ALBERT

Description: The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has led the design and build of the new world-class vibroacoustic test capabilities at the NASA GRC's Plum Brook Station in Sandusky, Ohio, USA from 2007-2011. SAIC-Benham has completed construction of a new reverberant acoustic test facility to support the future testing needs of NASA's space exploration program and commercial customers. The large Reverberant Acoustic Test Facility (RATF) is approximately 101,000 cu ft in volume and was designed to operate at a maximum empty chamber acoustic overall sound pressure level (OASPL) of 163 dB. This combination of size and acoustic power is unprecedented amongst the world's known active reverberant acoustic test facilities. Initial checkout acoustic testing was performed on March 2011 by SAIC-Benham at test levels up to 161 dB OASPL. During testing, several branches of the gaseous nitrogen (GN2) piping system, which supply the fluid to the noise generating acoustic modulators, failed at their "t-junctions" connecting the 12 inch supply line to their respective 4 inch branch lines. The problem was initially detected when the oxygen sensors in the horn room indicated a lower than expected oxygen level from which was inferred GN2 leaks in the piping system. In subsequent follow up inspections, cracks were identified in the failed "t-junction" connections through non-destructive evaluation testing . Through structural dynamic modeling of the piping system, the root cause of the "t-junction" connection failures was determined. The structural dynamic assessment identified several possible corrective design improvements to the horn room piping system. The effectiveness of the chosen design repairs were subsequently evaluated in September 2011 during acoustic verification testing to 161 dB OASPL.

Description: The NASA Engineering and Safety Center (NESC) and Lockheed Martin (LM) performed random vibration testing on a single spring strut development unit to assess its ability to withstand qualification level random vibration environments. Failure of the strut while exposed to random vibration resulted in a follow-on failure investigation, design changes, and additional development tests. This paper focuses on the results of the failure investigations referenced in detail in the NESC final report [1] including identified lessons learned to aid in future design iterations of the spring strut and to help other mechanism developers avoid similar pitfalls.

Description: The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has led the design and build of the new world-class vibroacoustic test capabilities at the NASA GRC's Plum Brook Station in Sandusky, Ohio, USA from 2007 to 2011. SAIC-Benham has completed construction of a new reverberant acoustic test facility to support the future testing needs of NASA's space exploration program and commercial customers. The large Reverberant Acoustic Test Facility (RATF) is approximately 101,000 cubic feet in volume and was designed to operate at a maximum empty chamber acoustic overall sound pressure level (OASPL) of 163 dB. This combination of size and acoustic power is unprecedented amongst the world s known active reverberant acoustic test facilities. Initial checkout acoustic testing was performed on March 2011 by SAIC-Benham at test levels up to 161 dB OASPL. During testing, several branches of the gaseous nitrogen (GN2) piping system, which supply the fluid to the noise generating acoustic modulators, failed at their T-junctions connecting the 12 in. supply line to their respective 4 in. branch lines. The problem was initially detected when the oxygen sensors in the horn room indicated a lower than expected oxygen level from which was inferred GN2 leaks in the piping system. In subsequent follow up inspections, cracks were identified in the failed T-junction connections through non-destructive evaluation testing. Through structural dynamic modeling of the piping system, the root cause of the T-junction connection failures was determined. The structural dynamic assessment identified several possible corrective design improvements to the horn room piping system. The effectiveness of the chosen design repairs were subsequently evaluated in September 2011 during acoustic verification testing to 161 dB OASPL.

Description: The semi-empirical force-limited vibration method was developed and implemented for payload testing to limit the structural impedance mismatch (high force) that occurs during shaker vibration testing. The method has since been extended for use in analytical models. The Space Communications and Navigation Testbed (SCAN Testbed), known at NASA Glenn Research Center (GRC) as, the Communications, Navigation, and Networking re-Configurable Testbed (CoNNeCT) project utilized force-limited testing and analysis following the semi-empirical approach. This presentation presents the steps in performing a force-limited analysis and then compares the results to test data recovered during the CoNNeCT force-limited random vibration qualification test that took place at NASA Glenn Research Center (GRC) in the Structural Dynamics Laboratory (SDL) December 19, 2010 - January 7, 2011. A compilation of lessons learned and considerations for future force-limited tests is also included.

Description: Recently, the MPCV Orion European Service Module Structural Test Article (E-STA) underwent sine vibration testing using the multi-axis shaker system at NASA GRC Plum Brook Station Mechanical Vibration Facility (MVF). An innovative approach using measured constraint shapes at the interface of E-STA to the MVF allowed high-quality fixed base modal parameters of the E-STA to be extracted, which have been used to update the E-STA finite element model (FEM), without the need for a traditional fixed base modal survey. This innovative approach provided considerable program cost and test schedule savings. This paper documents this modal survey, which includes the modal pretest analysis sensor selection, the fixed base methodology using measured constraint shapes as virtual references and measured frequency response functions, and post-survey comparison between measured and analysis fixed base modal parameters.

Description: Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber (DEA) under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. The presence of this energy absorbing device reduced the peak impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to a system-integrated finite element model of the test article developed in parallel with the test program. In preparation for the full-scale crash test, a series of sub-scale and MD-500 mass simulator tests were conducted to evaluate the impact performances of various components and subsystems, including new crush tubes and the DEA blocks. Parameters defined for the system-integrated finite element model were determined from these tests. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the full-scale crash test without the DEA. This combination of heuristic and quantitative methods identified modeling deficiencies, evaluated parameter importance, and proposed required model changes. The multidimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and copilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. One lesson learned was that this approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and pretest predictions. Complete crash simulations with validated finite element models can be used to satisfy crash certification requirements, potentially reducing overall development costs.

Description: The objective of this challenge is to develop a data-based probabilistic model of uncertainty to predict the behavior of subsystems (payloads) by themselves and while coupled to a primary (target) system. Although this type of analysis is routinely performed and representative of issues faced in real-world system design and integration, there are still several key technical challenges that must be addressed when analyzing uncertain interconnected systems. For example, one key technical challenge is related to the fact that there is limited data on target configurations. Moreover, it is typical to have multiple data sets from experiments conducted at the subsystem level, but often samples sizes are not sufficient to compute high confidence statistics. In this challenge problem additional constraints are placed as ground rules for the participants. One such rule is that mathematical models of the subsystem are limited to linear approximations of the nonlinear physics of the problem at hand. Also, participants are constrained to use these models and the multiple data sets to make predictions about the target system response under completely different input conditions. Our approach involved initially the screening of several different methods. Three of the ones considered are presented herein. The first one is based on the transformation of the modal data to an orthogonal space where the mean and covariance of the data are matched by the model. The other two approaches worked solutions in physical space where the uncertain parameter set is made of masses, stiffnesses and damping coefficients; one matches confidence intervals of low order moments of the statistics via optimization while the second one uses a Kernel density estimation approach. The paper will touch on all the approaches, lessons learned, validation 1 metrics and their comparison, data quantity restriction, and assumptions/limitations of each approach. Keywords: Probabilistic modeling, model validation, uncertainty quantification, kernel density

Description: The history of structural dynamics testing research over the past four decades at the Langley Research Center of the National Aeronautics and Space Administration is reviewed. Beginning in the early sixties, Langley investigated several scale model and full-scale spacecraft including the NIMBUS and various concepts for Apollo and Viking landers. Langley engineers pioneered the use of scaled models to study the dynamics of launch vehicles including Saturn I, Saturn V, and Titan III. In the seventies, work emphasized the Space Shuttle and advanced test and data analysis methods. In the eighties, the possibility of delivering large structures to orbit by the Space Shuttle shifted focus towards understanding the interaction of flexible space structures with attitude control systems. Although Langley has maintained a tradition of laboratory-based research, some flight experiments were supported. This review emphasizes work that, in some way, advanced the state of knowledge at the time.

Description: NASA and its contractors are working on structural concepts for absorbing impact energy of aerospace vehicles. Recently, concepts in the form of multi-cell honeycomb-like structures designed to crush under load have been investigated for both space and aeronautics applications. Efforts to understand these concepts are progressing from tests of individual cells to tests of systems with hundreds of cells. Because of fabrication irregularities, geometry irregularities, and material properties uncertainties, the problem of reconciling analytical models, in particular LS-DYNA models, with experimental data is a challenge. A first look at the correlation results between single cell load/deflection data with LS-DYNA predictions showed problems which prompted additional work in this area. This paper describes a computational approach that uses analysis of variance, deterministic sampling techniques, response surface modeling, and genetic optimization to reconcile test with analysis results. Analysis of variance provides a screening technique for selection of critical parameters used when reconciling test with analysis. In this study, complete ignorance of the parameter distribution is assumed and, therefore, the value of any parameter within the range that is computed using the optimization procedure is considered to be equally likely. Mean values from tests are matched against LS-DYNA solutions by minimizing the square error using a genetic optimization. The paper presents the computational methodology along with results obtained using this approach.

Description: The present work addresses the development of an experimental and computational procedure for validating finite element models. A torus structure, part of an inflatable/rigidizable Hexapod, is used to demonstrate the approach. Because of fabrication, materials, and geometric uncertainties, a statistical approach combined with optimization is used to modify key model parameters. Static test results are used to update stiffness parameters and dynamic test results are used to update the mass distribution. Updated parameters are computed using gradient and non-gradient based optimization algorithms. Results show significant improvements in model predictions after parameters are updated. Lessons learned in the areas of test procedures, modeling approaches, and uncertainties quantification are presented.