• Journal of Navigation and Port Research
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• v.44 no.2
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• pp.53-64
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• 2020

This paper discusses the hydrodynamic characteristics of a catamaran at low speed. In this study, the Delft 372 catamaran model was selected as the target hull to analyze the hydrodynamic characteristics by using the RANS (Reynold-Averaged Navier-Stokes) numerical method. First, the turbulence study and mesh independent study were conducted to select the appropriate method for numerical calculation. The numerical method for the CFD (Computational Fluid Dynamic) calculation was verified by comparing the hydrodynamic force with that obtained experimentally at high speed condition and it rendered a good agreement. Second, the virtual captive model test for a catamaran at low speed was conducted using the verified method. The drift test with drift angle 0-180 degrees was performed and the resulting hydrodynamic forces were compared with the trends of other ship types. Also, the pure rotating test and yaw rotating test proposed by Takashina, (1986) were conducted. The Fourier coefficients obtained from the measured hydrodynamic force were compared with those of other ship types. Conversely, pure sway test and pure yaw test also were simulated to obtain added mass coefficients. By analyzing these results, the hydrodynamic coefficients of the catamaran at low speed were estimated. Finally, the maneuvering simulation in low speed conditions was performed by using the estimated hydrodynamic coefficients.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.2
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• pp.117-127
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• 2019

Vessel's ice speed performances will be verified in ice sea trial but environmental conditions of ice fields are changeable according to the weather condition of ice trial area. Speed performance has to correct in the no wind, wave and current etc. after sea trial. Especially finding ice fields which is exact the same as owner's ice thickness and strength requirements is not easy. Therefore speed correction according to environment condition has to be done after sea trial measurements. Correction methods for ice thickness, ice strength, wave, wind and ship draft, trim, ice drift etc. are checked in ice sea trial based on literature review such as ISO standard, ITTC recommendation, journal papers and proceedings of conferences. Possibility of application for current and ice drift correction in ice field are discussed and measuring schemes and procedures of correction methods are described in this paper. All of correction schemes are calculated for 'Araon' which is ice breaking research vessel with Arctic and Antarctic ice field test results. Analyzed results shows that Araon is satisfied with her official ice speed performance of 3 knots with 10MW power at 1m ice thickness, 570kPa ice flexural strength.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.74-81
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• 2006

This paper proposes the sensorless vector control scheme of a Non-salient permanent-magnet synchronous motor (SPMSM) using programmable low pass filter (PLPF) to estimate a stator flux with the information of a rotor position and speed. The sesorless vector control of PMSM using PLPF can solves the dc drift problem associated with a pure integrator and a LPF. Also, the PLPF has the phase and gain compensator to estimate exactly rotor position and speed. Therefore, the information of a position and speed is exactly estimated because the drift and offset problems are solved by the PLPF. The experimental results show good performance over the 10[%] of the rated speed and under load condition.

• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.3
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• pp.216-222
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• 2017

The rotor position of a PM synchronous motor is commonly estimated from the mathematical model for the sensorless control without rotor position sensors. For the magnet flux-based rotor position estimator in the stationary reference frame, the magnet flux estimator for estimating rotor position and speed includes the integrator. The integrator in the magnet flux estimator may accumulate the offset of the current sensors and the voltage drift. This continuous accumulation of the offset may cause the drift and overflow in the integrator, such that the estimated rotor position and speed may fail to track the real rotor position and speed. In this paper, the magnet flux estimator without integrator is proposed to avoid overflow in the integrator. The proposed rotor position and speed estimator based on magnet flux estimator are verified through simulation and experiment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.375-379
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• 1997

Thermal drift of the machine tool spindle due to temperature increase dominates the major source of the machine tool error. To compensate the thermal errors, software based error correction methods could be implemented. In th~s case, we need model to map the relationship between temperature and thermal distortion. Traditionally, two or three different methods have been trled: step increase of spindle speed, constant, random. The latter two methods are described in the document of ISOlDIS230-3. In this research, three different methods were verified through the experiments from the viewpoint of compensation of thermal distortion. Constant spindle speed turned out good enough for monitoring the behavior of the thermal drift and modeling the relationship between temperature and thermal distortion.

• Electrical & Electronic Materials
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• v.10 no.9
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• pp.922-929
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• 1997

As the size of semiconductor devices shrinks in the horizontal as well as vertical dimension it is difficult to estimate the transport-velocity of electron because they drift in non-equilibrium with a few scattering. In this paper HYbrid Monte Carlo simulator which employs the drift-diffusion model for hole-transport and Monte Carlo model for electron-transport in order to reduce the simulation time and increase the accuracy as well has been developed and applied to analyze the electron-transport in InAlAs/InGaAs HBT which is attractive for an ultra high speed active device in high speed optical fiber transmission systems in terms of the velocity and energy distribution as well as cutoff frequency.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.57 no.3
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• pp.236-245
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• 2021

In this study, a drifting test using a experimental vessel (2,966 tons) in the northern waters of Jeju was carried out for the first time in order to obtain the fundamental data for drift. During the test, it was shown that the average leeway speed and direction by GPS position were 0.362 m/s and 155.54° respectively and the leeway rate for wind speed was 8.80%. The analysis of linear regression modes about leeway speed and direction of the experimental vessel indicated that wind or current (i.e. explanatory variable) had a greater influence upon response variable (e.g. leeway speed or direction) with the speed of the wind and current rather than their directions. On the other hand, the result of multiple regression model analysis was able to predict that the direction was negative, and it was demonstrated that predicted values of leeway speed and direction using an experimental vessel is to be more influential by current than wind while the leeway speed through variance and covariance was positive. In terms of the leeway direction of the experimental vessel, the same result of the leeway speed appeared except for a possibility of the existence of multi-collinearity. Then, it can be interpreted that the explanatory variables were less descriptive in the predicted values of the leeway direction. As a result, the prediction of leeway speed and direction can be demonstrated as following equations. Ŷ₁= 0.4031-0.0032X₁+0.0631X₂-0.0010X₃+0.4110X₄ Ŷ₂= 0.4031-0.6662X₁+27.1955X₂-0.6787X₃-420.4833X₄ However, many drift tests using actual vessels and various drifting objects will provide reasonable estimations, so that they can help search and rescue fishing gears as well.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.41 no.3
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• pp.199-206
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• 2005

As the basic study about improvement of yellow croaker drift gill net fishing implement and development of the fishing system, this study drew problem after synthetically analyzing hauling system of yellow croaker drift gill net used in the coast of Chuja Island and tested several characters and analyzed in hauling process with 5 step net hauler model for improving the problem. The analysis results are as follows. When the angle between axises of drum centers was small, it showed the tendency that hauling time was fast. Hauling time was faster when drum was 5 step rather than 3 step. When drum was 5 step, slippery phenomenon was small and hauling was stable. Tension was larger when drum was 5 step rather than 3 step. When drum was 5 step, the range of change of the maximum and minimum value was small and hauling was stable. When drum was 3 step, there was following formula between hauling time ($Ht_3$) and angle between axises of drum centers ($A_g$) $Ht_3$ : ($7.15Hs^{-0.81}$) $A_g^{-0.81}$, when drum was 5 step there was following formula.$Ht_5$ : ($6.45Hs^{-0.75}$) $A_g0.10$, here, Hs is hauling speed. When drum was 3 step and hauling speed was 28cm/sec, tension was $T=0.08A_8^3-1.60A_g^3-0.49A_g+369.56(r=0.99)$, when drum was 5 step, tension was, $T=-0.01A_g^3+1.96A_g^2-34.05A_g+414.58$ (r-0.99), here, T was tension(g).

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.60 no.1
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• pp.57-70
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• 2024

In order to present a predictive drift model, Jeju National University's training ship was tested for about 11 hours and 40 minutes, and 81 samples that selected one of the entire samples at ten-minute intervals were subjected to regression analysis after verifying outliers and influence points. In the outlier and influence point analysis, although there is a part where the wind direction exceeds 1 in the DFBETAS (difference in Betas) value, the CV (cumulative variable) value is 6%, close to 1. Therefore, it was judged that there would be no problem in conducting multiple regression analyses on samples. The standard regression coefficient showed how much current and wind affect the dependent variable. It showed that current speed and direction were the most important variables for drift speed and direction, with values of 47.1% and 58.1%, respectively. The analysis showed that the statistical values indicated the fit of the model at the significance level of 0.05 for multiple regression analysis. The multiple correlation coefficients indicating the degree of influence on the dependent variable were 83.2% and 89.0%, respectively. The determination of coefficients were 69.3% and 79.3%, and the adjusted determination of coefficients were 67.6% and 78.3%, respectively. In this study, a more quantitative prediction model will be presented because it is performed after identifying outliers and influence points of sample data before multiple regression analysis. Therefore, many studies will be active in the future by combining them.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1299-1310
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• 2018

In this study, we analyzed distribution and movement trends using in-situ observations and particle tracking methods to understand the movement of the drift ice in the Arctic Ocean. The in-situ movement data of the drift ice in the Arctic Ocean used ITP (Ice-Tethered Profiler) provided by NOAA (National Oceanic and Atmospheric Administration) from 2009 to 2018, which was analyzed with the location and speed for each year. Particle tracking simulates the movement of the drift ice using daily current and wind data provided by HYCOM (Hybrid Coordinate Ocean Model) and ECMWF (European Centre for Medium-Range Weather Forecasts, 2009-2017). In order to simulate the movement of the drift ice throughout the Arctic Ocean, ITP data, a field observation data, were used as input to calculate the relationship between the current and wind and follow up the Lagrangian particle tracking. Particle tracking simulations were conducted with two experiments taking into account the effects of current and the combined effects of current and wind, most of which were reproduced in the same way as in-situ observations, given the effects of currents and winds. The movement of the drift ice in the Arctic Ocean was reproduced using a wind-imposed equation, which analyzed the movement of the drift ice in a particular year. In 2010, the Arctic Ocean Index (AOI) was a negative year, with particles clearly moving along the Beaufort Gyre, resulting in relatively large movements in Beaufort Sea. On the other hand, in 2017 AOI was a positive year, with most particles not affected by Gyre, resulting in relatively low speed and distance. Around the pole, the speed of the drift ice is lower in 2017 than 2010. From seasonal characteristics in 2010 and 2017, the movement of the drift ice increase in winter 2010 (0.22 m/s) and decrease to spring 2010 (0.16 m/s). In the case of 2017, the movement is increased in summer (0.22 m/s) and decreased to spring time (0.13 m/s). As a result, the particle tracking method will be appropriate to understand long-term drift ice movement trends by linking them with satellite data in place of limited field observations.