• Tunnel and Underground Space
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• v.10 no.3
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• pp.486-491
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• 2000

Blasting vibrations velocity had been used to design blasting pattern and predict damage-possibility of structures. As vibration levels are currently required to estimate the damage concerning human-body and livestock, so measured vibration velocities must be transformed into vibration levels. In this study, the digital filter program was developed to transform measured data into vibration levels. Simple harmonic vibrations and measured data obtain by Blastmate series (Instantel Inc.) were applied to the digital filter program. As a result, simple harmonic vibrations and measured data were successfully transformed into vibration levels using the developed program. Measured data from any instrument with ASCII output-function will similarly be transformed into level units.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.241-246
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• 2000

Blasting vibrations velocity had been used to design blasting pattern and predict damage-possibility of structures. As vibration levels are currently required to estimate the damage concerning human-body and livestock, so measured vibration velocities must be transformed into vibration levels. In this study, the digital filter program was developed to transform measured data into vibration levels. Simple harmonic vibrations and measured data obtained by Blastmate series (Instantel Inc.) were applied to the digital filter program. As a result, simple harmonic vibrations and measured data were successfully transformed into vibration levels using the developed program. Measured data from any instrument with ASCII output-function will similarly be transformed into level units.

• Fisheries and Aquatic Sciences
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• v.1 no.1
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• pp.48-62
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• 1998

Seasonal volume transport on the Texas-Louisiana continental shelf is investigated in terms of objectively fitted transport streamfunction fields based on the current meter data of the Texas­Louisiana Shelf Circulation and Transport Processes Study. Adopted here for the objective mapping is a method employing a two-dimensional truncated Fourier representation of the streamfunction over a domain, with the amplitudes determined by least square fit of the observation. The fitting was done with depth-averaged flow rather than depth-integrated flow to reduce the root-mean-square error. The fitting process filters out $11\%$ of the kinetic energy in the monthly mean transport fields. The shelf-wide pattern of streamfunction fields is similar to that of near-surface velocity fields over the region. The nearshore transport, about 0.1 to 0.3 Sv $(1 Sv= 10^6\;m^3/sec)$, is well correlated with the seasonal signal of along-shelf wind stress. The spring transport is weak compared to other seasons in the inner shelf region. The transport along the shelf break is large and variable. In the southwestern shelf break, transport amounts up to 4.7 Sv, which is associated with the activities of the encroaching of energetic anticyclonic eddies originated in Loop Current of the eastern Gulf of Mexico. The first empirical orthogonal function (EOF) of streamfunction variability contains $67.3\%$ of the variance and shows a simple, shelf-wide, along-shelf pattern of transport. The amplitude evolution of the first EOF is highly correlated (correlation coefficient: 0.88) with the evolution of the along-shelf wind stress. This provides strong evidence that the large portion of seasonal variation of the shelf transport is wind-forced. The second EOF contains $23.7\%$ of the variance and shows eddy activities at the southwestern shelf break. The correlation coefficient between the amplitudes of the second EOF and wind stress is 0.42. We assume that this mode is coupled a periodic inner shelf process with a non-periodic eddy process on the shelf break. The third EOF (accounting for $7.2\% of the variance) shows several cell structures near the shelf break associated with the variability of the Loop Current Eddies. The amplitude time series of the third EOF show little correlation with the along-shelf wind.

• The Journal of Korean Physical Therapy
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• v.20 no.3
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• pp.9-18
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• 2008

Purpose: We determined the effect of global synkinesis(GS) on gait ability, muscle contraction, and central neuron action potentials in post-stroke hemiplegic subjects. Methods: Thirty hemiplegia patients were evaluated for walking ability, muscle contraction, central neuron action potential, and comparing differences between the H-GS(high-global synkinesis) group and L-GS(low-global synkinesis) group. To obtain the GS level, surface electromyography(EMG) data were digitized and processed to root mean square(RMS). Walking ability was tested with a modified motor assessment scale(MMAS), a 10 m walking test, timed up and go(TUG) test, and a Fugl-Meyer assessment(FMA). Muscle contraction ability was measured as maximal isometric contraction(MIC) peak, MIC slope, and MIC ramp up using mechanomyography(MMG). Central neuron action potential was measured as the H/Mmax ratio or V/Mmax ratio using EMG. The data were analyzed with t-tests to determine the statistical significance. Results: MMAS(p<0.01), 10 m walking velocity(p<0.01), TUG(p<0.01), FMA-HKA(Hip, Knee, Ankle)(p<0.05), FMA-coordination(p<0.05), MIC peak (p<0.05), MIC slope(p<0.01), and MIC ramp up(p<0.05) were significantly different between H-GS and L-GS, as was the V/Mmax ratio(p<0.05), but H/Mmax was not. Conclusion: Lower GS levels indicated better walking ability and motor function. Therefore, intervention programs should consider GS levels in gait training of chronic hemiplegia.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1632-1648
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• 2005

The effects of Reynolds number on the non-nulling calibration of a typical cone-type five-hole probe have been investigated for the representative Reynolds numbers in turbomachinery. The pitch and yaw angles are changed from - 35 degrees to 35 degrees with an angle interval of 5 degrees at six probe Reynolds numbers in range between $6.60{\times}10^3\;and\;3.17{\times}10^4$. The result shows that not only each calibration coefficient itself but also its Reynolds number dependency is affected significantly by the pitch and yaw angles. The Reynolds-number effects on the pitch- and yaw-angle coefficients are noticeable when the absolute values of the pitch and yaw angles are smaller than 20 degrees. The static-pressure coefficient is sensitive to the Reynolds number nearly all over the pitch- and yaw-angle range. The Reynolds-number effect on the total-pressure coefficient is found remarkable when the absolute values of the pitch and yaw angles are larger than 20 degrees. Through a typical non-nulling reduction procedure, actual reduced values of the pitch and yaw angles, static and total pressures, and velocity magnitude at each Reynolds number are obtained by employing the calibration coefficients at the highest Reynolds number ($Re=3.17{\times}10^4$) as input reference calibration data. As a result, it is found that each reduced value has its own unique trend depending on the pitch and yaw angles. Its general tendency is related closely to the variation of the corresponding calibration coefficient with the Reynolds number. Among the reduced values, the reduced total pressure suffers the most considerable deviation from the measured one and its dependency upon the pitch and yaw angles is most noticeable. In this study, the root-mean-square data as well as the upper and lower bounds of the reduced values are reported as a function of the Reynolds number. These data would be very useful in the estimation of the Reynolds-number effects on the non-nulling calibration.

• Bulletin of the Society of Naval Architects of Korea
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• v.27 no.3
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• pp.38-46
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• 1990

A numerical solution method of the boundary integral equation for axisymmetric potential flows is presented. Those are represented by ring source and ring vorticity distribution. Strengths of ring source and ring vorticity are approximated by linear functions of a parameter $\zeta$ on a segment. The geometry of the body is represented by a cubic B-spline. Limiting integral expressions as the field point tends to the surface having ring source and ring vorticity distribution are derived upto the order of ${\zeta}ln{\zeta}$. In numerical calculations, the principal value integrals over the adjacent segments cancel each other exactly. Thus the singular part proportional to $\(\frac{1}{\zeta}\)$ can be subtracted off in the calculation of the induced velocity by singularities. And the terms proportional to $ln{\zeta}$ and ${\zeta}ln{\zeta}$ can be integrated analytically. Thus those are subtracted off in the numerical calculations and the numerical value obtained from the analytic integrations for $ln{\zeta}$ and ${\zeta}ln{\zeta}$ are added to the induced velocity. The four point Gaussian Quadrature formula was used to evaluate the higher order terms than ${\zeta}ln{\zeta}$ in the integration over the adjacent segments to the field points and the integral over the segments off the field points. The root mean square errors, $E_2$, are examined as a function of the number of nodes to determine convergence rates. The convergence rate of this method approaches 2.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.99-118
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• 2012

The aim of this study is to define a correlation between spatial distribution characteristics of FFG(Functional Feeding Groups) of aquatic insects and related environmental factors in the Geum River based on the theory of RCC(River Continuum Concept). For that objective we had used SMRA(Stepwise Multiple Regression Analysis) method to analyze close relationship between the distribution of aquatic insects and the physical and chemical factors that may affect their inhabiting environment in the study area. And then, a probabilistic method named Frequency Ratio Model(FRM) and spatial analysis function of GIS were applied to produce a predictive distribution map of biota community considering their distribution characteristics according to the environmental factors as related variables. As a result of SMRA, the values of decision coefficient for factors of elevation, stream width, flow velocity, conductivity, temperature and percentage of sand showed higher than 0.5. Therefore these 6 environmental factors were considered as major factors that might affect the distribution characteristics of aquatic insects. Finally, we had calculated RMSE(Root Mean Square Error) between the predicted distribution map and prior survey database from other researches to verify the result of this study. The values of RMSE were calculated from 0.1892 to 0.4242 according to each FFG so we could find out a high reliability of this study. The results of this study might be used to develop a new estimation method for aquatic ecosystem with macro invertebrate community and also be used as preliminary data for conservation and restoration of stream habitats.

• Smart Media Journal
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• v.9 no.4
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• pp.176-186
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• 2020

The size and shape of crops are diverse, and the growing environment is also different. Therefore, when one uses a drone to spray pesticides, the characteristics of each crop must be considered, and flight conditions such as the flight height and forwarding velocity of the drone should be changed. The droplet flow of pesticides is affected by various flight conditions, and a large change occurs in the sprayed area. As a result, an uneven distribution of liquid may be formed at the wake, and the transport efficiency will be decreased as well as there would be a risk of toxic scatter. Therefore, this paper analyzes the degree of distribution of pesticides to the crops through numerical analysis when pesticide is sprayed onto the selected three crops with different characteristics by using agricultural drones with different flight conditions. On the purpose of establishing a guideline for spraying pesticides using a drone in accordance with the characteristics of crops, this paper compares the amount of pesticides distributed in the crops at the wake of nozzle flow using the figure of merit, and the sum of transported liquid rate divided by the root mean square of the probability density function.