• Journal of the Korean Geotechnical Society
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• v.31 no.11
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• pp.49-60
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• 2015

Open-water sediment disposal has many applications in costal construction. Dumping of sediment in open water can be divided into descending stage under water and sedimentation stage on the seabed, and retained rate is evaluated from analyzed results of these two successive stages. Descending particle cloud have two distinct thermal and swam phase, and trajectory equations for each phase are derived to describe settling velocity and radius of particle cloud. For sedimentation stage, a numerical simulator is used to calculate growth factors for particle fiction angle and current velocity. Retained rate is defined as a mass rate of remained sediment inside the circle which has a center at dumping point on the sea level and user-defined effective radius. Retained rate map for Singapore coast is presented with water depth of 20 m, current velocity of 0.0~1.5 m/s, and effective radius of 5 m. It will decrease sediment mass loss during disposal operation and minimize surrounding environmental pollution.

• Journal of Environmental Science International
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• v.32 no.12
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• pp.899-914
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• 2023

Various seeding materials for cloud seeding are being used, and sodium chloride powder is one of them, which is commonly used. This study analyzed the experimental results of multi-aircraft cloud seeding in connection with Republic of Korea Air Force (CN235) and KMA/NIMS(Korea Meteorological Administration/National Institute of Meteorological Sciences) Atmospheric Research Aircraft. Powdered sodium chloride was used in CN235 for the first time in South Korea. The analysis of the cloud particle size distributions and radar reflectivity before and after cloud seeding showed that the growth efficiency of powdery seeding material in the cloud is slightly higher than that of hygroscopic flare composition in the distribution of number concentrations by cloud aerosol particle diameter (10 ~ 1000 ㎛). Considering the radar reflectivity, precipitation, and numerical model simulation, the enhanced precipitation due to cloud seeding was calculated to be a maximum of 3.7 mm for 6 hours. The simulated seeding effect area was about 3,695 km², which corresponds to 13,634,550 tons of water. In the precipitation component analysis, as a direct verification method, the ion equivalent concentrations (Na⁺, Cl^-, Ca²⁺) of the seeding material at the Bukgangneung site were found to be about 1000 times higher than those of other non-affected areas between about 1 and 2 hours after seeding. This study suggests the possibility of continuous multi-aircraft cloud seeding experiments to accumulate and increase the amount of precipitation enhancement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.72-77
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• 2014

There are two main technologies to implement cloud effect in flight simulator, cloud modeling using particle system and texture mapping. In former case, this approach may cause a low frame rate while unrealistic cloud effect is observed in latter case. To Solve this problem, in this paper, we propose how to apply fog effect into camera to display more realistic cloud effect with high frame rate. The proposed method is tested with massive terrain database environment through implemented software by using OpenSceneGraph. As a result, compared to texture mapping method, the degree of difference on frame rate is 1 or 2Hz while the cloud effect is significantly improved as realistic as particle system.

• Advances in nano research
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• v.15 no.6
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• pp.513-520
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• 2023

The exponential proliferation of cutting-edge computing technologies has spurred organizations to outsource their data and computational needs. In the realm of cloud-based computing environments, ensuring robust security, encompassing principles such as confidentiality, availability, and integrity, stands as an overarching imperative. Elevating security measures beyond conventional strategies hinges on a profound comprehension of malware's multifaceted behavioral landscape. This paper presents an innovative paradigm aimed at empowering cloud service providers to adeptly model user behaviors. Our approach harnesses the power of a Particle Swarm Optimization-based Probabilistic Neural Network (PSO-PNN) for detection and recognition processes. Within the initial recognition module, user behaviors are translated into a comprehensible format, and the identification of malicious nano-structures behaviors is orchestrated through a multi-layer neural network. Leveraging the UNSW-NB15 dataset, we meticulously validate our approach, effectively characterizing diverse manifestations of malicious nano-structures behaviors exhibited by users. The experimental results unequivocally underscore the promise of our method in fortifying security monitoring and the discernment of malicious nano-structures behaviors.

• Atmosphere
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• v.30 no.1
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• pp.75-89
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• 2020

Current in-situ airborne probes that measure the sizes of ice crystals smaller than 50 ㎛ are based on the concept that the measured intensity of light scattered by a particle in the forward and/or backward direction can be converted to particle size. The relationship between particle size and scattered light used in forward scattering probes is based on Mie theory, which assumes the refractive index of particle is known and all particles are spherical. Not only are small crystals not spherical, but also there are a wide variety of non-spherical shapes. Although it is well known that the scattering properties of non-spherical ice crystals differ from those of spherical shapes, the impacts of non-sphericity on derived in-situ particle size distributions are unknown. Thus, precise relationships between the intensity of scattered light and particle size and shape are required, as based on accurate calculations of scattering properties of ice crystals. In this study, single-scattering properties of ice crystals smaller than 50 ㎛ are calculated at a wavelength of 0.55 ㎛ using a numerically exact method (i.e., discrete dipole approximation). For these calculations, hexagonal ice crystals with varying aspect ratios are used to represent the shapes of natural small ice crystals to determine the errors caused by non-spherical ice crystals measured by forward scattering probes. It is shown that the calculated errors in sizing nonspherical ice crystals are at least 13% and 26% in forward (4~12°) and backward (168~176°) directions, respectively, and maximum errors are up to 120% and 132%.

• Nuclear Engineering and Technology
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• v.21 no.1
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• pp.40-47
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• 1989

For the effective design of a beam forming structure of the negative-ion-based neutral beam injector, a computer program based on a particle simulation model is developed for the calculation of charged particle motions in the electrostatic fields. The motions of negative ions inside the acceleration tube of a multiple-aperture triode are computed at finite time steps. The electrostatic potentials are obtained from the Poisson's equation by the finite difference method. The successive overrelaxation method is used to solve the matrix equation. The particle and force weighting methods are used on a cloud-in-cell model. The optimum design of the beam forming structure has been studied by using this computer code for the various conditions of elctrodes. The effects of the acceleration-deceleration gap distance, the thickness of the deceleration electrode and the shape of the acceleration electrode on beam trajectories are exmined to find the minimum beam divergence. Some numerical illustrations are presented for the particle movements at finite time steps in the beam forming tubes. It is found in this particle simulation modelling that the shape of the acceleration electrode is the most significant factor of beam divergence.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.10
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• pp.1738-1747
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• 2003

Smoothed Particle Hydrodynamics (SPH), a pure Lagrangian numerical method, is applied to analysis of penetration phenomenon of bumper plate which is installed outside of spacecraft hull to protect the spacecraft against hypervelocity meteorite impact. Effects of SPH parameters, such as artificial viscosities, smoothing lengths, numbers of particles and time increments, are analysed by comparing the SPH simulation results with experimental ones with regard to subsequent formation of debris cloud. An optimum range of parameter values is determined by error analysis and various SPH numerical results are compared with experiments.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.605-610
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• 2014

Clouds play an important role in climate change, in the prediction of local weather, and also in aviation safety when instrument assisted flying is unavailable. Presently, various ground-based instruments used for the measurements of the cloud base height or velocity. Lidar techniques are powerful and have many applications in climate studies, including the clouds' temperature measurement, the aerosol particle properties, etc. Otherwise, it is very circumscribed in cloud velocity measurements because there is no Doppler effect if the clouds move in the perpendicular direction to the laser beam path of Doppler lidar. In this paper, we present a method for the measurement of cloud velocity using lidar's range detection and DIC (Digital Image Correlation) system to overcome the disadvantage of Doppler lidar. The lidar system acquires the distance to the cloud, and the cloud images are tracked using the developed fast correlation algorithm of DIC. We acquired the velocities of clouds using the calculated distance and DIC algorithm. The measurement values had a linear distribution.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5972-5989
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• 2019

With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid mechanism of particle swarm optimization (PSO) and differential evolution (DE) algorithms based on Spark (SparkPSODE). The SparkPSODE algorithm is a parallel algorithm, in which the RDD and island models are employed. The island model is used to divide the global population into several subpopulations, which are applied to reduce the computational time by corresponding to RDD's partitions. To preserve population diversity and avoid premature convergence, the evolutionary strategy of DE is integrated into SparkPSODE. Finally, SparkPSODE is conducted on a set of benchmark problems on LSGO and show that, in comparison with several algorithms, the proposed SparkPSODE algorithm obtains better optimization performance through experimental results.

• Atmosphere
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• v.17 no.1
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• pp.101-108
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• 2007

To observe and analyze the cloud and fog characteristics, the METeorological Research Institute (METRI) has established the Cloud Physics Observation System (CPOS) by implementing the cloud observation instruments: Forward Scattering Spectrometer Probe (FSSP), PARticle SIze and VELocity (PARSIVEL), Microwave Radiometer (MWR), Micro Rain Radar (MRR), and 3D-AWS at the Daegwallyeong Enhanced Mountain Weather Observation Center. The cloud-related products of CPOS and the validation status for the size distribution of FSSP, the precipitable water of MWR, and the rainfall rate of MRR and PARSIVEL are described.