Air void clustering in concrete

Date

2014-08-01

Journal Title

Journal ISSN

Volume Title

Publisher

Kansas State University

Abstract

Air void clustering around coarse aggregate in concrete has been identified as a potential source of low strengths in concrete mixes by several Departments of Transportation around the country. Research was carried out to (1) develop a quantitative measure of air void clustering around aggregates, (2) investigate whether air void clustering can be reproduced in a laboratory environment, (3) determine if air void clustering can blamed for lower compressive strengths in concrete mixes, (4) and identify potential factors that may cause clustering. Five types of coarse aggregate and five different air entraining agents were included in the laboratory study to see if aggregate type or chemical composition of air entraining agent directly relates to air void clustering. A total of 65 mixes were made, implementing the frequently used technique of retempering that has been previously associated with air void clustering around aggregates. Compressive strength specimens as well as samples for hardened void analysis were made. Compressive strength at 7 and 28 days was determined and the automated hardened void analysis (including a new method of clustering evaluation) was performed on all samples. It was found that it is possible to reproduce air void clustering in laboratory conditions. However, the results have shown that retempering does not always cause air void clustering. It was also observed that air void clustering is not responsible for a decrease in compressive strength of retempered concrete as neither aggregate type nor chemical composition of air entraining agent had a significant impact on severity of void clustering around coarse aggregate particles. It was also found that the total air content and an inhomogeneous microstructure and not air void clustering were responsible for lower strengths.

Description

Keywords

concrete, cement, air void analysis, air void clustering, image processing

Graduation Month

August

Degree

Master of Science

Department

Department of Civil Engineering

Major Professor

Kyle A. Riding

Date

2014

Type

Thesis

Citation