The Imaging X-ray Polarimetry Explorer (IXPE) will add polarization to the properties (time, energy, and position) observed in x-ray astronomy. A NASA Astrophysics Small Explorer (SMEX) in partnership with the Italian Space Agency (ASI), IXPE will measure the 2–8-keV polarization of a few dozen sources during the first 2 years following its 2021 launch. The IXPE Observatory includes three identical x-ray telescopes, each comprising a 4-m-focal-length (grazingincidence) mirror module assembly (MMA) and a polarization-sensitive (imaging) detector unit (DU), separated by a deployable optical bench. The Observatory’s Spacecraft provides typical subsystems (mechanical, structural, thermal, power, electrical, telecommunications, etc.), an attitude determination and control subsystem for 3-axis stabilized pointing, and a command and data handling subsystem communicating with the science instrument and the Spacecraft subsystems.
A number of future space based science instruments key to NASA's Origins program require exceptionally large and precise support structures. The scale of these structures and stringency of their dimensional stability will present a number of challenges in the ground verification testing stage of their development and deployment. This paper will discuss a number of the unique challenges involved in developing validation procedures for these structures. It will also describe a novel approach to the development and validation of nonlinear component models of the structural mechanics. This "Component in the Loop" approach offers the ability to directly measure the in situ coupled behavior of a structural component as part of the ex situ component testing process. This testing methodology would allow the coupled system level response of the larger structure to be assessed without the need for assuming particular nonlinear component model forms. The proposed method is not limited to conducting virtual system tests. Feedback functions can be specifically designed to maximize the sensitivity of the output with respect to uncertain parameter(s). Maximum sensitivity is desired to accurately characterize the parameter in question, which is fundamental in model updating procedures.