• Journal of Korean Society of Transportation
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• v.28 no.3
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• pp.119-130
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• 2010

Reconstruction analysis of traffic accident is done by analyzing diverse data such as the road, accident traces and damage on the automobile. Most data can be a variable in the process of analysis, and measurement error of the data occurs from the investigator, tool and the given environment. Therefore, accident analysis always has some risks of measurement uncertainty. This research quantify the uncertainty in traffic accident analysis by conducting repetitive measurement experiments for variables with high probability of uncertainly such as length (i.e. geometric structure of the road, tire marks) and coefficient of friction. This paper also suggests an analysis result for the uncertainly of photographic observation of automobile crush measurement. These statistical distributions can help determine appropriate ranges for the input data in order to estimate the accident reconstruction uncertainty.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.331-332
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.118-125
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• 1997

Non-contacting optical microscopes are increasingly used in recent industrial applications of probes for coordinate measuring machines. They have been found more efficient than conventional touch trigger porbes with ball tips especially in inspecting small-sized objects. There are two major factors affecting measuring accuracy: (1) geometric relations between coordinate systems, (2) magnification ratios of a microscope. In order to determine the magnification ratios exactly, optical imaging of edge was theroretically analyzed and practically adopted to image processing for edge detection. In addition, this paper proposes a geometric calibration method to obtain exact coordinates of measured points from the relations between the machine coordinate system and the image. In the method, the error according to the squareness between the machine axises was also removed. The method was practically adopted to a real coordinate measuring machine. An ultraprecision measurement of 0.2 um uncertainty can be practically achieved.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.438-443
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• 2003

In this paper, we propose a control algorithm for two-wheel mobile robot that can move the rider to his or her command and autonomously keep its balance. The control algorithm is based on a mixed $H_2/H_{\infty}$ control scheme. In this control problem the main issue is to move the rider while keeping its balance in the presence of disturbances and parameter uncertainties. The disturbance force caused by uneven road surfaces and the uncertainty due to different rider's heights are considered. To this end we first consider a state feedback controller as a basic framework. Secondly, we obtain the state feedback gain $K_2$ minimizing the $H_2$ norm and the state feedback gain $K_{\infty}$ minimizing the $H_{\infty}$ norm over the whole range of parameter uncertainty. Finally, we select mixed $H_2$/$H_{\infty}$ state feedback controller K as the geometric mean of $K_2$ and $K_{\infty}$. Simulation results show that the mixed $H_2/H_{\infty}$ state feedback controller combines the effects of the optimal $H_2$ state feedback controller and robust $H_{\infty}$ controller state feedback controller efficiently in the presence of disturbance and parameter uncertainty.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.311-330
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• 2007

Model-based predictions of structural behavior are negatively affected by uncertainties of various type and in various stages of the structural analysis. The present paper focusses on dynamic analysis and addresses the effects of uncertainties concerning material and geometric parameters, mainly in the context of modal analysis of large-scale structures. Given the large number of uncertain parameters arising in this case, highly scalable simulation-based methods are adopted, which can deal with possibly thousands of uncertain parameters. In order to solve the reliability problem, i.e., the estimation of very small exceedance probabilities, an advanced simulation method called Line Sampling is used. In combination with an efficient algorithm for the estimation of the most important uncertain parameters, the method provides good estimates of the failure probability and enables one to quantify the error in the estimate. Another aspect here considered is the uncertainty quantification for closely-spaced eigenfrequencies. The solution here adopted represents each eigenfrequency as a weighted superposition of the full set of eigenfrequencies. In a case study performed with the FE model of a satellite it is shown that the effects of uncertain parameters can be very different in magnitude, depending on the considered response quantity. In particular, the uncertainty in the quantities of interest (eigenfrequencies) turns out to be mainly caused by very few of the uncertain parameters, which results in sharp estimates of the failure probabilities at low computational cost.

• Journal of the Society of Naval Architects of Korea
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• v.54 no.5
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• pp.387-392
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• 2017

There is a constant demand for hull variation related to ship design. Various input variables are generally given to achieve the objective functions assigned by each variation process. When dealing with geometric shapes accompanied by nonlinear operations during the variation process, vague relationships or uncertainties among input variables are commonly observed. Therefore, it is strongly recommended to identify those uncertainty factors in advance. A method to modify the shape of a closed hull form with a new area and a centroid had been introduced as a new process of hull variation. Since uncertainty between input variables still existed in the method, however, it was not easy for the user to enter the area and the corresponding centroid. To overcome this problem, a method is presented in this paper to provide the feasible region of centroids for a given area. By utilizing the concept and techniques used in the statistics such as the number of samples, probability, margin error, and level of confidence, this method generates the distribution of possible centroids along the regression curve. The result shows that the method helps the user to choose an appropriate input value following his or her design intention.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.755-763
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• 2020

The critical flow phenomenon has been studied because of its significant effect for design basis accidents in nuclear power plants. Transition points from thermal non-equilibrium to equilibrium are different according to the geometric effect on the critical flow. This study evaluates the uncertainty parameters of the critical flow model for analysis of DBA (Design Basis Accident) with the MARS-KS (Multi-dimensional Analysis for Reactor Safety-KINS Standard) code used as an independent regulatory assessment. The uncertainty of the critical flow model is represented by three parameters including the thermal non-equilibrium factor, discharge coefficient, and length to diameter (L/D) ratio, and their ranges are determined using large-scale Marviken test data. The uncertainty range of the thermal non-equilibrium factor is updated by the MCDA (Model Calibration through Data Assimilation) method. The updated uncertainty range is confirmed using an LBLOCA (Large Break Loss of Coolant Accident) experiment in the LOFT (Loss of Fluid Test) facility. The uncertainty ranges are also used to calculate an LBLOCA of the APR (Advanced Power Reactor) 1400 NPP (Nuclear Power Plants), focusing on the effect of the PCT (Peak Cladding Temperature). The results reveal that break flow is strongly dependent on the degree of the thermal non-equilibrium state in a ruptured pipe with a small L/D ratio. Moreover, this study provides the method to handle the thermal non-equilibrium factor, discharge coefficient, and length to diameter (L/D) ratio in the system code.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.3
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• pp.198-206
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• 2009

This paper presents the reduction of the positional uncertainty of an ultrasonic sensor ring with overlapped beam pattern for the efficient obstacle detection of a mobile robot. Basically, it is assumed that a relatively small number of inexpensive low directivity ultrasonic sensors are installed at regular spacings along the side of a circular mobile robot with their beams overlapped. First, for both single and double obstacles, we show that the positional uncertainty inherent to an ultrasonic sensor can be reduced using the overlapped beam pattern, and also quantify the relative improvement in positional uncertainty. Second, given measured distance data from one or two ultrasonic sensors, we devise the geometric method to determine the position of an obstacle with respect to the center of a mobile robot. Third, we examine and compare existing ultrasonic sensor models, including Gaussian distribution, parabolic distribution, uniform distribution, and impulse, and then build the sensor model of overlapped ultrasonic sensors, adequate for obstacle detection in terms of positional uncertainty and computational requirement. Finally, through experiments using our prototype ultrasonic sensor ring, the validity of overlapped beam pattern for reduced positional uncertainty and efficient obstacle detection is demonstrated.

• Tunnel and Underground Space
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• v.12 no.3
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• pp.189-197
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• 2002

In recent years, the probabilistic analysis has been used in rock slope engineering. This is because uncertainty is pervasive in rock slope engineering and most geometric and geotechnical parameters of discontinuity and rock masses are involved with uncertainty. Whilst the traditional deterministic analysis method fails to properly deal with uncertainty, the probabilistic analysis has advantages quantifying the uncertainty in parameters. As a probabilistic analysis method, the Monte Carlo simulation has been used commonly. However, the Monte Carlo simulation requires many repeated calculations and therefore, needs much effort and time to calculate the probability of failure. In contrast, the point estimate method involves a simple calculation with moments for random variables. In this study the probability of failure in rock slope is evaluated by the point estimate method and the results are compared to the probability of failure obtained by Monte Carlo simulation method.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.63-73
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• 2010

This paper presents the optimal design method of an overlapped ultrasonic sensor ring for reduced positional uncertainty, and its application to the obstacle detection with improved resolution. Basically, it is assumed that a set of ultrasonic sensors are installed to form a circle at regular intervals with their beams overlapped. First, exploiting the overlapped beam pattern, the positional uncertainty inherent to an ultrasonic sensor is shown to be significantly reduced. Second, for an ideal ultrasonic sensor ring of zero radius, the effective beam width is defined to represent the positional uncertainty, and the optimal number of ultrasonic sensors required for minimal effective beam width is obtained. Third, for an actual ultrasonic sensor ring of nonzero radius, the design index is defined to represent the degree of positional uncertainty, and an optimal design of an overlapped ultrasonic sensor ring consisting of commercial ultrasonic sensors with low directivity is given. Fourth, given measured distances from ultrasonic sensors, the geometric method is described to compute the obstacle position with reference to the center of a mobile robot. Finally, through experiments using our overlapped ultrasonic sensor ring prototype, the validity and performance of the proposed method is demonstrated.