以颗粒状和粉末状膨润土防水毯(GCLs)为对象,运用GDS (global digital systems)全自动渗透仪开展渗透试验,研究CaCl_2溶液作用下GCLs渗透性能的温度效应,初步探讨其机理。试验表明:当水化液为0.05mol/L的CaCl_2溶液时,两种GCLs渗透系数随温度升高呈现增大趋势;当水化液为去离子水时,颗粒状GCL渗透系数随温度升高而减小,粉末状GCL渗透系数随温度升高而增大。去离子水情况下,膨润土吸附结合水量随温度升高而减小;CaCl_2溶液作用下,吸附结合水量较去离子水情况大幅降低。当CaCl_2溶液浓度一定时,膨润土膨胀指数随温度升高而略有增大;当温度一定时,膨润土膨胀指数随CaCl_2溶液浓度升高而显著减小。以去离子水进行试验时:颗粒状和粉末状GCLs渗透系数随温度的变化主要影响因素为凝胶态蒙脱石数量,其次为流体黏滞系数和吸附结合水量;颗粒状GCLs膨润土孔隙结构越不均匀,凝胶态蒙脱石数量的影响就越显著,导致渗透系数随温度升高而减小、固有渗透率随温度升高显著降低。以CaCl_2溶液进行试验时,两种GCLs渗透系数随温度变化的主要受流体黏滞系数和吸附结合水量的影响,而受凝胶态蒙脱石数量的影响较小。孔隙溶液性质、温度和膨润土类型均对GCLs的防渗性能具有重要影响。 相似文献
Acta Geotechnica - There is extensive data to show that heating and cooling produces irrecoverable deformations in clays under fully drained conditions. The effects are most pronounced for normally... 相似文献
To stabilise the tunnel faces and slopes in soft clay for the Airport Link construction in Australia, fracture grouting and glass fibre-reinforced plastic (GFRP) soil nails are proposed for the soil improvement as well as ease of handling. The compensation caused by the fracture grouting and the gain in strength due to consolidation as well as the geonail have stabilised the soft clay during construction. Only a small amount of ground settlement during soft clay box-jacking operation is generated so that the railway traffic above the embankment can be maintained without interference. The design method of the fracture grouting ground improvement study for this difficult project is discussed in this paper. Extensive laboratory and field tests were employed to verify the design assumptions and to fine-tune the ground improvement studies. The success of this project in poor ground conditions results from combined efforts of extensive field tests, an improved ground improvement design method and a realistic numerical analysis to assess the unstable/highly stressed zones for the placement of soil reinforcement. 相似文献
Biogrouting is a new ground improvement method that has been studied in recent years. This method involves mainly the use of a microbially induced calcite precipitation process to bind soil particles to increase the strength or to fill in the pores of soil or joints of rock for seepage control. There are two major challenges in the use of biogrout for seepage control through rock joints. The first is how to inject the biogrout solutions, and the second is to understand the mechanisms for the formation of calcite under seepage flow. In this paper, a study on the injection of biogrout solution and the formation of precipitates along a circular 1D flow channel is presented. To minimize the influence of flow, a new one-phase injection method to inject bacterial solution and cementation agents simultaneously was adopted in this study. Factors affecting the formation and distribution of precipitates along the flow channel such as flow velocity, flow rate, and aperture of flow channel were investigated. The experimental results indicated that less calcite was precipitated at locations further away from the injection point due to depletion of the reactants’ concentrations along the flow path. Using the one-phase injection method, the bacterial activity had a major effect on the accumulation of the calcite on the inner surface of the flow channel. The total calcite precipitated on the surface of the flow channel increased slightly with increasing bacterial activity or flow rate. An equation to predict the distance travelled by the biosolution has been derived based on the testing results.
China Ocean Engineering - Coastal wave energy resources have enormous exploitation potential due to shorter weather window, closer installation distance and lower maintenance cost. However, impact... 相似文献
Large dams and reservoirs alter not only the natural flow regimes of streams and rivers but also their flooding cycles and flood magnitudes. Although the effect of dams and reservoirs has been reported for some vulnerable locations, the understanding of the inner-basin variation with respect to the effects remains limited. In this study, we analyse the Three Gorges Dam (TGD) built on the Changjiang mainstream (Yangtze River) to investigate the dam effect variations in the system of interconnected water bodies located downstream. We investigated the effect of flow alterations along the downstream river network using discharge time series at different gauging stations. The river–lake interactions (referring to the interactions between the Changjiang mainstream and its tributary lakes i.e. the Dongting and Poyang lakes) and their roles in modifying the TGD effect intensity were also investigated in the large-scale river–lake system. The results show that the water storage of the tributary lakes decreased after the activation of the TGD. Severe droughts occurred in the lakes, weakening their ability to recharge the Changjiang mainstream. As a consequence, the effect of the TGD on the Changjiang flow increase during the dry season diminished quickly downstream of the dam, whereas its impact on the flow decrease during the wet season gradually exacerbated along the mainstream, especially at sites located downstream of the lake outlets. Therefore, when assessing dam-induced hydrological changes, special attention should be paid to the changes in the storage of tributary lakes and the associated effects in the mainstream. This is of high importance for managing the water resource trade-offs between different water bodies in dam-affected riverine systems. 相似文献
ABSTRACTThe spatio-temporal residual network (ST-ResNet) leverages the power of deep learning (DL) for predicting the volume of citywide spatio-temporal flows. However, this model, neglects the dynamic dependency of the input flows in the temporal dimension, which affects what spatio-temporal features may be captured in the result. This study introduces a long short-term memory (LSTM) neural network into the ST-ResNet to form a hybrid integrated-DL model to predict the volumes of citywide spatio-temporal flows (called HIDLST). The new model can dynamically learn the temporal dependency among flows via the feedback connection in the LSTM to improve accurate captures of spatio-temporal features in the flows. We test the HIDLST model by predicting the volumes of citywide taxi flows in Beijing, China. We tune the hyperparameters of the HIDLST model to optimize the prediction accuracy. A comparative study shows that the proposed model consistently outperforms ST-ResNet and several other typical DL-based models on prediction accuracy. Furthermore, we discuss the distribution of prediction errors and the contributions of the different spatio-temporal patterns. 相似文献
