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3.2.12 Optimizing High-Performance Concretes Using Mixture Designs

Eric S. Lagergren

James J. Filliben

Lynne B. Hare

Statistical Engineering Division, ITL

Dale P. Bentz

Ken A. Snyder

Building Materials Division, BFRL

Marcia Simon

Federal Highway Administration (FHWA)

Optimizing high-performance concrete is currently more of an art than a science. Some guidelines are available for selecting optimal conditions, but no systematic approach is used to identify these conditions. As a result, trial and error or ``one-factor-at-a-time" designs are typically used to identify best mixtures. A collaboration is underway between the FHWA and NIST's Statistical Engineering and Building Materials Divisions to investigate the feasibility of using mixture design and analysis techniques for optimizing high-performance concrete. A second objective is to develop a World Wide Web service for users to design and analyze mixture experiments for optimizing concrete mixes.

In the first phase of this work, a laboratory experiment was conducted to study six mixture components: water, cement, fine and coarse aggregate, superplasticizer, and silica fume. The first four components produce concrete. The last two enhance specific properties yielding ``high-performance" concrete. The properties of interest are workability, air content, strength, and chloride ion permeability. Since the proportions of the six components were constrained to a subset of the full mixture space, standard Scheffé simplex designs could not be used. Instead, a modified distance-based design was used. First, a list of candidate design points was generated including all vertices, edge centroids, constraint plane centroids, and the overall centroid. The distance criterion selects points from the candidate list to cover the experimental region in a balanced manner, maximizing the minimum Euclidean distance between points. The modification is made to ensure that the design is capable of fitting a second-order Scheffé polynomial. Additional points were included to check the adequacy of the fitted model, estimate repeatability, and check for statistical control for a total of 36 design points.

The second phase of the project is to develop a Web service for users to optimize high-performance concretes. This service will assist users in constructing mixture designs and analyzing the resulting data. Since users may have limited knowledge of statistics, the focus will be on generating informative data using good experiment design techniques and graphical methods of analysis.

The lab experiment has been completed and properties are currently being measured. Data will be analyzed by fitting an appropriate model and graphically interpreting the model via response trace plots and contour plots on 3-component simplex projections.



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Date created: 7/20/2001
Last updated: 7/20/2001
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