• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.5
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• pp.43-47
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• 2012

A evaluation for the strength of rock includes a lot of uncertainty due to existence of discontinuity surface and weakness plain in the rock mass, so essential test results and other data for the resonable strength analysis are absolutely insufficient. Therefore, a analytical technique to reduce such uncertainty can be required. A probabilistic analysis technique has mainly to make up for the uncertainty to investigate the strength of rock mass. Recently, a artificial neural networks, as a more newly analysis method to solve several problems in the existing analysis methodology, trends to apply to study on the rock strength. In this study the unconfined compressive strength from basic physical property values of sedimentary rock, black shale and red shale, distributed in Daegu metropolitan area is estimated, using the artificial neural networks. And the applicability of the analysis method is investigated. From the results, it is confirmed that the unconfined compressive strength of the sedimentary rock can be easily and efficiently predicted by the analysis technique with the artificial neural networks.

• Structural Engineering and Mechanics
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• v.56 no.2
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• pp.257-273
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• 2015

Numerical value of correlation between effective parameters in the strength of a structure is as important as its stochastic properties in determining the safety of the structure. In this article investigation is made about the variation of coefficient of correlation between effective parameters in corrosion initiation time of reinforcement and the time of concrete cover cracking in reinforced concrete (RC) structures. Presence of many parameters and also error in measurement of these parameters results in uncertainty in determination of corrosion initiation and the time to crack initiation. In this paper, assuming diffusion process as chloride ingress mechanism in RC structures and considering random properties of effective parameters in this model, correlation between input parameters and predicted time to corrosion is calculated using the Monte Carlo (MC) random sampling. Results show the linear correlation between corrosion initiation time and effective input parameters increases with increasing uncertainty in the input parameters. Diffusion coefficient, concrete cover, surface chloride concentration and threshold chloride concentration have the highest correlation coefficient respectively. Also the uncertainty in the concrete cover has the greatest impact on the coefficient of correlation of corrosion initiation time and the time of crack initiation due to the corrosion phenomenon.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1376-1391
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• 2015

In bus delay-tolerant networks, the route of bus is determinate but its arrival time is indeterminate. However, most conventional approaches predict future contact without considering its uncertainty, which makes a limitation on routing performance. A novel approach is proposed by employing interval algebra to characterize the contact's uncertainty and time-varying nature. The contact is predicted by using the Bayesian estimation to achieve a better routing performance. Simulation results show that this approach achieves a good balance between delivery latency and delivery ratio.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2009.11a
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• pp.459-468
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• 2009

Analysis of the uncertainty to have engineering solution of gas-dynamic and hydrodynamic problems is based on the comparison the prospective engineering solution with experimental result. In this paper, the mathematical model to estimate heat flux along gas-dynamic channel wall and the solution sequence are shown. Statistical information and generalizing experimental characteristics about gas- and hydro-dynamic channels were applied to the mathematical model. As the results, it is possible to draw a conclusion that models of the integrated approach, using the averaged statistical data of generalizing characteristics for a turbulent flow, without consideration of the turbulent mechanism (characteristic pulsations), can predict a nominal operating regime for gas-dynamic and hydrodynamic systems. The probable deviation of operating regime for newly designed the gas-dynamic channel can achieve 20% from a regime predicted on a basis 1-D or 3-D modelling irrespective of a kind of used models.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.118-123
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• 1998

The neurotics analysis of a liquid metal reactor fur burning minor actinides has shown that uncertainties in the nuclear data of several key minor actinide isotopes can introduce large uncertainties in the predicted performance of the core. A comprehensive sensitivity and uncertainty analysis was performed on a 1200 MWth actinide burner designed for a low burnup reactivity swing, negative doppler coefficient, and low sodium void worth. Sensitivities were generated using depletion perturbaton methods for the equilibrium cycle of the reactor and covariance data was taken ENDF-B/V and other published sources. The relative uncertainties in the burnup swing, doppler coefficient, and void worth were conservatively estimated to be 180%, 91%, and 46%, respectively.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.2
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• pp.45-51
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• 2009

A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters(e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the predicted of thaw depths in cold regions is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters and temperature data can lead to significant uncertainty in predicting thaw penetration.

• The Journal of Korea Robotics Society
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• v.13 no.2
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• pp.121-128
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• 2018

Obstacle avoidance is one of the most important parts of autonomous mobile robot. In this study, we proposed safe and efficient local path planning of robot for obstacle avoidance. The proposed method detects and tracks obstacles using the 3D depth information of an RGB-D sensor for path prediction. Based on the tracked information of obstacles, the paths of the obstacles are predicted with probability circle-based spatial search (PCSS) method and Gaussian modeling is performed to reduce uncertainty and to create the cost function of caution. The possibility of collision with the robot is considered through the predicted path of the obstacles, and a local path is generated. This enables safe and efficient navigation of the robot. The results in various experiments show that the proposed method enables robots to navigate safely and effectively.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.627-637
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• 1994

In this study, a predictive fuzzy control algorithm to supervise the elevator system with plural cars is developed and its performance is evaluated. The proposed algorithm is based on fuzzy in-ference system to cope with multiple control objects and uncertainty of system state. The control objects are represented as linguistic predictive fuzzy rules and simplified reasoning method is utilized as a fuzzy inference method. Real-time simulation is performed with respect o all possible modes of control, and the resultant controls ard predicted. The predicted rusults are then utilized as the control in-puts of the fuzzy rules. The feasibility of the proposed control algorithm is evaluated by graphic simulator on computer. Finallu, the results of graphic simulation is compared with those of a conventional group control algorighm.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.445-450
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• 1998

In this paper, a robust nonlinear prediction-type controller (RNPC) is developed for the continuous time nonlinear system whose control objective is composed of system output and its desired value. The basic control law of RNPC is derived such that the future response of the system is first predicted by appropriate functional expansions and the control law minimizing the difference between the predicted and desired responses is then calculated. RNPC which involves two controls, i.e., the auxiliary and robust controls into the basic control, shows the stable closed loop dynamics of nonlinear system of any relative degree and provides the robustness to the nonlinear system with parameter/modeling uncertainty. Simulation tests for the position control of a two-link rigid body manipulator confirm the performance improvement and the robustness of RNPC.

• Journal of Astronomy and Space Sciences
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• v.11 no.2
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• pp.147-153
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• 1994

We present a deep(B, V) color-magnitude diagram (CMD) of the Galactic globular cluster NGC 4372. According to the recent inside-out picture of Galaxy formation, this cluster is predicted to be one of the oldest globulat clusters in the Galaxy. Our CMD shows a well defined main-sequence extending ∼ 2 magnitudes below the trunoff. Despite the uncertainty that stems from the small sample size of bright stars, comparison with the Revised Yale Isochrones suggests that this cluster may indeed be one of the oldest (∼16.6 Gyrs) globular clusters in our Galaxy.