Collaborative Research Strain-rate Dependent Properties of Cement-Based Materials: A Multi-Scale Experimental and Modeling Effort

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

This proposal outlines a joint experimental and computational program aimed at developing the framework for a multi-scale model of cement-based materials, which will provide for advances in quantitative descriptions of their heterogenous structure and an ability to predict the effect of loading rate on failure in materials ranging from normal strength concrete to fiber-reinforced ultrahigh performance concrete. Specifically, the proposed activities are divided into four tasks: 1) quantitative characterization of multi-scale structure and meso-scale fluctuations in structural descriptors; 2) development of micromechanical models for predicting strain-rate dependent behavior of concrete/cementitious materials; 3) stochastic simulation-based modeling of variations in meso-scale constitutive properties of concrete/cementitious materials; and, 4) full-scale finite element model of samples under uniaxial/biaxial compression at varying strain rates, along with experimental validation using Kolsky bar equipment. The research conducted through the proposed activities will address the important problem of impact loading on concrete materials, by providing new modeling paradigms and experimental techniques to address the strain-rate-dependent failure of cement-based materials. These protocols can form the basis for improved blast-resistance of materials and more effective structural design. In addition, the techniques are also expected to be applicable to the broader family of brittle materials under high strain rates, such as modeling failure of rocks under mining blasts or ceramic armors under ballistic loading. The proposed activities represent a multi-institutional collaboration, which will provide students mentored by the PIs exposure not only to the expertise of both PIs, but also to the educational research environments at each of the involved institutions. Each PI will mentor one Ph.D. student and undergraduate researchers who will all be encouraged to travel to the other institution on a regular basis to share findings.