A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
AI-Assisted optimisation of green concrete mixes incorporating recycled concrete aggregates
Highlights The MOO of RAC mix design is proposed using data-driven CS modelling. Environmental and production costs are targeted to achieve sustainable RAC. The proposed framework provides efficient solutions in a cost-effective manner.
Abstract Maximising the content of supplementary cementitious materials as a partial replacement for Portland cement and using recycled concrete aggregates as a full or partial replacement for coarse aggregates are among the widely adopted strategies in the design of green concrete. However, the synergetic implications of adopting both approaches on concrete properties add complexity to the design of green concrete mixes. This paper proposes a novel AI-based multi-objective optimisation framework addressing the lack of a systematic method to formulate these concretes and solves the common multi-objective mix design problems. The framework is developed for the mix proportioning of green concrete mixes containing recycled concrete aggregates and commonly used supplementary cementitious materials while considering the desired compressive strength. The proposed optimisation model leverages a dataset of about 2,120 mixes and employs an extreme gradient boosting machine to model the compressive strength requirements as a mechanical constraint throughout the optimsiation process. Moreover, a set of key environmental objectives, including minimising global warming, acidification, fossil fuel depletion potentials, and the cost of production, are targeted. The effectiveness of the framework is validated through case studies across different strength ranges. The results indicate a significant improvement in environmental sustainability indicators, including a 19.6% and 21.6% reduction in global warming and acidification potentials, besides considerable cost savings of up to 23.7% without compromising the mechanical performance of concrete.
AI-Assisted optimisation of green concrete mixes incorporating recycled concrete aggregates
Highlights The MOO of RAC mix design is proposed using data-driven CS modelling. Environmental and production costs are targeted to achieve sustainable RAC. The proposed framework provides efficient solutions in a cost-effective manner.
Abstract Maximising the content of supplementary cementitious materials as a partial replacement for Portland cement and using recycled concrete aggregates as a full or partial replacement for coarse aggregates are among the widely adopted strategies in the design of green concrete. However, the synergetic implications of adopting both approaches on concrete properties add complexity to the design of green concrete mixes. This paper proposes a novel AI-based multi-objective optimisation framework addressing the lack of a systematic method to formulate these concretes and solves the common multi-objective mix design problems. The framework is developed for the mix proportioning of green concrete mixes containing recycled concrete aggregates and commonly used supplementary cementitious materials while considering the desired compressive strength. The proposed optimisation model leverages a dataset of about 2,120 mixes and employs an extreme gradient boosting machine to model the compressive strength requirements as a mechanical constraint throughout the optimsiation process. Moreover, a set of key environmental objectives, including minimising global warming, acidification, fossil fuel depletion potentials, and the cost of production, are targeted. The effectiveness of the framework is validated through case studies across different strength ranges. The results indicate a significant improvement in environmental sustainability indicators, including a 19.6% and 21.6% reduction in global warming and acidification potentials, besides considerable cost savings of up to 23.7% without compromising the mechanical performance of concrete.
AI-Assisted optimisation of green concrete mixes incorporating recycled concrete aggregates
Zandifaez, Peyman (author) / Asadi Shamsabadi, Elyas (author) / Akbar Nezhad, Ali (author) / Zhou, Hongyu (author) / Dias-da-Costa, D. (author)
2023-05-16
Article (Journal)
Electronic Resource
English
Performance of Bituminous Mixes Containing Emulsion-Treated Recycled Concrete Aggregates
| British Library Online Contents | 2018
Frost-Resistance of Concrete Incorporating Aggregates Made of Recycled Concrete
| British Library Conference Proceedings | 1998