• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.58-72
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• 2009

The main activities of container terminals are to load container freights to vessels, discharge them from vessels, and store them in the storage yard. Container terminals make many operational plans to execute these functions effectively. If the plans do not consider enough the loads of related resources, they may have low actualities. This study discusses the optimal yard planning model which considers various resources, such as the storage yard, yard cranes, internal vehicles, and travel lanes, in container terminals. The model determines the groups and amounts of containers which are stored in each storage block by using the resource profile. The yard planning problem is represented to the multi-commodity minimal cost flow problem and is formulated to the linear programming model. In order to explain the application of the mathematical model, the numerical examples are presented. Additionally, the relationship between the average load ratio and the relocation ratio is discussed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.3
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• pp.209-219
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• 2013

The present paper deals with the extension of AUSMPW+ scheme into two-fluid model for multiphase flow. AUSMPW+ scheme is the improvement of a single-phase AUSM+ scheme by designing pressure-based weighting functions to prevent oscillations near a wall and shock instability after a strong shock. Recently, Kitamura and Liou assessed a family of AUSM-type schemes with two-fluid model governing equations [K. Kitamura and M.-S. Liou, Comparative study of AUSM-Family schemes in compressible multi-phase flow simulations, ICCFD7-3702 (2012)]. It was observed that the direct application of the single-phase AUSMPW+ did not provide satisfactory results for most of numerical test cases, which motivates the current study. It turns out that, by designing pressure-based weighting functions, which play a key role in controlling numerical diffusion for two-fluid model, problems reported in can be overcome. Various numerical experiments validate the proposed modification of AUSMPW+ scheme is accurate and robust to solve multiphase flow within the framework of two-fluid model.

• Journal of the Korean Society of Visualization
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• v.16 no.1
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• pp.37-41
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• 2018

The two-fluid model is widely used for practical applications involving multi-phase flows in chemical reactor, nuclear reactor, desalination systems, boilers, and internal combustion engine. There are several modeling terms in the two-fluid model, which must be determined properly. This study suggests the best models for turbulent vertical bubbly flow.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.1 s.6
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• pp.43-56
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• 2005

This research has examined a time series analysis(TSA) of an every hour traffic information such as occupancy, a traffic flow, and a speed, a statistical model of a surveyed data on the traffic fundamental diagram and an expand aspect of a traffic jam by many Parts of the traffic flow. Based on the detected data from traffic accidents on the Cheonan-Nonsan high way and events when the road volume decreases dramatically like traffic accidents it can be estimated from the change of occupancy right after accidents. When it comes to a traffic jam like events the changing gap of the occupancy and the mean speed is gentle, in addition to a quickness and an accuracy of a detection by the time series analyse of simple traffic index is weak. When it is a stable flow a relationship between the occupancy and a flow is a linear, which explain a very high reliability. In contrast, a platoon form presented by a wide deviation about an ideal speed of drivers is difficult to express by a statical model in a relationship between the speed and occupancy, In this case the speed drops shifty at 6$\~$8$\%$ occupancy. In case of an unstable flow, it is difficult to adopt a statistical model because the formation-clearance Process of a traffic jam is analyzed in each parts. Taken the formation-clearance process of a traffic jam by 2 parts division into consideration the flow having an accident is transferred to a stopped flow and the occupancy increases dramatically. When the flow recovers from a sloped flow to a free flow the occupancy which has increased dramatically decrease gradually and then traffic flow increases according as the result analyzed traffic flow by the multi regime as time series. When it is on the traffic jam the traffic flow transfers from an impeded free flow to a congested flow and then a jammed flow which is complicated more than on the accidents and the gap of traffic volume in each traffic conditions about a same occupancy is generated huge. This research presents a need of a multi-regime division when analyzing a traffic flow and for the future it needs a fixed quantity division and model about each traffic regimes.

• Korean Journal of Hydrosciences
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• v.10
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• pp.35-46
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• 1999

An integrated system of GIS and water quality model was suggested including the pollutant loads from the watershed. The developed system consits of two parts. First part is the information on landuse and several surface factors concerning the overland flow processes of water and pollutants. Second part is the modeling modules which include storm event pollutant load model(SEPLM), non-storm event pollutant load model(NSPLM), and river water quality simulation model(RWQSM). Models can calculate the pollutant load from the study area. The databases and models are linked through the interface modules resided in the overall system, which incorporate the graphical display modules and the operating scheme for the optimal use of the system. The developed system was applied to the Chungju multi-purpose reservoir to estimate the pollutant load during the four selected rainfall events between 1991 and 1993, based upon monthly basis and seasonal basis in drought flow, low flow, normal flow and wet flow.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.88-97
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• 2023

Traffic flow prediction is of great significance in urban planning and traffic management. As the complexity of urban traffic increases, existing prediction methods still face challenges, especially for the fusion of spatiotemporal information and the capture of long-term dependencies. This study aims to use the fusion model of graph neural network to solve the spatio-temporal information fusion problem in traffic flow prediction. We propose a new deep learning model Spatio-Temporal Information Fusion using Graph Neural Networks (STFGNN). We use GCN module, TCN module and LSTM module alternately to carry out spatiotemporal information fusion. GCN and multi-core TCN capture the temporal and spatial dependencies of traffic flow respectively, and LSTM connects multiple fusion modules to carry out spatiotemporal information fusion. In the experimental evaluation of real traffic flow data, STFGNN showed better performance than other models.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.2
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• pp.649-658
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• 1996

Small-amplitude harmonic oscillations of multi-cylinders are considered both experimentally and theoretically. For the theoretical model, the flow regime is separated into inner and outer regions. In the inner region, the flow is governed by the generalized Stokes boundary layer equation. In the outer region, the full Navier-Stokes equation for the steady streaming flow is solved numerically by using ADI scheme and FVM coupled with the boundary integral method. Flow visualization experiments are conducted by using the Laser Sheet Image Technique. The case of two circular cylinders and square cylinders with variable distances are chosen as a typical example. Although experimental results are based on the flow in the finite domain, both experimental and numerical results agree well qualitatively. As the separation of cylinders is increased, a numerical result shows the asymptotic convergence to a single cylinder case.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.3 s.246
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• pp.222-229
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• 2006

Three dimensional turbulent flow in the scroll volute of centrifugal compressor has been numerically investigated in this paper by solving the Navier-Stokes equations and $\kappa-\varepsilon$ equation model. The computational grid for the flow field of the scroll volute has been constructed based on the multi-block grid concept, which is good to avoid the central grid singularity as well as to promote grid stretching toward the volute wall. Numerical result has been obtained for both the two- and three- dimensions. For the latter flow, result of the scroll volute flow is compared with that of the straight conical volute. This comparison has sorted out the characteristic features of the three-dimensional scroll-type volute flow of centrifugal compressor.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.235-247
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• 2021

Today, the cloud computing has become a major demand of many organizations. The major reason behind this expansion is due to its cloud's sharing infrastructure with higher computing efficiency, lower cost and higher fle3xibility. But, still the security is being a hurdle that blocks the success of the cloud computing platform. Therefore, a novel Multi-tenant Decentralized Information Flow Control (MT-DIFC) model is introduced in this research work. The proposed system will encapsulate four types of entities: (1) The central authority (CA), (2) The encryption proxy (EP), (3) Cloud server CS and (4) Multi-tenant Cloud virtual machines. Our contribution resides within the encryption proxy (EP). Initially, the trust level of all the users within each of the cloud is computed using the proposed two-stage trust computational model, wherein the user is categorized bas primary and secondary users. The primary and secondary users vary based on the application and data owner's preference. Based on the computed trust level, the access privilege is provided to the cloud users. In EP, the cipher text information flow security strategy is implemented using the blowfish encryption model. For the data encryption as well as decryption, the key generation is the crucial as well as the challenging part. In this research work, a new optimal key generation is carried out within the blowfish encryption Algorithm. In the blowfish encryption Algorithm, both the data encryption as well as decryption is accomplishment using the newly proposed optimal key. The proposed optimal key has been selected using a new Self Improved Cat and Mouse Based Optimizer (SI-CMBO), which has been an advanced version of the standard Cat and Mouse Based Optimizer. The proposed model is validated in terms of encryption time, decryption time, KPA attacks as well.