Gongcheng Kexue Yu Jishu/Advanced Engineering Science

The water holding capacity of unsaturated soils is usually reflected by the changing laws of soil-water characteristic curves. The important influence of factors such as load and temperature on the soil-water characteristic curve has been gradually recognized, but studies on the combined effect of moisture-load-heat on the soil-water characteristic curve are rarely reported, and the analysis of its dominant influence factors is even rarer. In order to explore the water holding capacity of silty clay under the combined action of moisture-load-heat, this paper carried out dry-wet cycle experiments of silty clay under different vertical stress and temperature conditions, and analyzed the influence mechanism, characteristics and characteristics of each factor. Importance, and established a predictive model reflecting the interaction of multiple factors. The research results show that With the increase of the vertical stress, the air intake value of unsaturated soil increases, the dehumidification rate decreases, and the hysteresis effect of the dry-wet cycle process becomes stronger, and it shows the same characteristics at all temperatures. Comparing the experimental curves under the same vertical stress and different temperatures, it is found that the air intake value of the soil is relatively slightly lower when the temperature is higher. The vertical stress has the greatest influence on the water holding capacity of the soil, but it is mainly limited to the low suction stage the dry-wet cycle has the second effect, and it will rapidly decay as the number of cycles increases the temperature has a small influence and is When the suction value or density is high, it can be ignored. The improved L model based on the Logistic curve is more suitable for the soil-water characteristic curve fitting of Badong silty clay than the commonly used V-G model. The comprehensive research results show that the root cause of the change of the characteristic value caused by the vertical stress is the change of the internal pore structure, which leads to the difference in water holding performance; temperature mainly affects the water holding performance of the soil in a low-stress and low-suction state 3 types The degree of influence of occurrence conditions on water holding capacity of silty clay is vertical stress>dry-wet cycle>temperature distribution the improved L model can effectively reflect the evolution of water holding capacity of silty clay under the combined action of moisture-load-heat feature.

Landslides often occur in steep mountain areas during heavy rainstorms. Establishing landslide prediction models is one of the essential strategies for disaster prevention in mountain areas. The kinematic subsurface-flow approximation and the infinite-slope instability analysis were used to develop a rainfall-induced shallow landslide prediction model. Firstly, the runoff hydrograph and the temporal variation of soil water storage were obtained by calculating the runoff yield and concentration of slope according to the theory of the kinematic subsurface-flow approximation. Then the temporal variation characteristics of saturated water level was studied. Finally, based on the theory of the infinite-slope instability analysis, and the analyzed slope stability the temporal variation of factor of safety was calculated. The Namasia District in Kaohsiung of Taiwan was chosen as a studied area to test the applicability of the model. It was found that the predicted location of landslide occurrence during Typhoon Morakot is consistent with those obtained from satellite images, and the values of the calibrated model parameters are consistent with physical meanings, which shows that the physically based model has good reliability. Moreover, the variation of the slope factor of safety was analyzed by applying double-peak design hyetographs with different rainfall peaks. The result showed that when the rainfall increases, the subsurface flow, and the saturated water level raise quickly to result in the decreasing of factor of safety value. On the contrary, while the rainfall decreases, the rate of subsurface outflow is higher than rainfall intensity, the saturated water level would drop slowly. Hence, the slope factor of safety is increasing and gradually returns to its natural state. Moreover, the influence of soil thickness on slope stability was further studied during the rainstorms. The results showed that factor of safety is reduced as the increasing of the soil thickness. It also reveals that if a low-peak rainfall occurs and followed by a high-peak rainfall, it would result in a higher possibility of landslides. It was expected that this study can give a clear physical explanation for the landslide occurrence and provide a useful tool for landslide prediction.

The structural and morphological characterization of rock mass is of great significance to the excavation and construction of geotechnical and geological engineering. Digital panoramic borehole camera technology is an important means to obtain the structural morphology of rock mass quickly and effectively in the borehole. In view of the highlighted problems of the existing digital panoramic borehole camera system and its analysis software during the complex environment investigation, a method of fast mosaic and fusion of circular image from original borehole panoramic video was proposed. In this method, the borehole video image is transformed into several ordered narrowband images, and the image features are detected, matched, and filtered, so as to realize the rapid mosaic and fusion of panoramic borehole images. Results show that this method can quickly complete the continuous mosaic and fusion of panoramic video images without the help of a compass or electronic compass and depth encoder. The horizontal resolution, vertical resolution, and the image clarity of the mosaic image are raised by one magnitude. The actual working time can be halved. The process of forming the mosaic image can be intelligent processing and automated analysis. It can reduce the burden of researchers and improve work efficiency. This method can quickly and effectively form a high-quality borehole panoramic image without deviation based on the borehole video image’s inherent characteristics, which promotes the development of borehole camera technology and provides a more convenient and effective technical means for high-precision rock mass engineering investigation.

The key to the evaluation of freeze-thaw performance of lightweight aggregate concrete after disaster lies in the accurate quantitative description and prediction of its freeze-thaw performance under the specific disaster degree. The initial stress damage of lightweight aggregate concrete was applied by repeated loading to simulate the disaster, and the relative dynamic elastic modulus was taken as the evaluation index to study the freezing-thawing performance of lightweight aggregate concrete with the initial damage degree of 0, 0.05, 0.12, 0.19 and 0.27, respectively. The grey system theory was introduced into concrete frost resistance durability study, the relative dynamic elastic modulus measured data was used to build prediction model of freeze-thaw resistance of stress-damaged lightweight aggregate concrete based on GM(1,1), and corresponding comparation with the revised Loland concrete damage model and accuracy analysis was performed; The GM(1,1) prediction model was used to evaluate the effect of initial stress damage on the frost resistance durability of lightweight aggregate concrete and predict its frost resistance life. The results showed that the initial stress damage could accelerate the freeze-thaw performance degradation of lightweight aggregate concrete, and the higher the initial stress damage degree was, the faster the deterioration rate would be. The average relative error of GM(1,1) model was less than 4.5% under each initial damage degree, and the prediction accuracy of GM(1,1) model was generally higher than that of the revised Loland model. Lightweight aggregate concrete had a good freezing-thawing resistance, and its freezing-thawing resistance life could reach 45 years in central and western Inner Mongolia. When the initial damage degree was 0.05, 0.12, 0.19 and 0.27, the freezing-thawing resistance life was shortened to 30 years, 25 years, 17.5 years and 10 years, respectively. The prediction model of freeze-thaw performance of stress-damaged lightweight aggregate concrete based on GM(1,1) could accurately evaluate the whole process of freeze-thaw performance of the damaged lightweight aggregate concrete after disaster, which provided theoretical basis for guiding the engineering practice of lightweight aggregate concrete in cold and dry regions of north China.

In order to solve the problem of low computational efficiency of adaptive beamforming algorithms in ultrasonic imaging, an adaptive beamforming algorithm for ultrasonic array with the combination of spatial sampling and coherence factor was proposed. The maximum decimation factor with different numbers of array elements was deduced according to the beam pattern. The sparse echo data was obtained by spatially sampling the whole array element data using the maximum decimation factor. Therefore, the amount of data used for beamforming was greatly reduced. Taking the spatial sampling data as the input of a beamformer and constructing the covariance matrix as Toeplitz matrix, the adaptive weights of the sampling data were obtained according to the principle of minimum variance. Then, the adaptive weights were modified by introducing the coherence factor to highlight the effective information of the sampling data. Under the case of unequal data and spatial sampling data, the proposed algorithm, minimum variance algorithm and minimum variance algorithm combined with coherence factor were used to simulate the imaging of cracks and cross-drilled holes respectively. The results show that: for unequal data, the imaging quality of the proposed algorithm is between the other two algorithms; in terms of imaging time, compared with the other two algorithms, the average imaging time of the proposed algorithm is reduced by more than 85%. For the same spatial sampling data, the imaging quality of the proposed method is better than the other algorithms; in terms of imaging time, compared with the other two algorithms, the average imaging time of the proposed algorithm is reduced by more than 65%.