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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2019

Motion Cueing for Stall Recovery Training in Commercial Transport Simulators

Starting in 2019, airline pilots will be required to perform full stall recovery training in flight simulators. Historically, training simulators weren't required to provide training at conditions outside their normal flight envelope. Post-stall aircraft models are generally required to be implemented to simulate the aircraft response after the stall point. In addition, motion cues need to adequately represent this response to ensure the skills learned in simulator training are directly usable in real flight. This paper provides and overview of six simulator experiments conducted at NASA Ames Research Center to develop a motion cueing strategies for stall recovery training in commercial transport simulators. One of the experiments verified an enhanced motion cueing strategy for stall recovery training on a level-D-certified full flight simulator. This study showed that the enhanced motion results in lower maximum roll angles in the stall maneuver, lower minimum load factors in the recovery, lower numbers of secondary stick shakers in the stall recovery, and a lower maximum airspeed in the recovery. These results indicate that relatively minor enhancements to the motion logic of heritage commercial transport simulators can significantly improve pilot performance in simulated stall recoveries, and potentially improve stall recovery training.

stall recovery↗
NASA NTRS2018

A Quantitative Analysis of Systematic Differences in the Positions and Proper Motions of Gaia DR2 with Respect to VLBI

We have analysed the differences in positions of 9081 matched sources between the GaiaData Release 2 (DR2) and very long baseline interferometry (VLBI) catalogues. The medianposition uncertainty of matched sources in the VLBI catalogue is a factor of two larger thanthe median position uncertainty in Gaia DR2. There are 9 per cent matched sources withstatistically significant offsets between both catalogues. We found that the reported positionalerrors should be rescaled by a factor of 1.3 for VLBI and 1.06 for Gaia and, in addition, the Gaiaerrors should be multiplied by the square root of chi squared per degree of freedom in order tobest fit the normalized position differences to the Rayleigh distribution. We have establishedthat the major contributor to statistically significant position offsets is the presence of opticaljets. Among the sources for which the jet direction was determined, the position offsets areparallel to the jet directions for 62 per cent of the outliers. Among the matched sources withsignificant proper motion, the fraction of objects with proper motion directions parallel tojets is a factor of three greater than on average. Such sources have systematically higher chisquared per degree of freedom. We explain these proper motions as a manifestation of thesource position jitter caused by flares, which we predicted earlier. Therefore, the assumptionthat quasars are fixed points, and thus that differential proper motions determined with respectto quasar photocentres can be regarded as absolute proper motions, should be treated withgreat caution.

Petrov, L.↗
NASA NTRSDate not supplied

Motion Magnification to Visualize the Modes of Space Structures

Traditional structural testing involves using accelerometers and strain gages to measure the motion. While this traditional instrumentation suite has proven accurate, it is limited to capture data only in the discrete locations where the transducers are placed. Additionally, applying the instrumentation can be a difficult and labor intensive task. By using video cameras, the motion of the test article – such as a launch vehicle or launch vehicle payload – can be easily captured at any location in the field of view and easily visualized using a post-processing technique called Motion Magnification. It is also much easier to place video cameras to measure motion rather than having to place contact sensors, especially when placement locations can be limited on final flight hardware. Recently, a team of MIT Lincoln Laboratory (MITLL) and NASA Marshall Space Flight Center (MSFC) have been collaborating to use Motion Magnification to measure the dynamics of large space structures. This presentation will detail some of the results of this collaboration.

Eric Colby Stewart↗
NASA NTRSDate not supplied

Motion Magnification to Visualize the Modes of Space Structures

Traditional structural testing involves using accelerometers and strain gages to measure the motion. While this traditional instrumentation suite has proven accurate, it is limited to capture data only in the discrete locations where the transducers are placed. Additionally, applying the instrumentation can be a difficult and labor intensive task. By using video cameras, the motion of the test article – such as a launch vehicle or launch vehicle payload – can be easily captured at any location in the field of view and easily visualized using a post-processing technique called Motion Magnification. It is also much easier to place video cameras to measure motion rather than having to place contact sensors, especially when placement locations can be limited on final flight hardware. Recently, a team of MIT Lincoln Laboratory (MITLL) and NASA Marshall Space Flight Center (MSFC) have been collaborating to use Motion Magnification to measure the dynamics of large space structures. This presentation will detail some of the results of this collaboration.

Eric Colby Stewart↗
NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗
NASA NTRS2020

Multi-Agent Motion Planning using Deep Learning for Space Applications

State-of-the-art motion planners cannot scale to a large number of systems. Motion planning for multiple agents is an NP (non-deterministic polynomial-time) hard problem, so the computation time increases exponentially with each addition of agents. This computational demand is a major stumbling block to the motion planner's application to future NASA missions involving the swarm of space vehicles. We applied a deep neural network to transform computationally demanding mathematical motion planning problems into deep learning-based numerical problems. We showed optimal motion trajectories can be accurately replicated using deep learning-based numerical models in several 2D and 3D systems with multiple agents. The deep learning-based numerical model demonstrates superior computational efficiency with plans generated 1000 times faster than the mathematical model counterpart.

Madani, Ramtin↗
NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗
DOE OSTI2025

Impact of representative ground motion level on seismic PSA with the boundary between overestimation and underestimation

One commonly used approach in seismic probabilistic safety assessment (PSA) is the discrete method. This method follows the standard PSA framework and can be applied to various models, such as multi-unit models, while reducing computational costs using standard software. However, due to the inability to subdivide intervals infinitely, the discrete method approximates with a finite number of subintervals. In practice, different numbers of subintervals are applied, and the representative ground motion level is selected based on expert judgment. When employing a smaller number of subintervals, it is important to take caution to prevent underestimation. This study analyzes the impact of the representative ground motion level on seismic risk. It confirms that underestimation can occur with a small number of subintervals depending on the representative ground motion level. This study also proposes a method for determining the boundary of underestimation and overestimation. The method is demonstrated through examples, providing a mathematical foundation for selecting appropriate representative ground motion levels. By avoiding underestimation, this research helps prevent the oversight of significant risk contributors and enhances the understanding of seismic risk.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Decoherence and Brownian motion of a polarizable particle near a medium

Optically levitated nanoparticles are ideal experimental testbeds for investigating macroscopic superpositions and microscopic thermodynamics. Integrating such levitated nanoparticles with photonic structures can enable strong coupling between their center-of-mass motion and guided photonic modes, facilitating enhanced control and probing of their motion. When coupling a particle to a photonic structure, such as a waveguide, the effects of fluctuations become prominent at nanoscales. In this work, we analyze the classical and quantized center-of-mass motion of a polarizable particle interacting with the fluctuations of the electromagnetic field in the presence of a medium. We derive a position localization master equation for the particle's quantized center of mass, and examine its classical center-of-mass momentum diffusion, elucidating correspondences between classical and quantum Brownian motion of polarizable particles near media. We study the decoherence rate of the particle in the presence of a planar surface as a function of temperature and distance from the surface, comparing it to common sources of decoherence. Our results are pertinent to experiments aimed at preparing levitated nanospheres in macroscopic quantum states and investigating their Brownian dynamics.

Brownian motion↗
DOE OSTI2025

A Novel Approach for Computing Rigid Body Motion Using Linear Accelerations

Here, a novel approach is presented for computing general rigid body motion based on a few known linear accelerations. This method utilizes linear acceleration data obtained from three distinct points on the body, all within a body-fixed reference frame. The only requirement is that the three chosen points must not be collinear. A system of differential-algebraic equations is derived, combining principles of rigid body kinematics with theory of the rotation group SO(3). These equations provide a framework for numerically computing various motion parameters, including angular velocity, angular acceleration, body orientation, velocity field, acceleration field, and displacement field. By numerically solving this system of equations, we can fully characterize rigid body motion in three-dimensional space. A numerical example is provided to demonstrate the practical implementation and efficacy of the proposed technique, illustrating its potential for accurate motion computation in various applications.

42 ENGINEERING↗
DOE OSTI2025

Insights into Slip-Rate Time Functions, Rupture Parameter Correlations, and Ground Motions from Validated Multicycle Earthquake Ruptures

Earthquake strong-motion predictions using kinematic source modeling require knowledge of the slip-rate functions (SRFs) along the rupture and their distinct characteristics in asperities, background (off-asperity) areas and near the surface. Here, in this study we analyzed SRFs from well-validated, self-consistent, and fully dynamic rupture models from earthquake cycles obeying a rate-and-state friction law, from our companion study (Galvez et al., 2021). The shapes of SRFs in asperities are well described by the regularized Yoffe function (RYF), which has only two parameters: rise time T r and smoothing time T s , which control the generation of long- and short-period ground motions, respectively. In background areas, we demonstrate that, in addition to the primary rupture, multiple secondary ruptures may also nucleate from rupture heterogeneities related to asperities, resulting in SRFs with multiple peaks. Because it is impossible to fit a multiple-peak SRF by the single-peak RYF, we describe SRFs in background areas in an effective way by fitting their amplitude spectra with the RYF spectra. Such spectrally effective RYFs capture salient aspects of seismic-wave generation and can be used in rupture generators for strong motion prediction. We found that small T s values correlate with small characteristic weakening distances, large peak slip rates (PSRs), and large rupture velocities. T r values are larger in background areas and smaller in asperities. Within the shallow aseismic zone, T s values approximately quadruple whereas T r values approximately double. Because of this dominant T s increase, PSR values decrease in the near-surface zone. These features indicate that the generation of strong motions by the near-surface portions of the rupture is negligible in the studied scenarios.

Geosciences↗
NASA NTRS1962

Analytical Study of the Tumbling Motions of Vehicles Entering Planetary Atmospheres

The tumbling motion of vehicles entering planetary atmospheres is analyzed. A differential equation governing the tumbling motion, its arrest, and the subsequent oscillatory motion is obtained and identified as the equation for the fifth Painleve transcendant. An approximate analytical solution for the transcendant is derived. Comparisons with results obtained from numerical integration of the exact equations of motion indicate that the solution for the angle-of-attack history is sufficiently accurate to be of practical use.

PLANETARY ENTRY↗
NASA NTRS2002

Monocular motion adaptation affects the perceived trajectory of stereomotion

Perceived stereomotion trajectory was measured before and after adaptation to lateral motion in the dominant or nondominant eye to assess the relative contributions of 2 cues: changing disparity and interocular velocity difference. Perceived speed for monocular lateral motion and perceived binocular visual direction (BVD) was also assessed. Unlike stereomotion trajectory perception, the BVD of static targets showed an ocular dominance bias, even without adaptation. Adaptation caused equivalent biases in perceived trajectory and monocular motion speed, without significantly affecting perceived BVD. Predictions from monocular motion data closely match trajectory perception data, unlike those from BVD sources. The results suggest that the interocular velocity differences make a significant contribution to stereomotion trajectory perception.

Depth Perception/physiology↗
NASA NTRS2000

Stimulus configuration determines the detectability of motion signals in noise

We measured the detectability of moving signal dots in dynamic noise to determine whether local motion signals are preferentially combined along an axis parallel to the direction of motion. Observers were asked to detect a signal composed of three dots moving in a linear trajectory among dynamic noise dots. The signal dots were collinear and equally spaced in a configuration that was either parallel to or perpendicular to their trajectory. The probability of detecting the signal was measured as a function of noise density, over a range of signal dot spacings from 0.5 degrees to 5.0 degrees. At any given noise density, the signal in the parallel configuration was more detectable than that in the perpendicular configuration. Our four observers could tolerate 1.5-2.5 times more noise in the parallel configuration. This improvement is not due merely to temporal summation between consecutive dots in the parallel trajectory. Temporal summation functions measured on our observers indicate that the benefit from spatial coincidence of the dots lasts for no more than 50 ms, whereas the increased detectability of the parallel configuration is observed up to the largest temporal separations tested (210 ms). These results demonstrate that dots arranged parallel to the signal trajectory are more easily detected than those arranged perpendicularly. Moreover, this enhancement points to the existence of visual mechanisms that preferentially organize motion information parallel to the direction of motion.

Non-NASA Center↗
NASA NTRS1998

Relationship between selected orientation rest frame, circular vection and space motion sickness

Space motion sickness (SMS) and spatial orientation and motion perception disturbances occur in 70-80% of astronauts. People select "rest frames" to create the subjective sense of spatial orientation. In microgravity, the astronaut's rest frame may be based on visual scene polarity cues and on the internal head and body z axis (vertical body axis). The data reported here address the following question: Can an astronaut's orientation rest frame be related and described by other variables including circular vection response latencies and space motion sickness? The astronaut's microgravity spatial orientation rest frames were determined from inflight and postflight verbal reports. Circular vection responses were elicited by rotating a virtual room continuously at 35 degrees/s in pitch, roll and yaw with respect to the astronaut. Latency to the onset of vection was recorded from the time the crew member opened their eyes to the onset of vection. The astronauts who used visual cues exhibited significantly shorter vection latencies than those who used internal z axis cues. A negative binomial regression model was used to represent the observed total SMS symptom scores for each subject for each flight day. Orientation reference type had a significant effect, resulting in an estimated three-fold increase in the expected motion sickness score on flight day 1 for astronauts who used visual cues. The results demonstrate meaningful classification of astronauts' rest frames and their relationships to sensitivity to circular vection and SMS. Thus, it may be possible to use vection latencies to predict SMS severity and duration.

short duration↗
NASA NTRS1998

Posture, locomotion, spatial orientation, and motion sickness as a function of space flight

This article summarizes a variety of newly published findings obtained by the Neuroscience Laboratory, Johnson Space Center, and attempts to place this work within a historical framework of previous results on posture, locomotion, motion sickness, and perceptual responses that have been observed in conjunction with space flight. In this context, we have taken the view that correct transduction and integration of signals from all sensory systems is essential to maintaining stable vision, postural and locomotor control, and eye-hand coordination as components of spatial orientation. The plasticity of the human central nervous system allows individuals to adapt to altered stimulus conditions encountered in a microgravity environment. However, until some level of adaptation is achieved, astronauts and cosmonauts often experience space motion sickness, disturbances in motion control and eye-hand coordination, unstable vision, and illusory motion of the self, the visual scene, or both. Many of the same types of disturbances encountered in space flight reappear immediately after crew members return to earth. The magnitude of these neurosensory, sensory-motor and perceptual disturbances, and the time needed to recover from them, tend to vary as a function of mission duration and the space travelers prior experience with the stimulus rearrangement of space flight. To adequately chart the development of neurosensory changes associated with space flight, we recommend development of enhanced eye movement systems and body position measurement. We also advocate the use of a human small radius centrifuge as both a research tool and as a means of providing on-orbit countermeasures that will lessen the impact of living for long periods of time with out exposure to altering gravito-inertial forces. Copyright 1998 Elsevier Science B.V.

Flight Experiment↗
NASA NTRS1995

Reliability of psychophysiological responses across multiple motion sickness stimulation tests

Although there is general agreement that a high degree of variability exists between subjects in their autonomic nervous system responses to motion sickness stimulation, very little evidence exists that examines the reproducibility of autonomic responses within subjects during motion sickness stimulation. Our objectives were to examine the reliability of autonomic responses and symptom levels across five testing occasions using the (1) final minute of testing, (2) change in autonomic response and the change in symptom level, and (3) strength of the relationship between the change in symptom level and the change in autonomic responses across the entire motion sickness test. The results indicate that, based on the final minute of testing, the autonomic responses of heart rate, blood volume pulse, and respiration rate are moderately stable across multiple tests. Changes in heart rate, blood volume pulse, respiration rate, and symptoms throughout the test duration are less stable across the tests. Finally, autonomic responses and symptom levels are significantly related across the entire motion sickness test.

NASA Discipline Neuroscience↗
NASA NTRS1994

Motion Control of Rover-Mounted Manipulators

This paper presents a simple online approach for motion control of rover-mounted manipulators. An integrated kinetic model of the rover-plus-manipulator system is derived which incorporates the nonholonomic rover constraint with the holonomic end-effector constraint. The redundancy introduced by the rover mobility is exploited to perform a set of user-specified additional tasks during end-effector motion. The configuration control approach is utilized to satisfy the nonholonomic rover constraint, while accomplishing the end-effector motion and the redundancy resolution goal simultaneously. This framework allows the user to assign weighting factors to the rover movement and manipulator motion, as well as to each task specification. The computational efficiency of the control scheme makes it particularly suitable for real-time implementation. The proposed method is applied to a planar two-jointed arm mounted on a rover, and computer simulation results are presented for illustration.

robotics rover manipulator holonomic end-effector ↗