Publications by authors named "Chenchen Luan"
Article Synopsis
- * The study creates a reliable model for predicting the compressive strength of FAGC and optimizes its mixture design to minimize CO2 emissions, utilizing advanced techniques like polynomial regression and ensemble learning.
- * An optimal FAGC mixture design program demonstrates a 16.7% reduction in CO2 emissions at 50 MPa compressive strength, and compared to PCC, FAGC achieves a 60.3% reduction in emissions, offering engineers practical tools for sustainable concrete design.
There have been a few attempts to develop prediction models of splitting tensile strength and reinforcement-concrete bond strength of FAGC (low-calcium fly ash geopolymer concrete), however, no model can be used as a design equation. Therefore, this paper aimed to provide practical prediction models. Using 115 test results for splitting tensile strength and 147 test results for bond strength from experiments and previous literature, considering the effect of size and shape on strength and structural factors on bond strength, this paper developed and verified updated prediction models and the 90% prediction intervals by regression analysis.
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