Predictive modeling of large scale historic masonry monuments: Uncertainty quantification and model validation

This paper focuses on establishing confidence in model predictions through the validation of numerical models with a specific focus on large scale masonry structures. Through an overview of various case study applications, this presentation will discuss the relevant phases of model validation: numerical model development, field experimentation, model calibration and validation. The main goals of this paper are (i) to discuss where modeling errors and uncertainties originate and (ii) to present an approach to obtain model predictions that are statistically consistent with their respective measurements. Our approach considers all major sources of error and uncertainty, which originate from the numerical solutions of differential equations (numerical uncertainty), imprecise model input parameter values (parameter uncertainty), incomplete definitions of underlying physics due to assumptions and idealizations (bias error) and variability in measurements (experimental uncertainty). This paper provides an overview of the best-practices for developing finite element models for large-scale masonry monuments, designing and executing calibration experiments as well as calibrating numerical models under uncertainty.