Optimized design method for underwater anti-dispersive cement-based materials based on multi-scale coupling of molecular dynamics and machine learning

Water flow in underwater grouting causes severe slurry dispersion, compromising cement-based material stability. Traditional empirical mix design cannot simultaneously optimize fluidity, anti-dispersion performance, and mechanical strength. To solve this, we propose a multi-scale framework combining...

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Detalles Bibliográficos

Autores principales:	Lingfeng Zhao, Zengguang Xu, Xican Cui, Jingxin Pan, Fan Zhang, Zimeng Chen, Cheng Cao, Junrui Chai
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Elsevier 2026-04-01
Colección:	Developments in the Built Environment
Materias:	Molecular Dynamics (MD) Machine learning (XGBoost–SHAP) Anti-dispersion cementitious materials Interfacial interaction mechanisms Diffusion and hydration dynamics Multi-scale design framework
Acceso en línea:	http://www.sciencedirect.com/science/article/pii/S266616592600061X
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