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David J. Piatak

Publications and source records attributed to David J. Piatak.

Comparison of Corcos-Based and Experimentally-Derived Coherence Factors for Buffet Forcing Function Estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Function (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurement-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimentally-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain nonturbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

transonic buffet↗

Analysis of Transonic Unsteady Aerodynamic Environments using Unsteady Pressure Sensitive Paint for the Space Launch System Block 1 Cargo Launch Vehicle

Predicting launch vehicle unsteady aerodynamic loads due to buffet remains a significant challenge. Current practices for modeling buffet environments involve the development of buffet forcing functions using unsteady pressure measurements acquired during wind-tunnel tests. These practices often result in significant uncertainty in buffet environments for coupled loads analyses due to the complex spatio-temporal nature of the unsteady pressure field and challenge of its estimation using discrete sensors. Unsteady pressure sensitive paint, on the other hand, can provide unsteady pressure data at a comparatively high-spatial-density and may overcome the challenge of unsteady pressure field estimation with discrete sensors and lead to improvements in the development of buffet forcing functions. In this paper, comparisons of the fluctuating pressure field are made for the Space Launch System Block 1 cargo launch vehicle measured using unsteady pressure sensitive paint and pressure transducers.

buffet↗

Analysis of Transonic Unsteady Aerodynamic Environments using Unsteady Pressure Sensitive Paint for the Space Launch System Block 1 Cargo Launch Vehicle

Predicting launch vehicle unsteady aerodynamic loads due to buffet remains a significant challenge. Current practices for modeling buffet environments involve the development of buffet forcing functions using discrete unsteady pressure measurements acquired during wind-tunnel tests. These practices often result in significant uncertainty in buffet environments for coupled loads analyses due to the complex spatio-temporal nature of the unsteady pressure field and the challenge of its estimation using discrete sensors. Unsteady pressure sensitive paint, on the other hand, can provide unsteady pressure data at a comparatively high spatial density and may overcome the challenge of unsteady pressure field estimation with discrete sensors and lead to improvements in the development of buffet forcing functions. In this paper, comparisons of the fluctuating pressure field are made for the Space Launch System Block 1 cargo launch vehicle measured using unsteady pressure sensitive paint and pressure transducers.

buffet↗

Coherence Analysis of the Space Launch System using Unsteady Pressure Sensitive Paint

Transonic buffet forces are a major source of unsteady loading on launch vehicles, thus requiring accurate estimation for efficient vehicle design. The state of the art in modeling these unsteady loads utilizes wind-tunnel tests where the fluctuating pressures are measured by pressure transducers (PTs) at discrete locations on a rigid buffet model. These pressures are then integrated over the surface of the vehicle to yield a series of orthogonal centerline loads called buffet forcing functions (BFFs). Typically, the PT layout aims at resolving the pressure correlation along the longitudinal axis of the vehicle. As a result, the distribution of azimuthal correlation and its impact on the estimated BFFs are not well known. To fill these gaps, extremely high-spatial-resolution uPSP data were collected for three different configurations of the Space Launch System in the NASA Ames Research Center 11-Foot Transonic Unitary Plan Wind Tunnel. The spatio-temporal behavior of the pressure correlation on these vehicles is analyzed and flow features of interest are investigated. It is shown that terminal shocks interacting with turbulence are a source of increased azimuthal coherence, especially when the shock develops at a junction. Vortex shedding off the forward attachment hardware that connects the core stage to the solid rocket boosters (SRBs) is the most severe buffet environment on the vehicle. The associated fluctuating pressures are shown to be highly coherent as far as the vehicle tail and up to 40 degrees away from the boosters. For selected areas of the vehicle, factoring the azimuthal coherence into the attenuation of discrete-measurements-based BFFs results in under prediction relative to the BFFs obtained from full integration of the uPSP data.

buffet↗

Development of Buffet Forcing Functions Using Frequency-Dependent Coherence Factors

The current accepted approach to modeling launch vehicle transonic buffet environments is to acquire time-correlated unsteady pressure measurements at discrete locations on a model-scale wind-tunnel model and use these measurements to develop buffet forcing functions (BFFs).Part of the BFF development process is the application of coherence factors to account for the discrete nature of the pressure measurement used in the development of the BFFs. Presently, the Space Launch System (SLS) program divides the launch vehicle into distinct aerodynamic regions, within which, the coherence lengths are assumed to be constant. The coherence factors are computed by averaging the coherence function between sensors within the region over a specified frequency range. The present work validates and examines the impact of two proposed changes to the development of longitudinal coherence factors used in the development of launch vehicle BFFs. One change is to employ frequency-dependent coherence factors instead of coherence factors based on the mean of the coherence function. The second proposed change replaces the aerodynamic regions with a moving-segment approach that varies the calculated coherence lengths as a function of longitudinal location of the transducers. The impact of these approaches is examined using data from two rigid buffet model wind-tunnel tests: (1)a notional launch vehicle geometry through the comparison of discrete measurement-basedBFFs to loads developed by continuous integration of unsteady pressure sensitive paint data and (2) the SLS Block 1 Cargo vehicle configuration for which BFFs have been previously developed using less-mature methods. The trends from this examination of updated coherence factor approaches ultimately result in more intuitive results than currently-accepted coherence methods.

buffet, unsteady aerodynamics, launch vehicle, win↗

Parametric Study of the Forward Attachment Geometry for the Space Launch System Next Generation Booster

Launch vehicle transonic buffet environments can generate large dynamic structural loads and vibratory responses. For the Space Launch System (SLS) vehicle, the highest transonic buffet environments have been observed in the multibody region between the core and solid rocket boosters, particularly downstream of the booster forward attachment. The buffet environment is particularly sensitive to the outer mold line (OML) of the forward attachment, and even relatively minor geometry changes can have large impacts on buffet and other aerodynamic environments. The SLS program is redesigning the booster for the Block 2 vehicle to support updated mission goals. This redesign necessitated changes in the forward attachment geometry, which raised concerns about the buffet and vibroacoustic environments. A preliminary study was conducted that developed multiple forward attachment geometries that satisfied the programmatic requirements, but the aerodynamic environment impacts were unclear. In March 2022, a wind-tunnel test was conducted at the NASA Ames 11- by 11-foot Transonic Wind Tunnel to study these environments generated from each of the configurations in order to select the most viable candidate. This paper will discuss this test campaign, the results from the parametric study, as well as general observations regarding OML features that impact the buffet environment. Buffet environments will be presented and compared for each configuration and comparisons presented where applicable.

buffet↗

Initial Whirl-Flutter Characterization of the TiltRotor Aeroelastic Stability Testbed

This paper discusses the initial wind tunnel test of the TiltRotor Aeroelastic Stability Testbed (TRAST). TRAST is a generic tiltrotor testbed developed in collaboration between NASA and the Army. Ultimately, this test was a checkout of the model systems, functionality and familiarization, but also obtained subcritical whirl-flutter data in the terms of frequency and damping. Flutter data include two main configurations with different pitch spring stiffness, referred to as 4k and 8k, that were tested at various rotor speeds and airspeeds at the NASA Langley Transonic Dynamics Tunnel. The test included two modes of drivetrain operation: powered and windmilling. However, powered mode of operation was only conducted with the 8k pitch spring. This test reinforced the traditional knowledge of whirl-flutter trends such as flutter speed would decrease with an increase in rotor speed. The critical mode consistently being the wing vertical bending mode. The chord mode as expected was not affected by the pitch spring and was likely to go unstable at a tunnel airspeed slightly beyond the wing vertical bending mode. There were also test specific challenges such as the TRAST modal damping was more sensitive to temperature and amplitude motor than was expected. This test gathered valuable data on the baseline characterization of TRAST, how to improve the model and test practices for future wind tunnel testing. Additionally, a new more automated method for experimental subcritical damping determination based on the Stockwell transform has been demonstrated that may lead to more consistent whirl-flutter stability boundaries.

whirl flutter↗