A Comprehensive Dataset for Validating Predictive Models of Young's Modulus Evolution during Cement Hydration

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Authors: guodong Cheng, Rong Zhao, Lei Chen, Tao, Qian, Haoguang Wei, Kuizhen Fang
Cited by: 0

Abstract

A systematically integrated and standardized dataset was present, designed to provide benchmark data for developing and validating predictive models of the time-dependent mechanical properties of cementitious materials. All data underwent extraction, cleaning, and standardization, and were stored in a structured format for easy access and reuse. The dataset provides paired measurements of porosity and Young's modulus over hydration time, and can be used to evaluate the applicability of existing models, support multiscale numerical simulations, train data-driven models, and serve as a teaching case study.

Fields of Study & Subjects

Concrete and Cement Materials Research Concrete Properties and Behavior Innovative concrete reinforcement materials

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
5 February 2026
Document type
Dataset