• International Journal of Naval Architecture and Ocean Engineering
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• v.3 no.2
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• pp.122-125
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• 2011

In this work, the movement pattern of a floating breakwater is numerically analyzed using Smoothed Particle Hydrodynamic (SPH) method as a Lagrangian scheme. At the seaside, the regular incident waves with varying height and period were considered as the dynamic free surface boundary conditions. The smooth and impermeable beach slope was defined as the bottom boundary condition. The effects of various boundary conditions such as incident wave characteristics, beach slope, and water depth on the movement of the floating body were studied. The numerical results are in good agreement with the available experimental data in the literature The results of the movement of the floating body were used to determine the transmitted wave height at the corresponding boundary conditions.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.4
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• pp.125-134
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• 2015

In this paper, we present an algorithm based on particle filter to determine the state of human movement. We calculate speed from consecutive positioning data with time, latitude and longitude. The speed values are averaged with previous speed values and thus act as basis for particle filter. We use the fact that human speed distribution follows exponential distribution approximately. An algorithm based on particle filter has been developed and utilized. Human movement state are probabilistically described in this research, and the probability is to determine whether a person is in moving state or in stable state. The experimental results are provided in various ways.

• 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.

• Journal of the Korean Geotechnical Society
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• v.32 no.10
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• pp.31-40
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• 2016

In order to investigate the change in soil arch structure developed within the soil subjected to trapdoor movement, various responses in the deformed particle assembly were observed via photoelastic measurement technique. The particle assembly was composed of the regularly stacked model particles coated by thin photoelastic material. Variation of the internal structure transmitting contact forces were observed by taking images showing the photoelastic responses and compared with the change in slip lines and pressures measured by load cells placed beneath the assembly. Initial soil arch structure established immediately after the trapdoor movement collapsed progressively and meanwhile a new extended structure was developed against further movement of the trapdoor. For the sufficient movement of the trapdoor, initially identical regions bounded by the soil arch structure and slip lines were separated and the region enclosed by slip lines became a part of the region loosing the transmitting contact forces identified by photoelastic measurement.

• Journal of Fisheries and Marine Sciences Education
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• v.28 no.3
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• pp.831-840
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• 2016

Hydrodynamic condition can be used to predict particle movement within water column and the results used to optimize environmental conditions for effective site selection, setting of environmental quality standard, waste dispersion, and pathogen transfer. To predict the extent of movement of particle from land, 3D hydrodynamic model that includes particle tracking module was applied to Geoje Bay and to calibrate particle tracking model, floating buoy measurement is operated. The model results show that short time is required for particles released into system from river to be transported to the shellfish farming area. It takes about 2 days for the particles to shellfish farming area under mean flow condition. It meant Geoje Bay, especially shellfish farming area is vulnerable to anthropogenic waste from river.

• Journal of the Korean Mathematical Society
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• v.36 no.1
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• pp.139-157
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• 1999

Consider a supercritical Bellman-Harris process evolving from one particle. We superimpose on this process the additional structure of movement. A particle whose parent was at x at its time of birth moves until it dies according to a given Markov process X starting at x. The motions of different particles are assumed independent. In this paper we show that when the movement process X is standard Brownian the proportion of particles with position $\leq${{{{ SQRT { t} }}}} b and age$\leq$a tends with probability 1 to A(a)$\Phi$(b) where A(.) and $\Phi$(.) are the stable age distribution and standard normal distribution, respectively. We also extend this result to the case when the movement process is a Levy process.

• Transactions on Electrical and Electronic Materials
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• v.15 no.6
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• pp.333-337
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• 2014

In this study, the use of a discharging process for charged particles is proposed to achieve an ideal electrical balance or neutralization and to improve the electrical and optical properties of a reflective electronic display. Here, negatively charged particles (white) and positively charged particles (black) are used. The q/m (charge per mass for a particle) values of the black and white particles are $+4.5{\mu}C/g$ and $-4.5{\mu}C/g$, respectively. We compared the movement of the charged particles by varying their discharging time. Stable movement of the charged particles is obtained with an appropriate discharging time, which resulted in improvements of the optical properties of the panel.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.319-326
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• 2009

PSO(Particle Swarm Optimization) is an optimization algorithm in which simple particles search an optimal solution using shared information acquired through their own experiences. PSO applications are so numerous and diverse. Lots of researches have been made mainly on the parameter settings, topology, particle's movement in order to achieve fast convergence to proper regions of search space for optimization. In standard PSO, since each particle uses only information of its and best neighbor, swarm does not explore diverse regions and intended to premature to local optima. In this paper, we propose a new particle's movement strategy in order to explore diverse regions of search space. The strategy is that each particle moves according to relative weights of several better neighbors. The strategy of exploring diverse regions is effective and produces less local optimizations and accelerating of the optimization speed and higher success rates than standard PSO. Also, in order to raise success rates, we propose a strategy for checking whether swarm falls into local optimum. The new PSO algorithm with these two strategies shows the improvement in the search speed and success rate in the test of benchmark functions.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.4
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• pp.9-14
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• 2007

This study reviewed the behavior(movement) characteristics of floating marine debris flowing in the Nakdong River Estuary using a simple numerical particle-tracking model on the conditions of the maximum water discharge outflow from the Nakdong River barrage during the passage of typhoon Maemi in 2003. The simulation showed that the particle distribution and movement of floating marine debris in the Nakdong River Estuary reached a stable state at 72 hours after the typhoon had passed, during the flood period of river discharge. The quantity of floating particles distributed on the east coast of Gadeok and Jinu Islands increased by 40% at 33 hours after starting the model, while the change in other sea areas was 20-40%.