Papadopoulos has primary research and teaching interests in mechanics, including nonlinear structural analysis, computational mechanics, and biomechanics. He is also active in engineering education and engineering ethics, particularly in the subjects of mechanics education and appropriate technology. At UPRM Papadopoulos serves as the coordinator of the Engineering Mechanics Committee in the Department of General Engineering. He also co-coordinates the Social, Ethical, and Global Issues (SEGI) in Engineering Program and Forums on Philosophy, Engineering, and Technology.
Papadopoulos has diverse research and teaching interests in structural mechanics, biomechanics, appropriate technology, engineering ethics, and engineering education. He serves as Secretary of the ASEE Mechanics Division and serves on numerous committees at UPRM that relate to undergraduate and graduate education.
Hernandez-Negron has research interest in civil engineering and engineering education. During his studies in Civil Engineering and Surveying in the University of Puerto Rico Mayaguez (UPRM), he had the opportunity of do summer internship and research, assist professors and also being part of the directive board in different Societies and Organizations. His goal when he culminates the B.Sc. studies is contribute by developing new projects for the sole purpose of helping society. He says, "Within my goals there is my need to continue my studies in a Doctor of Philosophy's degree. Every step of the experience in my studies and life fills me with enthusiasm and encourages me to keep going."
In this study concrete mixtures with nanosilica particles (NS), silica fume (SF), and fly ash (FA) were tested for compressive strength, permeability via the rapid chloride ion permeability test (RCPT) and the costs were estimated for each mixture design. Model equations were generated from the empirical data and used to predict compressive strength and permeability for mixes containing NS, SF, and FA, with dosages within the tested range. After establishing the accuracy of the predictive model equations, three goals were established. The first objective was finding the optimal dosage of NS when it is the only admixture considered; the results indicate that the highest level tested of NS%=3 is the optimal dosage. The second objective was to find the maximum compressive strength and lowest permeability when all three admixtures are considered, for both tests, the best performing mixture contained NS%=3, SF%=20 and FA%=0. Finally, the predictive models were used simultaneously in order to find mixtures with the best cost. The predictive models found mixture designs that were able to improve performance, while simultaneously reducing costs when compared with the control mixture.
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