• Journal of The Korean Society of Agricultural Engineers
• /
• v.52 no.6
• /
• pp.39-48
• /
• 2010

Sediment yields from Imha watershed were simulated during 1993-2008 using Hydrologic Simulation Program-Fortran (HSPF). Using observed daily stream flow for 2004-2008 and hourly suspended solid concentration for three events during 2006, HSPF was calibrated and validated at the sites of Imha and Youngyang for stream flow and Dongchun and Jangpachun for sediment yield. The calibration and validation results represented high model efficiency for simulating daily stream flow and hourly suspended solid. The determination coefficients of calibration and validation were 0.90 and 0.81 for daily stream flow, and 0.91 and 0.86 for monthly stream flow, respectively. Based on model tolerances for calibration and validation of stream flow, HSPF performance for simulating stream flow represented 'very good'. The determination coefficients of calibration and validation were 0.94-0.96 and 0.95 for hourly sediment yields, respectively. The average yearly sediment yield during 1993-2008 was 122,290 ton/year and most of sediment yield (77 % of total yield) were generated from June to August. The calibrated HSPF simulated well the movement of water and eroded soil within Imha watershed.

• Nuclear Engineering and Technology
• /
• v.37 no.1
• /
• pp.118-126
• /
• 2005

While emergency operating procedures (EOPs) occupy an important role in the management of various abnormal situations in nuclear power plants (NPPs), current technology for the validation of EOPs still largely depends on manual review. A validation method for EOPs of NPPs is thus proposed based on dynamic multi-level flow modeling (MFM). The MFM modeling procedure and the EOP validation procedure are developed and provided in the paper. Application of the proposed method to EOPs of an actual NPP shows that the proposed method provides an efficient means of validating EOPs. It is also found that the information on state transitions in MFM models during the management of abnormal situations is also useful for further analysis on EOPs including their optimization.

• Journal of the Society of Naval Architects of Korea
• /
• v.40 no.2
• /
• pp.1-10
• /
• 2003

It is important to understand the flow characteristics such as wave and wake development around a ship for the design of the hull forms with better resistance and propulsive performance. The experimental results explicating the local flow characteristics are also invaluable for validation of the physical and numerical modeling of CFD codes, which are recently gaining acknowledgements as efficient tools for hull form evaluation This paper describes velocity and wave profiles measured in the towing tank for the KRISO 138K LNG Carrier (KLNG) model with propeller and rudder. The results contained in this paper can provide the valuable information on the effect of propeller and rudder on stern flow characteristics of the modern commercial hull form, furthermore, the present experimental data will provide important database for CFO validation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.8B
• /
• pp.707-718
• /
• 2008

The methodology of classifying traffics is changing from payload based or port based to machine learning based in order to overcome the dynamic changes of application's characteristics. However, current state of traffic classification using machine learning (ML) algorithms is ongoing under the offline environment. Specifically, most of the current works provide results of traffic classification using cross validation as a test method. Also, they show classification results based on traffic flows. However, these traffic classification results are not useful for practical environments of the network traffic monitoring. This paper compares the classification results using cross validation with those of using split validation as the test method. Also, this paper compares the classification results based on flow to those based on bytes. We classify network traffics by using various feature sets and machine learning algorithms such as J48, REPTree, RBFNetwork, Multilayer perceptron, BayesNet, and NaiveBayes. In this paper, we find the best feature sets and the best ML algorithm for classifying traffics using the split validation.

• Journal of computational fluids engineering
• /
• v.14 no.4
• /
• pp.78-85
• /
• 2009

Cavitating flow simulation is of practical importance for many engineering systems, such as marine propellers, pump impellers, nozzles, injectors, torpedoes, etc. The present work has focused on the simulation of cavitating flow past cylinders with strong side flows. The governing equation is the Navier-Stokes equation based on the homogeneous mixture model. The momentum and energy equation is in the mixture phase while the continuity equation is solved liquid and vapor phase, separately. An implicit dual time and preconditioning method are employed for computational analysis. For the code validation, the results from the present solver have been compared with experiments and other numerical results. A fairly good agreement with the experimental data and other numerical results have been obtained. After the code validation, the strong side flow was applied to include the wake flow effects of the submarine or ocean tide.

• Journal of Korea Water Resources Association
• /
• v.41 no.10
• /
• pp.969-982
• /
• 2008

As hydrological models have been progressively developed, they are recognized as appropriate tools to manage water resources. Especially, the need to evaluate the effects of landuse and climate change on hydrological phenomena has been increased, which requires powerful validation methods for the hydrological models to be employed. As measured streamflow data at many locations may not be available, or include significant errors in application of hydrological models, streamflow data simulated by models only might be used to conduct hydrological analysis. In many cases, reducing errors in model simulations requires a powerful model validation method. In this research, we demonstrated a validation methodology of SWAT model using observed flow in two basins with different physical characteristics. First, we selected two basins, Gap-cheon basin and Yongdam basin located in the Guem River Basin, showing different hydrological characteristics. Next, the methodology developed to estimate parameter values for the Gap-cheon basin was applied for estimating those for the Yongdam basin without calibration a priori, and sought for validation of the SWAT. Application result with SWAT for Yongdam basin showed $R_{eff}$ ranging from 0.49 to 0.85, and $R^{2}$ from 0.49 to 0.84. As well, comparison of predicted flow and measured flow in each subbasin showed reasonable agreement. Furthermore, the model reproduced the whole trends of measured total flow and low flow, though peak flows were rather underestimated. The results of this study suggest that SWAT can be applied for predicting effects of future climate and landuse changes on flow variability in river basins. However, additional studies are recommended to further verify the validity of the mixed method in other river basins.

• Nuclear Engineering and Technology
• /
• v.45 no.5
• /
• pp.665-674
• /
• 2013

This paper presents the development and validation methods of the FUTURE (FUel cycle analysis Tool for nUcleaR Energy) code, which was developed for a dynamic material flow evaluation and economic analysis of the nuclear fuel cycle. This code enables an evaluation of a nuclear material flow and its economy for diverse nuclear fuel cycles based on a predictable scenario. The most notable virtue of this FUTURE code, which was developed using C# and MICROSOFT SQL DBMS, is that a program user can design a nuclear fuel cycle process easily using a standard process on the canvas screen through a drag-and-drop method. From the user's point of view, this code is very easy to use thanks to its high flexibility. In addition, the new code also enables the maintenance of data integrity by constructing a database environment of the results of the nuclear fuel cycle analyses.

• Nuclear Engineering and Technology
• /
• v.45 no.6
• /
• pp.745-752
• /
• 2013

For thermo-fluid and safety analyses of a High Temperature Gas-cooled Reactor (HTGR), intensive efforts are in progress in the developments of the GAMMA+ code of Korea Atomic Energy Research Institute (KAERI) and the AGREE code of the University of Michigan (U of M). One of the important requirements for GAMMA+ and AGREE is an accurate modeling capability of a bypass flow in a prismatic core. Recently, a series of air experiments were performed at Seoul National University (SNU) in order to understand bypass flow behavior and generate an experimental database for the validation of computer codes. The main objective of the present work is to validate the GAMMA+ and AGREE codes using the experimental data published by SNU. The numerical results of the two codes were compared with the measured data. A good agreement was found between the calculations and the measurement. It was concluded that GAMMA+ and AGREE can reliably simulate the bypass flow behavior in a prismatic core.

• 한국전산유체공학회:학술대회논문집
• /
• 2009.11a
• /
• pp.177-184
• /
• 2009

Cavitating flow simulation is of practical importance for many engineering systems, such as marine propellers, pump impellers, nozzles, injectors, torpedoes, etc. The present work has focused on the simulation of cavitating flow past cylinders with strong side flows. The governing equation is the Navier-Stokes equation based on the homogeneous mixture model. The momentum and energy equation is in the mixture phase while the continuity equation is solved liquid and vapor phase, separately. An implicit dual time and preconditioning method are employed for computational analysis. For the code validation, the results from the present solver have been compared with experiments and other numerical results. A fairly good agreement with the experimental data and other numerical results have been obtained. After the code validation, the strong side flow was applied to include the wake flow effects of the submarine or ocean tide.

• Journal of Korea Multimedia Society
• /
• v.24 no.10
• /
• pp.1403-1413
• /
• 2021

In this paper, we investigate automated data validation techniques for artificial intelligence training, and also disclose open-source frameworks, such as Google's TensorFlow Data Validation (TFDV), that support automated data validation in the AI model development process. We also introduce an experimental study using public data sets to demonstrate the effectiveness of the open-source data validation framework. In particular, we presents experimental results of the data validation functions for schema testing and discuss the limitations of the current open-source frameworks for semantic data. Last, we introduce the latest studies for the semantic data validation using machine learning techniques.