The integration of CFD modeling and simulation into plume measurement programs

Abstract

Reducing the costs and the risks associated with the acquisition of diagnostic measurements is a major concern for test program managers at the Arnold Engineering Development Center (AEDC). AEDC’s test engineers are also facing advanced testing requirements for futuristic propulsion systems operating at conditions beyond conventional ground test cell capabilities. To meet these challenging requirements, engineers and physicists are increasingly relying on the integration of proven computational methodologies into propulsion and aerodynamic test measurement programs. The AEDC exhaust plume measurement team was the first to take advantage of computational fluid dynamics (CFD) capabilities and establish formal testing procedures that include pretest CFD simulations. The simulations are used for test planning guidance and to complement posttest analysis efforts. This testing process demonstrated that physics-based CFD methodologies can be applied effectively to optimize test planning efforts, improve the probability of acquiring useful, high-quality measurements, and enhance post-test data analyses. The payoffs are improved data quality and fewer risks associated with meeting all test objectives. In addition, the scope of posttest measurement analyses and reporting efforts are broadened by the insight.gained from CFD simulations. However, the primary driver for advocating this approach is the reduction in testing costs that can result from practical applications of validated CFD models. Support to Test Planning Plume phenomenology measurement programs conducted by the AEDC radiometric team benefit from close integration of measurement diagnostics and proven CFD methodologies. Pretest CFD predictions are an essential part of AEDC’s standard radiometric measurement process. Personnel working in the disciplines of CFD and diagnostics attend test planning meetings and continue to interact closely throughout the test program. During the initial test planning activities, pretest CFD results are applied to guide the test configuration setup and to optimize the instrument dynamic range settings and calibration limits. If the calibration sources and the instruments’ dynamic ranges closely bracket the actual measurement, the measurement uncertainties can be reduced considerably. Support for Diagnostic Development Efforts CFD has been instrumental in the success of diagnostic development and proof-of-concept measurement programs. At NASA Marshall’s Advanced Engine Test Facility (AETF), CFD simulations were used to support the development of the Optical Plume Anomaly Detector (OPAD). The OPAD diagnostic system is a nonintrusive technique currently used for health monitoring of the Space Shuttle Main Engine (SSME) during static sea-level testing.’ The success of the OPAD measurement relies on precisely locating and nonintrusively probing the high-temperature flow region immediately downstream of the Mach disc. Figure 1 is a composite of computed static temperature contours resulting from CFD simulations of the SSME operating at two power settings during sealevel static testing conditions. The power levels shown in this figure differ by 20 percent and the SSME nozzle operates in an overexpanded condition at both conditions. The primary test objective * The research reported herein was performed by the Arnold Engineering Development Center (AEDC), Air Force Materiel Command. Work and analysis for this research were performed by personnel of Sverdrup Technology, Inc., AEDC Group, technical services contractor for AEDC. Further reproduction is authorized to satisfy needs of the U. S. Government. + Senior Member, AIAA. This paper is declared a work of the U. S. government and not subject to copyright protection in the United States. 1 American Institute of Aeronautics and Astronautics was to nonintrusively probe the flow immediately downstream of the Mach disc during static stand firings using optical methods. The basis of the OPAD methodology is to detect characteristic emissions from trace metallic particulates that result from erosion of engine parts as the submicron particles are heated in the high-temperature region downstream of the Mach disc. In order to detect the very weak emission levels, flow regions of high temperature and pressure are probed. Precise information concerning where the Mach disc is located and its movement relative to changes in and repetitive testing to recover lost data is expensive. Therefore, acquiring critical, high-quality, complete measurement collections during each testing opportunity is expected. The cost of the complete CFD effort was less than $lOK. Mr. W. T. Powers, the NASA OPAD program manager, estimates that the use of CFD tools to support the OPAD development program ultimately reduced the planning and test preparation times by 2 weeks. Additionally, according to Mr. Powers, less testing time (fewer conditions) was required once the CFD methodology was validated and proven reliable. the engine power settings are needed to position the OPAD’s field of view (FOV). The CFD simulations accurately predicted relative Mach disc locations and sizes and instrumentation alignments were adjusted accordingly. Static temperature contours, like those shown in Fig. 1, were also applied to optimize the calibration ranges, determine instrument range settings, and estimate the emission levels of the heated metallic species. This insight was instrumental in obtaining measurement uncertainties less than 10 percent at most conditions. Having this type of information prior to the test is a factor in reducing the risk associated with acquiring useful data and definitely contributed to the success of the OPAD development and demonstration testing. The cost of the AETF test setup for a 300-set engine firing is nominally $200K. The additional cost of installing, calibrating, and analyzing the data from the diagnostic systems range from $75K-$1 OOK. The entire test process from planning the test to reporting the Flow Direction