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At least 181 records · Page 10

All sources NASA NTRS DOE OSTI

NASA NTRS2016

Exhibition of Stochastic Resonance in Vestibular Perception

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transitions. Post flight sensorimotor changes include spatial disorientation, along with postural and gait instability that may degrade operational capabilities of the astronauts and endanger the crew. A sensorimotor countermeasure that mitigates these effects would improve crewmember safety and decrease risk. The goal of this research is to investigate the potential use of stochastic vestibular stimulation (SVS) as a technology to improve sensorimotor function. We hypothesize that low levels of SVS will improve sensorimotor perception through the phenomenon of stochastic resonance (SR), when the response of a nonlinear system to a weak input signal is enhanced by the application of a particular nonzero level of noise. This study aims to advance the development of SVS as a potential countermeasure by 1) demonstrating the exhibition of stochastic resonance in vestibular perception, a vital component of sensorimotor function, 2) investigating the repeatability of SR exhibition, and 3) determining the relative contribution of the semicircular canals (SCC) and otolith (OTO) organs to vestibular perceptual SR. A constant current stimulator was used to deliver bilateral bipolar SVS via electrodes placed on each of the mastoid processes, as previously done. Vestibular perceptual motion recognition thresholds were measured using a 6-degree of freedom MOOG platform and a 150 trial 3-down/1-up staircase procedure. In the first test session, we measured vestibular perceptual thresholds in upright roll-tilt at 0.2 Hz (SCC+OTO) with SVS ranging from 0-700 μA. In a second test session a week later, we re-measured roll-tilt thresholds with 0, optimal (from test session 1), and 1500 μA SVS levels. A subset of these subjects, plus naive subjects, participated in two additional test sessions in which we measured thresholds in supine roll-rotation at 0.2 Hz (SCC) and upright y-translation at 1 Hz (OTO) with SVS up to 700 μA. A sinusoidal galvanic vestibular stimulation (GVS) perceptual threshold was also measured on each test day and used to normalize the SVS levels across subjects. In roll-tilt thresholds with SVS, the characteristic SR curve was qualitatively exhibited in 10 of 12 subjects, and the improvement in motion threshold was significant in 6 subjects, indicating that optimal SVS improved passive body motion perception in a way that is consistent with classical SR theory. A probabilistic comparison to numeric simulations further validated these experimental results. On the second test session, 4 out of the 10 SR exhibitors showed repeated improvement with SVS compared to the no SVS condition. Data collection is ongoing for the last two test sessions in which SCC and OTO only perceptual motion recognition thresholds are being measured with SVS. The final results of these test sessions will give insight into whether vestibular perceptual SR can occur when only one type of vestibular sensor is sensing motion or if it is more evident when sensory integration between the SCC and OTO is occurring during the motion. The overall purpose of this research is to further quantify the effects of SVS on various sensorimotor tasks and to gain a more fundamental understanding of how SVS causes SR in the vestibular system. In the context of human space flight, results from this research will help in understanding how SVS may be practically implemented in the future as a component of a comprehensive countermeasure plan for G-transition adaptation.

Galvan-Garza, R. C.↗

NASA NTRS2016

Development and Implementation of a Generic Analysis Template for Structural-Thermal-Optical-Performance Modeling

Performance-related effects of system level temperature changes can be a key consideration in the design of many types of optical instruments. This is especially true for space-based imagers, which may require complex thermal control systems to maintain alignment of the optical components. Structural-Thermal-Optical-Performance (STOP) analysis is a multi-disciplinary process that can be used to assess the performance of these optical systems when subjected to the expected design environment. This type of analysis can be very time consuming, which makes it difficult to use as a trade study tool early in the project life cycle. In many cases, only one or two iterations can be performed over the course of a project. This limits the design space to best practices since it may be too difficult, or take too long, to test new concepts analytically. In order to overcome this challenge, automation, and a standard procedure for performing these studies is essential. A methodology was developed within the framework of the Comet software tool that captures the basic inputs, outputs, and processes used in most STOP analyses. This resulted in a generic, reusable analysis template that can be used for design trades for a variety of optical systems. The template captures much of the upfront setup such as meshing, boundary conditions, data transfer, naming conventions, and post-processing, and therefore saves time for each subsequent project. A description of the methodology and the analysis template is presented, and results are described for a simple telescope optical system.

Scola, Salvatore↗

NASA NTRS2016

Improving Fidelity of Launch Vehicle Liftoff Acoustic Simulations

Launch vehicles experience high acoustic loads during ignition and liftoff affected by the interaction of rocket plume generated acoustic waves with launch pad structures. Application of highly parallelized Computational Fluid Dynamics (CFD) analysis tools optimized for application on the NAS computer systems such as the Loci/CHEM program now enable simulation of time-accurate, turbulent, multi-species plume formation and interaction with launch pad geometry and capture the generation of acoustic noise at the source regions in the plume shear layers and impingement regions. These CFD solvers are robust in capturing the acoustic fluctuations, but they are too dissipative to accurately resolve the propagation of the acoustic waves throughout the launch environment domain along the vehicle. A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed to improve such liftoff acoustic environment predictions. The framework combines the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin (DG) solver, Loci/THRUST, developed in the same computational framework. Loci/THRUST employs a low dissipation, high-order, unstructured DG method to accurately propagate acoustic waves away from the source regions across large distances. The DG solver is currently capable of solving up to 4th order solutions for non-linear, conservative acoustic field propagation. Higher order boundary conditions are implemented to accurately model the reflection and refraction of acoustic waves on launch pad components. The DG solver accepts generalized unstructured meshes, enabling efficient application of common mesh generation tools for CHEM and THRUST simulations. The DG solution is coupled with the CFD solution at interface boundaries placed near the CFD acoustic source regions. Both simulations are executed simultaneously with coordinated boundary condition data exchange.

Liever, Peter↗

NASA NTRS2016

Sub-scale Waterflow Cavitation and Dynamic Transfer Function Testing of an Oxidizer Turbo-Pump Combined Inducer and Impeller

In 2009 and 2010, Concepts NREC prepared for and performed a series of tests on a 52% scale of a version of the Pratt & Whitney Rocketdyne J-2X Oxidizer Turbopump under a Phase III SBIR with NASA MSFC. The test article was a combined inducer and impeller, tested as a unit. This paper presents an overview of the test rig and facility, instrumentation, signal conditioning, data acquisition systems, testing approach, measurement developments, and lessons learned. Results from these tests were presented in the form of two papers at the previous JANNAF joint propulsion conference, in December of 2011.

Karon, D. M.↗

NASA NTRS2018

Examining the Ability of an FSO Receiver to Simultaneously Communicate with Multiple Transmitters

FSO (Free-Space Optical)-based communication systems experience difficulty with receiving and separating signals arising from multiple transmitters, a capability that would facilitate implementation of MIMO (Multiple-In, Multiple-Out) systems. Current implementations require multiple, distinct optical antennas, each tracking a single user, which proves bulky and costly, especially if the transmitters are moving and must be tracked. A fiber-bundle receiver has the potential to use multiple pathways, corresponding to the individual fibers within the receiver, to capture different combinations of the incoming optical signals. If the bundle provides linear combining of the optical signals from both the individual fibers in the bundle and amongst the incoming optical signals, signal processing could extract the individual signals from the combinations. In this paper, we experimentally investigate whether the fiber-bundle receiver possesses sufficient linearity of operation to allow the separation of two signals by simple processing algorithms, for both turbulent and non-turbulent conditions. Data from two distinct sources enters a single-bundle, single field of view receiver, and a basis signal from one transmitter provides the reference for performing simple subtraction-based extraction of the unknown signal from the other transmitter. The experimental results show that the receiver does operate linearly, and that the linear operation remains sufficiently intact in the presence of turbulence to extract a recognizable copy of one signal from the other. The ability of the fiber bundle receiver to mitigate turbulence effects appears to assist in maintaining this sufficient level of linearity.

Fibers↗

NASA NTRS2021

Genomic Changes Driven by Radiation-Induced DNA Damage and Microgravity in Human Cells

The space environment consists of a complex mixture of different types of ionizing radiation and altered gravity that represents a threat to humans during space missions. In particular, individual radiation sensitivity is strictly related to the risk of space radiation carcinogenesis. Therefore, in view of future missions to the Moon and Mars, there is an urgent need to estimate as accurately as possible the individual risk from space exposure to improve the safety of space exploration. In this review, we survey the combined effects from the two main physical components of the space environment, ionizing radiation and microgravity, to alter the genetics and epigenetics of human cells, considering both real and simulated space conditions. Data collected from studies on human cells are discussed for their potential use to estimate individual radiation carcinogenesis risk from space exposure.

space radiation↗

NASA NTRSDate not supplied

Influence of the Space Environment on Geopolymer Lunar Concrete

NASA is set to embark on the next era of human space exploration on the Artemis program. An eventual goal of the program is to maintain a human presence on the lunar surface. With such a goal comes the challenge of providing durable infrastructure that is suitable for the Moon and utilizes in-situ resources. Bringing materials form Earth poses a financial burden and increased safety concern. The composition of the lunar soil makes it advantageous to create a geopolymer concrete material. The lunar regolith can be used in the as found condition on the lunar surface and most of the mixing solution can be extracted form the regolith. It is envisioned than any concrete infrastructure would make use of additive manufacturing techniques with a temporary controlled environment enclosure to mitigate the harsh lunar conditions. Data is needed to benchmark how the material behaves once exposed to such an extreme environment so structural failures are mitigated.

Peter J. Collins↗

NASA NTRSDate not supplied

Exploration Extravehicular Mobility Unit (xEMU) 11 Foot Vacuum Chamber Upgrades Test Results

The Exploration Extravehicular Mobility Unit (xEMU) uncrewed 11 foot vacuum chamber testing evaluated the capabilities of the 11 foot vacuum chamber facility to support advanced spacesuit testing. The government reference design xEMU spacesuit provided a high-fidelity test article to demonstrate 11 foot vacuum chamber capabilities which included: gas loading of the chamber at varying simulated metabolic rates and open loop suit abort operations, Intravehicular Activity (IVA) vacuum access, consumables recharge, IVA vehicle-provided thermal loop cooling, and IVA vehicle-provided power. To demonstrate the xEMU airlock operations transitioning from IVA to EVA conditions without a test subject in the suit, test support equipment was developed to remotely actuate both the Exploration, Servicing, and Cooling Umbilical (ESCU) and the vacuum access umbilical. This test also evaluated the performance of the Exploration Portable Life Support System (xPLSS) at vacuum conditions. Data was collected and analyzed for carbon dioxide (CO2) scrubbing performance of the Rapid Cycle Amine (RCA) swingbed, for thermal regulation performance of the Suit Water Membrane Evaporator (SWME), and for sensor performance across the xPLSS. This paper will detail the findings of the testing performed with these upgrades which discussed previously laid out in ICES-2025-342.

Robert F Marsch↗

NASA NTRSDate not supplied

Exploration Extravehicular Mobility Unit 11 Foot Vacuum Chamber Upgrades Test Results

Robert Marsch↗

NASA NTRS2026

Effects of Multisensory Virtual Reality Nature on Affect, Presence, and Restorativeness

Virtual reality (VR) can provide access to restorative environments and sensory stimulation for individuals in isolated, confined, and extreme environments. We developed a nature-based VR intervention featuring three scenes (Garden, Forest, Beach) and examined the effects of multisensory augmentation with location-based olfactory, wind, and thermal stimuli (VR+OWT). Over a two-week period, fifty-one participants were assigned to a no-intervention control, standard audiovisual VR, or augmented VR (VR+OWT) condition. Data collection included weekly assessments of affect, stress, and cognitive performance; post-VR measures of affect, presence, and perceived restorativeness; and open-ended feedback. Both VR and VR+OWT groups produced immediate and sustained reductions in negative affect with no sustained systematic benefits on cognitive performance. The addition of olfactory, wind, and thermal stimuli enhanced presence for some scenes; however, feedback indicated that sensory mismatches and stimulus intensity occasionally detracted from the experience and may have contributed to lower coherence ratings in the VR+OWT group. In contrast, the perceived restorativeness of the VR environment was driven primarily by scene content (Garden vs Forest vs Beach) rather than the level of sensory stimulation. These findings support the potential of virtual nature to promote well-being and underscore the importance of coherence across sensory modalities for multisensory augmentation.

Virtual Reality Intervention↗

DOE OSTI2021

Weather and Random Forest-based Load Profiling Approximation Models and its Transferability across Climate Zones

This study is to provide predictive understanding of the associations of various weather attributes with residential and commercial load profiles, for a variety of climate zones and seasons. In this work, machine learning (ML) approaches were used to identify and quantify the impacts of various weather attributes on residential and commercial electricity demand and its components across the western United States. Performance and transferability of the developed ML models were then evaluated across different temperate zones (e.g., southern, middle, and northern US) and across coastal, mid-continent, and wet zones, with inputs of weather condition data from the National Oceanic and Atmospheric Administration (NOAA) at representative weather stations. The predictive models were developed based on the ranked/screened factors using the regression tree (RT) and random forest (RF) approaches, for five different scenarios (seasons).

load composite, Random Forest, regression tree, lo↗

DOE OSTI2021

Real-time Data Analytics for Condition Monitoring of Complex Industrial Systems

Modern industrial systems are now fitted with several sensors for condition monitoring. This is advantageous because these sensors can provide mass amounts of data that have the potential for aiding in tasks such as fault detection, diagnosis, and prognostics. However, the information valuable for performing these tasks is often clouded in noise and must be mined from high-dimensional data structures. Therefore, this dissertation presents a data analytics framework for performing these condition monitoring tasks using high-dimensional data. Demonstrations of this framework are detailed for challenges related to power generation systems in automobiles, power plants, and aircraft engines. These implementations leverage data collected from state-of-the-art, industry class test-rigs. Results indicate the ability of this framework to develop effective methodologies for condition monitoring of complex systems.

Peters, Benjamin↗

NASA NTRS1985

Unsteady turbulent boundary-layer experiments with rapidly changing free-stream conditions

Selected data sets produced by the Stanford Unsteady Turbulent Boundary Layer Program are compared to analytic solutions of the Stokes equations for different kinds of imposed, organized unsteadiness. Good agreement is found, qualifying the facility as one that faithfully produces flows of different prescribed unsteady conditions. Data sets from the facility are therefore considered especially suitable for comparison with predictions of turbulence models for unsteady flows. New data describing the development of an unsteady separation bubble are presented.

Brereton, G. J.↗

NASA NTRS1990

Evaluation of equilibrium turbulence for a naturally developing hypersonic boundary layer at nonadiabatic wall conditions

Experimental data for defining test conditions necessary for a naturally developing hypersonic equilibrium turbulent boundary layer are presented. The tests were conducted at nominal boundary-layer edge Mach number of 6.2 and 5.0; the adiabatic wall to actual wall temperature ratio was 5.4. The data indicate that a momentum thickness Reynold number of at least 4000 is required for an equilibrium turbulent boundary layer. Based on the above results, a test envelope defining equilibrium flow conditions for an eight-foot high-temperature tunnel in terms of the basic facility operating conditions is given for a Mach-7 nozzle configuration. Representative experimental results for two-dimensional and three-dimensional test articles are assessed, including results of complete and partial adaptation and of residual-interference calculations.

Albertson, Cindy W.↗

DOE OSTI2025

Data for: "Wall conditioning effects of boron powder injection in KSTAR with a tungsten divertor"

This data set consists of the data used to generate the figures in the paper titled "Wall conditioning effects of boron powder injection in KSTAR with a tungsten divertor" in the journal Nuclear Fusion, 2025.

boron powder injection↗

NASA NTRS1975

Reactions of astronauts under weightless conditions

Experimental data show that weightlessness conditions lasting 5 days or more (18-25) do not produce significant disturbances in physical reactions of astronauts, with the exception of some singularities in functioning of the cardiovascular system: A reduction in heart rate and somewhat large fluctuations in the physiological indicators of cutaneogalvanic reactions.

Kasyan, I. I.↗

NASA NTRS2002

Retrieval of Atmospheric and Surface Parameters from AIRS/AMSU/HSB Data Under Cloudy Conditions

New state of the art methodology is described to analyze AIRS/AMSU/HSB data in the presence of multiple cloud formations. The methodology forms the basis for the AIRS Science Team algorithm which will be used to analyze AIRS/AMSU/HSB data on EOS Aqua. The cloud clearing methodology requires no knowledge of the spectral properties of the clouds. The basic retrieval methodology is general and extracts the maximum information from the radiances, consistent with the channel noise covariance matrix. The retrieval methodology minimizes the dependence of the solution on the first guess field and the first guess error characteristics. Results are shown for AIRS Science Team simulation studies with multiple cloud formations. These simulation studies imply that clear column radiances can be reconstructed under partial cloud cover with an accuracy comparable to single spot channel noise in the temperature and water vapor sounding regions, temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 1deg K in 1 km thick layers from the surface to 700 mb, 1 km layers from 700 mb to 300 mb, 3 km layers from 300 mb to 30 mb, and 5 km layers from 30 mb to 1 mb, and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 1 km layers from the surface to nearly 200 mb.

Susskind, Joel↗

DOE OSTI2025

Pavement condition and climatic data in southeast Texas: A dataset for evaluating flood impacts on pavement performance

Effective pavement maintenance is essential for economic stability, optimal network performance, and roadway safety. Achieving this requires thorough evaluation of pavement conditions, including structural integrity, surface roughness, and distress characteristics. Pavement performance indicators play a critical role in influencing vehicle safety and ride quality. Recent advances have emphasized the use of data-driven modeling to anticipate pavement behavior, with the goal of optimizing resource allocation and refining Maintenance and Rehabilitation (M&R) strategies through accurate condition assessment. A foundational requirement for these modeling efforts is the availability of standardized, high-quality datasets that can support robust and reproducible infrastructure analysis. This data article presents a comprehensive dataset assembled to facilitate pavement performance prediction, with a geographic focus on Southeast Texas, particularly the flood-vulnerable area of Beaumont. The dataset encompasses pavement and traffic attributes, meteorological records, flood simulation outputs, ground deformation measurements, and topographic indices, enabling detailed examination of both load-associated and non-load-associated degradation mechanisms. Data preprocessing was performed using ArcGIS Pro, Microsoft Excel, and Python to ensure consistency and usability in data-driven modeling applications, including machine learning workflows. Key contributions of this dataset include its utility in analyzing the climatic and environmental factors affecting pavement conditions, identifying critical predictive features, and enabling in-depth correlation analysis across diverse variables. By filling existing gaps in input variable selection resources, this dataset supports the development of predictive tools for estimating future maintenance demand and enhancing the resilience of pavement networks in flood-impacted areas. The resource highlights the importance of standardized datasets for advancing pavement management practices and provides a robust foundation for ongoing infrastructure performance modeling.

42 ENGINEERING↗