Degree Type


Date of Award


Degree Name

Doctor of Philosophy


Civil, Construction, and Environmental Engineering

First Advisor

Kejin Wang


Concrete rheology is important because it affects the workability and uniformity of fresh concrete as well as the properties of the hardened concrete. In this dissertation, new models for predicting mortar and concrete rheological properties were developed;The present study includes both experimental and modeling work. In the experimental study, mortar and concrete specimens were prepared with consideration of three factors: paste or mortar rheology, aggregate properties, and aggregate content. The aggregate properties were characterized with the uncompacted void content and friction angle. Effects of these aggregate properties on mortar and concrete rheology were studied using a Brookfield and portable IBB rheometer, respectively. Using the artificial neural network as a tool to analyze the test data, the relative degree of importance of the factors that influence mortar and concrete rheological behavior were evaluated, and the important factors were then considered in the proposed models. The experimental results indicated that aggregate with low uncompacted void content generally provided the concrete with low yield stress and viscosity, while aggregate with high friction angle generally resulted in high yield stress and viscosity;In the modeling study, concrete was considered as a two-phase material, consisting of mortar and coarse aggregate. Mortar and concrete rheological behavior was assumed mainly controlled by (1) the excess paste/mortar thickness of fine/coarse aggregate, and (2) the friction between the aggregate particles. The excess paste/mortar thickness and aggregate friction were calculated and used to develop functions that relate to mortar and concrete rheology. Statistical analyses were performed on the test data to obtain specific relationships between the concrete rheology parameters and the paste/mortar properties as well as the excess paste/mortar thickness in the concrete. The modeling results demonstrated that the predicted concrete rheological parameters had very good correlations with the measured results. It is expected that the developed models can be used not only for concrete rheology prediction but also for designing concrete mixtures with improved rheology.



Digital Repository @ Iowa State University,

Copyright Owner

Jiong Hu



Proquest ID


File Format


File Size

193 pages