MAINSTREAM ENGINEERING CORP — Department of Defense STTR Phase I: ABSTRACT: Experimental testing of dynamic models has been performed for more than 50 year

Description

ABSTRACT: Experimental testing of dynamic models has been performed for more than 50 years and a wealth of data exists for individual models. However, this data is often either restricted as proprietary or is not suitable for CSE tool validation as a result of incomplete model or test information. Mainstream Engineering proposes to design, fabricate, and test a scaled fighter for aeroelastic research utilizing rigorous and robust testing techniques which will guarantee high fidelity data collection for CSE tool validation. Mainstream will assess the merits and deficiencies of various manufacturing processes with respect to fabrication cost, model build and instrumentation time, and testing accuracy and repeatability. In Phase I, Mainstream will design the scaled model along with peripheral components and perform subsonic tests. For a Phase II program, Mainstream will conduct additional testing at transonic conditions after successful CSE validation of subsonic data. Mainstream believes this approach will limit overall program risk by first testing and validating in the subsonic flow regime prior to testing and validating in the transonic flow regime. Design methodology and data collected during these tests will be made publicly available to help validate CSE tools. BENEFIT: While the initial work for this program is for scaled fighter aircraft, the design, fabrication, and testing methods developed are applicable for various aerodynamic bodies, including commercial aircraft, missiles, and unmanned aerial systems (UAS/UAV). This experimental effort addresses these technology needs by providing a set of high fidelity subsonic aeroelastic research data along with design methodology guidelines. Public domain availability of this data set is instrumental in the development of CSE tools, since it will allow single and multi-physics simulation tools to be benchmarked against a common data set.