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Oleg Goushcha

Publications and source records attributed to Oleg Goushcha.

Validation of Shadowgraph Spectral Analysis using an SLS Block 2 Wind-Tunnel Model

A flow quantification method has previously been developed that uses high-speed shadowgraph images to extract frequency content of a transonic flow field around a wind-tunnel model. In this method, a classical spectral analysis is performed on a set of shadowgraph image pixels to identify their intensity fluctuation frequencies. The spatial change of the image intensity is related to the second derivative of the density gradient. Examining the change of the density gradient as a function of time can be used to understand the flow field pressure fluctuations. Pressure measurements collected during a Booster Obsolescence Life Extension Forward Attachment Structure Trade Study Test are used to calibrate the shadowgraph-based measurements. The test was performed at the NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-foot test section and investigated aerodynamic environment downstream of various booster forward attachment hardware geometries of the Space Launch System Block 2 Cargo configuration. Time-correlated shadowgraph video and model surface pressure measurements were acquired during the test and served as an ideal opportunity to calibrate and validate the shadowgraph image intensity method.

Shadowgraph↗

Validation of Shadowgraph Spectral Analysis using an SLS Block 2 Wind-Tunnel Model

A flow quantification method has previously been developed that uses high-speed shadowgraph images to extract frequency content of a transonic flow field around a wind-tunnel model. In this method, a classical spectral analysis is performed on shadowgraph video pixels to identify their intensity fluctuation frequencies. The spatial change of the image intensity is related to the second derivative of the density gradient. Examining the change of the density gradient as a function of time can be used to understand the flow-field pressure fluctuations. Time-varying pressure measurements collected during a Space Launch System (SLS) unsteady aerodynamic test of an advanced Block 2 booster design are used to calibrate the shadowgraph-based measurements. The test was performed at the NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-foot test section and investigated the aerodynamic environment downstream of candidate booster forward attachment hardware geometries of the SLS Block 2 Cargo configuration. Time-correlated shadowgraph video and model surface pressure measurements were acquired during the test and served as an ideal opportunity to calibrate and validate the shadowgraph image intensity method.

Shadowgraph↗

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↗

Validation of Shadowgraph Spectral Analysis using an SLS Block 2 Wind-Tunnel Model

A flow quantification method has previously been developed that uses high-speed shadowgraph images to extract frequency content of a transonic flow field around a wind-tunnel model. In this method, a classical spectral analysis is performed on shadowgraph video pixels to identify their intensity fluctuation frequencies. The spatial change of the image intensity is related to the second derivative of the density gradient. Examining the change of the density gradient as a function of time can be used to understand the flow-field pressure fluctuations. Time-varying pressure measurements collected during a Space Launch System (SLS) unsteady aerodynamic test of an advanced Block 2 booster design are used to calibrate the shadowgraph-based measurements. The test was performed at the NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-foot test section and investigated the aerodynamic environment downstream of candidate booster forward attachment hardware geometries of the SLS Block 2 Cargo configuration. Time-correlated shadowgraph video and model surface pressure measurements were acquired during the test and served as an ideal opportunity to calibrate and validate the shadowgraph image intensity method.

Shadowgraph↗

Artemis I Flight Instrumentation Data Quality Assessment and Processing

This paper is in support of the SciTech 2024 Space Launch System Aerosciences Special Sessions being organized by Brent Pomeroy and Jeremy Pinier. On November 16th, 2022, NASA launched the inaugural test flight of the Space Launch System (SLS) carrying the Orion capsule into a high orbit far beyond the Moon. The launch vehicle was instrumented with over three thousand flight instrumentation sensors, which monitored aerodynamic, acoustic, structural, and thermal environments. These data are intended to validate experimental and numerical tools used to predict the design environments which the vehicle experiences during launch and ascent. Prior to launch, tests were performed at the SLS Systems Integration Laboratory (SIL) using flight-like avionics and on the integrated flight hardware of Artemis I at the Vehicle Assembly Building (VAB). The purpose of these tests was to characterize the data acquisition units (DAUs) used to record and telemeter flight data to ground stations in order to assure that flight test objectives can be achieved and to quantify the expected quality of the flight data. In addition, pre-flight assessment and development of tools and methods used to process and disseminate flight data at the Huntsville Operations Support Center (HOSC) were conducted and adjustments made with respect to DAU time-synchronization prior to and after the flight. This paper summarizes these tests and some aspects of the post processing of data are discussed.

Developmental Flight Instrumentation↗

Comparison of Wind-Tunnel and Flight Unsteady Pressure Stochastic Characteristics for the Space Launch System Artemis I Flight

Over the course of more than ten years, numerous wind-tunnel tests have been conducted to acquire data for characterizing the unsteady pressure environments expected to act on the Space Launch System Block 1 crew launch vehicle during ascent. These wind-tunnel tests of highly-instrumented rigid models are the current standard for the estimation of unsteady environments. Following the successful launch of the Artemis I mission, the extensive flight data acquired can be analyzed to evaluate the accuracy of unsteady pressure environments predicted in subscale wind-tunnel testing in comparison to the flight test data. In this paper, analyses focusing on data from several Space Launch System wind-tunnel tests and the Artemis I flight test are presented, including assessments of test-to-test, tunnel-to-tunnel, and tunnel-to-flight stochastic characteristics and preflight modeling validity based on wind-tunnel testing. In general, the fluctuating pressure environments measured during the several preflight subscale wind-tunnel tests compare favorably and provide relatively accurate estimates of the environments measured during flight. Discrepancies in fluctuating magnitudes, spatial extent of regions of unsteadiness, and narrowband frequency peaks are noted in the multibody region aft of the solid rocket booster forward attachment to the core stage.

wind-tunnel↗

Developmental Flight Instrumentation: Review of Space Shuttle, Ares I-X, and Artemis I

Ascent vehicles in the developmental stages of the program are instrumented with Developmental Flight Instrumentation (DFI) sensors. These sensors establish a link between a vehicle and engineers on the ground to communicate conditions experienced during the ascent. These data are then compared to pre-flight predictions used in the design process. The aerodynamic, acoustic, thermal, and structural data are either telemetered to ground stations during the ascent or stored on the vehicle for post-flight recovery and archived at the Huntsville Operations Support Center (HOSC). Following NASA's Artemis I Space Launch System (SLS) launch on November 16, 2020, data from three separate programs are available at the HOSC: Space Shuttle Program (Space Transport System (STS)), Constellation Program (Ares I-X), and Artemis Program (SLS). Availability of these data presents a unique opportunity to examine DFI data from three distinct vehicles and analyze the broad impact of the DFI data on the understanding of transonic aerodynamics. Classical spectrogram and Empirical Mode Decomposition techniques were used to present data in aerodynamically analogous regions on each vehicle. On the SLS and Ares I-X, a region downstream of the Launch Abort System motors was chosen. Comparing SLS and the STS, a region downstream of booster Froward Attach Hardware was selected as analogous flow region. Some other regions of interest were also identified. Although similarities in flow features on three vehicles were identified, some challenges in the comparison were also encountered, especially due to poor temporal and spatial resolution of Shuttle measurements.

Space Shuttle↗

Comparisons of Artemis I and Wind Tunnel Buffet Environments and Induced Structural Responses

This paper presents comparisons of buffet forcing functions (BFFs) and associated structural responses for the Space Launch System from two data sources: 1) Artemis I (AR01) Developmental Flight Instrumentation (DFI) and 2) transonic wind-tunnel (WT) tests. Failures of DFI sensors prevented the development of a complete set of flight-based BFFs, where each BFF is based on azimuthal integration over 360-degrees of unsteady pressures acquired by sensor rings placed at many longitudinal stations along the vehicle. Instead, a set of equivalent flight- and WT-based BFFs was developed based on functional DFI and WT sensors that share the same locations. Root-mean-square (rms) levels of equivalent BFFs from flight and WT data are in-family for most of the cardinal Mach numbers. However, at stations downstream of the booster forward attachment (FA) protuberance, the rms of flight-based BFFs exceed their WT counterparts. Strikingly, vortex-shedding off the FA protuberance occurs at lower frequencies during flight than in WT experiments. This frequency shift propagates onto the spectrum of flight-measured vs. WT-based structural responses. Aside from vortex-shedding frequency mismatch, a generally good agreement between AR01 and WT-based responses is an indirect indication that WT buffet environments are fairly well representative of their AR01 counterpart.

transonic buffet↗

Artemis I Flight Instrumentation Data Quality Assessment and Processing

This paper is in support of the SciTech 2024 Space Launch System Aerosciences Special Sessions being organized by Brent Pomeroy and Jeremy Pinier. On November 16th, 2022, NASA launched an inaugural test flight of the Space Launch System (SLS) carrying the Orion capsule around the moon. The vehicle was instrumented with thousands of Developmental Flight Instrumentation (DFI) sensors, which monitored aerodynamic, acoustic, structural, and thermal environments. These data are used to validate experimental and numerical tools used to predict conditions the vehicle experiences during ascent. Prior to launch, a set of tests were performed to quantify the expected quality of the DFI flight data. These included testing of individual components, such as data acquisition units, at the Systems Integration Laboratory (SIL) and testing of integrated vehicle components at the Vehicle Assembly Building (VAB). This paper summarizes these tests. Some aspects of post processing of data are also discussed.

Developmental Flight Instrumentation↗

Development of Buffet Forcing Functions for a Transonic Condition Exhibiting Bimodal Flow Behavior

A wind-tunnel test campaign was used to derive Buffet Forcing Functions (BFFs) of the Space Launch System Block 1B vehicle configuration by measuring and integrating unsteady surface pressures on a 3-percent scale rigid buffet model (RBM) tested at the NASA Langley Transonic Dynamics Tunnel. The model was tested at predetermined and repeatable pitch and side-slip angles and flow Mach numbers encompassing a full range of possible flight conditions. Although each data point was collected at a steady wind-tunnel condition, a transient, bimodal flow behavior was observed in some Mach 1.10 measurements. The pressure time series was alternating between two states, which differed either in mean or fluctuation amplitude values, or both. As a consequence of this behavior, segments of the resultant BFFs can differ based on the duration that each measurement spends in a particular state. In this paper, a methodology is proposed, which envelopes the range of BFFs magnitudes resulting from this random bimodal phenomenon in pressure time histories of certain sensors.

wind-tunnel testing↗

A Database of CFD-Based Buffet Forcing Functions for Artemis I Structural Response Evaluation

Time-accurate FUN3D simulations are utilized to estimate buffet-induced unsteady forces experienced by the Space Launch System during the Artemis I (AR01) flight. A set of FUN3D simulations was developed that employed time-accurate mesh translations to simulate the changing velocity and attitude based on the AR01 best estimated trajectory. In these simulations, referred to as accelerating-flow simulations, the freestream Mach number increased from 0.80 to 1.92. Additional time-accurate simulations were obtained at constant freestream Mach number equal to 0.95, 1.18, 1.70, thereby simulating stationary conditions experienced by the flow in a wind-tunnel. On the grounds of favorable comparisons between simulated and flight-measured environments, the FUN3D-based surface pressures were utilized to develop a buffet forcing function (BFF) database. This BFF database was analyzed to characterize the spatial distribution and frequency content of the buffet forces during transonic and supersonic portions of the AR01 flight. The region of interest is located downstream of the forward attachment (FA) hardware between the core stage and the solid rocket boosters where vortex shedding off the FA protuberance produces significant unsteadiness. The analysis reveals that, at transonic and supersonic conditions, buffet forces that are based on constant freestream Mach number data are a good approximation of those based on accelerating-flow simulations.

transonic buffet↗