The aim of the study was to solve the problem of drainage stability of pavement base in cold and Cloudburst area. With porous concrete as the research object, an optimum design of porous concrete was determined using a step filling and orthogonal test method, and the relationship between the porosity and the connected porosity of the porous concrete was analyzed. Furthermore, drainage performance and frost resistance of the pavement, compressive strength of the porous concrete, bending strength, and compressive elastic modulus were studied. The results show that the effects of water-cement ratio on the strength of porous concrete based on the step filling method are the most significant. In addition, the connected porosity and goal porosity have a good linear relationship; that is, the drainage performance increases with the increase in connected porosity, whereas the frost resistance, compressive strength, flexural tensile strength, and compressive elastic modulus decrease with the increase in connected porosity. Based on an engineering project in Inner Mongolia (in China), it was shown that porous concrete with a goal porosity of 15% used as a pavement base could meet the requirements of cold weather, showers, and heavy traffic.
Terraces are an important cultivated land resource. Terrace abandonment affects the soil quality, soil and water conservation benefits, and biodiversity of terraces. Therefore, it is important to quantify the number and spatial distribution of abandoned terraces to protect cultivated land and food security. However, the traditional remote sensing method cannot identify small plots and make accurate assessment of abandoned farmland quickly in mountainous areas. To accurately identifying abandoned terraces, this study used semantic segmentation based on deep learning and change detection to identify abandoned terraces and their spatial distribution in a small watershed on the Loess Plateau in 2021. A comparative analysis of the accuracy of three deep learning models revealed that RefineNet is superior to DeepLabv3+ and DeepLabv3 for identifying abandoned terraces. The user's accuracy, producer's accuracy, overall accuracy, and appa values for RefineNet were 0.817, 0.894, 0.800, and 0.539, respectively. For change detection, the corresponding values were 0.821, 0.753, 0.731, and 0.426, respectively. In addition, semantic segmentation produced better recognition results than change detection in complex terrain and geomorphological areas. The abandoned terraces in the study area were mainly distributed in mountainous areas far from residential areas and more likely at high elevations with large slopes. This study provides a new method for recognizing abandoned terraces and spatial distribution information for managing and utilizing abandoned terraces.
In order to determine the color modified emulsified asphalt and its preparation process in cold areas represented by Hulunbuir, Inner Mongolia, a variety of materials such as saturated hydrocarbon A, petroleum resin B, copolymer C, copolymer D, and plasticizer E were selected to simulate four components of asphalt are used to prepare colored asphalt, and a colored modified emulsified asphalt suitable for cold regions is developed by the preparation process of emulsified asphalt emulsifying and modifying. The performance of the prepared colored modified emulsified asphalt was analyzed, and the optimal dosage range of modifier, emulsifier, stabilizer, and pH adjuster was determined, and the high and low temperature performance of colored modified emulsified asphalt was improved to adapt to environment of cold areas. Through the colored micro-surfacing mix design to determined the optimal emulsified asphalt dosage, and the test compares the surface performance and durability of the ordinary micro-surfacing mixture and the colored micro-surfacing mixture, which proves that the CMS-3 type mixture has good water sealing effect, anti-slip performance and ability of water damage resistance.
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