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Novel LCA-centric mix design approach for alkali-activated EAF slag with hybrid optimization techniques

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dc.contributor.author Lahoti, Mukund
dc.contributor.author Pradhan, Subhasis
dc.date.accessioned 2025-04-17T07:15:42Z
dc.date.available 2025-04-17T07:15:42Z
dc.date.issued 2024-12
dc.identifier.uri https://link.springer.com/article/10.1007/s11356-024-35731-3
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/18661
dc.description.abstract This study presents an innovative life cycle assessment (LCA)-centric approach for optimizing the mix design of alkali-activated materials (AAMs) as sustainable alternatives to ordinary portland cement (OPC). The AAMs are developed using electric arc furnace slag (EAFS) and fly ash as precursors. The environmental performance is evaluated using the ReCiPe midpoint methodology, considering both mass and economic allocation methods. The results indicate that global warming potential and terrestrial ecotoxicity are the primary environmental impact categories across all mixes and allocation scenarios. A Taguchi-based hybrid optimization technique, integrating gray relational analysis (GRA) and analytical hierarchical process (AHP)-weighted GRA, is employed to determine the optimal mix design based on fresh properties, mechanical performance, durability, and sustainability indices. The AHP-GRA analysis reveals that mixes containing at least 50% EAFS perform better than OPC in terms of overall sustainability. A blend of 75% EAFS and 25% fly ash is recommended for achieving the best balance between performance and environmental impact, offering a promising alternative for sustainable construction practices. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Civil engineering en_US
dc.subject Life cycle assessment (LCA) en_US
dc.subject LCA-centric approach en_US
dc.subject Alkali-activated materials (AAMs) en_US
dc.subject Ordinary Portland Cement (OPC) en_US
dc.title Novel LCA-centric mix design approach for alkali-activated EAF slag with hybrid optimization techniques en_US
dc.type Article en_US


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