Machine learning optimized dry lean geopolymer concrete with reclaimed asphalt pavement for sustainable pavement applications

Abstract This study develops a process-based optimization strategy for dry lean geopolymer concrete (DLGC) using reclaimed asphalt pavement (RAP) material via response surface methodology (RSM) and machine learning (ML) approaches. A Box–Behnken design with 156 experimental runs considered six param...

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Autori principali:	M. Abhay, B. Manjunatha, Nagaraj M. Tattien, H. T. Avinash, Kalappa Sutar, SKrishna Rao
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Springer 2026-03-01
Serie:	Discover Sustainability
Soggetti:	Geopolymer concrete Reclaimed asphalt pavement Response surface methodology Machine learning Sustainable construction Mix optimization
Accesso online:	https://doi.org/10.1007/s43621-025-02447-4
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