System Architecture Optimization: An Open Source Multidisciplinary Aircraft Jet Engine Architecting Problem

Decisions regarding the system architecture are important and taken early in the design
process, however suffer from large design spaces and expert bias. Systematic design space
exploration techniques, like optimization, can be applied to system architecting. Realistic engineering benchmark problems are needed to enable development of optimization algorithms
that can successfully solve these black-box, hierarchical, mixed-discrete, multi-objective architecture optimization problems. Such benchmark problems support the development of more
capable optimization algorithms, more suitable methods for modeling system architecture design space, and educating engineers and other stakeholders on system architecture optimization
in general. In this paper, an engine architecting benchmark problem is presented that exhibits
all this behavior and is based on the open-source simulation tools pyCycle and OpenMDAO.
Next to thermodynamic cycle analysis, the proposed benchmark problem includes modules
for the estimation of engine weight, length, diameter, noise and NOx emissions. The problem
is defined using modular interfaces, allowing to tune the complexity of the problem, by vary-
ing the number of design variables, objectives and constraints. The benchmark problem is
validated by comparing to pyCycle example cases and existing engine performance data, and
demonstrated using both a simple and a realistic problem formulation, solved using the multi-
objective NSGA-II algorithm. It is shown that realistic results can be obtained, even though
the design space is subject to hidden constraints due to the engine evaluation not converging
for all design points.