Due to the benefits of pollution reduction, energy saving, and recycling of resources associated with the recycled concrete, together with the apparent thermal storage thermal insulation yield of expandable polystyrene (EPS) template, the heat transfer dynamics of their combination has become a contemporary study topic. In this research work, an investigation of the heat transfer coefficient (U) of EPS template recycled-concrete shear wall has been carried out. Four different concrete mixtures shear wall samples having different insulation types were developed for the purpose of quantifying their thermal outputs. Both temperature (T) and humidity (H) affection to thermal conductivity coefficient (λ) of reinforced concrete and the EPS template were investigated, correspondingly. The λ0°C (relative variation for a 0°C of temperature variation in T) of cement mortar, recycled-concrete shear wall, and ordinary concrete shear wall were measured being 0.7526, 1.2463, and 1.3750 W·m−1·K−1, respectively. And the λ calculation of EPS was carried out being 0.0396 W·m−1·K−1. A corrected calculation method was put forward to application in practical work that could reflect the real U value in a more precise manner. These results brought to light the fact that the heat preservation output of recycled-concrete shear wall posed to be comparatively more improved than that of ordinary concrete shear wall. We put forth the suggestion for the use of corrected calculation method in the calculation and analysis of U of EPS template recycled-concrete composite shear wall in the climatic conditions of Beijing. The results revealed the fact that the U of EPS template recycled-concrete shear wall was dominantly controlled by the change of thermal conductivity changes of EPS template. The monthly mean U increased with increasing Tout and decreased with decreasing Tout. The smaller the U of the enclosure wall was, the better the thermal stability of the wall was experienced.
Modified Damage Index Calculation Method for Frame-Shear Wall Building Considering Multiple Demand Parameters
