Abstract
In order to study the quality control and evaluation methods of self-compacting concrete (SCC) pumping process in Shenzhen-Zhongshan Bridge and similar projects, sample test is performed on self-compacting concrete mixture collected from the pumping field of the E1-E4 steel shell immersed tube; Then a database base on relationship between the variation parameters and the target performance is established. On this basis, the Grey system theory is adopted to analyze the parameter sensitivity of the SCC pumping performance to the different kinds of variables. The results show that variables are related to target performance and some of the variables have a significant influence. Using the powerful data mining capability of support-vector machine and Bayesian statistical inference in the case of uncertain exact mathematical relationship between independent variables and dependent variables, implicit and explicit prediction models of variation of SCC pumping performance are respectively established by pumping distance, number of elbows, pumping time and environmental temperature as the control parameters. Finally, the comparisons between the measured data and calculation result prove that both models have good prediction accuracy and stability.
Highlights
The Shenzhen-Zhongshan Bridge is a world-class megaproject integrating “super-large span bridge-artificial island-undersea immersed tube tunnel-underwater interchange”
If the self-compacting concrete (SCC) the steel shell immersed tube tunnel project of the pumped on site can be used as the test object, its Shenzhen-Zhongshan Bridge, using the correlation corresponding performance indicators can be obtained, analysis method of gray system theory, combining the the correlation between the influencing parameters scientific problems of pumping performance indicators before and after on-site pumping and the pumping with modern data mining technology, the implicit and performance can be established, the quality control of explicit models between the key parameters and the SCC can be improved and guide subsequent tube section target performance are established respectively in order or the construction process of similar projects, the quality to provide references for the prediction and quality of pumping can be in better control
All data comes from the sampling test results of SCC pouring of E1-E4 tube sections in Shenzhen-Zhongshan Bridge, considering the influence of pumping distance, the number of elbows in the pumping pipe, the pumping time of the concrete in the pump pipe, and the environmental temperature on the pumping performance
Summary
The Shenzhen-Zhongshan Bridge is a world-class megaproject integrating “super-large span bridge-artificial island-undersea immersed tube tunnel-underwater interchange”. If the SCC the steel shell immersed tube tunnel project of the pumped on site can be used as the test object, its Shenzhen-Zhongshan Bridge, using the correlation corresponding performance indicators can be obtained, analysis method of gray system theory, combining the the correlation between the influencing parameters scientific problems of pumping performance indicators before and after on-site pumping and the pumping with modern data mining technology, the implicit and performance can be established, the quality control of explicit models between the key parameters and the SCC can be improved and guide subsequent tube section target performance are established respectively in order or the construction process of similar projects, the quality to provide references for the prediction and quality of pumping can be in better control. The prediction accuracy and The steel shell immersed tube section in algorithm robustness can be guaranteed Another type of Shenzhen-Zhongshan Bridge adopted SCC of C50 data mining technology that is different from machine strength class.
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