Dynamic-data-driven damage prediction in aerospace composite structures Conference Paper uri icon

abstract

  • © 2016, American Institute of Aeronautics and Astronautics. All right reserved. The designs of military and civilian aircraft and rotorcraft are rapidly increasing in complexity in response to the demands placed on these vehicles. In order to increase the durability of these vehicles and decrease weight, composite materials are currently experiencing a widespread adoption, both in the military and civilian aircraft design. As a result, in order to decrease costs associated with the operation, maintenance, and, in some cases, loss of these vehicles, it is desirable to have a Dynamically Data-Driven Application System (DDDAS) framework that can reliably predict the onset and progressions of structural damage in geometrically and materially complex aerospace composite structures operating in the environments typical of these vehicles. In this work we present further enhancement of the original DDDAS framework and introduce the so-called Multiscale DDDAS framework for damage prediction in aerospace structures. The intended application of the framework is the analysis of aerospace vehicles, like the Unmanned Aerial Vehicles (UAVs), undergoing complex maneuvering scenarios.

author list (cited authors)

  • Korobenko, A., Pigazzini, M., Singh, V., Kim, H., Allaire, D., Willcox, K., Marsden, A. L., & Bazilevs, Y.

publication date

  • January 2016