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Mechanisms of Hydration and Setting of Ordinary Portland Cement in Simple and Complex Systems

Project Information

Project Abstract: 

The focus of this project was on clearly defining the causes of the onset and end of the induction period of alite, which controls set, strength, and subsequent microstructural development. The researchers simulated the presence of mineral and chemical admixtures by introducing aluminate and sulfate ions and organic retarders at ratios known to perturb normal hydration. They used new experimental methods capable of measuring chemical and microstructural changes on the nanometer to micron scale during hydration. The goal is to use this insight to improve the ability of the National Institute of Standards and Technology's (NIST’s) HydratiCA model to predict hydration kinetics and microstructure in the presence of supplementary cementitious materials, such as fly ash, slag, and metakaolin, as well as organic admixtures. This detailed understanding also will lead to improvement of the boundary nucleation and growth (BNG) model to permit prediction of hydration kinetics and setting behavior in a software tool that is powerful but simple enough to be used in the field.

Project Status: 
Project Funding Amount (Contract Award Amount): 
Start Date: 
Thursday, July 5, 2012
End Date: 
Sunday, June 4, 2017
Public Access Plan: 
FHWA AMRP Program: 
Exploratory Advanced Research
Project Outputs: 

This project's breakthroughs in the measurement and analysis of concrete materials are matched by modeling advances that help researchers better design and interpret experiments. The resulting new understanding of hydration mechanisms and development has been used by the project researchers to improve the HydratiCA model developed by NIST, which is currently the most sophisticated tool for simulating hydration. The improved model will be able to generate both microscale and macroscale predictions of hydration behavior under a much wider range of conditions than previously possible. Researchers also have developed SimBNG, a boundary nucleation and growth model that is powerful but also fast enough and simple enough to be used in the field.