Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

The ONIX model: a parameter-free multiscale framework for the prediction of self-desiccation in concrete

Pathirage, M., Bentz, D. P., Di Luzio, G., Masoero, E. and Cusatis, G. 2019. The ONIX model: a parameter-free multiscale framework for the prediction of self-desiccation in concrete. Cement and Concrete Composites 103 , pp. 36-48. 10.1016/j.cemconcomp.2019.04.011

[thumbnail of 828B86AB-3E80-4E06-B943-8CF7AEC7B785.pdf] PDF - Accepted Post-Print Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (7MB)


The traditional approach for predicting self-desiccation is to simulate hygro-mechanics directly at the macroscale and to provide hydration-related inputs via phenomenological constitutive models. This manuscript presents instead a novel method that consists of obtaining inputs to such constitutive relations from direct simulations of cement hydration at the microscale, using a state-of-the-art simulator, namely the Cement Hydration in Three Dimensions (CEMHYD3D). This allows avoiding lengthy calibrations from experimental data. The prediction capabilities of the proposed model are demonstrated using experimental data of self-desiccation relevant to about 50 different mix designs of concrete, mortar and cement paste, with water to cement ratios ranging from 0.20 to 0.68 and silica fume to cement ratios from 0.0 to 0.39. The mixes are characterized by various cement chemical compositions, particle size distributions and Blaine finenesses, and the experiments span numerous time scales, from one week up to two years.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Publisher: Elsevier
ISSN: 0958-9465
Date of First Compliant Deposit: 15 October 2021
Date of Acceptance: 12 April 2019
Last Modified: 06 Nov 2023 23:03

Citation Data

Cited 20 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item


Downloads per month over past year

View more statistics