• Geomechanics and Engineering
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• v.31 no.4
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• pp.375-384
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• 2022

The variation of the undrained shear strength (c_u) is an important consideration for assessing slope stability in engineering practice. Previous studies focused on the three-dimensional (3D) stability of slopes in normally consolidated clays generally assume the undrained shear strength increases linearly with depth but does not vary in the horizontal direction. To assess the 3D stability of slopes with spatially varying undrained shear strength, the kinematic approach of limit analysis was adopted to obtain the upper bound solution to the stability number based on a modified failure mechanism. Three types failure mechanism: the toe failure, face failure and below-toe failure were considered. A serious of charts was then presented to illustrate the effect of key parameters on the slope stability and failure geometry. It was found that the stability and failure geometry of slopes are significantly influenced by the gradient of c_u in the depth direction. The influence of c_u profile inclination on the slope stability was found to be pronounced when the increasing gradient of c_u in the depth direction is large. Slopes with larger width-to-height ratio B/H are more sensitive to the variation of c_u profile inclination.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2000.11a
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• pp.177-182
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• 2000

This paper predicted the equivalent stiffness of spatially reinforced composites (SRC) using the volume average of a fiber rod and matrix stiffness, and the strength of SRC using the stiffness reduction and the modified Tsai-Wu composite failure theory. Those equivalent engineering constants are used to analyze the mechanical behavior and the failure of SRC structures. Because the distribution of equivalent engineering constants is varying with the change in SRC shape, we made a program that predicts engineering constants of SRC. Both 3-D and 4-D SRC show the smallest tensile modulus and the largest shear modulus at the maximum rotated direction from each rod. Also the strength properties show the same tendency.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.180-180
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• 2023

To improve global risk management, understanding the characteristics and distribution of precipitation is crucial. However, obtaining spatially and temporally resolved climatic data remains challenging due to sparse gauge observations and limited data availability, despite the use of satellite and reanalysis products. To address this challenge, merging available precipitation products has been introduced to generate spatially and temporally reliable data by taking advantage of the strength of the individual products. However, most of the existing studies utilize all the available products without considering the varying performances of each dataset in different regions. Comprehensively considering the relative contributions of each parent dataset is necessary since their contributions may vary significantly and utilizing all the available datasets for data merging may lead to significant data redundancy issues. Hence, for this study, we introduce a site-specific precipitation merging method that utilizes the Quadruple Collocation (QC) approach, which acknowledges the existence of error-cross correlation between the parent datasets, to create a high-resolution global daily precipitation data from 2001-2020. The performance of multiple gridded precipitation products are first evaluated per region to determine the best combination of quadruplets to be utilized in estimating the error variances through the QC approach and computation of merging weights. The merged precipitation is then computed by adding the precipitation from each dataset in the quadruplet multiplied by each respective merging weight. Our results show that our approach holds promise for generating reliable global precipitation data for data-scarce regions lacking spatially and temporally resolved precipitation data.

• Geomechanics and Engineering
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• v.23 no.3
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• pp.261-273
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• 2020

This paper presents an efficient method utilizing user-defined computer functional codes to determine the reliability of an embankment slope with spatially varying soil properties in real time. The soils' mechanical properties varied with the soil layers that had different degrees of compaction and moisture content levels. The Latin Hypercube Sampling (LHS) for the degree of compaction and Kriging simulation of moisture content variation were adopted and programmed to predict their spatial distributions, respectively, that were subsequently used to characterize the spatial distribution of the soil shear strengths. The shear strength parameters were then integrated into the Geostudio command file to determine the safety factor of the embankment slope. An explicit metamodal for the performance function, using the Kriging method, was established and coded to efficiently compute the failure probability of slope with varying moisture contents. Sensitivity analysis showed that the proposed method significantly reduced the computational time compared to Monte Carlo simulation. About 300 times LHS Geostudio computations were needed to optimize precision and efficiency in determining the failure probability. The results also revealed that an embankment slope is prone to high failure risk if the degree of compaction is low and the moisture content is high.

• Journal of the Optical Society of Korea
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• v.20 no.6
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• pp.752-761
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• 2016

Hyperspectral images are often contaminated with stripe noise, which severely degrades the imaging quality and the precision of the subsequent processing. In this paper, a variational model is proposed by employing spectral-spatial adaptive unidirectional variation and a sparse representation. Unlike traditional methods, we exploit the spectral correction and remove stripes in different bands and different regions adaptively, instead of selecting parameters band by band. The regularization strength adapts to the spectrally varying stripe intensities and the spatially varying texture information. Spectral correlation is exploited via dictionary learning in the sparse representation framework to prevent spectral distortion. Moreover, the minimization problem, which contains two unsmooth and inseparable $l_1$-norm terms, is optimized by the split Bregman approach. Experimental results, on datasets from several imaging systems, demonstrate that the proposed method can remove stripe noise effectively and adaptively, as well as preserve original detail information.

• Wind and Structures
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• v.13 no.1
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• pp.1-20
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• 2010

The recommended factored design wind load effects for overhead lattice transmission line towers by codes and standards are evaluated based on the applicable wind load factor, gust response factor and design wind speed. The current factors and design wind speed were developed considering linear elastic responses and selected notional target safety levels. However, information on the nonlinear inelastic responses of such towers under extreme dynamic wind loading, and on the structural capacity curves of the towers in relation to the design capacities, is lacking. The knowledge and assessment of the capacity curve, and its relation to the design strength, is important to evaluate the integrity and reliability of these towers. Such an assessment was performed in the present study, using a nonlinear static pushover (NSP) analysis and incremental dynamic analysis (IDA), both of which are commonly used in earthquake engineering. For the IDA, temporal and spatially varying wind speeds are simulated based on power spectral density and coherence functions. Numerical results show that the structural capacity curves of the tower determined from the NSP analysis depend on the load pattern, and that the curves determined from the nonlinear static pushover analysis are similar to those obtained from IDA.

• Composite Materials and Engineering
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• v.3 no.3
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• pp.221-239
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• 2021

This paper presents a multiscale modeling method for sheet molding compound (SMC) composites through a novel bundle packing reconstruction algorithm based on a micro-CT (Computed Tomography) image processing. Due to the complex flow pattern during the compression molding process, the SMC composites show a spatially varying orientation and overlapping of fiber bundles. Therefore, significant inhomogeneity and anisotropy are commonly observed and pose a tremendous challenge to predicting SMC composites' properties. For high-fidelity modeling of the SMC composites, the statistical distributions for the fiber orientation and local volume fraction are characterized from micro-CT images of real SMC composites. After that, a novel bundle packing reconstruction algorithm for a high-fidelity SMC model is proposed by considering the statistical distributions. A method for evaluating specimen level's strength and stiffness is also proposed from a set of high-fidelity SMC models. Finally, the proposed multiscale modeling methodology is experimentally validated through a tensile test.

• Earthquakes and Structures
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• v.10 no.5
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• pp.989-1012
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• 2016

The structural dynamic behavior and yield strength considering both ductility and strain rate effects are analyzed in this article. For the single-degree-of-freedom (SDOF) system, the relationship between the relative velocity and the strain rate response is deduced and the strain rate spectrum is presented. The ductility factor can be incorporated into the strain rate spectrum conveniently based on the constant-ductility velocity response spectrum. With the application of strain rate spectrum, it is convenient to consider the ductility and strain rate effects in engineering practice. The modal combination method, i.e., square root of the sum of the squares (SRSS) method, is employed to calculate the maximum strain rate of the elastoplastic multiple-degree-of-freedom (MDOF) system under uniform excitation. Considering the spatially varying ground motions, a new response spectrum method is developed by incorporating the ductility factor and strain rate into the conventional response spectrum method. In order to further analyze the effects of strain rate and ductility on structural dynamic behavior and yield strength, the cantilever beam (one-dimensional) and the triangular element (two-dimensional) are taken as numerical examples to calculate their seismic responses in time domain. Numerical results show that the permanent displacements with and without considering the strain rate effect are significantly different from each other. It is not only necessary in theory but also significant in engineering practice to take the ductility and strain rate effects into consideration.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.