SBIR/STTR Award attributes
There are currently over ten thousand Unmanned Aerial Systems (UAS’s) in military operations in support of domestic training events and overseas contingency missions for their versatility in meeting the Warfighters’ requirements, including intelligence, surveillance and reconnaissance. The mission profile of UAS’s typically involves multiple segments, such as releasing from storage, dashing, and loitering, which pose conflicting design specifications and result in a compromised UAS design. Morphing UAS’s (MUAS’s) have shown potential in optimizing the aerodynamic characteristics by configuration adaptation and achieving consistently superior performance for all the mission segments. However, the morphing typically needs to be facilitated by flexible skins and compliant aero-structures, which may introduce complex fluid-structural interactions (FSI). The FSI of actuated aero-structures results in an aeroservoelastic problem and may severely impact the structural integrity, dynamical stability, flight dynamics and control of the MUAS. Due to the tight coupling between the morphing mechanism and the vehicle structure, the FSI effect must be considered in the early design stage of the vehicle; this calls for a computational design tool capable of the rapid assessment of the morphing technologies for multi-mission MUAS with FSI effects. Such a tool shall help Army engineers to develop high-performance MUAS’s that can adapt the structure to respond optimally to Soldier needs and, ultimately, facilitate the success of Army operations. To address the Army need for UAS’s with enhanced multi-mission performances using morphing technologies, AnalySwift proposes to develop a new Rapid Aeroservoelastic Design Framework for Morphing Unmanned Aerial Systems (RADMUAS). RADMUAS is based on a new design that utilizes AnalySwift’s commercial code SwiftComp for the fast yet accurate modeling of complex structural anisotropy and heterogeneity, together with a set of established open-source multi-disciplinary analysis and optimization (MDAO) tools. The innovation in the so-called fidelity decomposition approach will enable the RADMUAS to perform near-high-fidelity rapid trade study of a MUAS for possible morphing technologies and multi-segment mission profiles. As a result, this framework offers a capability to perform fluid-structural interaction analysis of MUAS’s with large deformation and low-mass structures, an analysis accuracy of over 90% and a computational acceleration by a factor of 1000, an efficient trade study of MUAS involving detailed actuator analysis, and a flexible license mechanism suitable for parallelized computing, which directly address the Army engineers’ requirements. In Phase I, AnalySwift will demonstrate the feasibility of RADMUAS through a prototype that can perform rapid trade study of an example MUAS configuration. In Phase II, RADMUAS will be extended to support different morphing technologies and enable the MDAO of generic MUAS’s.
