• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.605-615
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• 2010

This study demonstrates the feasibility of small satellite, namely PROBA platform with the compact high resolution imaging spectrometer (CHRIS), for aerosol retrieval in Hong Kong. The rationale of our technique is to estimate the aerosol reflectances by decomposing the Top of Atmosphere (TOA) reflectances from surface reflectance and Rayleigh path reflectances. For the determination of surface reflectances, the modified Minimum Reflectance Technique (MRT) is used on three winter ortho-rectified CHRIS images: Dec-18-2005, Feb-07-2006, Nov-09-2006. For validation purpose, MRT image was compared with ground based multispectral radiometer measurements and atmospherically corrected Landsat image. Results show good agreements between CHRIS-derived surface reflectance and both by ground measurement data as well as by Landsat image (r>0.84). The Root-Mean-Square Errors (RMSE) at 485, 551 and 660nm are 0.99%, 1.19%, and 1.53%, respectively. For aerosol retrieval, Look Up Tables (LUT) which are aerosol reflectances as a function of various AOT values were calculated by SBDART code with AERONET inversion products. The CHRIS derived Aerosol Optical Thickness (AOT) images were then validated with AERONET sunphotometer measurements and the differences are 0.05~0.11 (error=10~18%) at 440nm wavelength. The errors are relatively small compared to those from the operational moderate resolution imaging spectroradiometer (MODIS) Deep Blue algorithm (within 30%) and MODIS ocean algorithm (within 20%).

• Wind and Structures
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• v.17 no.3
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• pp.299-315
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• 2013

Numerical research on four typical configurations of noise mitigation structures and their characteristics of wind loads are reported in this paper. The turbulence model as well the model parameters, the modeling of the equilibrium atmospheric boundary layer, the mesh discretization etc., were carefully considered in the numerical model to improve the numerical accuracy. Also a numerical validation of one configuration with the wind tunnel test data was made. Through detailed analyses of the wind load characteristics with the inclined part and the wind incidence angle, it was found that the addition of an inclined part to a noise mitigation structure at-grade would affect the mean nett pressure coefficients on the vertical part, and that the extent of this effect depends on the length of the inclined part itself. The magnitudes of the mean nett pressure coefficients for both the vertical part and the inclined part of noise mitigation structure at-grade tended to increase with length of inclined part. Finally, a comparison with the wind load code British/European Standard BS EN 1991-1-4:2005 was made and the envelope of the mean nett pressure coefficients of the noise mitigation structures was given for design purposes. The current research should be helpful to improve current wind codes by providing more reasonable wind pressure coefficients for different configurations of noise mitigation structures.

• Journal of the Society of Naval Architects of Korea
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• v.30 no.3
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• pp.75-89
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• 1993

The present paper describes an application of UA(Uncertainty Analysis) to seakeeping model test, basically according to the Performance Test Code of ASME(American Society of Mechanical Engineers), in which all the possible error sources involved in the preparation of test, calibration of instruments, data acquisition and analysis are quantified, and summed up with error propagation coefficients to the final uncertainties. The differences between the static test such as resistance and propulsion test and the dynamic test like seakeeping test are clearly identified during all the procedures of UA and asymmetric bias errors are considered. The DRE(data reduction equation) subject to present UA are the heave and pitch response amplitude operator and nondimensionalized absolute frequency. The usefulness of UA in seakeeping test were confirmed not only for quantifying errors and improving measurement accuracy but also for the validation of various seakeeping analysis tools.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.275-285
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• 2019

Web-assemblies are a new binary standard designed to improve the performance of Web browser JavaScript. Web-assemblies are becoming a new web standard that can run at near native speed with efficient execution, concise representation, and code written in multiple languages. However, current Web-assembly vulnerability verification is limited to the Web assembly interpreter language, and vulnerability verification of Web-assembly binary itself is insufficient. Therefore, it is necessary to verify the safety of the web assembly itself. In this paper, we analyze how to operate the web assembly and verify the safety of the current web-assembly. In addition, we examine vulnerability of existing web -assembly and analyze limitations according to existing safety verification method. Finally, we introduce web-assembly API based fuzzing method to overcome limitation of web-assembly safety verification method. This verifies the effectiveness of the proposed Fuzzing by detecting crashes that could not be detected by existing safety verification tools.

• Nuclear Engineering and Technology
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• v.51 no.6
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• pp.1708-1714
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• 2019

The purpose of the critical evaluation of the spent fuel pool (SFP) is to verify that the maximum effective multiplication factor ($K_{eff}$) is less than the critical safety limit at 100% stored condition of the spent fuel with the maximum reactivity. At nuclear power plants, the storage standard of spent fuel, ie, the loading curve, is established to prevent criticality from being generated in SFP. Here, the loading curve refers to a graph showing the minimum discharged burnup versus the initial enrichment of spent fuel. Recently, US NRC proposed the new critical safety assessment guideline (DSS-ISG-2010-01, Revision 0) of PWR SFPs and most of utilities in US is following it. Of course, the licensed criterion of the maximum effective multiplication factor of SFP remains unchanged and it should be less than 0.95 from the 95% probability and the 95% confidence level. However, the new guideline is including the new evaluation methodologies like the application of the axial burnup profile, the validation of depletion and criticality code, and trend analysis. Among the new evaluation methodologies, the most important factor that affects $K_{eff}$ is the axial burnup profile of spent fuel. US NRC recommends to consider the axial burnup profiles presented in NUREG-6801 in criticality analysis. In this paper, criticality effect was evaluated considering three profiles, respectively: i) Axial burnup profiles presented in NUREG-6801. ii) Representative PWR axial burnup profile. iii) Uniform axial burnup profile. As the result, the case applying the axial burnup profiles presented in NUREG-6801 showed the highest $K_{eff}$ among three cases. Therefore, we need to introduce a new methodology because it can be issued if the axial burnup profiles presented in NUREG/CR-6801 are applied to the domestic nuclear power plants without any other consideration.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.213-225
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• 2020

Floating Offshore Wind Turbines (FOWT) installed in the deep sea regions where stable and strong wind flows are abundant would have significantly improved energy production capacity. When designing FOWT, it is essential to understand the stability and motion performance of the floater. Water tank model tests are required to evaluate these aspects of performance. This paper describes a model test and numerical simulation for a 750-kW semi-submersible platform wind turbine model-II. In the previous model test, the 750-kW FOWT model-I suffered slamming phenomena from extreme wave conditions. Because of that, the platform freeboard of model-II was increased to mitigate the slamming load on the platform deck structure in extreme conditions. Also, the model-I pitch Response Amplitude Operators (RAO) of simulation had strong responses to the natural frequency region. Thus, the hub height of model-II was decreased to reduce the pitch resonance responses from the low-frequency response of the system. Like the model-I, 750-kW FOWT model-II was built with a 1/40 scale ratio. Furthermore, the experiments to evaluate the performance characteristics of the model-II wind turbine were executed at the same location and in the same environment conditions as were those of model-I. These tests included a free decay test, and tests of regular and irregular wave conditions. Both the experimental and simulation conditions considered the blade rotating effect due to the wind. The results of the model tests were compared with the numerical simulations of the FOWT using FAST (Fatigue, Aerodynamics, Structures, and Turbulence) code from the National Renewable Energy Laboratory (NREL).

• Journal of the Korean Society of Propulsion Engineers
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• v.24 no.6
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• pp.69-77
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• 2020

A quasi one-dimensional multi-phase reaction flow analysis code is developed for the performance analysis of liquid pintle thrusters. Unsteady flow field, droplet evaporation, finite reaction and film cooling models are composed as the major models of the performance analysis. The droplet vaporization takes account of Abramzon's vaporization model, and the combustion employs a flamelet model based on detail chemical reactions. Shine's model is applied for the film cooling calculation. To verify each model, the Sod shock tube, single droplet vaporization, kerosene droplets combustion, and film length are evaluated.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.7
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• pp.497-505
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• 2022

Performance and hub vibratory load analyses for a lift-offset coaxial rotor are conducted using a rotorcraft comprehensive analysis code, CAMRAD II. The lift-offset coaxial rotor is trimmed to match the total rotor thrust(lift-offset coaxial rotor's thrust) or the individual rotor thrust(upper and lower rotor thrusts, respectively) in this study. The individual rotor's lift and torque, and effective rotor lift to drag ratio for the total rotor are investigated for various advance ratios and lift-offset values. The two result sets with different trim methods are similar to each other and they are correlated well with the wind-tunnel test results. Therefore, the present study using CAMRAD II validates successfully the aeromechanics modeling and analysis techniques for the lift-offset coaxial rotor.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.95-103
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• 2022

Quick and accurate understanding of the situation in a severe accident is essential for conducting the appropriate accident management and response using the accident diagnosis information. This study employed deep learning technology to diagnose severe accidents through the major safety parameters transferred from a nuclear power plant (NPP) to AtomCARE. After selecting the major accident scenarios to consider, a learning database was established for particular scenarios affiliated with major scenarios by performing a large number of severe accident analyses using MAAP5 code. The severe accident diagnosis technology, which classifies detailed accident scenarios using the major safety parameters from NPPs, was developed by training it with the established database . Verification and validation were conducted by blind test and principal component analysis. The technology developed in this study is expected to be extended and applied to all severe accident scenarios and be utilized as a base technology for quick and accurate severe accident diagnosis.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.94-107
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• 2022

Accidents prevention and mitigation is the highest priority of nuclear power plant (NPP) operation, particularly in the aftermath of the Fukushima Daiichi accident, which has reignited public anxieties and skepticism regarding nuclear energy usage. To deal with accident scenarios more effectively, operators must have ample and precise information about key safety parameters as well as their future trajectories. This work investigates the potential of machine learning in forecasting NPP response in real-time to provide an additional validation method and help reduce human error, especially in accident situations where operators are under a lot of stress. First, a base-case SGTR simulation is carried out by the best-estimate code RELAP5/MOD3.4 to confirm the validity of the model against results reported in the APR1400 Design Control Document (DCD). Then, uncertainty quantification is performed by coupling RELAP5/MOD3.4 and the statistical tool DAKOTA to generate a large enough dataset for the construction and training of neural-based machine learning (ML) models, namely LSTM, GRU, and hybrid CNN-LSTM. Finally, the accuracy and reliability of these models in forecasting system response are tested by their performance on fresh data. To facilitate and oversee the process of developing the ML models, a Systems Engineering (SE) methodology is used to ensure that the work is consistently in line with the originating mission statement and that the findings obtained at each subsequent phase are valid.