• New & Renewable Energy
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• v.9 no.3
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• pp.14-19
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• 2013

Comparative evaluation of offshore wind retreival software, which use the satellite images taken by Synthetic Aperture Radar sensor; SARTools of CLS-SOPRONO, France and SpaceEye of London Research and Development Corporation, Canada is carried out. For a reference satellite image, ENVISAT ASAR imagery of Jeollanam-do Wan-do area when the winter-time northwestern wind prevails is processed by CMOD_IFR2, CMOD4, CMOD5 algorithms. Wind speed difference and its relative ratio are calculated to evaluate uncertainty of software selection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.149-157
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• 2008

If we use the microwave of SAR, we can observe ocean in spite of severe weather or night time. The sea surface image of SAR has numerous information about atmospheric phenomena related to surface wind field. The extracted wind information from SAR can be used diversely. In order to extract sea wind speed from SAR image, a generated wind direction from SAR and sigma nought should be input into wind model. Therefore, wind speed can be obtained by input wind direction into CMOD5 Model. Azimuth angle using CMOD5 Model is generated by added $90^{\circ}$ to Look angle which is extracted from SAR data file. A gained wind direction spectrum from SAR image has $180^{\circ}$ ambiguity because of 2D-FFT. This ambiguity should decide to use the location of land, wind direction in field or the result of numerical model. Consequently, wind direction using 2D-FFT is $3^{\circ}{\sim}7^{\circ}$ differences with actual surveying data. Wind speed by CMOD5 model is similar to actual surveying data as below 2m/s.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.4
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• pp.706-711
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• 2006

In order to retrieve ocean wind from SAR() image, and to estimate and validate between SAR-derived wind and in-situ wind, with RADAR SAR ocean images and real time marine meteorological data. It was used images with more than 10km to analyze the band of wind in SAR image by FFT(First Fourier Transformation) method and was used CMOD5 as wind retrieval model to retrieve ocean wind. In this study, generally it showed good results as RMS presented 0.8m/s for speed and 8 degree for direction, and especially when wind was hish speed, it presented very good results.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.729-741
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• 2011

Wind speeds have long been estimated from C-band VV-polarized SAR data by using the CMOD algorithms such as CMOD4, CMOD5, and CMOD_IFR2. Some SAR data with HH-polarization without any observations in VV-polarization mode should be converted to VV-polarized value in order to use the previous algorithms based on VV-polarized observation. To satisfy the necessity of polarization ratio (PR) for the conversion, we retrieved the conversion parameter from full-polarized SIR-C SAR image off the east coast of Korea. The polarization ratio for SIR-C SAR data was estimated to 0.47. To assess the accuracy of the polarization ratio coefficient, pseudo VV-polarized normalized radar cross section (NRCS) values were calculated and compared with the original VV-polarized ones. As a result, the estimated psudo values showed a good agreement with the original VV-polarized data with an root mean square error by 0.99 dB. We applied the psudo NRCS to the estimation of wind speeds based on the CMOD wind models. Comparison of the retrieved wind field with the ECMWF and NCEP/NCAR reanalysis wind data showed relatively small rms errors of 1.88 and 1.91 m/s, respectively. SIR-C HH-polarized SAR wind retrievals met the requirement of the scatterometer winds in overall. However, the polarization ratio coefficient revealed dependence on NRCS value, wind speed, and incident angle.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.4
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• pp.203-210
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• 2004

This study reviewed various current methods of evaluating the toughness of steel fiber reinforced concrete specimens and criticized the use of various multiples of first-crack deflection to define toughness indices. The load-CMOD curve to determine toughness, instead of load-deflection curve, was used. The notched steel fiber reinforced concrete specimens With different water/cement ratio(0 35, 0.40, 0.45, 0 50) and fiber volume content(0.0%, 0 5%, 1 0%, 1.5%) were tested under third point bending.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.475-487
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• 2010

Sea surface wind field was retrieved from high-resolution SIR-C SAR data by using CMOD algorithms off the east coast of Korea. In order to extract wind direction information from SAR data, a two-dimensional spectral analysis method was applied to the normalized radar cross section of the image. An $180^{\circ}$-ambiguity problem in the determination of wind direction was solved by selecting a direction nearest to the wind vector of the ECMWF reanalysis data. Comparison of the wind retrieval patterns with the ECMWF and NCEP/NCAR dataset showed RMS errors in the range of 1.30 to $1.72\;ms^{-1}$. In contrast, comparison of wind directions revealed large errors of greater than $60^{\circ}$, which is enormously higher than the permitted limit of about $20^{\circ}$ for satellite scatterometer winds. Compared with wind speed results from different algorithms, wind vectors based on commonly-used CMOD4 algorithm showed good agreement with those derived by other algorithms such as CMOD_IFR2 and CMOD5, particularly at medium winds from 4 to $8\;ms^{-1}$. However, apparent discrepancy appeared at low winds (< $4\;ms^{-1}$). This study also addressed an importance of accurate wind direction data to improve the accuracy of wind speed retrieval and discussed potential causes of wind retrieval errors from SAR data.

• Magazine of the Korea Concrete Institute
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• v.9 no.3
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• pp.127-135
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• 1997

In this study, the wedge splitting tcst (WST) was carried out for the fatigue wack growth behavior of concrete. Selected test variables were concrete compressive strength of 28, 60 and 118 MI%, and stress ratio with 2 levels (6. 13%). In oder to make the designed stress ratio, the maximum and thr minimum fatigue loading level were 75-85% and 5- 10% of ultimate static load, respectively. Fatigue testing was preceded by crack mout.h opening displacement (CMOI)) compliance calibration tcst, and then the fatigue crack growth was computed by crack lcngth vs. (lMOI) compliance relations acquisited by the CMOD compliance calibration technique. To evaluate thc validity of CMOD compliancc calibration techniquc, the crack length p~mlicted by this method was cornpard with the crack length by linear elastic fracture mechanics(LEFIbl) and dyeing test. On the basis of the experimental results, a LRFhl-based c.mpirica1 model for f'at,igue crack growth rate(da/dN-AKI relationships) was presented. The fat,igut. crack growth ratc increased with the strength of concwtc. It appcars that t.he da/tiN-AKI relationships was influenced by stress ratio, however, the effect is diminished with an increase of strength. The comparisons between CblOl) compliance calibration technique anti the other. methods gave the validity of' ('MOD compliance calibration technique for the LZXT.

• Magazine of the Korea Concrete Institute
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• v.6 no.1
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• pp.131-141
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• 1994

This experimental study was performed to lnvestigate the effects of the lergths dnd volume contents of glued hooked steel fiber for the fracture toughness and strength of c oncretc. The notched steel fiber reinforced concrete beams with different flber length(30, 60mm) and fiber volume content(O.0, 0.5, 1.0, 1.5, 2.0%) were tested under 3-point benclmg, md 1 he flexural strengths, fracture energy and CMOD were obtained from the experimental data. The fracture energy v~ds used as d means to evaluate the fracture toughness ot concrete. The results showed that the frdcture toughness and 5trength of conuett. were generally increased ds the content of steel fiber was inc~edsed, arid the length of steel ilber had a great efiect on the flexural strength but little on the compressive itrength and fractule toughness. And also, considering the distributions of steel fiber, workablity and the maxinium size of coarse dqgregates, the optimum content of steel fiber seemed to be about 1.0 '0, and when lts length uias longer the results were somewhat tavorable.

• Journal of the Korean Recycled Construction Resources Institute
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• v.6 no.4
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• pp.349-356
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• 2018

In this study, material properties of steel fiber reinforced high strength concrete (FRHSC) with the compressive strength of about 120MPa were modeled. Steel fiber content of 1.0%, 1.5%, and 2.0% was considered as experimental variable. First of all, compressive strength tests were carried out to determine compressive characteristics of concrete, and compressive stress-strain curves were modeled. For conventional concrete with moderate compressive strength, the stress-strain curves are in the form of parabolic curves, but in the case of high strength concrete reinforced with steel fiber, the curves increase linearly in the form of the straight line. In addition, to understand the tensile properties of FRHSC, the crack mouth opening displacement (CMOD) test was performed, and the tensile stress-CMOD curve was calculated through inverse analysis. When the steel fiber content increased from 1.0% to 1.5%, there was a significant difference of tensile strength. However, when the amount of steel fiber was increased from 1.5% to 2.0%, there was no significant difference of tensile strength, which might result from the poor dispersion and arrangement of steel fiber in concrete.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.286-291
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• 1998

SAR has provided weather independent images on land and sea surface, which can be used for extracting various useful informations. Recently attempts to estimate wind field parameters from SAR images over the oceans have been made by various groups over the world. Although scatterometer loaded in ERS-1 and ERS-2 observes the global wind vector field at spatial resolution of 50 Km with accuracies of $\pm$2m/s in speed, the spatial resolution may not be good enough for applications in coastal regions. It is weil known the sea surface roughness is closely correlated to the wind field, but the wind retrieval algorithms from SAR images are yet in developing stage. Since the radar backscattering properties of the SAR images are principally the same as that of scatterometer, some previous studies conducted by other groups report the success in mesoscale coastal wind field retrievals using ERS SAR images. We have tested SWA (SAR Wind Algorithm) and CMOD4 model for estimation of wind speed using an ERS-1 SAR image acquired near Cheju Island, Korea, in October 11, 1994. The precise estimation of sigma nought and the direction of wind are required for applying the CMOD4 model to estimate wind speed. The wind speed in the test sub-image is estimated to be about 10.5m/s, which relatively well agrees to the observed wind speed about 9.0m/s at Seoguipo station. The wind speed estimation through the SWA is slightly higher than that of CMOD4 model. The sea surface condition may be favorable to SWA on the specific date. Since the CMOD4 model requires either wind direction or wind speed to retrieve the wind field, we should estimate the wind speed first using other algorithm including SWA. So far, it is not conclusive if the SWA can be used to provide input wind speed data for CMOD4 model or not. Since it is only initial stage of implementing the wind field retrieval algorithms and no in-situ observed data is currently avaliable, we are not able to evaluate the accuracy of the results at the moment. Therefore verification studies should be followed in the future to extract reliable wind field information in the coastal region using ERS SAR images.