Multi-criteria guided deep learning for 3D microstructure reconstruction of cementitious materials from a single 2D image: application to transport properties-Reference-Cited by-同舟云学术

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Multi-criteria guided deep learning for 3D microstructure reconstruction of cementitious materials from a single 2D image: application to transport properties

Published:2024-10 Issue: Volume:447 Page:138164
ISSN:0950-0618
Container-title:Construction and Building Materials
language:en
Short-container-title:Construction and Building Materials

Author:

Xu Wenxiang,Wu Haotian,Sun Qian,Han Yu,Jiang Jinyang,Liu Jiaping

Funder

Science Fund for Distinguished Young Scholars of Jiangsu Province

National Major Science and Technology Projects of China

National Natural Science Foundation of China

State Key Laboratory of High Performance Civil Engineering Materials

Publisher

Elsevier BV

Reference65 articles.

1. Pore crystallization and expansion of cement pastes in sulfate solutions with and without chlorides;Ran;Cem. Concr. Res.,2023

2. Representative elementary volume (REV) of cementitious materials from three-dimensional pore structure analysis;Yio;Cem. Concr. Res.,2017

3. Porous media: geometry and transports;Adler,2013

4. Development of pore structure, moisture sorption, and transport properties in fly ash blended cement-based materials;Linderoth;Constr. Build. Mater.,2020

5. Performance-based approaches for concrete durability: state of the art and future research needs;Beushausen;Cem. Concr. Res.,2019

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