Machine-made sand instead of natural sand has become an inevitable choice for the sustainable development of the concrete industry. Orthogonal experiment and grey correlation analysis were used to investigate the performance of machine-made tuff sand concrete. The optimal concrete mix ratio of machine-made sand was obtained by orthogonal test and its working performance was verified. Grey correlation analysis was applied to compare the factors affecting the mechanical properties of the machine-made sand concrete. The test results show that the sand rate has the greatest degree of influence on slump and slump expansion. The mineral admixture has the greatest effect on the 7-day compressive strength of the concrete. Additionally, the water–cement ratio has the greatest influence on the 28-day compressive strength. The mechanical and working properties of the machine-made sand concrete reach the optimum condition when the mineral admixture is 20%, the sand rate is 46%, the stone powder content is 10% and the water–cement ratio is 0.30. Comparing different fine aggregate concretes of similar quality, we conclude that the mechanical and working properties of tuff sand concrete and limestone sand concrete and river sand concrete are similar. The compressive strengths of the mechanism concrete show the greatest correlation with roughness and the least correlation with stone powder content. The stone powder content has almost no effect on the compressive strength of concrete when the stone powder content does not exceed a certain range. The results of the study point out the direction for the quality control of concrete with machine-made sand.
Thermal cracking in pile caps caused by concrete hydration heat will affect the safety and durability of long-span cable-stayed bridges. Therefore, effective prediction and control of concrete bridges hydration heat has been a challenging problem. In this study, the temperature of hydration heat in mass concrete pile caps belonging to a long-span cable-stayed bridge in China were monitored. Then, we adopt support vector machine regression (SVR) to establish the correlation between influencing variables and the temperature of hydration heat. The monitoring data are used to train to realize the short-term prediction of concrete temperature. The predicted results show that the SVR has a high accuracy, and the deviation between the prediction results and the measured values is quite small. The prediction performance of SVR for temperature of hydration heat of mass concrete is obviously better than that of BP neural network. The SVR prediction model can predict the temperature of 2-3 days with high accuracy. Based on the prediction results, temperature control method can be taken in advance to reduce the possibility of thermal cracks, which is of great significance for the safety and durability of actual engineering construction.INDEX TERMS Mass concrete, heat of hydration, support vector machine, regression model, temperature prediction.
The rapid development of highway engineering has made slope stability an important issue in infrastructure construction. To meet the needs of green vegetation growth, ecological recovery, landscape beautification and the economy, long-term monitoring research on high-slope micrometeorology has important practical significance. Because of that, we designed and created a new slope micrometeorological monitoring and predicting system (SMMPS). We innovatively upgraded the cloud platform system, by adding an ARIMA prediction system and data-fitting system. From regularly sensor-monitored slope micrometeorological factors (soil temperature and humidity, slope temperature and humidity, and slope rainfall), a data-fitting system was used to fit atmospheric data with slope micrometeorological data, the trend of which ARIMA predicted. The slope was protected in time to prevent severe weather damage to the slope vegetation on a large scale. The SMMPS, which upgrades its cloud platform, significantly reduces the cost of long-term monitoring, protects slope stability, and improves the safety of rail and road projects.
In order to study the protection performance of silane coating on in-service concrete structures in a sulfate environment, we collect concrete samples in the field to simulate the concrete erosion process by accelerated erosion with wetting–drying cycles. We place the samples into protected, exposed and control groups corresponding to a corrosive environment with silane protection, corrosive environment without protection and general environment for three different service conditions. A combination of ultrasonic velocimetry, CT (Computed Tomography) scan imaging, NMR (Nuclear Magnetic Resonance) pore structure analysis, strength testing and other methods are used to analyze the strength, ultrasonic wave velocity, pore structure and other characteristics of the specimens during sulfate erosion. Based on the test results, the protective effect of silane coating on concrete structures under sulfate attack is quantitatively analyzed, and an index for judging the damage rate of specimens is proposed to quantitatively analyze the protective effect of silane coating. The research results show that the damage of the concrete structure under silane protection in a sulfate-attack environment can be reduced by more than 50%; its integrity damage index and strength damage index are easily affected by the location of local defects, which leads to a decrease in the protection efficiency of the surface silane coating.
Machine-made sand is gradually replacing natural sand to achieve sustainable development. Experimental studies and gray-correlation analysis were used to study the properties of tunnel slag machine-made mortar and concrete. The properties of machine-made mortar with different stone powder content were analyzed through experiments. By analyzing the performance of machine-made sand concrete with equal amounts of cement replaced by stone powder, the optimum replacement ratio is obtained. Gray-correlation analysis was used to compare the degree of influence of fineness modulus and stone powder content on the performance of concrete. Scanning electron microscopy (SEM) and X-ray diffractometry (XRD) were used to analyze the microstructure of tunnel slag sand concrete. The test results showed that the flexural and compressive strengths of the machine-made sand concrete were greater than the standard sand with the same stone powder content. The 28-day flexural and compressive strengths had a maximum difference of more than 30%. The best stone powder content of the machine-made mortar is in the range of 5% to 8%. When the replacement cement content of stone powder is about 6%, the mechanical and working properties of machine-made sand concrete achieve the optimal state. The lower the stone powder content, the closer the mechanical and working properties of machine-made sand concrete and river sand concrete. The correlation between the performance of machine-made sand concrete and fineness modulus is the largest. When the stone powder content is low, it has almost no effect on the compressive strength of concrete. The results point out the direction for the quality control of tunnel slag machine-made sand concrete.
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