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