• Earthquakes and Structures
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• v.25 no.4
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• pp.249-267
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• 2023

Various methods for determining the damping ratio have been proposed by scholars both domestically and abroad. However, no comparative analysis of different determination methods has been seen yet. In this study, typical sand (Fujian standard sand) and cohesive soils were selected as experimental objects, and undrained strain-controlled dynamic triaxial tests were conducted. The differences between existing damping ratio determination methods were theoretically compared and analyzed. The results showed that the hysteresis curve of cohesive soils had better symmetry and more closely conformed to the definition of equivalent linear viscoelasticity. For non-cohesive soils, the differences in damping ratio determined by six methods were significant. The differences decreased with increasing confining pressure and relative density, but increased gradually with increasing shear strain, especially at high shear strains, where the maximum relative error reached 200%. For cohesive soils, the differences in damping ratio determined by six methods were relatively small, with a maximum relative error of about 50%. Moreover, they were less affected by effective confining pressure and had the same changing trend under different effective confining pressures. The damping ratio determination method has a large effect on the seismic response of soils distributed by non-cohesive soils, with a maximum relative error of about 15% for the PGA and up to about 30% for the Sa. However, for soil layers distributed by cohesive soils, the damping ratio determination method has less influence on the seismic response. Therefore, it is necessary to adopt a unified damping ratio determination method for non-cohesive soils, which can effectively avoid artificial errors caused by different determination methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.64-72
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• 2016

In this paper, we utilize a Gaussian process to predict the power consumption in the air-conditioning system. As the power consumption in the air-conditioning system takes a form of a time-series and the prediction of the power consumption becomes very important from the perspective of the efficient energy management, it is worth to investigate the time-series model for the prediction of the power consumption. To this end, we apply the Gaussian process to predict the power consumption, in which the Gaussian process provides a prior probability to every possible function and higher probabilities are given to functions that are more likely consistent with the empirical data. We also discuss how to estimate the hyper-parameters, which are parameters in the covariance function of the Gaussian process model. We estimated the hyper-parameters with two different methods (marginal likelihood and leave-one-out cross validation) and obtained a model that pertinently describes the data and the results are more or less independent of the estimation method of hyper-parameters. We validated the prediction results by the error analysis of the mean relative error and the mean absolute error. The mean relative error analysis showed that about 3.4% of the predicted value came from the error, and the mean absolute error analysis confirmed that the error in within the standard deviation of the predicted value. We also adopt the non-parametric Wilcoxon's sign-rank test to assess the fitness of the proposed model and found that the null hypothesis of uniformity was accepted under the significance level of 5%. These results can be applied to a more elaborate control of the power consumption in the air-conditioning system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.5
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• pp.529-536
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• 2008

Researches about 3-D Positioning system using GPS were carried out many-sided by national organs, laboratories, the worlds of science. And most of researches were development of relative positioning algorithm and its applications. Relative positioning has a merit, which can eliminate error in received signals. But its error increase due to distance of baseline. GPS absolute positioning is a method that decides the position independently by the signals from the GPS satellites which are received by a receiver at a certain position. And it is necessary to correct various kinds of error(clock error, effect of ionosphere and troposphere, multi-path etc.). In this study, results of PPP(Precise Point Positioning) used Bernese GPS software was compared with notified coordinates by the NGII(National Geographic Information Institute) in order to analyze the positional accuracy of permanent GPS sites. And the results were compared with results of AUSPOS - Online GPS Processing Service for comparison with relative positioning.

• Smart Structures and Systems
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• v.26 no.2
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• pp.175-184
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• 2020

Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

• The Journal of the Acoustical Society of Korea
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• v.15 no.4E
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• pp.45-52
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• 1996

One common procedure in the approximate solution of a nonclassically damped linear system is to neglect the off-diagonal elements of the normalized damping matrix. A tight error bound, which can be computed with relative ease, is given for this method of solution. The role that modal coupling plays in the control of error is clarified. If the normalized damping matrix is strongly diagonally dominant, it is shown that adequate frequency separation is not necessary to ensure small errors.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1155-1160
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• 1991

Active part mating algorithm using 6-axis force sensor data for the assembly automation and/or teletobotics is presented and experimented. Parts to be mated are cylindrical and have no chamfers. There are basically two modes. One is the normal mode with only a positional error, the other is the tilted mode with an orientational error in addition to a positional error. The used algorithm distinguishes a contact external to the hole from that of internal to the hole in order to perform part-mating in spite of the relative tilt between the hole and the peg.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.254-262
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• 1990

A predictive functional relationship model is presented for the calibration problem in which the standard as well as the nonstandard measurements are subject to error. For the estimation of the relationship between the two measurements, the ordinary least squares and maximum likelihood estimation methods are considered, while for the prediction of unknown standard measurementswe consider direct and inverse approaches. Relative performances of those calibration procedures are compared in terms of the asymptotic mean square error of prediction.

• Journal of the Korean Statistical Society
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• v.35 no.3
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• pp.317-329
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• 2006

In the problem of estimating the error variance in the balanced fixed- effects one-way analysis of variance (ANOVA) model, Ghosh (1994) proposed hierarchical Bayes estimators and raised a conjecture for which all of his hierarchical Bayes estimators are admissible. In this paper we prove this conjecture is true by representing one-way ANOVA model to the distributional form of a multiparameter exponential family.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.207-214
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• 1999

Optimal estimating functions for a class of autoregressive models with GARCH(1,1) error are discussed. The asymptotic properties of the estimator as the solution of the optimal estimating equation are investigated for the models. We have also some simulation results which suggest that the proposed optimal estimators have smaller sample variances than those of the Conditional least-squares estimators under the heavy-tailed error distributions.

• Journal of Astronomy and Space Sciences
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• v.33 no.1
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• pp.45-54
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• 2016

This study developed an approach for improving Carrier-phase Differential Global Positioning System (CDGPS) based realtime satellite relative navigation by applying laser baseline measurement data. The robustness against the space operational environment was considered, and a Synthetic Wavelength Interferometer (SWI) algorithm based on a femtosecond laser measurement model was developed. The phase differences between two laser wavelengths were combined to measure precise distance. Generated laser data were used to improve estimation accuracy for the float ambiguity of CDGPS data. Relative navigation simulations in real-time were performed using the extended Kalman filter algorithm. The GPS and laser-combined relative navigation accuracy was compared with GPS-only relative navigation solutions to determine the impact of laser data on relative navigation. In numerical simulations, the success rate of integer ambiguity resolution increased when laser data was added to GPS data. The relative navigational errors also improved five-fold and two-fold, relative to the GPS-only error, for 250 m and 5 km initial relative distances, respectively. The methodology developed in this study is suitable for application to future satellite formation-flying missions.