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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Sensitivity of Space Launch System Buffet Forcing Functions to Buffet Mitigation Options

Time-varying buffet forcing functions arise from unsteady aerodynamic pressures and are one of many load environments, which contribute to the overall loading condition of a launch vehicle during ascent through the atmosphere. The buffet environment is typically highest at transonic conditions and can excite the vehicle dynamic modes of vibration. The vehicle response to these buffet forcing functions may cause high structural bending moments and vibratory environments, which can exceed the capabilities of the structure, or of vehicle components such as payloads and avionics. Vehicle configurations, protuberances, payload fairings, and large changes in stage diameter can trigger undesirable buffet environments. The Space Launch System (SLS) multi-body configuration and its structural dynamic characteristics presented challenges to the load cycle design process with respect to buffet-induced loads and responses. An initial wind-tunnel test of a 3-percent scale SLS rigid buffet model was conducted in 2012 and revealed high buffet environments behind the booster forward attachment protuberance, which contributed to reduced vehicle structural margins. Six buffet mitigation options were explored to alleviate the high buffet environments including modified booster nose cones and fences/strakes on the booster and core. These studies led to a second buffet test program that was conducted in 2014 to assess the ability of the buffet mitigation options to reduce buffet environments on the vehicle. This paper will present comparisons of buffet forcing functions from each of the buffet mitigation options tested, with a focus on sectional forcing function rms levels within regions of the vehicle prone to high buffet environments.

Piatak, David J.↗
NASA NTRSDate not supplied

Evaluation of Preliminary Buffet Forcing Function Development based on Wind-Tunnel Tests of Geometrically-similar Models

The current state-of-the-art for launch vehicle buffet load estimation involves wind tunnel testing of highly instrumented rigid models and data processing of experimental unsteady pressure measurements to estimate the fluctuating aerodynamic loads. The model and instrumentation requirements to accomplish this type of testing are significant. The rigid model, in particular, must be built with relatively high geometric fidelity to approximate similar aerodynamic phenomena that will occur during the full-scale vehicle flight. Due to this requirement, several iterative wind tunnel tests are often required during the design maturation of the vehicle. For preliminary buffet load estimation, however, data from previous launch vehicle wind tunnel tests of geometrically similar models can be used to provide initial buffet environment estimates before a high geometric fidelity wind tunnel test has been conducted. In this paper, two components of this preliminary buffet estimation process are described: (1) assembly of buffet forcing functions from multiple data sources and (2) scaling of these buffet forcing functions to geometrically-similar components of a target vehicle configuration. The impacts of these estimation methods on the full-vehicle buffet forcing functions, including their longitudinal distribution along the vehicle, frequency-content at individual stations, and station-to-station coherence, are investigated. Considerations for using these methods to extrapolate wind tunnel data to geometrically similar models are also discussed.

Patrick S Heaney↗
NASA NTRS2019

Measurement and Analysis of Terminal Shock Oscillation and Buffet Forcing Functions on a Launch Vehicle Payload Fairing

The buffet loads on a launch vehicle payload shroud can be impacted by the unsteadiness associated with a terminal shock at high subsonic speeds. At these conditions, flow accelerates to supersonic speeds on the nose of the payload fairing and is terminated by a normal shock on the cylindrical section downstream of the nose cone/cylinder shoulder. The location of the terminal shock and associated separated boundary layer is affected by the freestream Mach number, Reynolds number, and the pitch/yaw of the launch vehicle. Furthermore, even when the freestream conditions and vehicle attitude are constant, this terminal shock oscillates on the surface of the vehicle. The time-varying surface pressure associated with the terminal shock results in unsteady aerodynamic loads that may interact with vehicle structural dynamic modes and the guidance and control of the vehicle. Buffet testing of a 3-percent scale rigid buffet model of a launch vehicle cargo configuration with a tangent-ogive payload shroud was conducted in 2012 and in 2016. Initial buffet forcing functions (BFFs) utilized a coarse pressure sensor distribution on the vehicle surface in which a single longitudinal station with eight sensors observed the terminal shock environment at Mach 0.90. An examination of these circumferential pressures reveal large impulse-like pressure fluctuations and an asymmetry in pressure when the vehicle is at a nonzeroangle of attack that result in high BFFs. Revisions to the shock integration region were made based on computational fluid dynamics and shadowgraph video of shock motion to better represent the BFFs and reduce the high loads resulting from this environment. To more clearly understand this terminal shock environment, a second wind tunnel test was conducted with a dense distribution of 256 sensors at the terminal shock location. These sensor arrays presents a unique opportunity to observe the unsteady terminal shock environment and to characterize the impact of various integration schemes on the BFFs. This paper presents a summary of the development of BFFs for this terminal shock and a detailed analyses of shock region pressure coefficients, coherence, BFFs, shock location time histories, and power spectral density to help guide development of BFFs for other launch vehicle test and analysis programs.

Piatak, David J.↗
NASA NTRSDate not supplied

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.

FUN3D↗
NASA NTRSDate not supplied

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↗
NASA NTRS2016

Effect of Surface Pressure Integration Methodology on Launch Vehicle Buffet Forcing Functions

The 2014 test of the Space Launch System (SLS) Rigid Buffet Model conducted at the NASA Langley Transonic Dynamics Tunnel employed an extremely high number of unsteady pressure transducers. The high channel count provided an opportunity to examine the effect of transducer placement on the resulting buffet forcing functions (BFFs). Rings of transducers on the forward half of the model were employed to simulate a single-body vehicle. The impact of transducer density, circumferential distribution, and loss of a single transducer on the resulting BFFs were examined. Rings of transducers on the aft half of the SLS model were employed to examine the effect of transducer density and circumferential distribution on BFFs for a multi-body configuration. Transducer placement considerations with respect to model size, facility infrastructure, and data acquisition system capabilities, which affect the integration process, are also discussed.

Sekula, Martin K.↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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-based BFFs 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↗
NASA NTRSDate not supplied

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

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Functions (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-measurements-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 experimental-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.

buffet↗
NASA NTRS2023

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↗
NASA NTRS2019

Assessment of Buffet Forcing Function Development Process Using Unsteady Pressure Sensitive Paint

A wind tunnel test was conducted at the Ames Unitary Plan Wind Tunnel to characterize the transonic buffet environment of a generic launch vehicle forebody. The test examined a highly instrumented version of the Coe and Nute Model 11 test article first tested in the 1960s. One of the measurement techniques used during this test was unsteady pressure sensitive paint (uPSP) developed at the Arnold Engineering Development Complex. This optical measurement technique measured fluctuating pressures at over 300,000 locations on the surface of the model. The high spatial density of these measurements provided an opportunity to examine in depth the assumptions underpinning the development of buffet forcing functions (BFFs) used in the development of the Space Launch System vehicle. The comparison of discrete-measurement-based BFFs to BFFs developed by continuous surface pressure integration indicates that the current BFF development approach under predicts low frequency content of the BFFs while over predicting high frequency content. Coherence-based adjustments employed to reduce over prediction in the surface integration of discrete pressure measurements contribute to the inaccuracy of the BFFs and their implementation should be reevaluated.

Sekula, Martin K.↗
NASA NTRS2011

Comparison of Ares I-X Wind-Tunnel Derived Buffet Environment with Flight Data

The Ares I-X Flight Test Vehicle (FTV), launched in October 2009, carried with it over 243 buffet verification pressure sensors and was one of the most heavily instrumented launch vehicle flight tests. This flight test represented a unique opportunity for NASA and its partners to compare the wind-tunnel derived buffet environment with that measured during the flight of Ares I-X. It is necessary to define the launch vehicle buffet loads to ensure that structural components and vehicle subsystems possess adequate strength, stress, and fatigue margins when the vehicle structural dynamic response to buffet forcing functions are considered. Ares I-X buffet forcing functions were obtained via wind-tunnel testing of a rigid buffet model (RBM) instrumented with hundreds of unsteady pressure transducers designed to measure the buffet environment across the desired frequency range. This paper discusses the comparison of RBM and FTV buffet environments, including fluctuating pressure coefficient and normalized sectional buffet forcing function root-mean-square magnitudes, frequency content of power-spectral density functions, and force magnitudes of an alternating flow phenomena. Comparison of wind-tunnel model and flight test vehicle buffet environments show very good agreement with root-mean-square magnitudes of buffet forcing functions at the majority of vehicle stations. Spectra proved a challenge to compare because of different wind-tunnel and flight test conditions and data acquisition rates. However, meaningful and promising comparisons of buffet spectra are presented. Lastly, the buffet loads resulting from the transition of subsonic separated flow to supersonic attached flow were significantly over-predicted by wind-tunnel results.

Piatak, David J.↗
NASA NTRS2015

Overview of the Space Launch System Transonic Buffet Environment Test Program

Fluctuating aerodynamic loads are a significant concern for the structural design of a launch vehicle, particularly while traversing the transonic flight environment. At these trajectory conditions, unsteady aerodynamic pressures can excite the vehicle dynamic modes of vibration and result in high structural bending moments and vibratory environments. To ensure that vehicle structural components and subsystems possess adequate strength, stress, and fatigue margins in the presence of buffet and other environments, buffet forcing functions are required to conduct the coupled load analysis of the launch vehicle. The accepted method to obtain these buffet forcing functions is to perform wind-tunnel testing of a rigid model that is heavily instrumented with unsteady pressure transducers designed to measure the buffet environment within the desired frequency range. Two wind-tunnel tests of a 3 percent scale rigid buffet model have been conducted at the Langley Research Center Transonic Dynamics Tunnel (TDT) as part of the Space Launch System (SLS) buffet test program. The SLS buffet models have been instrumented with as many as 472 unsteady pressure transducers to resolve the buffet forcing functions of this multi-body configuration through integration of the individual pressure time histories. This paper will discuss test program development, instrumentation, data acquisition, test implementation, data analysis techniques, and several methods explored to mitigate high buffet environment encountered during the test program. Preliminary buffet environments will be presented and compared using normalized sectional buffet forcing function root-meansquared levels along the vehicle centerline.

Piatak, David J.↗
NASA NTRS2010

Ares Launch Vehicle Transonic Buffet Testing and Analysis Techniques

It is necessary to define the launch vehicle buffet loads to ensure that structural components and vehicle subsystems possess adequate strength, stress, and fatigue margins when the vehicle structural dynamic response to buffet forcing functions are considered. In order to obtain these forcing functions, the accepted method is to perform wind-tunnel testing of a rigid model instrumented with hundreds of unsteady pressure transducers designed to measure the buffet environment across the desired frequency range. The buffet wind-tunnel test program for the Ares Crew Launch Vehicle employed 3.5 percent scale rigid models of the Ares I and Ares I-X launch vehicles instrumented with 256 unsteady pressure transducers each. These models were tested at transonic conditions at the Transonic Dynamics Tunnel at NASA Langley Research Center. The ultimate deliverable of the Ares buffet test program are buffet forcing functions (BFFs) derived from integrating the measured fluctuating pressures on the rigid wind-tunnel models. These BFFs are then used as input to a multi-mode structural analysis to determine the vehicle response to buffet and the resulting buffet loads and accelerations. This paper discusses the development of the Ares I and I-X rigid buffet model test programs from the standpoint of model design, instrumentation system design, test implementation, data analysis techniques to yield final products, and presents normalized sectional buffet forcing function root-mean-squared levels.

Piatak, David J.↗
NASA NTRSDate not supplied

Validation of the Corcos Model for the Space Launch System using Unsteady Pressure Sensitive Paint

During atmospheric ascent launch vehicles (LVs) experience large dynamic loads at transonic conditions where aerodynamic buffet is most critical. To estimate buffet loads, coupled loads analyses typically utilize suitable forcing functions, called buffet forcing functions (BFFs). One of the key buffet environment contributors is the turbulent boundary layer (TBL) on the LV outer skin. The TBL-induced fluctuating pressures can be estimated using the widely-accepted Corcos model. In the context of transonic buffet, the performance of this model is not well established, partly because of lack of data. To fill this gap, NASA recently acquired extremely high-spatial-density data for the Space Launch System (SLS) vehicle, using the unsteady pressure sensitive paint (uPSP) optical measurement technique. A methodology is developed for validation of the Corcos model using these unique data, with a focus on the LV-design application. The model hypotheses are verified and the model parameters are empirically tuned. For selected panels on the vehicle, BFF coherence factors are derived based on the Corcos model and the associated panel BFFs are compared to uPSP data. It is shown that the modeled BFFs are in agreement with direct integration of uPSP data, except for regions where pressure fluctuations are spatially nonuniform. In those regions, the Corcos-based BFFs exhibit inherent limitations of BFF estimation methods that rely on discrete pressure measurements.

buffet↗