Abstract
Desert sand is one of the current research hotspots in alternative materials for concrete aggregates. In the process of practical application, compressive strength is an essential prerequisite for studying other properties. Based on the current research situation, a prediction technology of compressive strength of desert sand concrete (DSC) is proposed based on an artificial neural network (ANN) and a particle swarm optimization (PSO). The technology is a prediction model that adjusts the network architecture by using the PSO method based on the ANN optimization model. Water-binder ratio, sand ratio, replacement rate of desert sand, desert sand type, fly ash content, silica fume content, air content, and slump were selected as the neural network’s inputs. The compressive strength data of 118 different combinations of influencing variables were tested to establish the dataset. The results show that the PSO method is efficient for the ANN in DSC compressive strength research. Furthermore, referring to this method, DSC is applied to the shotcrete of tunnels in construction engineering successfully, and the dust particle content during construction is evaluated.
Highlights
Growing infrastructure needs worldwide have created an unprecedented demand for concrete
If there are too many variables, the accuracy of artificial neural network (ANN) prediction would be significantly affected. erefore, we proposed an optimized ANN based on particle swarm optimization (PSO). e ANN and PSO can predict desert sand concrete (DSC)’s compressive strength under the combined action of 8 variables
3.12 27.3 184 305 Qualified 1.21 26.2 47.8 5.2 8.0 were used, with fineness modulus values of 0.27, 0.30, 1.03, and 0.57, respectively. e gradation curves of the manufactured sand and the desert sand are shown in Figure 2(a). e particle size of the desert sand was smaller than that of the fine sand, and the manufactured sand was medium sand. e mineral composition, as analyzed by X-ray diffraction (XRD), is shown in Figure 2(b). e four types of desert sand’s main mineral types and contents were almost the same as those of the river sand. ey were significantly different from the minerals in the manufactured sand, consisting of calcium carbonate calcite
Summary
Growing infrastructure needs worldwide have created an unprecedented demand for concrete. E current research on DSC mainly focuses on the physical and chemical properties of desert sand [9,10,11], the conventional properties of DSC [12,13,14,15,16,17,18,19], and ultra (very)fine aggregate concrete [20,21,22]. In these studies, the highfrequency research variables include replacement rate of desert sand, sand rate, etc. This study is a pioneering work for using the ANN and PSO in predicting primary DSC performance and trying to use DSC in tunnel shotcrete, which is of great significance to more engineering applications
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