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At least 613 records · Page 34

Spectral Analysis of Integrated Pressures on Patches with Unsteady Pressure-Sensitive Paint Measurements

This paper describes the spectral analysis of integrated pressures on patches of the scale model of the Space Launch System Block 1 cargo vehicle with the Unsteady Pressure-Sensitive Paint measurements, which were collected in the ascent transient aerodynamics test with the Unitary Plan Wind Tunnel 11-by-11-foot Transonic Wind Tunnel in September 2019 at NASA Ames Research Center. The patches are defined with x station values, indicating the position along length of the vehicle, and azimuth angles of the scale model. For each patch, the polygons are determined from the surface cells of the grid of the model, clipped with the edges of the patch, and each of the polygons is divided into triangles. The integrated pressure of the patch is determined as the ratio of the sum of the forces on the triangles over the sum of the areas of the triangles. For each run of the test, the cross power spectral density and magnitude squared coherence are computed from the time series of the integrated pressures on the patches. The results of pressure integration and spectral analysis are presented, and the data consistency of the test is demonstrated. The work described in this paper is a part of NASA’s development of a new state-of-the-art uPSP capability in production wind tunnels. Funding for this research was provided by the NASA Aeroscience Evaluation and Test Capabilities Project.

Pressure-Sensitive Paint↗

SLS Integrated Modal Test Uncertainty Quantification using the Hybrid Parametric Variation Method

Uncertainty in structural loading during launch is a significant concern in the development of spacecraft and launch vehicles. Small variations in launch vehicle and payload mode shapes and their interaction can result in significant variation in system loads. In many cases involving large aerospace systems it is difficult, not economical, or impossible to perform a system modal test. However, it is still vital to obtain test results that can be compared with analytical predictions to validate models. Instead, the “Building Block Approach” is used in which system components are tested individually. Component models are correlated and updated to agree as best they can with test results. The Space Launch System consists of a number of components that are assembled into a launch vehicle. Finite element models of the components are developed, reduced to Hurty/Craig-Bampton models and assembled to represent different phases of flight. The only opportunity to obtain modal test data from an assembled Space Launch System will be during the Integrated Modal Test. There is always uncertainty in every model, which flows into uncertainty in predicted system results. Uncertainty Quantification is used to determine statistical bounds on prediction accuracy based on model uncertainty. For the Space Launch System, model uncertainty is at the Hurty/Craig-Bampton component level. Uncertainty in the Hurty/Craig-Bampton components is quantified using the hybrid parametric variation approach that combines parametric and nonparametric uncertainty. Uncertainty in model form is one of the biggest contributors to uncertainty in complex built-up structures. This type of uncertainty cannot be represented by variations infinite element model input parameters and thus cannot be included in a parametric approach. However, model-form uncertainty can be modeled using a nonparametric approach based on random matrix theory. The hybrid parametric variation method requires the selection of dispersion values for the Hurty/Craig-Bampton fixed-interface eigenvalues, and the Hurty/Craig-Bampton stiffness matrices. Component test/analysis frequency error is used to identify the fixed-interface eigenvalue dispersions, while test/analysis cross-orthogonality is used to identify stiffness dispersion values. The hybrid parametric variation uncertainty quantification approach is applied to the Space Launch System Integrated Modal Test configuration. Monte Carlo analysis is performed, and statistics are determined for modal correlation metrics, frequency response from Integrated Modal Test shakers to selected accelerometers, as well as other metrics for determining how well target modes are excited and identified. If the predicted uncertainty envelopes future Integrated Modal Test results, then there will be increased confidence in the utility of the component-based hybrid parametric variation uncertainty quantification approach.

Uncertainty Quantification↗

NASA Space Launch System Prepares for Key Hotfire Test Before Vehicle Integration

NASA this year is working toward the final major integrated hardware and avionics test for its Space Launch System (SLS), the agency’s new super heavy-lift vehicle to send large, strategic payloads to the Moon, Mars and beyond. As the backbone of the Artemis human lunar exploration program, Artemis I SLS operations will then shift to the launch site and integration for the inaugural mission. For this final major test of the first vehicle NASA has built exclusively for deep space exploration since the Saturn V, a NASA/Boeing/Aerojet Rocketdyne team will conduct the final core stage “green run” test at NASA's Stennis Space Center with a dramatic firing of all four core stage engines. This test will validate the operation of the stage structures, main propulsion system, engines, avionics, and software. Following data review, stage inspection, and refurbishment, the stage will be barged to NASA’s Kennedy Space Center to continue integration of the Artemis I launch vehicle. Already underway is assembly of the mission’s five-segment solid rocket boosters. The mission’s upper stage and spacecraft adapters also are staged at the launch site ready for integration. Even as the Artemis I SLS proceeds toward launch later this year, the Artemis II and Artemis III vehicles are coming together, with core stages, engines, boosters, upper stage, and payload accommodations in various stages of manufacturing and/or processing. Planning is also underway for additional core stages and a new, more powerful upper stage that will increase lunar payload mass. SLS is the anchor transportation leg of a plan for sustained human exploration of the Moon, including the first human landing later in the decade. This paper will discuss SLS progress to date and expected 2021 milestones.

Bruce R. Askins↗

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗

DIP Architecture and Data Integration Services

This workshop will cover DIP architecture and data integration services. Participants will get a look at how the DIP architecture is set-up as well as how data integration services are planned to be hosted on the platform. The DIP architecture review is intended to cover how DIP was envisioned and how DIP is being developed to address data needs across the industry. Participants will have a chance to provide feedback on the DIP architecture and gain insight into how one might interface with the DIP to send or receive data. The data integration services portion is intended to cover DIP’s technical approach to data integration. As an example implementation, there will be a first look at possible data fusion on the platform, including utilizing NASA’s Fuser, and tailoring for industry data consumers. Descriptions, at a high-level, of input to and output of the Fuser will also be discussed.

ATM-X↗

Recap of DIP Workshop Series: #1 DIP Architecture and Data Integrations Services

This workshop will cover DIP architecture and data integration services to obtain feedback from America for Airlines (A4A) Air Traffic Management Council (ATMC). Participants will get a look at how the DIP architecture is set-up as well as how data integration services are planned to be hosted on the platform. The DIP architecture review is intended to cover how DIP was envisioned and how DIP is being developed to address data needs across the industry. Participants will have a chance to provide feedback on the DIP architecture and gain insight into how one might interface with the DIP to send or receive data. The data integration services portion is intended to cover DIP’s technical approach to data integration. As an example implementation, there will be a first look at possible data fusion on the platform, including utilizing NASA’s Fuser, and tailoring for industry data consumers. Descriptions, at a high-level, of input to and output of the Fuser will also be discussed.

ATM-X↗

Integrating the Science Opportunity Analyzer with a Reusable Opportunity Search Framework

In our interactions with the Science Opportunity Analyzer (SOA) software, we recognized how its ability to search for geometric events in space is a need for robotic space missions in general. To satisfy this need, we propose the Tychonis framework, which is built upon the principles of: (1) separations of concerns, (2) extensibility, (3) reusability, and (4) independent verification and validation. Tychonis’ separation of concerns results in the availability of different constructs to model geometric events and search for them. These constructs can be extended by users as needed and reused across missions without changes. Given the low coupling between concerns, and the fact Tychonis can be augmented in isolation, its constructs can be validated independently from other pieces of software. This paper elaborates on these topics and presents an integration case study between Tychonis and SOA that relies on the concept of dynamic integration. Dynamic integration entails that augmentations of the framework are reflected automatically in the host application without any changes to the host application’s code. The SOA-Tychonis integration case study can be extrapolated to other tools that need to search for geometric events as the pattern repeats across implementations: (i) the manipulation of a user interface to model opportunities, (ii) the execution of algorithms to search for opportunities, and (iii) the presentation of search results to users. Overall, Tychonis’ is a story about how the application of proven software principles and good design choices can reduce risk and cost to space missions

Soria, Manel↗

An Integrated Recursive Framework for Arbitrarily Multiscale and Multi-fidelity Modeling

The NASA Multiscale Analysis Tool (NAMSAT) serves as a state-of-the-art, “plug and play,” massively multiscale modeling (M3) platform for hierarchical materials and structures. The development of NASMAT has focused on modularity, upgradability and maintainability, interoperability, and utility. Application Program Interfaces (APIs) have been developed to facilitate the integration NASMAT into other programs (commercial, research, and user-defined) as well as the integration of other codes into NASMAT. NASMAT is an integrated, recursive platform that seamlessly allows for an arbitrary number of scales, and a variety of modeling fidelity, in a single, non-linear analysis. Thus, the macroscopic response of a material can be directly linked to the behavior of the microstructure(s), including subscale defects, making it a suitable tool for integrated computational materials engineering (ICME) because . Examples using NASMAT for simulation of polycrystalline metals at elevated temperatures will be presented.

Multiscale Modeling↗

Towards Integrated Computational Materials Engineering for Quantifying Performance Impacts of Microstructure and Defect Interactions in Powder Bed Fusion Parts

Powder bed fusion (PBF) additive manufacturing (AM) enables the creation of parts with complexity and functionality levels that were previously impossible with traditional manufacturing methods. By modifying the laser power, hatch spacing, or the numerous other processing parameters, the PBF process supports the production of a wide set of materials and geometries. However, that same process parameter design flexibility causes the process-design space of PBF to be massive and expensive to explore experimentally. Another challenge is quality variation across a build. As a part is being built, geometric variance between locations, such as at a thin-wall section vs. the bulk material, may cause the specified processing parameters to no longer be acceptable for producing defect-free printing. Furthermore, if the processing parameters deviate during the print process, it is difficult to assess if the part will still perform satisfactorily. Integrated Computational Materials Engineering (ICME) provides a way to understand and address these various challenges. This talk will present advancements in process-structure simulations of PBF at NASA Langley Research Center. The ability to simulate grain-scale PBF microstructures using the Physically Based Monte Carlo method will be demonstrated and compared to experimental measurements. Techniques for simulating three-dimensional lack-of-fusion and keyhole porosity defects based on the specific processing conditions and approaches for integrating the two porosity prediction techniques alongside the computational microstructure evolution models will be shown. Finally, the integration of simulated PBF microstructures, embedded process defects, and crystal plasticity finite element models to elucidate the interaction of porosity and microstructure on micromechanical fields will be demonstrated. These integrated techniques demonstrate an example of using ICME to relate processing to performance for PBF AM materials. With continued maturity, it is hoped that such ICME approaches will lead to next-generation computational-materials supported qualification and certification of AM parts.

Additive manufacturing↗

Obtaining Accurate Derivatives Across Adaptive-Step Integration

Obtaining derivatives through the integration of a set of ordinary differential equations is of interest to a number of fields of research. Approaches for doing so that are available in the literature, however, do not account for details associated with variable step integrator that cause inaccuracies in the total derivatives. In this paper, we explore the causes of the accumulation of derivative error in adaptive-step Runge-Kutta integration schemes and propose a solution to eliminate them. The new algorithm proposed is a transformation of each step of a Runge-Kutta integration into a set of residual equations. This work demonstrates the improvement in accuracy of total derivatives when the new algorithm is utilized.

Kaushik Ponnapalli↗

Testing the Effectiveness of Integrated Plume Shield for a Hall Thruster

Hall thrusters have been shown to exhibit side plumes with varying degree of erosive power. This article presents the concept of the integrated plume shield for the purpose of mitigating the erosive power of said side plume. A test was conducted on a low-power Hall thruster with and without integrated plume shield and the effect on thruster performance and plume characteristics were measured. Collected data shows that the thruster performed identically to within uncertainty in terms of thrust, specific impulse, and discharge oscillation characteristics. Plume measurements showed up to a 48% reduction in ion current density when averaging over 80° to 105° from the firing axis. A brief analytical study was performed to determine the advantages and disadvantages of using integrated plume shield as opposed to using spacecraft surface covering and placing thrusters on booms. The integrated plume shield was found to provide varying level of advantages in mass, design restrictions, and complexity, which are likely to lead to major cost savings in the long term.

Electric Propulsion↗

(ODIN): An Open Source, Low-Latency Data Integration & Visualization Framework for the NASA System Wide Safety Project's Disaster Response Safety Demonstration Series

The Open Data Integration Framework (ODIN) is an open source, low latency data integration and visualization framework (https://github.com/NASARace/race-odin) developed under NASA’s System WideSafety Program to demonstrate new safety capabilities designed to improve US airspace operations. Safety demonstrations are a set of increasingly complex (from public safety perspective) disaster response scenarios under which air systems must operate with increased capacity and include: 1) Wildland fire response, 2) Hurricane relief and recovery, 4) Emergency medical delivery via UAS and 4) Urban disaster relief. To accommodate disaster response, ODIN is field deployable and can scale on one or more multi-core, commodity laptops operating with full to limited or intermittent internet connectivity, conditions likely encountered during operations. ODIN runs as webserver with local, persistent data storage to serve either public or a secured, ad hoc network (e.g., an incident command post). The current released ODIN, ODIN-Fire is tailored for wildland fire management incorporating information on satellite overpasses with links to the near real-time data and imagery from the respective agencies. Included are winds data, an important variable for emergency responders and airspace operations, and high-resolution wind forecasts generated by super-computing resources and ingested into ODIN. As an open-source project, ODIN has attracted interest from multiple entities. We will show how 1) a commercial field instrument and data provider uses ODIN to help users visualize, publish and integrate their in-situ sensor network data and 2) ODIN’s capabilities to ingest, integrate and display near-real time satellite data with air traffic and a USFS winds forecast model used in fire response and post-fire assessment. Within NASA ODIN demonstrated novel, near terminal airspace safety capabilities for a project close-out event and previously it monitored the national airspace in real-time to meet an agency milestone. ODIN is presently under development for the anticipated hurricane relief and response demonstration notionally scheduled for the 2025-27 time frame and is available from NASA's github at the above link.

Aeronautics↗

xEMU Suit Integrated Audio Communications System: Ambient and EVA Pressure Testing System Performance

Testing across several airlock and EVA thermal and pressure scenarios has demonstrated that the Integrated Audio System of NASA’s Exploration Extravehicular Mobility Unit (xEMU) spacesuits transmits and receives intelligible audio communications without the use of a commcap or similar worn device. The xEMU audio system consists of internal loudspeakers and digital microphones (Integrated Communications System –ICS) combined with an adaptive Acoustic Echo Canceller (AEC), outbound voice operated transmission (VOX), and automatic gain control (AGC). Transducers are mounted in an “exploded commcap” configuration with helmet-attached speakers near the ears and three microphones positioned at the collar. The AGC removes inbound audio signals (e.g.,suit, Mission Control, Lander, C&W tones) from the outbound comms stream, reducing echo and feedback (squeal) in low-noise suit environments. The reduction of worn communication equipment increases crewmember comfort, range of movement, and situational awareness. However, test results also highlight the need for proper fan, duct, pump, and gas flow integration with suit acoustics and audio. Ductwork may serve as waveguides for various component and structure-borne noise. Sharply angled ducts can generate turbulent-flow noise. Gas flow from inlets above the crewmember’s head can generate noise when cascading over the faceplate and collar (or commcap) microphones. Sufficient acoustic noise levels (1) require increased gain to boost inbound audio, and (2) may distort signals resulting in AEC disruption or artifacts. Suit-noise levels decline with reduced pressure (density), but then elevated speech and audio effort/power become necessary. Whether the Integrated Audio System, commcap, or other device is used, suit acoustic noise can mask speech in outbound comms. This reduces intelligibility and requires other AECs/devices to suppress comms noise. Yet, adjusting a few components may yield significant improvement. We discuss xEMU audio functionality, demonstrate how acoustical treatment combined with inbound signal conditioning improved clarity during tests, and discuss future modifications.

xEMU↗

Overview of Integrated Random Vibration Testing of the NASA Orion Crew Survival Suit

The launch ascent and abort random vibration environments from NASA’s Orion spacecraft drove the need to test the NASA Orion Crew Survival Suit as an integrated system with exposure to the design levels. In order to properly characterize component responses, a series of integrated tests were designed to incorporate the interaction between a crew member, suit, seat, and the attenuation system. The first Development Test (2017) included human subjects, and was performed with early development seat and suit components, and low level inputs. It provided a baseline for frequency response and behavior of the integrated system. The next two tests, Development Test (2019) and Qualification Test (2020), used manikin surrogates to represent the crew member and increasing levels of component hardware fidelity in order to test to higher input levels. Testing was performed at NASA Johnson Space Center (JSC) and Kennedy Space Center (KSC) Vibration Labs and provided the input levels required to represent the ascent and abort vehicle profiles as well as recorded component response behavior from accelerometer instrumentation and high speed cameras. Inspection of the suit and related components showed that for all seat orientations, and input environments, no damage occurred. Additional pre and post-test checks confirmed the functionality of all suited hardware. Response data of the suited components generally showed heavy attenuation across most of the tested frequency range. Transmissibility plots showed some amplification of components at lower frequency ranges. Overall this series of integrated tests showed that 1) the use of surrogate manikins in the tests were adequate for representing crew in a vibration environment, 2) full vibration levels for ascent and abort were heavily attenuated in the suit components and were non-damaging, and 3) the suit and related components are qualified for the Orion random vibration environments.

Jeffrey D Suhey↗

On the Integration of Loudness Over Time for the Prediction of Single-Event Annoyance

Loudness is the quality of human perception that is most related to acoustic intensity and energy, however there is no agreed-upon way of integrating loudness over time for the prediction of noise-induced annoyance. Most noise metrics used today for aircraft certification and regulation employ the “Equal-Energy Hypothesis” (EEH) and sum the acoustical energy of one or more noise events over time to create a single metric value that represents the entire exposure. Using the EEH creates a natural tradeoff between the peak energy and the duration of a single noise event, the “hypothesis” being that this tradeoff optimally predicts annoyance in a wide variety of situations. This work proposes a strategy for integrating a loudness-like time series which is flexible in two ways: First, it includes a parameter b ∈ [0,1]. When b = 0, the metric will return the peak of the time series. At b = .5, the metric will behave in accordance with the EEH. At b = 1, the metric will penalize the duration of the sound more than the EEH would. Second, transformations are given so that the strategy can be computed from, or generate quantities in units analogous to, decibels (or phon), physical units (acoustic pressure/power), or perceptually-scaled units (sone). This approach is demonstrated on a dataset of annoyance responses to single events of UAV and road vehicle noise that is fit with an augmented linear regression. Analyses based on this integration of A-weighted level and the output of the “Zwicker” loudness model yield similar results: that subjects may have been slightly more sensitive to the durations of the events than the EEH would suppose, but that the EEH cannot be disproven using these data. The time-integrated metrics outperform both time-averaged and centile-based metrics.

Psychoacoustics↗

xEMU Suit Integrated Audio Communications System: Ambient and EVA Pressure Testing System Performance

Testing across several airlock and EVA thermal and pressure scenarios has demonstrated that the Integrated Audio System of NASA’s Exploration Extravehicular Mobility Unit (xEMU) spacesuits transmits and receives intelligible audio communications without the use of a commcap or similar worn device. The xEMU audio system consists of internal loudspeakers and digital microphones (Integrated Communications System –ICS) combined with an adaptive Acoustic Echo Canceller (AEC), outbound voice operated transmission (VOX), and automatic gain control (AGC). Transducers are mounted in an “exploded commcap” configuration with helmet-attached speakers near the ears and three microphones positioned at the collar. The AGC removes inbound audio signals (e.g.,suit, Mission Control, Lander, C&W tones) from the outbound comms stream, reducing echo and feedback (squeal) in low-noise suit environments. The reduction of worn communication equipment increases crewmember comfort, range of movement, and situational awareness. However, test results also highlight the need for proper fan, duct, pump, and gas flow integration with suit acoustics and audio. Ductwork may serve as waveguides for various component and structure-borne noise. Sharply angled ducts can generate turbulent-flow noise. Gas flow from inlets above the crewmember’s head can generate noise when cascading over the faceplate and collar (or commcap) microphones. Sufficient acoustic noise levels (1) require increased gain to boost inbound audio, and (2) may distort signals resulting in AEC disruption or artifacts. Suit-noise levels decline with reduced pressure (density), but then elevated speech and audio effort/power become necessary. Whether the Integrated Audio System, commcap, or other device is used, suit acoustic noise can mask speech in outbound comms. This reduces intelligibility and requires other AECs/devices to suppress comms noise. Yet, adjusting a few components may yield significant improvement. We discuss xEMU audio functionality, demonstrate how acoustical treatment combined with inbound signal conditioning improved clarity during tests, and discuss future modifications.

xEMU↗

Overview of Integrated Random Vibration Testing of the NASA Orion Crew Survival Suit

The launch ascent and abort random vibration environments from NASA’s Orion spacecraft drove the need to test the NASA Orion Crew Survival Suit as an integrated system with exposure to the design levels. In order to properly characterize component responses, a series of integrated tests were designed to incorporate the interaction between a crew member, suit, seat, and the attenuation system. The first Development Test (2017) included human subjects, and was performed with early development seat and suit components, and low level inputs. It provided a baseline for frequency response and behavior of the integrated system. The next two tests, Development Test (2019) and Qualification Test (2020), used manikin surrogates to represent the crew member and increasing levels of component hardware fidelity in order to test to higher input levels. Testing was performed at NASA Johnson Space Center (JSC) and Kennedy Space Center (KSC) Vibration Labs and provided the input levels required to represent the ascent and abort vehicle profiles as well as recorded component response behavior from accelerometer instrumentation and high speed cameras. Inspection of the suit and related components showed that for all seat orientations, and input environments, no damage occurred. Additional pre and post-test checks confirmed the functionality of all suited hardware. Response data of the suited components generally showed heavy attenuation across most of the tested frequency range. Transmissibility plots showed some amplification of components at lower frequency ranges. Overall this series of integrated tests showed that 1) the use of surrogate manikins in the tests were adequate for representing crew in a vibration environment, 2) full vibration levels for ascent and abort were heavily attenuated in the suit components and were non-damaging, and 3) the suit and related components are qualified for the Orion random vibration environments.

Jeffrey Suhey↗

On the Integration of Loudness Over Time for the Prediction of Single-Event Annoyance

Loudness is the quality of human perception that is most related to acoustic intensity and energy, however there is no agreed-upon way of integrating loudness over time for the prediction of noise-induced annoyance. Most noise metrics used today for aircraft certification and regulation employ the “Equal-Energy Hypothesis” (EEH) and sum the acoustical energy of one or more noise events over time to create a single metric value that represents the entire exposure. Using the EEH creates a natural tradeoff between the peak energy and the duration of a single noise event, the “hypothesis” being that this tradeoff optimally predicts annoyance in a wide variety of situations. This work proposes a strategy for integrating a loudness-like time series which is flexible in two ways: First, it includes a parameter b ∈ [0,1]. When b = 0, the metric will return the peak of the time series. At b = .5, the metric will behave in accordance with the EEH. At b = 1, the metric will penalize the duration of the sound more than the EEH would. Second, transformations are given so that the strategy can be computed from, or generate quantities in units analogous to, decibels (or phon), physical units (acoustic pressure/power), or perceptually-scaled units (sone). This approach is demonstrated on a dataset of annoyance responses to single events of UAV and road vehicle noise that is fit with an augmented linear regression. Analyses based on this integration of A-weighted level and the output of the “Zwicker” loudness model yield similar results: that subjects may have been slightly more sensitive to the durations of the events than the EEH would suppose, but that the EEH cannot be disproven using these data. The time-integrated metrics outperform both time-averaged and centile-based metrics.

Psychoacoustics↗