A modular matrix-free approach to multidisciplinary design optimization

Abstract

The individual discipline feasible (IDF) formulation is a multidisciplinary design optimization (MDO) architecture that provides modularity for the underlying discipline solvers. Similar to reduced-space methods, the IDF formulation does not require the optimization algorithm to converge the state variables for each discipline in addition to the optimization variables; the state equations are still solved fully at each optimization iteration. However, IDF decouples the discipline equations from each other through the introduction of coupling variables and constraints to the optimization problem. Consequently, the discipline solutions at each optimization iteration can be performed independently and in parallel. This promotes the use of existing discipline-specific PDE solvers, and lowers the software development challenge of creating efficient coupled discipline analyses.