Graduate Student Workshop on Service Life Prediction of Concrete; Oregon State University; July 9-14, 2017

Oregon State University, Corvallis OR

Investigators

Abstract

This award will support a workshop for graduate students and faculty to participate a one-week course on experimental work and computational modeling on material evaluation, degradation mechanisms and prediction models. The workshop will be held at the Oregon State University in Corvallis, Oregon, July 9-14, 2017. As our existing infrastructure continues to age, it is of utmost importance to reliably assess and predict the performance of the remaining service life of existing assets. Computational modeling based on fundamental physics theories can be a powerful tool in achieving these goals while it can also be applicable to new constructions to optimize the materials selection and formulation for a desirable design life. Currently, courses related to material deterioration analysis and service life prediction modeling in the graduate civil engineering curriculum are scarce or limited to few institutions. This workshop offers a teaching model that can overcome this challenge. The course will be taught by a group of faculty members (national and international) with relevant research expertise. The outcomes of this course will enable civil engineering graduate students to gain fundamental knowledge related to service-life prediction and to integrate course materials into their current research. The objective of this workshop is to enhance graduate student learning and research efforts by infusing the basic science and theory to model and predict concrete performance. Students will be introduced to reactive-transport modeling of multi-species and multi-mechanistic transport in concrete; coupled modeling of corrosion propagation of embedded reinforcement and recent developments in coupling reactive processes, which are quantified using thermodynamic modeling, with numerical solutions of extended Nernst-Plank equation for multi-species transport. Basic thermodynamic modeling principles, Gibbs Free Energy Minimization processes and introduce open-source algorithms (e.g. GEMS framework) and thermodynamic databases (e.g. CEMDATA) that use this approach will also be explored. In addition, students will have hands on experience with different analytical equipment to evaluate laboratory and field aged cement and concrete samples. The instructors will incorporate the verification of prediction models using analytical results from those test data. Effective technical communication including proposal writing skills will also be introduced to the graduate students.