An Optimum Mix Design of High Strength Concrete using Genetic Algorithms

High-strength concrete (HSC) is a highly complex and evolving construction material. Careful selection of constituent materials must be employed to successfully proportion HSC mixtures. A guide for proportioning HSC by the American Concrete Institute (ACI) is available but the guide provides only a general idea of the proportions of the various components for HSC production. Presently, batching companies produce different trial mixes using the ACI guide and some trial and error considering the observed effect of each constituent material to the strength development of HSC in order to attain a target concrete strength. This method, however, requires plenty of mix design experimentation that is costly and time consuming. Through the years, trial mixes of HSC of various strengths have been compiled by batching companies. These trial mix data may be useful in deriving optimum mix designs of HSC.

This study explored the use of genetic algorithms (GA) in deriving optimum mix designs for HSC using data collected from a batching company. Three hundred ninety-six (396) HSC trial mixtures were analyzed to derive empirical equations for strength and slump which were adapted as GA fitness functions. The GA program generated optimum preliminary designs for concrete strengths in the range of 7,000 psi (48 MPA) to 10,000 psi (69 MPa) depending on the type of sand and whether silica fume is present or not. In-situ adjustments for the dosage of admixture and amount of water were applied to the GA preliminary mix designs to account for the moisture content and absorption of the aggregates. These mix designs were verified by implementing the mixture with in-situ adjustments and testing the concrete cylinders for compressive strength. The target values for strength and slump were obtained. Cost comparison also showed that the GA-HSC mix designs yielded lower material cost than the mix designs provided by the company indicating a near optimal and more economical mix design.

This is the undergraduate thesis of Iris Mae M. Malabatuan, Bertrand B. Teodosio and Analyn C. Yee Concepcion at Department of Civil Engineering, De La Salle University, Manila. CE faculty, Engr. Alden Paul Balili, who also completed his MSCE thesis on GA with application to RC Frames was a co-adviser of the group and his GA program was used in the thesis. The thesis group is a finalist for the 2011 Gold Thesis Award for the Structural Engineering Division.

ACKNOWLEDGEMENT:

The group members and the advisers wish to express their gratitude to D. M. Consunji, Inc. and its current president, Mr. Jorge A. Consunji, for granting the request to obtain concrete mix design data.