Don Estep
Department of Mathematics
Colorado State University
''Model Sensitivity Analysis, Uncertainty Quantification,
and Error Control in a Complex World"
"
Abstract
The investigation of multiscale, multiphysics
systems occupies a central position in science and engineering. The
cost and complexity of physical experimentation on such systems leads
to a strong reliance on mathematical modeling and numerical simulation
as analysis and design tools. Complexity (happily for mathematicians)
also increases the need for quantitative estimates of computational,
data, and model errors in simulations and the ability to control such
errors when possible. In this talk, I will describe a mathematical
foundation for investigating model sensitivity and quantifying uncertainty
and error based on adjoint problems, variational analysis, and generalized
Green's functions. These tools have a long history of application
in science and engineering and are connected to relatively recent
advances in a posteriori error analysis of finite element methods.
In this talk, I will show these tools apply to numerical error estimation,
model sensitivity analysis, data and parameter error, operator decomposition
for multiphysics problems, and adaptive error control. I will expose
the basic ideas in the context of finite dimensional problems, where
the mathematics is simple. Then, I will explain how they apply to
various differential equations and demonstrate their effectiveness
using a variety of examples.