• Journal of the Korean Geophysical Society
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• v.4 no.1
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• pp.21-33
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• 2001

Simultaneous inversion of first-arrivals of local earthquakes recorded by the Korea Meteorological Administration(KMA) seismograph network from 1991 to 1998 is made to derive 1D crustal velocity structure of the Korean peninsula. Twenty-nine events with 178 observations are used in the inversion. Average crustal P-wave velocity turns out to be about 6.3 km/sec, and crustal thickness and upper mantle P-wave velocity are estimated as 33 km and 7.9 km/sec, respectively. Results of inversion indicate the possibility of the low velocity layer in the lower crust. Joint inversion is applied to estimate hypocenters, station delays, and velocities simultaneously. Relative station corrections for 11 stations range from zero to about 1.2 sec. Analysis of the synthetic data shows that estimates of hypocenter locations and station corrections as well as averaged crustal structure are reliable for the given data set..

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.69-79
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• 2011

In this study, empirical site amplifications and S-wave velocity profiles for shallow and deep soils are estimated using earthquake ground motion records in metropolitan Manila, the Philippines. We first apply a spectral inversion technique to the earthquake records to estimate effects of source, path, and local site amplification. The earthquake data used were obtained during 36 moderate earthquakes at 10 strong-motion stations of an earthquake observation network in Manila. The estimated Q value of the propagation path is modelled as $54.6f^{1.1}$. Most of the source spectra can be approximated with the omega-square model. The site amplifications show characteristic features according to surface geological conditions. The amplifications at the sites in the coastal lowland and Marikina Valley shows predominant peaks at frequencies from 1 to 5 Hz, while those in the central plateau are characterised by no dominant peaks. These site amplifications are inverted to subsurface S-wave velocity. We, next, discuss the relationship between the amplifications and average S-wave velocity in the top 30m of the S-wave velocity profiles. The amplifications at low frequencies are well correlated with the averaged S-wave velocity. However, high-frequency amplifications cannot be sufficiently explained by the averaged S-wave velocity in the top 30 m. They are correlated more with the average of S-wave velocity over depths less than 30 m.

• Advances in aircraft and spacecraft science
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• v.7 no.4
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• pp.353-369
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• 2020

This paper presents the flutter analysis and optimum design of axially functionally graded box beam cantilever wing section by considering various geometric and material parameters. The coupled dynamic equations of the continuous model of wing system in terms of material and cross-sectional properties are formulated based on extended Hamilton's principle. By expressing the lift and pitching moment in terms of plunge and pitch displacements, the resultant two continuous equations are simplified using Galerkin's reduced order model. The flutter velocity is predicted from the solution of resultant damped eigenvalue problem. Parametric studies are conducted to know the effects of geometric factors such as taper ratio, thickness, sweep angle as well as material volume fractions and functional grading index on the flutter velocity. A generalized surrogate model is constructed by training the radial basis function network with the parametric data. The optimized material and geometric parameters of the section are predicted by solving the constrained optimal problem using firefly metaheuristics algorithm that employs the developed surrogate model for the function evaluations. The trapezoidal hollow box beam section design with axial functional grading concept is illustrated with combination of aluminium alloy and aluminium with silicon carbide particulates. A good improvement in flutter velocity is noticed by the optimization.

• Journal of Korea Multimedia Society
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• v.23 no.11
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• pp.1372-1382
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• 2020

This paper proposes a core technology for a micro river monitoring terminal device suitable for flood monitoring in small rivers and valleys. Our proposed device is basically equipped with a 77GHz radar, gyro and accelerometer sensors. To measure the flow velocity and water level, we proposed a signal processing technique that extracts pure water energy components from the observed Doppler velocity and reflection intensity from the radar. And to determine the stability of the river structure equipped with our device, we constantly monitor the displacement of the measured values of the gyro and accelerometer sensors. Experimental result verified that our method detects pure water energy in various river environments and distinguishes between flow velocity and water level well. And we verified that vibration and position change of structures can be determined through a gyro sensor. In future research, we will work to build a secure digital twin river network by lowering the cost of supplying RF-WAV devices. Also we expect our device to contribute to securing a preventive golden time in rivers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.71-77
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• 2015

In this paper, we propose a scheduling method for signal measurement and control algorithm execution in a multi-motor drive controller. The multi-motor controller which is used for vehicle control receives position/velocity command and performs position/velocity control and current control. Internal resource allocation and control algorithm execution timing are very important when one microcontroller is used for multi-motor drives. The control performance of the velocity control system is verified by varying ADC(Analog to Digital Converter) conversion timing and algorithm execution timing using real experiments.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1328-1332
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• 2006

As the city is developed, Sewerage outlet is installed for the discharge of rainfall special at new town or modified the existed sewerage network. But the sewerage outlet is influenced to the cannel flow. In this paper, for analyzing variation of flow properties by installing sewerage outlet, it was experimented a with $120^{\circ}$ channel junction. The water depth is rapidly increasing at the just before sewerage installed position, but the velocity is represented increasing at the just after sewerage installed position. In addition, the biggest increment of water depth and velocity is represented $3.0m^3/hr{\sim}4.0.m^3/hr$. At the position of the sewerage outlet installation, separate install at up and downstream is rather than only one position at up or down stream. If it was not install both installation, the upstream installation is better than downstream installation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.491-494
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• 2004

Neural Oscillator can be applied to oscillatory systems such as the image recognition, the voice recognition, estimate of the weather fluctuation and analysis of geological fluctuation etc in nature and principally, it is used often to pattern recoglition of image information. Conventional BPL(Back-Propagation Learning) and MLNN(Multi Layer Neural Network) are not proper for oscillatory systems because these algorithm complicate Learning structure, have tedious procedures and sluggish convergence problem. However, these problems can be easily solved by using a synchrony characteristic of neural oscillator with PLL(phase-Locked Loop) function and by using a simple Hebbian learning rule. And also, Recognition velocity of Korean Character can be improved by using a Neural Oscillator's learning accelerator factor η$\_$ij/

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.296-298
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• 1993

The performance of MODEL-BASED controller is influenced by model parameter errors and velocity measurement errors. To reduce this errors, Control methods by parameter adaptation and velocity estimation are studied. But because these controller has complex construction and need much computation time, the implementation of single processor system is difficult. This paper proposes a control scheme which combines an adaptive control law with a sliding observer using transputer network.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.7
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• pp.987-993
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• 2009

An experimental study is performed to investigate unsteady mixed convection in a horizontal channel with a heat source. Particle image velocimetry (PIV) with thermo-sensitive liquid crystal (TLC) tracers is used for visualization and analysis. This method allows simultaneous measurement of velocity and temperature fields at a given instant of time. Quantitative data of the temperature and velocity are obtained by applying the color-image processing to a visualized image, and neural network is applied to the color-to-temperature calibration. It is found that the periodic flow of mixed convection in a cavity appears at very low Reynolds numbers (Re<0.4), and the period decreases with increasing Reynolds numbers and increases with increasing aspect ratio.