• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.188-188
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• 2000

The most important problem in target tracking can be said to be modeling the tracking system correctly. Although the simple linear dynamic equation for this model has used until now, the satisfactory performance could not be obtained owing to uncertainties of the real systems in the case of designing the filters baged on the dynamic equations. In this paper, we propose the extended robust Kalman filter (ERKF) which can be applied to the real target tracking system with the parameter uncertainties. A nonlinear dynamic equation with parameter uncertainties is used to express the uncertain system model mathematically, and a measurement equation is represented by a nonlinear equation to show data from the radar in a Cartesian coordinate frame. To solve the robust nonlinear filtering problem, we derive the extended robust Kalman filter equation using the Krein space approach and sum quadratic constraint. We show the proposed filter has better performance than the existing extended Kalman filter (EKF) via 3-dimensional target tracking example.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.186-197
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• 1996

A multiple target tracking (MTT) problem is to track a number of targets in clusttered environment, where measurements may contain uncertainties of measurement origin due to clutter, missed detection, or other targets, as well as measurement noise errors. Hence, an MTT filter should be introduced to resolve this problem. In this paper, a neural network is rpoposed as an MTT filter.

• Journal of Mechanical Science and Technology
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• v.18 no.4
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• pp.689-698
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• 2004

Uncertainties generated from the individual measured variables have an influence on the uncertainty of the experimental result through a data reduction equation. In this study, a performance test of a single stage axial type turbine is conducted, and total-to-total efficiencies are measured at the various off-design points In the low pressure and cold state. Based on an experimental apparatus, a data reduction equation for turbine efficiency is formulated and six measured variables are selected. Codes are written to calculate the efficiency, the uncertainty of the efficiency, and the sensitivity of the efficiency uncertainty by each of the measured quantities. The influence of each measured variable on the experimental result is figured out. Results show that the largest uncertainty magnification factor (UMF) value is obtained by the inlet total pressure among the six measured variables, and its value is always greater than one. The UMF values of the inlet total temperature, the torque, and the RPM are always one. The uncertainty percentage contribution (UPC) of the RPM shows th, lowest influence on the uncertainty of the turbine efficiency, but the UPC of the torque has the largest influence to the result among the measured variables. These results are applied to find the correct direction for meeting an uncertainty requirement of the experimental result in the planning or development Phase of experiment, and also to offer ideas for preparing a measurement system in the planning phase.

• Journal of Radiation Protection and Research
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• v.43 no.1
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• pp.29-38
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• 2018

Background: Radon contributing about 42% of annual average dose, mainly comes from soil. In this paper, standard measurement procedures for soil radon exhalation rate are suggested and their measurement uncertainties are analyzed. Materials and Methods: We used accumulation method for estimating surface exhalation rate. The closed-loop measurement system was made up with a RAD7 detector and a surface chamber. Radon activity concentrations in the system were observed as a function of time, with data collection of 5 and 15-minute and the measurement time of 4 hours. Linear and exponential fittings were used to obtain radon exhalation rates from observed data. Standard deviations of measurement uncertainties for two approaches were estimated using usual propagation rules. Results and Discussion: The exhalation rates (E) from linear approach, with 30 minutes measurement time were $44.8-48.6mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.14-2.32atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with relative measurement uncertainty of about 10%. The contributions of fitting parameter A, volume (V) and surface (S) to the estimated measurement uncertainty of E were 59.8%, 30.1% and 10.1%, in average respectively. In exponential fitting, at 3-hour measurement we had E ranged of $51.6-69.2mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.46-3.30atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with about 15% relative uncertainty. Fitting with 4-hour measurement resulted E about $51.3-68.2mBq{\cdot}m^{-2} {\cdot}s^{-1}$ or $2.45-3.25atom{\cdot}cm^{-2}{\cdot}s^{-1}$ with 10% relative uncertainty. The uncertainty contributions in exponential approach were 75.1%, 13.4%, 8.7%, and 2.9% for total decay constant k, fitting parameter B, V, and S, respectively. Conclusion: In obtaining exhalation rates, the linear approach is easy to apply, but by saturation feature of radon concentrations, the slope tends to decrease away from the expected slope for extended measurement time. For linear approach, measurement time of 1-hour or less was suggested. For exponential approach, the obtained exhalation rates showed similar values for any measurement time, but measurement time of 3-hour or more was suggested for about 10% relative uncertainty.

• Atmosphere
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• v.25 no.1
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• pp.19-30
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• 2015

The Ka-band cloud radar (KCR) has been operated by the National Institute of Meteorological Research (NIMR) of Korea Meteorological Administration (KMA) at Boseong National Center for Intensive Observation of severe weather since 2013. Evaluation of data quality is an essential process to further analyze cloud information. In this study, we estimate the measurement error and the sampling uncertainty to evaluate data quality. By using vertically pointing data, the statistical uncertainty is obtained by calculating the standard deviation of each radar parameter. The statistical uncertainties decrease as functions of sampling number. The statistical uncertainties of horizontal and vertical reflectivities are identical (0.28 dB). On the other hand, the statistical uncertainties of Doppler velocity (spectrum width) are 2.2 times (1.6 times) larger at the vertical channel. The reflectivity calibration of KCR is also performed using X-band vertically pointing radar (VertiX) and 2-dimensional video disdrometer (2DVD). Since the monitoring of calibration values is useful to evaluate radar condition, the variation of calibration is monitored for five rain events. The average of calibration bias is 10.77 dBZ and standard deviation is 3.69 dB. Finally, the statistical characteristics of cloud properties have been investigated during two months in autumn using calibrated reflectivity. The percentage of clouds is about 26% and 16% on September to October. However, further analyses are required to derive general characteristics of autumn cloud in Korea.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.485-499
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• 2012

Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring; however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Hong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.

• Economic and Environmental Geology
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• v.37 no.1
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• pp.49-59
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• 2004

The concectration and distribution of contaminants obtained from a contaminated land investigation or an environmental geochemistry survey constitutes the basis of a decision-making process on environmental policies or of scientific researches. As the quality of data determines the reliability of the result, the investigation plan should be adjusted according to the purpose of the investigation. In general, the effort to improve the data quality had been focused mainly on the QA/QC procedures in laboratories. The rapid progress of analytical instrument has also contributed toward improving the analytical precision to a sacrificable degree. Nevertheless, in many cases, it is not the analytical precision that needs improvement for the better precision of overall measurement process: it is rather during the sampling process in the field that is responsible for the poor precision. To assess the data quality on a measured value, ISO recommends to provide information on "measurement uncertainty" along with the measured value. The measurement uncertainty in an environmental measurement context can be explained as the statistical number that expresses the degree of the uncertainty stemming from the sampling and analytical procedures. There is a cost involved in order to improve the precision of sampling and analytical methods so as to decrease the degree of measurement uncertainty. The economical point of compromise in an investigation planning can be achieved when the allowable degree of uncertainty has been set before-hand. The investigation can then be planned accordingly not to exceed the uncertainty limit. Furthermore, if the measurement uncertainty estimated from the preliminary investigation can be separated into sampling and analytical uncertainties, it can be used as a criterion where the resources for the investigation should be allotted cost-effectively to reinforce the weakest link of the whole investigation process. This paper aims to present a method of estimating the level of measurement uncertainty of a measured contamination concentration at a site used as an example and to show how the estimated uncertainty can be applied to serve the particular purpose of an investigation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.156.4-156
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• 2001

The uncertainties of an atmospheric re-entry flight with respect to stability and controllability are aerodynamic error, measurement error of the angle of attack, variation of dynamic pressure, wind, and trim position of the control surfaces, etc. During hypersonic flight, a future angle of attack is biased from a nominal schedule. In order words, because the angle of attack is estimated from the navigation data, estimation error occurs due to wind, atmospheric density variation, etc. Error models used in this study, include a standard deviation of +-3 sigma, and are the normal distribution of statistics. This paper shows the appraisement of tracking performance onto the reference trajectory, satisfaction of the initial condition of TAEM about the re-entry system.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1855-1866
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• 2003

This paper discusses an entire procedure for a robust controller design and its implementation of an AMB (active magnetic bearing) spindle, which is part II of the papers presenting details of system modeling and robust control of an AMB spindle. Since there are various uncertainties in an AMB system and reliability is the most important factor for applications, robust control naturally gains attentions in this field. However, tight evaluations of various uncertainties based on experimental data and appropriate performance weightings for an AMB spindle are still ongoing research topics. In addition, there are few publications on experimental justification of a designed robust controller. In this paper, uncertainties for the AMB spindle are classified and described based on the measurement and identification results of part I, and an appropriate performance weighting scheme for the AMB spindle is developed. Then, a robust control is designed through the mixed ${\mu}$ synthesis based on the validated accurate nominal model of part I, and the robust controller is reduced considering its closed loop performance. The reduced robust controller is implemented and confirmed with measurements of closed-loop responses. The AMB spindle is operated up to 57,600 rpm and performance of the designed controller is compared with a benchmark PID controller through experiments. Experiments show that the robust controller offers higher stiffness and more efficient control of rigid modes than the benchmark PID controller.