Mechanisms of recycled fine aggregates with different saturation degrees on mechanical properties and autogenous shrinkage behaviour of ultra-high performance concrete
Source abstract
Abstract
Recycled fine aggregate (RFA) extracted from construction and demolition (C&D) waste is characterized by high porosity, strong water absorption, and significant water release. It can not only mitigate the excessive autogenous shrinkage of ultra-high-performance concrete (UHPC), but also alleviate the over-exploitation of quartz sand. Therefore, this study proposes a new economic building material for preparing UHPC. It uses RFA with different saturation degrees (0 %, 50 %, and 100 %) to replace quartz sand (QS) and investigates the workability, compressive strength, autogenous shrinkage, resistance to chloride ion penetration, and microstructure of UHPC. The findings indicate that the degree of saturation and content of RFA are the key factors that influence the compressive strength and autogenous shrinkage of UHPC. The early autogenous shrinkage of UHPC is significantly reduced as the saturation degree and content of RFA increase, while the compressive strength is not obviously affected. Overall, using RFA with a 20 % replacement ratio and 100 % saturation degree is beneficial for mitigating autogenous shrinkage and enhancing the 28-day compressive strength. Compared with UHPC without RFA, the 28-day compressive strength increased by 16.6 %, while its 7-day autogenous shrinkage decreased by 90.47 %. Furthermore, the incorporation of 20 % saturated RFA shows the best internal curing effect, which improves the hydration level and reduces the porosity of UHPC. This study successfully provides a practical method for preparing environmentally friendly and low-shrinkage UHPC using RFA with different saturation degrees.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Innovative concrete reinforcement materials · Concrete and Cement Materials Research · Concrete Properties and Behavior
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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