The most significant difference between recycled and natural concretes lies in aggregates. The performance of recycled coarse aggregates directly affects the characteristics of recycled concrete. Therefore, an in-depth study of aggregate characteristics is of great significance for improving the quality of recycled concrete. Based on the coarse aggregate content, maximum aggregate size, and aggregate shape, this study uses experiments, theoretical analysis, and numerical simulation to reveal the impact of aggregate characteristics on the mechanical properties of recycled concrete. In this study, we selected the coarse aggregate content, maximum aggregate size, and the aggregate shape as design variables to establish the regression equations of the peak stress and elastic modulus of recycled concrete using the response surface methodology. The results showed that the peak stress and elastic modulus of recycled concrete reach the best when the coarse aggregate content is 45%, the maximum coarse aggregate size is 16 mm, and the regular round coarse aggregates occupy 75%. Such results provide a theoretical basis for the resource utilization and engineering design of recycled aggregates.

Recently, the use of the temperature tracer method has attracted a great deal of attention to study the dam leakage. Accurate estimation of temperature variations inside the dam is critical, and the task can be achieved by identifying which variables play more important roles in the hydrothermal coupling model (HTCM). In the present study, the HTCM of an embankment dam is defined based on the thermal conductivity model proposed by Lu et al. (2007). The thermal conductivity model needs several input parameters, many of which are usually determined by pedotransfer functions, which may introduce a certain degree of uncertainty. Using the Morris method, the embankment dam of a reservoir, located in Shaanxi province of China, was chosen as the case study to investigate the sensitivity of each parameter of the HTCM on the temperature field of the embankment dam. The sensitivity analysis showed that the hydraulic conductivity (K_s) of HTCM has the highest effect on the dam temperature field. On the other hand, the saturated water content (θ_s), residual water content (θ_r), and porosity (n) only slightly influence the temperature estimation of the model. Accordingly, the effects of these three parameters on the heat conduction and the subsequent temperature field of the dam can be neglected. Results of this study showed that the model correction workload can be substantially reduced. Hence, the efficiency of the model correction procedure leads to reasonable selection of decision parameters and can be significantly improved by reducing the number of these parameters for the HTCM of the embankment dam.