In the quest for sustainable construction materials, researchers are increasingly turning to waste products as valuable resources. A recent study led by Danial Nasr from the Department of Civil Engineering has made significant strides in this area, demonstrating how waste ceramic aggregates and rice husk ash can enhance the performance of self-compacting mortar. The research, published in the journal *Advances in Civil Engineering* (translated as “Advances in Civil Engineering”), not only highlights the potential of these materials but also showcases the power of artificial intelligence in predicting material properties.
Nasr and his team explored the combined use of rice husk ash (RHA) and ceramic waste (CW) as partial replacements for natural sand in asphalt mixtures. “The idea was to find a sustainable way to utilize these waste materials, which are often discarded, and to see how they could improve the mechanical properties of asphalt,” Nasr explained. The team conducted laboratory tests to evaluate the Marshall stability, flow, density, and void properties of the mixes.
The results were promising. The mixture containing 50% RHA and CW filler achieved the highest Marshall stability (9.6 kN) and the lowest flow value (2.1 mm) among all investigated mixtures. However, higher RHA content (75%) led to a decrease in stability due to the reduced formation of C─S─H gel and a less dense microstructure. “This indicates that there is an optimal level of replacement for these materials,” Nasr noted.
What sets this study apart is the use of advanced artificial intelligence techniques to predict the mechanical performance of the mixtures. The team developed two AI-based predictive models: support vector regression (SVR) and adaptive neuro-fuzzy inference system (ANFIS). The ANFIS model yielded the best predictive performance with an R2 value of 0.96 and a root mean square error (RMSE) of 0.21, indicating excellent agreement with the experimental results.
The implications of this research are significant for the construction industry. “AI-assisted mixture design can serve as a powerful tool to support the development of sustainable pavement materials,” Nasr said. By leveraging these technologies, companies can reduce their environmental impact while maintaining high performance standards.
The study also opens up new avenues for future research. As Nasr points out, “The combined use of RHA and CW can significantly improve the mechanical performance of asphalt mixtures up to an optimal replacement level.” This suggests that further exploration of these materials and their interactions could lead to even more sustainable and efficient construction practices.
In an industry increasingly focused on sustainability and efficiency, this research offers a glimpse into the future of construction materials. By harnessing the power of waste products and advanced AI techniques, the construction sector can move towards a more sustainable and innovative future. As Nasr and his team continue to push the boundaries of what’s possible, the industry can look forward to even more groundbreaking developments on the horizon.