• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2354-2370
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• 2015

The advantages of employing SCTP-based Concurrent Multipath Transfer (CMT) have been demonstrated to be very useful for data delivery over multi-homed wireless networks. However, there is still significant ongoing work addressing some remaining limitations and challenges. The most important concern when applying CMT to data delivery is related to handling packet reordering and buffer blocking. Another concern on this topic is that current sender-based CMT solutions seldom consider balancing the overhead and sharing the load between the sender and receiver. This paper proposes a novel Receiver-driven Cooperation-based Concurrent Multipath Transfer solution (CMT-Rev) with the following aims: (i) to balance overhead and share load between the sender and receiver, by moving some functions including congestion and flow control from the sender onto receiver; (ii) to mitigate the data reordering and buffer blocking problems, by using an adaptive receiver-cooperative path aggregation model, (iii) to adaptively transmit packets over multiple paths according to their receiver-inspired sending rate values, by employing a new receiver-aware data distribution scheduler. Simulation results show that CMT-Rev outperforms the existing CMT solutions in terms of data delivery performance.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.439-439
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• 2015

The temporal and spatial relationship of the weather elements such as rainfall and temperature is closely linked to the streamflow simulation, especially, to the flood forecasting problems. For the study area, Imjin river basin, which has the specific characteristics in geography with river cross operation between North and South Korea, the meteorological information in the northern area is totally deficiency, lead to the inaccuracy of streamflow estimation. In the paper, this problem is solved by using the combination of global (such as soil moisture content, land use) and local hydrologic components data such as weather data (precipitation, evapotranspiration, humidity, etc.) for the model-driven runoff (surface flow, lateral flow and groundwater flow) data in each subbasin. To compute the streamflow in Imjin river basin, this study is applied the hydrologic model SURR (Sejong Univ. Rainfall-Runoff) which is the continuous rainfall-runoff model used physical foundations, originally based on Storage Function Model (SFM) to simulate the intercourse of the soil properties, weather factors and flow value. The result indicates the spatial variation in the runoff response of the different subbasins influenced by the input data. The dependancy of runoff simulation accuracy depending on the qualities of input data and model parameters is suggested in this study. The southern region with the dense of gauges and the adequate data shows the good results of the simulated discharge. Eventually, the application of SURR model in Imjin riverbasin gives the accurate consequence in simulation, and become the subsequent runoff for prediction in the future process.

• The Korean Journal of Applied Statistics
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• v.9 no.2
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• pp.1-11
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• 1996

As an estimate of a location parameter for a given data set, $\alpha$-trimmed mean has been studied for a long time by many statisticians because of its nice propoerties including robustness. However, its performance depends on the proportion of trimming say $\alpha$. In this paper, we suggest a data-driven choice of $\alpha$ and study its validity. Also, we suggest a new estimator and consider double-bootstrap to improve its performance. By using simulation study, the proposed method is compared with the exiting one in various cases. Real data sets are also analyzed by using the proposed method.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.443-447
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• 1992

This study describes the strategy for advanced decision support system (ADSS) development for integrated management of water resources and quality in reservoir systems. The developed ADSS consists of database that contain hydrologic data, observed operational data, and data to support specific reservoir operations simulation, optimization models, and water quality models. The optimization model, mass balance simulation model and water quality models are used in a general prototype ADSS, menu driven controlling framework that assists the user to specify and evaluate the alternative operational scenarios at one time. These alternative scenarios are evaluated by the models and the results are compared through the use of a graphical based display system. This graphical based system uses an icon based schematic representation of the system to organize the presentation of the results. The ADSS includes the ability to use monthly or weekly time periods of analysis for the models and it can use monthly historical or stochastically generated inflows.

• Water for future
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• v.26 no.3
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• pp.47-61
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• 1993

A menu-driven shell program DSFS (Daily Streamflow Simulation Model), that can process the input data, optimize the parameters, execute the program, and graphically display the results of a modified tank model, was developed and applied to simulating daily streamflow from small watersheds. The model defines daily watershed evapotranspiration losses from potential values multiplied by monthly landuse coefficients and correction factors for soil water storage levels. The parameters were calibrated using observed hydrologic data for fifteen watersheds, and the results were correlated with watershed parameters to define empirical relationships. The proposed model was tested with streamflow data of ungaged conditions, and the simulation results overestimated the annual runoff.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.836-842
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• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.179-188
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• 1998

Local polynomial regression estimation is the most popular one among kernel type regression estimator. In local polynomial regression function esimation bandwidth selection is crucial problem like the kernel estimation. When the regression curve has complicated structure variable bandwidth selection will be appropriate. In this paper, we propose a variable bandwidth selection method fully data driven. We will choose the bandwdith by selecting minimising estiamted MSE which is estimated by the pilot bandwidth study via croos-validation method. Monte carlo simulation was conducted in order to show the superiority of proposed bandwidth selection method.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.331-351
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• 2012

In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.

• 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.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.373-378
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• 2011

As the number of deeply-underground subway station(DUSS) increases, the safety measures for DUSS have been requested. In this research, Shingumho station (The line # 5, Depth: 46m) has been selected as case-study for the analysis of smoke-spread speed with the different fire strength. Field test data measured for actual fan in DUSS was applied as a condition of a simulation. The whole station was covered in this analysis and total of 4 million grids were generated for this simulation. The fire driven flow was analyzed case by case to compare the smoke-spread effect according to the fire strength. in order to enhance the efficiency of calculation, parallel processing by MPI was employed and large eddy simulation method in FDS code was adopted.