• Geomechanics and Engineering
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• v.7 no.4
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• pp.375-401
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• 2014

It is generally accepted that material heterogeneity has a great influence on the deformation, strength, damage and failure modes of rock. This paper presents numerical simulation on rock failure process based on the characterization of rock heterogeneity by using a digital image processing (DIP) technique. The actual heterogeneity of rock at mesoscopic scale (characterized as minerals) is retrieved by using a vectorization transformation method based on the digital image of rock surface, and it is imported into a well-established numerical code Rock Failure Process Analysis (RFPA), in order to examine the effect of rock heterogeneity on the rock failure process. In this regard, the numerical model of rock could be built based on the actual characterization of the heterogeneity of rock at the meso-scale. Then, the images of granite are taken as an example to illustrate the implementation of DIP technique in simulating the rock failure process. Three numerical examples are presented to demonstrate the impact of actual rock heterogeneity due to spatial distribution of constituent mineral grains (e.g., feldspar, quartz and mica) on the macro-scale mechanical response, and the associated rock failure mechanism at the meso-scale level is clarified. The numerical results indicate that the shape and distribution of constituent mineral grains have a pronounced impact on stress distribution and concentration, which may further control the failure process of granite. The proposed method provides an efficient tool for studying the mechanical behaviors of heterogeneous rock and rock-like materials whose failure processes are strongly influenced by material heterogeneity.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.2161-2166
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• 2009

It is important for 0-6 hour nowcasting to provide for a high-quality initial condition in a meso-scale atmospheric model by a data assimilation of several observation data. The polarimetric radar data is expected to be assimilated into the forecast model, because the radar has a possibility of measurements of the types, the shapes, and the size distributions of hydrometeors. In this paper, an impact on rainfall prediction of the data assimilation of hydrometeor types (i.e. raindrop, graupel, snowflake, etc.) is evaluated. The observed information of hydrometeor types is estimated using the fuzzy logic algorism. As an implementation, the cloud-resolving nonhydrostatic atmospheric model, CReSS, which has detail microphysical processes, is employed as a forecast model. The local ensemble transform Kalman filter, LETKF, is used as a data assimilation method, which uses an ensemble of short-term forecasts to estimate the flowdependent background error covariance required in data assimilation. A heavy rainfall event occurred in Okinawa in 2008 is chosen as an application. As a result, the rainfall prediction accuracy in the assimilation case of both hydrometeor types and the Doppler velocity and the radar echo is improved by a comparison of the no assimilation case. The effects on rainfall prediction of the assimilation of hydrometeor types appear in longer prediction lead time compared with the effects of the assimilation of radar echo only.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.2
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• pp.167-177
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• 1996

To investigate the source-receptor relationships aerosol model has been used to simulate the distribution behavior of the yellow sand. Data for meteorological fields were obtained by Meso-scale Analysis and Prediction Model System/Seoul National University (MAPMS/SNU) for five days (10-14 April 1988). To obtain the distributions of concentration of yellow sand,the aerosol model has been modified to allow quantifications of relative concentration distributions of yellow sand. Source regions of yellow sand were delineated by soil maps of China and emission rate as a function of wind stress(Westphal et al., 1987). Using 3-dimensional wind fields the backward trajectories from 3 receptor grids at the layer of .sigma. =0.95, 0.9, 0.85, 0.8 were calculated. In order to facilitate quantitative assessment of source-receptor relationships, it was assumed that the perturbations in along-trajectory and cross-trajectory proceed linearly with time, in accord with Gaussian distribution characteristics. On the basis of this assumption, the probability fields were calculated from every grid point with source strength 1. Using these probability fields and emission retes, the potential contributions of upstream sources along the trajectories were estimated. The results of this study indicate that the application of trajectory modeling is useful in investigating the quantitative relationship between source and receptor regions.

• Structural Engineering and Mechanics
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• v.38 no.6
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• pp.803-823
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• 2011

In this paper, the three dimensional Parallel Realistic Failure Process Analysis ($RFPA^{3D}$-Parallel) code based on micromechanical model is employed to investigate the bonding behavior in FRP sheet bonded to concrete in single shear test. In the model, the heterogeneity of brittle disordered material at a meso-scale was taken into consideration in order to realistically demonstrate the mechanical characteristics of FRP-to-concrete. Modified Mohr-coulomb strength criterion with tension cut-off, where a stressed element can damage in shear or in tension, was adopted and a stiffness degradation approach was used to simulate the initiation, propagation and growth of microcracks in the model. In addition, a Master-Slave parallel operation control technique was adopted to implement the parallel computation of a large numerical model. Parallel computational results of debonding of FRP-concrete visually reproduce the spatial and temporal debonding failure progression of microcracks in FRP sheet bonded to concrete, which agrees well with the existing testing results in laboratory. The numerical approach in this study provides a useful tool for enhancing our understanding of cracking and debonding failure process and mechanism of FRP-concrete and our ability to predict mechanical performance and reliability of these FRP sheet bonded to concrete structures.

• Computers and Concrete
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• v.15 no.4
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• pp.485-501
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• 2015

Cooling by the flow of water through an embedded cooling pipe has become a common and effective artificial thermal control measure for massive concrete structures. However, an extreme thermal gradient induces significant thermal stress, resulting in thermal cracking. Using a mesoscopic finite-element (FE) mesh, three-phase composites of concrete namely aggregate, mortar matrix and interfacial transition zone (ITZ) are modeled. An equivalent probabilistic model is presented for failure study of concrete by assuming that the material properties conform to the Weibull distribution law. Meanwhile, the correlation coefficient introduced by the statistical method is incorporated into the Weibull distribution formula. Subsequently, a series of numerical analyses are used for investigating the influence of the correlation coefficient on tensile strength and the failure process of concrete based on the equivalent probabilistic model. Finally, as an engineering application, damage and failure behavior of concrete cracks induced by a water-cooling pipe are analyzed in-depth by the presented model. Results show that the random distribution of concrete mechanical parameters and the temperature gradient near water-cooling pipe have a significant influence on the pattern and failure progress of temperature-induced micro-cracking in concrete.

• Geomechanics and Engineering
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• v.36 no.2
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• pp.121-130
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• 2024

Many foundation projects are built on red-bed soft rocks, and the damage evolution of this kind of rocks affects the safety of these projects. At present, there is insufficient research on the damage evolution of red-bed soft rocks, especially the progressive process from mesoscopic texture change to macroscopic elastoplastic deformation. Therefore, based on the dual-porosity characteristics of pores and fissures in soft rock, we adopted a cellular automata model to simulate the propagation of these voids in soft rocks under an external load. Further, we established a macro-mesoscopic damage model of red-bed soft rocks, and its reliability was verified by tests. The results indicate that the relationship between the number and voids size conformed to a quartic polynomial, whereas the relationship between the damage variable and damage porosity conformed to a logistic curve. The damage porosity was affected by dual-porosity parameters such as the fractal dimension of pores and fissures. We verified the reliability of the model by comparing the test results with an established damage model. Our research results described the progressive process from mesoscopic texture change to macroscopic elastoplastic deformation and provided a theoretical basis for the damage evolution of these rocks.

• Journal of Ocean Engineering and Technology
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• v.38 no.4
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• pp.149-163
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• 2024

This paper employs the third-generation simulating waves nearshore (SWAN) ocean wave model to estimate and analyze storm waves induced by Typhoon Bolaven, focusing on its impact along the west coast and Jeju Island of Korea. Utilizing reanalyzed meteorological data from the Japan Meteorological Agency meso scale model (JMA-MSM), the study simulated storm waves from Typhoon Bolaven, which maintained its intensity up to high latitudes as it approached the Korean Peninsula in 2012. Validation of the SWAN model against observed wave data demonstrated a strong correlation, particularly in regions where wind speeds exceeded 20 m/s and wave heights surpassed 5 m. Results indicate significant storm wave heights across Jeju Island and Korea's west and southwest seas, with coastal grid points near islands recording storm wave heights exceeding 90% of the 50-year return period design wave heights. Notably, specific grid points near islands in the northern West Sea and southwest Jeju Island estimated storm wave heights at 90.22% and 91.48% of the design values, respectively. The paper highlights the increased uncertainty and vulnerability in coastal disaster predictions due to event-driven typhoons and emphasizes the need for enhanced accuracy and speed in typhoon wave predictions amid the escalating climate crisis.

• The Plant Pathology Journal
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• v.21 no.2
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• pp.111-118
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• 2005

Weather data for disease forecasts are usually derived from automated weather stations (AWS) that may be dispersed across a region in an irregular pattern. We have developed an alternative method to simulate local scale, high-resolution weather and plant disease in a grid pattern. The system incorporates a simplified mesoscale boundary layer model, LAWSS, for estimating local conditions such as air temperature and relative humidity. It also integrates special models for estimating of surface wetness duration and disease forecasts, such as the grapevine downy mildew forecast model, DMCast. The system can recreate weather forecasts utilizing the NCEP/NCAR reanalysis database, which contains over 57 years of archived and corrected global upper air conditions. The highest horizontal resolution of 0.150 km was achieved by running 5-step nested child grids inside coarse mother grids. Over the Finger Lakes and Chautauqua Lake regions of New York State, the system simulated three growing seasons for estimating the risk of grape downy mildew with 1 km resolution. Outputs were represented as regional maps or as site-specific graphs. The highest resolutions were achieved over North America, but the system is functional for any global location. The system is expected to be a powerful tool for site selection and reanalysis of historical plant disease epidemics.

• Transactions of Materials Processing
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• v.24 no.6
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• pp.395-399
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• 2015

A microstructure-based finite element simulation was conducted to predict the plastic strain ratio (R-value) of a dual-phase (DP) steel. The representative volume elements (RVEs) concept was adopted for the image-based FE modeling and a 3D model was constructed using sequential 2D images. Each phase was considered with the von-Mises yield criterion and the Swift model. The Swift parameters were defined by the empirical equations based on the chemical composition. The developed model was applied to analyze the effect of residual stress on the R-value and stress distribution. In order to consider the residual stress development after cold rolling, 10 % compression was applied in the thickness direction and unloaded before the tensile stress was applied in the rolling direction. The results showed a reasonable prediction for the R-value evolution: a sharp increase at small strains was well described and a transition followed in the downward direction. The R-value evolution was analyzed using the stress distribution change on the π-plane

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.3
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• pp.403-412
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• 2018

In this study, a three-dimensional variational(3DVAR) data assimilation system was developed for the operational numerical weather prediction(NWP) system at the Republic of Korea Air Force Weather Group. The Air Force NWP system utilizes the Weather Research and Forecasting(WRF) meso-scale regional model to provide weather information for the military service. Thus, the data assimilation system was developed based on the WRF model. Experiments were conducted to identify the nested model domain to assimilate observations and the period appropriate in estimating the background error covariance(BEC) in 3DVAR. The assimilation of observations in domain 2 is beneficial to improve 24-h forecasts in domain 3. The 24-h forecast performance does not change much depending on the estimation period of the BEC in 3DVAR. The results of this study provide a basis to establish the operational data assimilation system for the Republic of Korea Air Force Weather Group.