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Song Jun Young Sim Youngjong Jang Jaewon Hong Won-Taek Yun Tae Sup 《Acta Geotechnica》2020,15(7):1967-1980
Acta Geotechnica - To resolve the environmental and sustainability issues from fugitive dust emission and conventional mitigation methods, multiple experiments were conducted to evaluate the... 相似文献
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In the context of carbon capture and storage, deep underground injection of CO2 induces the geomechanical changes within and around the injection zone and their impact on CO2 storage security should be evaluated. In this study, we conduct coupled multiphase fluid flow and geomechanical modeling to investigate such geomechanical changes, focusing on probabilistic analysis of injection-induced fracture reactivation (such as shear slip) that could lead to enhanced permeability and CO2 migration across otherwise low-permeability caprock formations. Fracture reactivation in terms of shear slip was analyzed by implicitly considering the fracture orientations generated using the Latin hypercube sampling method, in one case using published fracture statistics from a CO2 storage site. The analysis was conducted by a coupled multiphase fluid flow and geomechanical simulation to first calculate the three-dimensional stress evolution during a hypothetical CO2 injection operation and then evaluate the probability of shear slip considering the statistical fracture distribution and a Coulomb failure analysis. We evaluate the probability of shear slip at different points within the injection zone and in the caprock just above the injection zone and relate this to the potential for opening of new flow paths through the caprock. Our analysis showed that a reverse faulting stress field would be most favorable for avoiding fracture shear reactivation, but site-specific analyses will be required because of strong dependency of the local stress field and fracture orientations. 相似文献
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Fluid flow through porous media is inherently associated with the detachment and migration of fine particles. The migration of fine particles and ensuing clogging is the main reason of flow rate decrease in porous media. Nanoparticle coating can be a promising method to prevent fines’ detachment and migration by changing electrical surface forces between the pore wall surface and the fine particles. In this study, the attraction and adhesion forces of the nanoparticle-coated surface are measured by atomic force microscope. The effect of the nanoparticle coating on the fines adsorption efficiency is then investigated. The results show that there is an increase in the adhesion force on the nanoparticle-coated surface and the significant improvement of the fines adsorption capacity by the nanoparticle coating. The research results are relevant to other research areas whenever migrating fines cause engineering problems. 相似文献
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The purpose of this study was to evaluate the effects of climate change on the drought and flood risks of a multipurpose dam. To achieve this, A2 climate change scenarios of RegCM3 were collected about Chungju Dam in Korea. To analyze drought risks, weather data obtained by the statistical downscaling method were entered to produce runoff series by runoff modeling and water balance was analyzed based on water use scenarios to review changes in the storage volume under climate change. To analyze flood risks, changes in water levels of the dam in future flood seasons were reviewed based on the current dam operation method. The results of the review indicated that both the drought and the flood risks of the dam would increase in the future. The reason was considered to be the movement of the flood season’s runoff characteristics from July and August to August and September because of climate change. Therefore, for climate change adaptation planning, not only quantitative changes in hydrologic values but also changes in temporal characteristics should be considered and given importance. 相似文献
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Much attention has been focused on investigating the effects of precipitation and temperature changes on runoff; however, the influence of wind speed, relative humidity and total solar radiation on hydrological components needs to be studied further. Hydrological responses to climate variations in a minimally disturbed mountainous watershed in the period 1971–2012 are identified and evaluated by statistical analysis and hydrological simulation. The results indicate that the impact of climate component changes on the hydrological process cannot be discounted. The temperature and relative humidity exhibit significant upward trends, while the wind speed exhibits a clear downward trend. The potential and actual evapotranspiration dramatically increased, but the observed pan evaporation substantially decreased. The surface water, soil water, baseflow and water yield are positively correlated with precipitation and relative humidity but negatively correlated with the temperature, wind speed and solar radiation. 相似文献
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Analysis and forecasting of water temperature are important for water ecological management. The objective of this study is to compare models for water temperature during the summer season for an impounded river. In a case study, we consider hydro-climatic and water temperature data for the Fourchue River (St-Alexandre-de-Kamouraska, Quebec, Canada) between 2011 and 2014. Three different models are applied, which are broadly characterized as deterministic (CEQUEAU), stochastic (Auto-regressive Moving Average with eXogenous variables or ARMAX) and nonlinear (Nonlinear Autoregressive with eXogenous variables or NARX). The efficiency of each model is analysed and compared. The results show that the ARMAX is the best performing water temperature model for the Fourchue River and the CEQUEAU model also simulates water temperature adequately without the overfitting issues that seem to plague the autoregressive models.
EDITOR M.C. AcremanASSOCIATE EDITOR R. Hirsch 相似文献
7.
Validation of an artificial neural network model for landslide susceptibility mapping 总被引：6，自引：3，他引：3
The aim of this study was to validate an artificial neural network model at Youngin, Janghung, and Boeun, Korea, using the
geographic information system (GIS). The factors that influence landslide occurrence, such as the slope, aspect, curvature,
and geomorphology of topography, the type, material, drainage, and effective thickness of soil, the type, diameter, age, and
density of forest, distance from lineament, and land cover were either calculated or extracted from the spatial database and
Landsat TM satellite images. Landslide susceptibility was analyzed using the landslide occurrence factors provided by the
artificial neural network model. The landslide susceptibility analysis results were validated and cross-validated using the
landslide locations as study areas. For this purpose, weights for each study area were calculated by the artificial neural
network model. Among the nine cases, the best accuracy (81.36%) was obtained in the case of the Boeun-based Janghung weight,
whereas the Janghung-based Youngin weight showed the worst accuracy (71.72%). 相似文献
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Landslide-related factors were extracted from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, and integrated techniques were developed, applied, and verified for the analysis of landslide susceptibility in Boun, Korea, using a geographic information system (GIS). Digital elevation model (DEM), lineament, normalized difference vegetation index (NDVI), and land-cover factors were extracted from the ASTER images for analysis. Slope, aspect, and curvature were calculated from a DEM topographic database. Using the constructed spatial database, the relationships between the detected landslide locations and six related factors were identified and quantified using frequency ratio (FR), logistic regression (LR), and artificial neural network (ANN) models. These relationships were used as factor ratings in an overlay analysis to create landslide susceptibility indices and maps. Three landslide susceptibility maps were then combined and applied as new input factors in the FR, LR, and ANN models to make improved susceptibility maps. All of the susceptibility maps were verified by comparison with known landslide locations not used for training the models. The combined landslide susceptibility maps created using three landslide-related input factors showed improved accuracy (87.00% in FR, 88.21% in LR, and 86.51% in ANN models) compared to the individual landslide susceptibility maps (84.34% in FR, 85.40% in LR, and 74.29% in ANN models) generated using the six factors from the ASTER images. 相似文献
9.
The purpose of this study is to quantify the magnitudes of surface conduction and pore water conduction from the measured electrical conductivity of kaolinite, with the ultimate goal of estimating the electrical conductivity of kaolinite with a wide range of pore water conductivities (σ w = 0.013–3.356 S/m) and porosities (n = 0.368–1.0). Therefore, the theoretical background of the electrical conductivity in soils was reviewed, and electrical conductivity measurements on kaolinite were performed using both slurry and consolidation tests in this study. The results of this study demonstrate that the variations of measured electrical conductivity (σ mix) with n are debatable according to the values of σ w, because a decrease in n results in both an increase in surface conduction (K s) and a decrease in pore water conduction (K w); this causes the relative magnitude of K s compared to that of K w to vary with σ w and n. Consequently, this study develops the relation between the porosity-normalized K s/K w and 1/σ w. Additionally, the surface conductivity of the tested kaolinite is back-calculated and compared with the previous relationship between K s and zeta potential of kaolinite. The measured and estimated σ mix values are compared with the varying pore water conductivity and porosity values. 相似文献
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