| Title |
Predicting the Strength of Recycled Aggregate Concrete |
| Authors |
Choi Hee-Bok ; Kim Gwang-Hee ; Kang Kyung-In |
| Keywords |
Concrete compressive strength ; Recycled concrete ; Recycled aggregates ; Artificial neural networks ; Maturity method |
| Abstract |
Testing of concrete compressive strength is performed on the 28th day after concrete placement. If the test result does not satisfy the required compressive strength, it means that it is so late to make improvements compressive strength. Therefore, the compressive strength estimation before the placement of concrete is highly desirable. In the compressive strength estimation of concrete on the 28th day, it is generally used maturity method that is utilized in strength estimation of normal concrete of existent. But, maturity method does not reflect special quality of recycled aggregate concrete, because it is made up of mathematical formula from specialists' experience about normal concrete. Therefore, this research gropes new compressive strength estimation method that can reflect enough special quality of recycled aggregate concrete. The collected experiment data of existing recycled aggregate concrete and utilized artificial neural networks as tool for estimating the compressive strength of recycled aggregate concrete. This research is to compare artificial neural networks with maturity method in estimating the compressive strength of recycled aggregate concrete. |