Journal Published Online: 11 January 2022
Volume 11, Issue 1

An Investigation on Bacterial Air-Entrained Concrete Permeability using Statistical Modeling

CODEN: ACEMF9

Abstract

In recent decades, bacterial self-healing concrete has gradually reached its deserved popularity because of its ecofriendly ability to heal cracks spontaneously. This study investigates the simultaneous effects of several factors such as air voids, bacterially impregnated mix water, curing environment, and surface treatment on the permeability of concrete. For this study, experiments were conducted using water absorption, water permeability, and carbonation depth as the response variables. The experiments were performed within the framework of a fractional factorial split-plot design, which led to a decrease in the number of experiments without loss of precision. For this purpose, 126 cubic specimens of different dimensions were cast. The statistical random effect model was run to study the significant relationships between the factors and the response variables. Results revealed that the use of bacteria in the mixed water led to significantly reduced water absorption (about 19 %) and carbonation depth under acidic conditions (about 32 %). Furthermore, water absorption decreased with increasing air voids in the bacteria-laden air-entrained concrete specimens up to 31 % and 50 % for the specimens with 5 and 8 % air voids, respectively, suggesting that air voids probably protected the bacteria from exposure to the deadly alkaline and dry conditions inside the concrete.

Author Information

Parastegari, Niloofar
Department of Civil Engineering, Isfahan University of Technology (IUT), Isfahan, Iran Department of Civil and Environmental Engineering, Oklahoma State University (OSU), Stillwater, OK, USA
Mostofinejad, Davood
Department of Civil Engineering, Isfahan University of Technology (IUT), Isfahan, Iran
Poursina, Davood
Department of Agricultural Economics, Oklahoma State University (OSU), Stillwater, OK, USA
Pages: 16
Price: $25.00
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Details
Stock #: ACEM20210010
ISSN: 2379-1357
DOI: 10.1520/ACEM20210010