Discipline: Nanoscience
Subcategory: Materials Science
Session: 2
Room: Park Tower 8216
Anamarie Cotto-Ramos - University of Puerto Rico, Mayaguez Campus
Co-Author(s): Saylisse Dávila, University of Puerto Rico, Mayaguez Campus Wandaliz Torres-García, University of Puerto Rico, Mayaguez Campus
While concrete is a construction material widely used around the world, its large carbon footprint and depletion of natural non-renewable aggregates has long instigated the need for alternative concrete mixtures. The substitution of natural aggregates and cement, using plastic aggregate and supplementary cementitious material, respectively, could be a potential solution to the problem. However, the large amount of materials required to produce concrete along with the difficulty of controlling its mixing process leads to concrete that can exhibit remarkable variability in its mechanical properties. Hence, a mixture experimental design is proposed to better understand how natural aggregates can be replaced with recycled plastic and cementitious material as type-F fly ash and silica nanoparticles without interfering with the baseline mechanical properties of structural concrete. An experiment contemplated a partial to complete substitution of natural aggregates for recycled plastic aggregates. The mixture components for this experiment are: cement, fly ash, nanoparticles of silica, tap water, coarse aggregate, plastic aggregate, fine aggregate, and superplasticizer. The experiment took into account two process variables at two levels each: type of recycled plastic and brand of nanoparticles of silica. The statistical software JMP® generated a mixture design for one cubic meter of concrete considered mixtures specifications and constraints. The responses of this experiment mixture design include concrete mixture cost (USD); mean compressive strength (MPa) at 7, 14 and 28 days of curing time; and variance of the compressive strength at 7 days. Experiment results suggest that all the mixture components and several interactions were significant. Furthermore, the results of a joint optimization on the five responses outlined the constrained experimental region that will be studied in sequential mixture designs.
Funder Acknowledgement(s): This material is based upon work supported by the National Science Foundation under Grant No. 1345156 (CREST program).
Faculty Advisor: Saylisse Dávila, saylisse.davila@upr.edu
Role: The methodology of this research was divided in four phases: 1. characterization of the mixture components; 2. experimental mixture design; 3. mixing procedure, specimen preparation, and testing method; and 4. the model fitting. I led the first and the third phases, while mentored undergraduate students that help me to carried out these phases. Also, I conducted the design and the model fitting with the supervision of my advisor.