Kriging, Polynomial Chaos Expansion, and Low-Rank Approximations in Material Science and Big Data Analytics.

In material science and engineering, the estimation of material properties and their failure modes is associated with physical experiments followed by modeling and optimization. However, proper optimization is challenging and computationally expensive. The main reason is the highly nonlinear behavior of brittle materials such as concrete.

Quantifying Material Uncertainty in Seismic Evaluations of Reinforced Concrete Bridge Column Structures.

In seismic performance evaluations, the force-deformation response of a structure is typically assessed using a deterministic analytical model, and inherent uncertainty is often neglected. For reinforced concrete structures, a source of uncertainty is variability in the mechanical properties of reinforcing steel and concrete (that is, material uncertainty). This paper presents an analytical investigation to quantify the impact of the statistical variability in mechanical properties of ASTM A706 Grade 60, 80, and 100 reinforcing steel and normalweight concrete on the seismic response of reinforced concrete bridge columns.