A Genetic Algorithm-Based Approach for Designing a Fixture That Preserves the Desired Dynamics of a Connecting Part

Complex aerospace systems are often more than just the sum of their parts. When tested individually, each component of the system has a certain dynamic response characterized by natural frequencies, mode shapes, and, for durability testing, failure modes. However, when assembled, this response often changes due to the added boundary conditions and interfaces. This change makes durability testing at the component level difficult because the failure modes observed may not be representative of those that will occur at the system level. Performing durability testing at the system level can be an even greater challenge due to difficulties accessing the connecting components, inaccessible proprietary design specifications, and different design timelines for the various components of the system. To overcome these challenges and perform meaningful, accurate durability testing, there is a need to simulate system-level boundary conditions during component-level testing. In this chapter, a genetic algorithm-based optimization approach is proposed to design a fixture for a component-level test that preserves the dynamics of the component determined while it is in the full assembly. It is assumed that the system-level dynamics of the component are known, but the boundary conditions and dynamics of the connecting parts are unknown.

To demonstrate the potential of this approach, the Box Assembly with Removable Component (BARC) is used to represent a system, where the top component is the component of interest. The dynamics of the top component were determined while it was installed in the full BARC using modal analysis. These natural frequencies and mode shapes were the target values used to evaluate an optimized fixture design. A finite element model of the BARC was developed, where the large box component was replaced with a “fixture,” represented by a generic design volume. The properties (density and modulus values) throughout the design volume were the parameters of the optimization problem, where the goal was to match the dynamics of the top component when attached to the optimized fixture to the target values, determined while the top component was installed in the BARC. The result of this approach produced a fixture design in which the first five natural frequencies of the top component were all within \(11\%\) of the target values, and three of the first five modal assurance criterion (MAC) values were greater than 0.8.