• Journal of the Korean Solar Energy Society
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• v.35 no.3
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• pp.1-8
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• 2015

The MERRA reanalysis data provided online by NASA was applied to predict the monthly energy productions of Donghai Bridge Offshore wind farms in China. WindPRO and WindSim that are commercial software for wind farm design and energy prediction were used. For topography and roughness map, the contour line data from SRTM combined with roughness information were made and used. Predictions were made for 11 months from July, 2010 to May, 2011, and the results were compared with the actual electricity energy production presented in the CDM(Clean Development Mechanism)monitoring report of the wind farm. The results from the prediction programs were close to the actual electricity energy productions and the errors were within 4%.

• Atmosphere
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• v.29 no.1
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• pp.53-59
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• 2019

The quality of troposphere ozone in three reanalysis datasets is evaluated with longterm ozonesonde measurement at Pohang, South Korea. The Monitoring Atmospheric Composition and Climate (MACC), European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERAI) and Modern Era Retrospective-Analysis for Research and Applications version 2 (MERRA2) are particularly examined in terms of the vertical ozone structure, seasonality and long-term trend in the lower troposphere. It turns out that MACC shows the smallest biases in the ozone profile, and has realistic seasonality of lower-tropospheric ozone concentration with a maximum ozone mixing ratio in spring and early summer and minimum in winter. MERRA2 also shows reasonably small biases. However, ERAI exhibits significant biases with substantially lower ozone mixing ratio in most seasons, except in mid summer, than the observation. It even fails to reproduce the seasonal cycle of lower-tropospheric ozone concentration. This result suggests that great caution is needed when analyzing tropospheric ozone using ERAI data. It is further found that, although not statistically significant, all datasets consistently show a decreasing trend of 850-hPa ozone concentration since 2003 as in the observation.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.49-56
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• 2004

Model updating is a very active research field, in which significant efforts has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are-unavoidably-corrupted with uncorrected noise content. In this paper, Reanalysis using frequency response functions for correlating and updating dynamic systems is presented. A transformation matrix is obtained from the relationship between the complex and the normal frequency response functions of a structure. The transformation matrix is employed to calculate the modified damping matrix of the system. The modified mass and stiffness matrices are identified from the normal frequency response functions by using the least squares method. One simulated system is employed to illustrate the applicability of the proposed method. The result indicate that the damping matrix of correlated finite element model can be identified accurately by the proposed method. In addition, the robustness of the new approach uniformly distributed measurement noise Is also addressed.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.30-33
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• 2005

Though sensible heat flux is one of heat flux components, it is generally considered that the importance is low compared with other components because of the small value. Actually sensible heat flux over the tropical ocean is extremely small, less than $100\;W/m^2$ .. However, it should be noted that sensible heat flux in boreal winter over the western boundary current regions is considerably large, about $100\;W/m^2$, and not neglected. In this study we carry out intercomparison of various global sensible heat flux data including not only satellite-derived data but also reanalysis data in order to clarify the characteristics of those data.

• Journal of Power System Engineering
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• v.16 no.2
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• pp.11-16
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• 2012

In this paper, the authors formulate the sensitivity analysis algorithm for the natural frequency of a torsional shafting by expanding the transfer stiffness coefficient method. The basic concept of the present algorithm is based on the transfer of sensitivity stiffness coefficient, which is the derivative of stiffness coefficient with respect to design parameter, at every node from the first node to the last node in analytical model. The effectiveness of the present algorithm is confirmed by comparing the results of the sensitivity analysis and those of the reanalysis for the natural frequencies of a torsional shafting with a constant cross section. In numerical calculation, the design parameter is the diameter of the shaft element of the torsional shafting.

• Korean Journal of English Language and Linguistics
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• v.1 no.2
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• pp.211-225
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• 2001

The prepositional object (PO) of an active sentence in English can sometimes be passivized, becoming the subject of the corresponding passive sentence. In particular, the verb (V) and preposition (P) in the English prepositional passive (P-Passive) are assumed to be reanalyzed to form a single structural unit, giving the status of a verbal object to the PO to be passivized. However, not every V+P sequence can undergo reanalysis, permitting the passivization of POs. Thus, we have to explain what licenses the reanalysis of V and p. resulting in an acceptable P-Passive sentence. In this paper, I will identify the factors which determine the passivization possibilities of POs and explain how they interact with one another. The results of this study will illustrate how formal and functional factors work together to form a major syntactic construction and to determine its grammaticality and acceptability.

• Journal of Ocean Engineering and Technology
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• v.2 no.1
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• pp.95-105
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• 1988

This paper describes the development of a reliability-based optimum design technique for such three dimensional tubular frames as off shore structures. The objective function is formulated for the structural weight. Constraints that probability of failure for the critical sections does not exceed the allowable probability of failure are set up. In the evaluation of the probability of failure, fatigue as well as buckling and plasticity failure are taken into account and the mean-value first-order second-moment method(MVFOSM) is applied for its calculation. In order to reduce the computing time required for the repeated structural analysis in the optimization process, reanalysis method is also applied. Application to two and three dimensional simple frame structures is performed. The influence of material properties, external forces, allowable failure probabilities and interaction between external forces on the optimum design is investigated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.101-108
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• 2000

An optimum design algorithm using efficient reanalysis is proposed for reliability-based optimization problems formulated as the minimization of initial cost and expected failure cost with reliability constraints. The reliability-based optimization is high cost to evaluate objective function and constraints needed reliability analysis. Therefore the sensitivity analysis of reliability index for approximated reanalysis is necessary. In this paper, three solution approaches are suggested and tested. The approaches include : (1) sensitivity analysis using finite difference; (2) sensitivity analysis using automatic differentiation (AD); and (3) sensitivity analysis with respect to intermediate variables using AD. Numerical example is optimized to show the reliability and effectiveness of the new algorithm.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.421-424
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• 2004

Model updating is a very active research field, in which significant efforts has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are-unavoidably-corrupted with uncorrelated noise content. In this paper, Reanalysis using frequency response functions for correlating and updating dynamic systems is presented. A transformation matrix is obtained from the relationship between the complex and the normal frequency response functions of a structure. The transformation matrix is employed to calculate the modified damping matrix of the system. The modified mass and stiffness matrices are identified from the normal frequency response functions by using the least squares method. Full scale pseudo dynamic pier test is employed to illustrate the applicability of the proposed method. The result indicate that the damping matrix of correlated finite element model can be identified accurately by the proposed method. In addition, the robustness of the new approach uniformly distributed measurement noise is also addressed.