• Journal of the Korean Society for Nondestructive Testing
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• v.37 no.2
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• pp.84-90
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• 2017

An ultrasonic synthetic aperture focusing technique (SAFT) using a root mean square (RMS) velocity model is proposed for pulse-echo immersion testing to improve the computational efficiency. Considering the immersion ultrasonic testing of a steel block as an example, three kinds of imaging were studied (B-Scan, SAFT imaging based on ray tracing technology and RMS velocity). The experimental results show that two kinds of SAFT imaging have almost the same imaging performance, while the efficiency of RMS velocity SAFT imaging is almost 25 times greater than the SAFT based on Snell's law.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.4179-4188
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• 2021

This study identifies efficient earthquake intensity measures (IMs) for seismic performances and fragility evaluations of the reactor containment building (RCB) in the advanced power reactor 1400 (APR1400) nuclear power plant (NPP). The computational model of RCB is constructed using the beam-truss model (BTM) for nonlinear analyses. A total of 90 ground motion records and 20 different IMs are employed for numerical analyses. A series of nonlinear time-history analyses are performed to monitor maximum floor displacements and accelerations of RCB. Then, probabilistic seismic demand models of RCB are developed for each IM. Statistical parameters including coefficient of determination (R²), dispersion (i.e. standard deviation), practicality, and proficiency are calculated to recognize strongly correlated IMs with the seismic performance of the NPP structure. The numerical results show that the optimal IMs are spectral acceleration, spectral velocity, spectral displacement at the fundamental period, acceleration spectrum intensity, effective peak acceleration, peak ground acceleration, A95, and sustained maximum acceleration. Moreover, weakly related IMs to the seismic performance of RCB are peak ground displacement, root-mean-square of displacement, specific energy density, root-mean-square of velocity, peak ground velocity, Housner intensity, velocity spectrum intensity, and sustained maximum velocity. Finally, a set of fragility curves of RCB are developed for optimal IMs.

• Journal of Environmental Science International
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• v.22 no.5
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• pp.581-589
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• 2013

Surface Image Velocimetry(SIV) is an instrument to measure water surface velocity by using image processing techniques. Since SIV is a non-contact type measurement method, it is very effective and useful to measure water surface velocity for steep mountainous streams, such as streams in Jeju island. In the present study, a surface imaging velocimetry system was used to calculate the flow rate for flood event due to a typhoon. At the same time, two types of electromagnetic surface velocimetries (electromagnetic surface current meter and Kalesto) were used to observe flow velocities and compare the accuracies of each instrument. The comparison showed that for velocity distributions root mean square error(RMSE) was 0.33 and R-squared was 0.72. For discharge measurements, root mean square error(RMSE) reached 6.04 and R-squared did 0.92. It means that surface image velocimetry could be used as an alternative method for electromagnetic surface velocimetries in measuring flood discharge.

• Journal of computational fluids engineering
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• v.16 no.4
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• pp.28-38
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• 2011

Large eddy simulation(LES) of fully developed turbulent pipe flow has been performed to investigate the effect of Reynolds number on the flow field at $Re_{\tau}$=180, 395, 590 based on friction velocity and pipe radius. A dynamic subgrid-scale model for the turbulent subgrid-scale stresses was employed to close the governing equations. The mean flow properties, mean velocity profiles and turbulent intensities obtained from the present LES are in good agreement with the previous numerical and experimental results currently available. The Reynolds number effects were observed in the mean velocity profile, root-mean-square of velocity fluctuations, Reynolds shear stress and turbulent viscosity.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.35-49
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• 2021

This paper presents a direct numerical simulation of turbulent flows over a bump in an open channel to examine the turbulence characteristics near divergent waves emanating from the bump and to investigate the interaction of the turbulences with the divergent waves. To verify the reliability of the simulations, the mean velocity profile and root-mean-square of velocity fluctuations are compared with previous data. The anisotropic invariant maps show that the ratio of the streamwise to spanwise velocity fluctuations plays an important role in characterizing the anisotropic nature of the separated shear layer behind the bump in the vicinity of the free surface. The vortex identification discloses a large-scale streamwise vortical structure from the mean velocity field and a cluster of small coherent structures from the instantaneous velocity field, which are responsible for the anisotropic characteristics of the turbulence beneath the free surface.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.508-519
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• 2021

In this study, a model was developed to predict the peak particle velocity (PPV) that affects people and the surrounding environment during blasting. Four machine learning models using the k-nearest neighbors (kNN), classification and regression tree (CART), support vector regression (SVR), and particle swarm optimization (PSO)-SVR algorithms were developed and compared with each other to predict the PPV. Mt. Yogmang located in Changwon-si, Gyeongsangnam-do was selected as a study area, and 1048 blasting data were acquired to train the machine learning models. The blasting data consisted of hole length, burden, spacing, maximum charge per delay, powder factor, number of holes, ratio of emulsion, monitoring distance and PPV. To evaluate the performance of the trained models, the mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) were used. The PSO-SVR model showed superior performance with MAE, MSE and RMSE of 0.0348, 0.0021 and 0.0458, respectively. Finally, a method was proposed to predict the degree of influence on the surrounding environment using the developed machine learning models.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.82-88
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• 2003

The nondestructive internal quality evaluation of agricultural products has been strongly required from the needs for individual inspection. Recently, the ultrasonic wave has been considered as a solution fur this problem, and an ultrasonic system was constructed for the ultrasonic NDE of fruits and vegetables in our previous work. In this paper, the practical applicability of our ultrasonic system is tested fur the inspection of internal defects (central cavity) in Atlantic potato. Sound speed and RMS of transmitted ultrasonic wave signal were measured and classification algorithm using 2 dimensional stochastic analysis. was presented. Experimental results showed greater value of sound speed and RMS (root mean square) of transmitted signal in normal samples than in abnormal samples with cavity. Also a stochastic method to distinguish normal and abnormal showed fault detection rate less than 5%.

• 한국연소학회:학술대회논문집
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• 2003.12a
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• pp.115-123
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• 2003

Simultaneous measurements of velocity and OH distribution were made using particle image velocimetry(PIV) and planar laser-induced fluorescence(PLIF) of OH radical in turbulent hydrogen nonpremixed flames with coaxial air. The OH radical was used as an approximate indicator of chemical reaction zone. The OH layer was correlated well with the stoichiometric velocity, $U_s$, instantaneously and on average. In addition, high strain-rate regions almost coincide with the OH distribution. The residence time in flame surface, calculated from the root-mean-square value of the radial velocity, is proportional to $(x/d_F)^{0.7}$. It is found that the mean value of principal strain rate on the OH layer can be scaled with $(x/d_F)^{-0.7}$ and therefore, the product of the residence time and the mean strain rate remains constant over all axial positions.

• Korean Journal of Remote Sensing
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• v.23 no.5
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• pp.421-430
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• 2007

This paper presents the results of the ocean surface current velocity estimation using 6 Radarsat-1 SAR images acquired in west coastal area near Incheon. We extracted the surface velocity from SAR images based on the Doppler shift approach in which the azimuth frequency shift is related to the motion of surface target in the radar direction. The Doppler shift was measured by the difference between the Doppler centroid estimated in the range-compressed, azimuth-frequency domain and the nominal Doppler centroid used during the SAR focusing process. The extracted SAR current velocities were statistically compared with the current velocities from the high frequency(HF) radar in terms of averages, standard deviations, and root mean square errors. The problem of the unreliable nominal Doppler centroid for the estimation of the SAR current velocity was corrected by subtracting the difference of averages between SAR and HF-radar current velocities from the SAR current velocity. The corrected SAR current velocity inherits the average of HF-radar data while maintaining high-resolution nature of the original SAR data.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.31-39
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• 2010

The goal of automatic velocity analysis is to extract accurate velocity from voluminous seismic data with efficiency. In this study, we developed an efficient automatic velocity analysis algorithm by using bootstrapped differential semblance (BDS) and Monte Carlo inversion. To estimate more accurate results from automatic velocity analysis, the algorithm we have developed uses BDS, which provides a higher velocity resolution than conventional semblance, as a coherency estimator. In addition, our proposed automatic velocity analysis module is performed with a conditional initial velocity determination step that leads to enhanced efficiency in running time of the module. A new optional root mean square (RMS) velocity constraint, which prevents picking false peaks, is used. The developed automatic velocity analysis module was tested on a synthetic dataset and a marine field dataset from the East Sea, Korea. The stacked sections made using velocity results from our algorithm showed coherent events and improved the quality of the normal moveout-correction result. Moreover, since our algorithm finds interval velocity ($\nu_{int}$) first with interval velocity constraints and then calculates a RMS velocity function from the interval velocity, we can estimate geologically reasonable interval velocities. Boundaries of interval velocities also match well with reflection events in the common midpoint stacked sections.