Interplay of numerical integration with gradient based optimization algorithms for robust design optimization

Engineers increasingly rely on computer simulation to develop new products and to understand emerging technologies. In practice, this process is permeated with uncertainty. Most of the computational tools developed for design optimization ignore or abuse the issue of uncertainty, whereas traditional methods for managing uncertainty are often prohibitively expensive. The ultimate goal of this work is the development of tractable computational tools that address these realities. As a small first step towards this goal, this paper explores the interaction between numerical integrators and gradient based optimizers for robust design optimization.