• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.5
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• pp.19-30
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• 2016

We presented a hydrodynamic modeling necessary to accurately reproduce shock-induced detonation of pyrotechnic initiator. The methodology for such numerical prediction of shock propagation is quite straight forward if the models are properly implemented and solved in a well-formulated shock physics code. A series of SSGT(Small Scale Gap Test) and detailed hydrodynamic simulation are conducted to quantify the shock sensitivity of an acceptor that contains 97.5% RDX. A TBI(Through Bulkhead Initiator) system, consisting of a train configuration of Donor(HNS+HMX) - Bulkhead(STS) - Acceptor(RDX), were investigated to further validate the interaction between energetic and non-reactive materials for predicting the detonating response for successful operation of such small pyro device.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.709-730
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• 2017

To address the challenge of unprecedented growth in mobile data traffic, ultra-dense network deployment is a cost efficient solution to offload the traffic over some small cells. The overlapped coverage areas of small cells create more than one candidate access points for one mobile user. Signal strength based user association in IEEE 802.11 results in a significantly unbalanced load distribution among access points. However, the effective bandwidth demand of each user actually differs vastly due to their different preferences for mobile applications. In this paper, we formulate a set of non-linear integer programming models for joint user association control and user demand guarantee problem. In this model, we are trying to maximize the system capacity and guarantee the effective bandwidth demand for each user by soft-association control with a software defined network controller. With the fact of NP-hard complexity of non-linear integer programming solver, we propose a Kernighan Lin Algorithm based graph-partitioning method for a large-scale network. Finally, we evaluated the performance of the proposed algorithm for the edge users with heterogeneous bandwidth demands and mobility scenarios. Simulation results show that the proposed adaptive soft-association control can achieve a better performance than the other two and improves the individual quality of user experience with a little price on system throughput.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1421-1434
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• 2020

The frequency and intensity of heatwaves have been increasing due to climate change. Since urban areas are more severely damaged by heatwaves as they act in combination with the urban heat island phenomenon, every possible preparation for such heat threats is required. Many overseas local governments build heat maps using a variety of spatial information to prepare for and counteract heatwaves, and prepare heatwave measures suitable for each region with different spatial characteristics within a relevant city. Building a heat map is a first and important step to prepare for heatwaves. The cases of heat map construction and thermal environment analysis involve various area distributions from urban units with a large area to local units with a small area. The method of constructing a heat map varies from a method utilizing remote sensing to a method using simulation, but there is no standard for using differentiated spatial information according to spatial scale, so each researcher constructs a heat map and analyzes the thermal environment based on different methods. For the above reason, spatial information standards required for building a heat map according to the analysis scale should be established. To this end, this study examined spatial information, analysis methodology, and final findings related to Korean and oversea analysis studies of heatwaves and urban thermal environments to suggest ways to improve the utilization efficiency of spatial information used to build urban heat maps. As a result of the analysis, it was found that spatial, temporal, and spectral resolutions, as basic resolutions, are necessary to construct a heat map using remote sensing in the use of spatial information. In the use of simulations, it was found that the type of weather data and spatial resolution, which are input condition information for simulation implementation, differ according to the size of analysis target areas. Therefore, when constructing a heat map using remote sensing, spatial, spectral, and temporal resolution should be considered; and in the case of using simulations, the spatial resolution, which is an input condition for simulation implementation, and the conditions of weather information to be inputted, should be considered in advance. As a result of understanding the types of monitoring elements for heatwave analysis, 19 types of elements were identified such as land cover, urban spatial characteristics, buildings, topography, vegetation, and shadows, and it was found that there are differences in the types of the elements by spatial scale. This study is expected to help give direction to relevant studies in terms of the use of spatial information suitable for the size of target areas, and setting monitoring elements, when analyzing heatwaves.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.342-350
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• 2009

Currently TMR feed produced in commercial plant is one of the major source to feed cattle for both beef and dairy farm. However, because of lack of cutting and mixing system for utilizing domestic produced firmly baled round roughage in commercial TMR plant, these commercial TMR feed can not satisfy to farmers both in quality and price points of view. In order to solve these problems, a farm group size TMR plant model was developed in this study. The model plant was consist of round bale receiving and cutting system, pneumatic conveying system for transfer the roughage which was cut at the cutter to TMR mixer through pneumatic conveyor, TMR mixer enable to soften the stiff rice strew and to mix with other ingredients, finished feed bin which can be transfer to either packing system or individual farm, packing system by tycon bag which contains 400 kg unit and bulk unloading system to individual farmer. Also, a simulation model ARENA was applied to the model system in order to evaluate and check the production rate in each unit process and operation rate of total system and to find out if there are any clogged unit system obstructing the smooth flow of the total process flow. Processing cycle for produce one batch of the model plant was less than 30 minutes. Thus, it will take less than four hours for producing 16 tons per day equivalent to 1,000 beef cattle's daily feed.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.65-70
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• 2001

We consider a hyper-redundant system that consists of many uniform units. The hyper-redundant system has many degrees of freedom and it can accomplish various tasks. Applysing the reinforcement learning to the hyper-redundant system is very attractive because it is possible to acquire various behaviors for various tasks automatically. In this paper we present a new reinforcement learning algorithm "Q-learning with propagation of motion". The algorithm is designed for the multi-agent systems that have strong connections. The proposed algorithm needs only one small Q-table even for a large scale system. So using the proposed algorithm, it is possible for the hyper-redundant system to learn the effective behavior. In this algorithm, only one leader agent learns the own behavior using its local information and the motion of the leader is propagated to another agents with time delay. The reward of the leader agent is given by using the whole system information. And the effective behavior of the leader is learned and the effective behavior of the system is acquired. We apply the proposed algorithm to a snake-like hyper-redundant robot. The necessary condition of the system to be Markov decision process is discussed. And the computer simulation of learning the locomotion is demonstrated. From the simulation results we find that the task of the locomotion of the robot to the desired point is learned and the winding motion is acquired. We can conclude that our proposed system and our analysis of the condition, that the system is Markov decision process, is valid.

• Atmosphere
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• v.17 no.1
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• pp.87-99
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• 2007

Simulation results of Asian Dust Aerosol Model (ADAM) for the period of April 7-9, 2006 were analyzed, comparing with observed PM10 data. ADAM simulated around ten times lower than on-site PM10 concentration in the source regions: Zhurihe, Tongliao, Yushe, Dalian and Huimin. As the result of this low concentration, transported amounts of Asian Dust were under-estimated as well. In order to quantify a forecasting accuracy, Bias and RMSE were calculated. Even though remarkably negative Biases and high RMSEs were observed, ADAM simulation had followed well up the time of dust outbreak and a transported path. However, the emission process to generate dust from source regions requires a great enhancement. The PM10 concentration at the surface reached up to $2,300{\mu}gm^{-3}$ at Baeknyoungdo and Seoul (Mt. Gwanak), up to $1,750{\mu}gm^{-3}$ at KGAWO about 18:00 LST in April 8, respectively; however, ADAM did not simulate the same result on its second peak. It is considered that traveling Asian dust might have been lagged over the Korean peninsula by the blocking of surface high pressure. Moreover, the current RDAPS's 30 km grid resolution (which ADAM adopts as the meteorological input data) might not adequately represent small-scale atmospheric motions below planetary boundary layer.

• Journal of Computing Science and Engineering
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• v.2 no.3
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• pp.249-273
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• 2008

Epidemic protocols have two fundamental assumptions. One is the availability of a mechanism that provides each node with a set of log(N) (fanout) nodes to gossip with at each cycle. The other is that the network size N is known to all member nodes. While it may be trivial to support these assumptions in small systems, it is a challenge to realize them in large open dynamic systems, such as peer-to-peer (P2P) systems. Technically, since the most fundamental parameter of epidemic protocols is log(N), without knowing the system size, the protocols will be limited. Further, since the network churn, frequently observed in P2P systems, causes rapid membership changes, providing a different set of log(N) at each cycle is a difficult problem. In order to support the assumptions, the fanout nodes should be selected randomly and uniformly from the entire membership. This paper investigates one possible solution which addresses both problems; providing at each cycle a different set of log(N) nodes selected randomly and uniformly from the entire network under churn, and estimating the dynamic network size in the number of nodes. This solution improves the previously developed distributed algorithm called Shuffle to deal with churn, and utilizes the Shuffle infrastructure to estimate the dynamic network size. The effectiveness of the proposed solution is evaluated by simulation. According to the simulation results, the proposed algorithms successfully handle network churn in providing random log(N0 fanout nodes, and practically and accurately estimate the network size. Overall, this work provides insights in designing epidemic protocols for large scale open dynamic systems, where the protocols behave autonomically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.724-730
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• 2017

SpaceWire invented for spacecrafts has Time-Code defined for time synchronization over SpaceWire network. A Time-Code suffers transmission delay of 14[bit-period] and jitter up to 10[bit-period] whenever it passes through a SpaceWire link, which is the primary cause of time synchronization error. This work presents a simple method to improve the time synchronization which uses two extended Time-Codes. Nodes on a SpaceWire network can find how much delay and jitter a received Time-Code has suffered while it passes through the network, and they can correct time synchronization error with this information. The proposed method was validated in a simulation environment developed based on OMNeT++. The simulation result showed that time synchronization error less than a few bit-periods can be achieved. The proposed method is cost effective and suitable for small-scale SpaceWire network systems.

• Journal of Environmental Science International
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• v.15 no.5
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• pp.417-430
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• 2006

We focused on improvement in simulation of wind fields for the complex coastal area. Local Analysis and Prediction System(LAPS) was used as a data assimilation method to improve initial conditions. Case studies of different LAPS inputs were performed to compare improvement of wind fields. Five cases have been employed : I) non data assimilation, II) all available data, III) AWS, buoy, QuikSCAT, IV) AWS, buoy, wind profiler, V) AWS, buoy, AMEDAS. Data assimilation can supplement insufficiency of the mesoscale model which does not represent detailed terrain effect and small scale atmospheric flow fields. Result assimilated all available data showed a good agreement to the observations rather than other cases and estimated veil the local meteorological characteristics including sea breeze and up-slope winds. Result using wind profiler data was the next best thing. This implies that data assimilation with many high-resolution sounding data could contribute to the improvements of good initial condition in the complex coastal area. As a result, these indicated that effective data assimilation process and application of the selective LAPS inputs played an important role in simulating wind fields accurately in a complex area.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.197-207
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• 2018

SMEs manufacturing Factory, which are small-scale production systems of various types, mass-produce and sell products in order to meet customer needs. This means that the company has an excessive amount of material supply to reduce the loss due to lack of inventory and high inventory maintenance cost. And the products that fail to respond to the demand are piled up in the management warehouse, which is the reality that the storage cost is incurred. To overcome this problem, this paper uses ARIMA model, a time series analysis technique, to predict demand in terms of seasonal factors. In this way, demand forecasting model based on economic order quantity model was developed to prevent stock shortage risk. Simulation is carried out to evaluate the effectiveness of the development model and to demonstrate the effectiveness of the development model as applied to SMEs in the future.