Study on the treatments and countermeasures for liquefiable foundation

This paper summarizes the current treatments and countermeasures for liquefiable foundations, and divides the existing anti-liquefaction countermeasures into two categories. One of the ideas is proceeding from the properties of liquefiable foundation soils, by the means of improvement for the soil’s qualities to enhance the capacity of soil’s anti-liquefaction in the early stage. The other idea is considering from the stress conditions of liquefiable foundation soils, and to reduce the liquefaction-induced disasters by changing the stress conditions of the soil. The advantages and disadvantages of various anti-liquefaction measures were analysed by verifying the effectiveness of field applications of anti-liquefaction measures against ground liquefaction hazards, and the applicable conditions of various anti-liquefaction measures were classified. This paper provides experience for resisting soil liquefaction disasters

Study on the treatments and countermeasures for liquefiable foundation

This paper summarizes the current treatments and countermeasures for liquefiable foundations, and divides the existing anti-liquefaction countermeasures into two categories. One of the ideas is proceeding from the properties of liquefiable foundation soils, by the means of improvement for the soil’s qualities to enhance the capacity of soil’s anti-liquefaction in the early stage. The other idea is considering from the stress conditions of liquefiable foundation soils, and to reduce the liquefaction-induced disasters by changing the stress conditions of the soil. The advantages and disadvantages of various anti-liquefaction measures were analysed by verifying the effectiveness of field applications of anti-liquefaction measures against ground liquefaction hazards, and the applicable conditions of various anti-liquefaction measures were classified. This paper provides experience for resisting soil liquefaction disasters

Corrosion behavior of heat-resistant stainless steel in high temperature molten glass

The development of the nuclear industry and nuclear energy have prompted studies focusing on disposal of nuclear waste in a green and safe way. The use of metal containers to fill glass solidified nuclear waste and then landfill is currently the dominant way in waste disposal. However, the high temperature corrosion caused by the high temperature molten glass on the surface of the metal container becomes an important factor accelerating the failure of the container. Therefore, an in-depth understanding of the corrosion behavior of metals in high temperature molten glass is necessary to ensure the safety of disposal of nuclear waste.The S30815 heat-resistant stainless steel was selected as the research object, and the corrosion morphology, composition and phase structure of the S30815 heat-resistant stainless steel kept in 1100 ℃ molten glass for different time were deeply analyzed. The results show that the molten glass corrodes inward along the grain boundary into the matrix and molten glass gradually replaces the steel by occupying the grain boundary and further penetrates the grains to form corrosion pits. Cr and Si elements in the heat-resistant stainless steel diffuse into the molten glass during corrosion, resulting in a decrease of content at the surface, and finally promote the transformation of metal surface from austenite to martensite. The corrosion of heat-resistant stainless steel by molten glass is alkaline dissolution. A continuous and stable oxide film cannot be formed on the surface, which means the corrosion will continue with the extension of holding time

Effects of Effective Precipitation and Accumulated Temperature on the Terrestrial EVI (Enhanced Vegetation Index) in the Yellow River Basin, China

To identify the vegetation dynamics and relationship with the hydrothermal conditions in the Yellow River basin (YRB), the spatial–temporal variations of EVI, effective precipitation (Epr), accumulated temperature (At), and their relationships were obtained based on the MODIS EVI data and meteorological data from the YRB during 2001–2020. The results indicate that EVI trends increased during 2001 to 2020, especially in the farmland, forestland, and grassland ecosystems. Epr and At have also increased over the last 20 years. Epr mostly increased faster in the grassland, and water bodies and wetland ecosystems. At mostly increased faster in the water bodies and wetland, desert, and forest ecosystems. Affected by Epr and At, the correlation between the EVI and hydrothermal conditions varied under different hydrothermal conditions. Compared to the At, the Epr was the restrictive factor for the EVI variations in the terrestrial ecosystem in the YRB. In addition, the dynamical thresholds of the EVI, Epr, and At were confirmed. This study can improve the understanding of vegetation variations and their response to regional climate change, which is critical for ecological conservation and the high-quality development of the YRB

Real‐time prediction and ponding process early warning method at urban flood points based on different deep learning methods

Abstract Accurate prediction of urban floods is regarded as one of the critical means to prevent urban floods and reduce the losses caused by floods. In this study, a refined prediction and early warning method system for urban flood and waterlogging processes based on deep learning methods is proposed. The spatial autocorrelation of rain and ponding points is analyzed by Moran's I (a common used statistic for spatial autocorrelation). For each ponding point, the relationship model between the rainfall process and ponding process is constructed based on different deep learning methods, and the results are analyzed and verified by mean absolute error (MAE), root mean square error (RMSE), Nash efficiency coefficient (NSE) and correlation coefficient (CC). The results show that the gradient boosting decision tree algorithm has the highest accuracy and efficiency (with a 0.001 m RMSE of the predicted and measured ponding depth) for ponding process prediction and is regarded as the most suitable method for ponding process prediction. Finally, the real‐time prediction and early warning of urban floods and waterlogging processes driven by rainfall forecast data are realized, and the results are verified by the measured data. The research results can provide theoretical support for urban flood prevention and control