these two parameters for safe drilling. On the other hand, the predicted safe mud window from Mogi-Coulomb is the widest while the Hoek-Brown is the narrowest and comparing the anticipated collapse failures from the failure criteria and breakouts observations from caliper data, indicates that Hoek-Brown overestimate the minimum mud weight to avoid breakouts while Mogi-Coulomb criterion give better forecast according to real observations.

• Mass Spectrometry Letters
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• v.5 no.2
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• pp.57-61
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• 2014

A gravimetric standard addition method combined with internal standard calibration has been successfully developed for the accurate analysis of total arsenic in a laver candidate reference material. A model equation for the gravimetric standard addition approach using an internal standard was derived to determine arsenic content in samples. Handlings of samples, As standard and internal standard were carried out gravimetrically to avoid larger uncertainty and variability involved in the volumetric preparation. Germanium was selected as the internal standard because of its close mass to the arsenic to minimize mass-dependent bias in mass spectrometer. The ion signal ratios of $^{75}As^+$ to $^{72}Ge^+$ (or $^{73}Ge^+$) were measured in high resolution mode ($R{\geq}10,000$) to separate potential isobaric interferences by high resolution ICP/MS. For method validation, the developed method was applied to the analysis of arsenic content in the NMIJ 7402-a codfish certified reference material (CRM) and the result was $37.07mg{\cdot}kg^{-1}{\pm}0.45mg{\cdot}kg^{-1}$ which is in good agreement with the certified value, $36.7mg{\cdot}kg^{-1}{\pm}1.8mg{\cdot}kg^{-1}$. Finally, the certified value of the total arsenic in the candidate laver CRM was determined to be $47.15mg{\cdot}kg^{-1}{\pm}1.32mg{\cdot}kg^{-1}$ (k = 2.8 for 95% confidence level) which is an excellent result for arsenic measurement with only 2.8 % of relative expanded uncertainty.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.12
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• pp.1-8
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• 2011

Actively in progress in the field of general industrial KOLAS (Korea Laboratory Accreditation Scheme) accreditation test the switch, router, network equipment, such as accreditation status in the field can not be found. Company's self-tsting or BMT (Bench Marking Test) through the evaluation process for network equipment, but the test reports issued by accredited laboratories with quality differences. Requested by public institutions or other providers of accredited test reports increasing demand for network equipment in Korea accredited testing laboratory shall be made as soon as possible. In this paper, as required by KOLAS in the field of network equipment testing laboratory accreditation program in the process acquired through the analysis of measurement uncertainty and, to propose effective direction.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.12
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• pp.1351-1358
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• 2011

To approximate the threshold of the fault detection and diagnosis (FDD) system, validation of the measurements is mandatory. Naturally, the system shows uncertainties due to measuring sensors - mostly thermocouples or RTDs - and due to repeatability. The uncertainty of a thermocouple comes from natural variation or a drift of the thermocouple measurement. Considering the natural variation behaves like zero-mean white noise, its natural variation can be characterized closely by the steady-state standard deviation. However, residuals between measurements and no-fault references in FDD systems show a statistical distribution with various uncertainties. In this paper, steady-state variations of measurement residuals were investigated by utilizing built-in temperature sensors in a heat pump for the model development and the final application.