Editorial - Intelligently designing cement and concrete through data analytics

Author:

Washburn Newell R.,Kurtis Kimberly E.

Publisher

Elsevier BV

Subject

General Materials Science,Building and Construction

Reference13 articles.

1. Advancing cement-based materials design through data science approaches;Rios;RILEM Tech. Lett.,2021

2. Deep learning to predict the hydration and performance of fly ash-containing cementitious binders;Han;Cem. Concr. Res.,2023

3. Literature-based data on pore solution compositions of cementitious systems;Albert;ETH Zurich Res. Collect.,2022

4. Taihao Han; Rohan Bhat; Sai Akshay Ponduru; Amit Sarkar; Jie Huang; Gaurav Sant; Hongya Ma; Narayanan Neithalath; Aditya Kumar. Supplementary Information: Deep Learning to Predict the Hydration and Performance of Fly Ash-Containing Cementitious Binders, https://ars.els-cdn.com/content/image/1-s2.0-S0008884623000054-mmc1.pdf Last accessed January 29, 2024.

5. Tianjie Zhang, RheologyNet: A Physics-Informed Neural Network Solution to Evaluate the Thixotropic Properties of Cementitious Materials, Software code, https://github.com/tjboise/RheologyNet Last accessed January 29, 2024.

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