Launch vehicle buffet loads have been determined by using unsteady pressure transducers that measure pressure fluctuations at several hundred locations on a wind runnel model and then integrating the pressure fluctuations over a specified area. Even with this very large number of sensors, the coverage is insufficient to provide accurate integrated unsteady loads on the vehicle and the coarse spacing of the sensors results in buffet environments that are often conservative in their prediction of buffet loads between the transducers. This results in additional structural weight to cover these conservative environments. Computational fluid dynamics (CFD) is potentially capable of modeling these environments but is currently too slow and not well validated for unsteady loads. NASA and the aerospace industry need a defendable, reliable method to estimate buffet forcing functions (BFF) from the limited unsteady pressure data that is available from wind-tunnel testing and to instill confidence in CFD techniques to obtain the same information. Recently, AEDC has begun development of an unsteady pressure sensitive paint (uPSP) capability for 16T that can acquire fluctuating pressures up to 20 kHz and has demonstrated a prototype on a generic weapons bay model. The excellent results from that test encouraged NASA Ames to request uPSP support for a launch vehicle buffet verification test in their 11-foot wind tunnel. A wind tunnel model identical in configuration to Model 11 tested by Coe and Nute was designed for the test In addition to the conventional unsteady pressure transducers and static pressure orifices, the model would be covered with uPSP to measure full surface fluctuating pressures. A 12.1-inch section of the second stage was instrumented with gages and accelerometers in hopes of directly measuring fluctuating loads. Verification of the uPSP is made through power spectral density (PSD) comparisons with conventional unsteady pressure transducers and comparisons of fluctuating section load integrations from PSP and transducers at each section (PSD and RMS loads). Additionally, the uPSP data quality is verified via auto correlation between cameras in overlap regions. The complete spatial distribution of the sound pressure level (SPL) at selected frequencies and RMS is presented to aid understanding of the data and provide additional insight The continuous uPSP illustrates the small coherence distance that is valid for conventional transducers to be applied in calculating unsteady forces, whereas the uPSP is not bound by this limitation. Analysis of the buffet forcing functions will be presented as RMS section loads (per unit length). The results of the test demonstrate the ability to determine more accurate buffet forcing functions using unsteady PSP than is possible with sparse point source instrumentation.
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