Machine learning can predict setting behavior and strength evolution of hydrating cement systems-Reference-Cited by-同舟云学术

Machine learning can predict setting behavior and strength evolution of hydrating cement systems

Published:2019-08-06 Issue:1 Volume:103 Page:480-490
ISSN:0002-7820
Container-title:Journal of the American Ceramic Society
language:en
Short-container-title:J Am Ceram Soc

Author:

Oey Tandré¹^ORCID,Jones Scott²,Bullard Jeffrey W.²^ORCID,Sant Gaurav¹³⁴⁵

Affiliation:

1. Laboratory for the Chemistry of Construction Materials (LC²), Department of Civil and Environmental Engineering University of California Los Angeles CA USA

2. Engineering Laboratory National Institute of Standards and Technology Gaithersburg MD USA

3. Institute for Carbon Management University of California Los Angeles CA USA

4. Department of Materials Science and Engineering University of California Los Angeles CA USA

5. California Nanosystems Institute University of California Los Angeles CA USA

Funder

Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles

Federal Highway Administration

National Institute of Standards and Technology

National Science Foundation

Publisher

Wiley

Subject

Materials Chemistry,Ceramics and Composites

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jace.16706

Reference31 articles.

1. Mechanisms of cement hydration

2. Characterization and Modeling of Pores and Surfaces in Cement Paste

3. Modeling and simulation of cement hydration kinetics and microstructure development

4. Modeling of strength of high-performance concrete using artificial neural networks

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