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At least 163 records · Page 9

Virtual Reality as a Medium for Sensorimotor Adaptation Training and Spaceflight Countermeasures

With the upcoming shift to extra‐long duration missions (1 year) aboard the ISS, sensorimotor adaptations during transitory periods in‐and‐out of microgravity are more important to understand and prepare for. Advances in virtual reality technology enables everyday adoption of these tools for entertainment and use in training. Experiencing virtual environments (VE) allows for the manipulation of visual flow to elicit automatic motor behavior and produce sensorimotor adaptation (SA). Recently, the ability to train individuals using repeatable and varied exposures to SA challenges has shown success by improving performance during exposure to a novel environment (Batson 2011). This capacity to 'learn to learn' is referred to as sensorimotor adaptive generalizability and, through the use of treadmill training, represents an untapped potential for individualized countermeasures. The goal of this study is to determine the feasibility of present head mounted displays (HMDs) to produce compelling visual flow information and the expected adaptations for use in future SA treadmill‐based countermeasures. Participants experience infinite hallways providing congruent (baseline) or incongruent visual information (half or double speed) via HMD while walking on an instrumented treadmill at 1.1m/s. As gait performance approaches baseline levels, an adaptation time constant is derived to establish individual time‐to‐adapt (TTA). It is hypothesized that decreasing the TTA through SA treadmill training will facilitate sensorimotor adaptation during gravitational transitions. In this way, HMD technology represents a novel platform for SA training using off‐the‐shelf consumer products for greater training flexibility in astronaut and terrestrial applications alike.

Madansingh, S.

Developing Personalized Sensorimotor Adaptability Countermeasures for Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. In this paper we will be presenting results from our ground-based study that show how behavioral, brain imaging and genomic data may be used to predict individual differences in sensorimotor adaptability to novel sensorimotor environments. This approach will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure, functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.

Global Response Patterns of Major Rainfed Crops to Adaptation by Maintaining Current Growing Periods and Irrigation

Increasing temperature trends are expected to impact yields of major field crops by affecting various plant processes, such as phenology, growth, and evapotranspiration. However, future projections typically do not consider the effects of agronomic adaptation in farming practices. We use an ensemble of seven Global Gridded Crop Models to quantify the impacts and adaptation potential of field crops under increasing temperature up to 6 K, accounting for model uncertainty. We find that without adaptation, the dominant effect of temperature increase is to shorten the growing period and to reduce grain yields and production. We then test the potential of two agronomic measures to combat warming-induced yield reduction: (i) use of cultivars with adjusted phenology to regain the reference growing period duration and (ii) conversion of rainfed systems to irrigated ones in order to alleviate the negative temperature effects that are mediated by crop evapotranspiration. We find that cultivar adaptation can fully compensate global production losses up to 2 K of temperature increase, with larger potentials in continental and temperate regions. Irrigation could also compensate production losses, but its potential is highest in arid regions, where irrigation expansion would be constrained by water scarcity. Moreover, we discuss that irrigation is not a true adaptation measure but rather an intensification strategy, as it equally increases production under any temperature level. In the tropics, even when introducing both adapted cultivars and irrigation, crop production declines already at moderate warming, making adaptation particularly challenging in these areas.

Minoli, Sara

Adaptive Hexapod Simulator Motion Based on Aircraft Stability

This paper determined the feasibility of an adaptive hexapod simulator motion algorithm based on aircraft roll stability. An experiment was conducted that used a transport aircraft model in the Vertical Motion Simulator at NASA Ames Research Center. Eighteen general aviation pilots flew a heading-capture task and a stall task consecutively under four motion configurations: baseline hexapod, adaptive hexapod, optimized hexapod, and full motion. The adaptive motion was more similar to the baseline hexapod motion in the heading-capture task when the aircraft was more stable, and more similar to the optimized hexapod motion in the stall task when the aircraft was more unstable. Pilot motion ratings and task performance in the heading-capture task under the adaptive hexapod motion were more similar to baseline hexapod motion compared to optimized hexapod motion. However, motion ratings and task performance in the stall task under the adaptive motion were not significantly more similar to the optimized hexapod motion compared to baseline hexapod motion. Motion ratings and overall task performance under optimized hexapod motion as opposed to baseline hexapod motion were always more similar to the full motion condition. This paper showed that adaptive motion based on aircraft stability is feasible and can be implemented in a straightforward way. More research is required to test the adaptive motion algorithm in different tasks.

Zaal, Peter M. T.

Verification of Anisotropic Mesh Adaptation for Turbulent Simulations over ONERA M6 Wing

Unstructured anisotropic mesh adaptation is known to be an efficient way to control discretization errors in Computational Fluid Dynamics (CFD) simulations. Method verification is required to provide the confidence for routine use in production analysis. The current work aims at verification of anisotropic mesh adaptation for RANS simulations over the ONERA M6 wing. The present verification study is performed using four different flow solvers, three different implementations of the metric field, and three mesh mechanics packages. Two of the flow solvers use stabilized finite-element discretizations (FUN3D-SFE and GGNS), one uses finite-volume discretization (FUN3D-FV), and the last one uses mixed finite-volume and finite element discretizations (Wolf). The mesh adaptation is based on an error estimator that aims to control the quadratic error term in the linear interpolation of Mach number. Two sets of adaptations were performed; the first one controls the interpolation error in L2 norm and the second one controls the interpolation error in L4 norm. Convergence studies were performed on the forces and the pitching moment using all four solvers, and the results are compared with previously verified convergence studies on fixed (nonadapted) meshes. Both forces and pitching moment on adapted meshes are found to be converging to the fine mesh values faster than those on fixed meshes. In addition to forces and moments, convergence of surface pressure and skin friction coefficients at various measurement locations on the wing are also presented. Adapted-mesh surface pressure distributions agree with the fine fixed mesh pressure distributions. Adapted-mesh skin friction distributions contain high frequency noise with mean values approaching the fixed mesh pressure skin friction distributions.

Aravind Balan

Automatic Boundary-Layer Adaptation of Structured Grids in VULCAN-CFD

In supersonic and hypersonic flow computations, well-resolved boundary layers are essential for accurate quantification of surface heating and transition prediction, particularly via linear stability analysis. Grid design for hypersonic flows with shocks, boundary-layer separation, and/or complex mean flow features incorporating spanwise/azimuthal inhomogeneities is a difficult issue. In comparison to a manual grid adaptation procedure, an autonomous grid adaptation technique offers significant improvements in computing time and solution quality. The VULCAN-CFD solver already includes a validated procedure for automatic adaption of structured grids to the bow shock. The present focus is on implementing an automatic boundary-layer adaptation capability in VULCAN-CFD that adapts structured, multiblock grids to both the bow shock and the boundary layer at the same time. The boundary-layer adaptation algorithm allows the user to specify the number of cells within the boundary layer, along with the input parameters used for detecting the edge of the boundary layer, namely, the variable used in the edge detection criterion,the edge detection method, the detection direction, and the relaxation factor used during the morphing of the grid. The algorithm automatically distributes grid points along the wall-normal direction to achieve a smooth variation in grid spacing from the edge of the boundary layer to a"junction" location within the outer part of the grid. Illustrative results are presented for three different high-speed configurations: the two-dimensional flow over a cylinder at Mach 17.6 and unit Reynolds number of Re=0.38x10^6 m^-1, the axisymmetric flow over a cone-cylinder-flare model at Mach 6.0 and Re = 10.5×10^6 m^-1, and the three-dimensional flow over a blunt, 7-degree half-angle cone at 5-degree angle of attack in a Mach 9.79 flow with Re = 17.1×10^6 m^-1. The automated boundary-layer adaptation is shown to provide an adequate grid topology that is aligned with the bow shock in the outer part of the grid and also resolves the viscous boundary-layer region close to the surface.

boundary layer transition

Effect of anisotropic mesh adaptation on surface pressure predictions for atmospheric entry simulations.

Recently, a metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that typically improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) during the atmospheric entry phase of Mars2020.

D. Ekelschot

Effect of Anisotropic Mesh Adaptation on Surface Pressure Predictions for Atmospheric Entry Simulations

A metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation (MEDLI2) suite.

Dirk Ekelschot

Drought adaptation index (DAI) based on BLUP as a selection approach for drought-resilient switchgrass germplasm

This study introduces a Drought Adaptation Index (DAI), derived from Best Linear Unbiased Prediction (BLUP), as a method to assess drought resilience in switchgrass (Panicum virgatum L.). A panel of 404 genotypes was evaluated under drought-stressed (CV) and well-watered (UC) conditions over four consecutive years (2019–2022). BLUP-estimated biomass yields were used to calculate the DAI, which enabled classification of genotypes into four adaptation groups: very well-adapted, well-adapted, adapted, and unadapted. The DAI was compared with conventional drought tolerance indices, including the Stress Susceptibility Index (SSI), Stress Tolerance Index (STI), Geometric Mean Productivity (GMP), and Yield Stability Index (YSI). Correlation analyses demonstrated strong agreement between DAI and these indices, supporting its validity and consistency. Biplot analyses using the Genotype plus Genotype-by-Environment Interaction (GGE) and Additive Main Effects and Multiplicative Interaction (AMMI) models revealed significant genotype-by-environment interactions (GEI) and identified J222.A, J463.A, and J295.A. A as high-performing genotypes, with J222.A exhibiting greater yield stability across treatments and years. Additionally, DAI isoline curves provided a graphical representation of differential genotype performance under drought and control conditions. These visualizations aided in distinguishing genotypes with stable and superior biomass yield across contrasting environments. Overall, the BLUP-based DAI is a robust and practical selection tool that improves the accuracy of identifying drought-resilient, high-yielding switchgrass genotypes. Its integration into breeding programs offers a comprehensive framework for improving biomass productivity and stress adaptation under variable climatic conditions. The application of DAI supports the development of climate-resilient cultivars and contributes to sustainable bioenergy and forage production systems.

BLUP

Adaptive anomaly detection for identifying attacks in cyber-physical systems: A systematic literature review

Modern cyberattacks in cyber-physical systems (CPS) rapidly evolve and cannot be deterred effectively with most current methods, which focus on characterizing past threats. Adaptive anomaly detection (AAD) is among the most promising techniques to detect evolving cyberattacks, with an emphasis on fast data processing and model adaptation. AAD has been researched extensively; however, to the best of our knowledge, our work is the first systematic literature review (SLR) on current research in this field. We present a comprehensive SLR, gathering 397 relevant papers and systematically analyzing 65 of them (47 research and 18 survey papers) on AAD in CPS from 2013 to November 2023. We introduce a novel taxonomy considering attack types, CPS application, learning paradigm, data management, and algorithms. Our findings show that most studies addressed either model adaptation or data processing, but rarely both simultaneously. This indicates a research gap in fully adaptive solutions. We also categorize algorithms, datasets, and attack characteristics, and summarize strengths and weaknesses across the literature. Our review provides a structured and accessible reference for researchers and practitioners, offering insights into key trends and highlighting limitations in current approaches. Finally, we outline several future research directions, including the need for integrated real-time processing and adaptive learning, explainability, and uncertainty quantification in AAD for CPS.

Adaptation

Sensorimotor aspects of high-speed artificial gravity: I. Sensory conflict in vestibular adaptation

Short-radius centrifugation offers a promising and affordable countermeasure to the adverse effects of prolonged weightlessness. However, head movements made in a fast rotating environment elicit Coriolis effects, which seriously compromise sensory and motor processes. We found that participants can adapt to these Coriolis effects when exposed intermittently to high rotation rates and, at the same time, can maintain their perceptual-motor coordination in stationary environments. In this paper, we explore the role of inter-sensory conflict in this adaptation process. Different measures (vertical nystagmus, illusory body tilt, motion sickness) react differently to visual-vestibular conflict and adapt differently. In particular, proprioceptive-vestibular conflict sufficed to adapt subjective parameters and the time constant of nystagmus decay, while retinal slip was required for VOR gain adaptation. A simple correlation between the strength of intersensory conflict and the efficacy of adaptation fails to explain the data. Implications of these findings, which differ from existing data for low rotation rates, are discussed.

Non-NASA Center

Cross-axis adaptation of torsional components in the yaw-axis vestibulo-ocular reflex

The three pairs of semicircular canals within the labyrinth are not perfectly aligned with the pulling directions of the six extraocular muscles. Therefore, for a given head movement, the vestibulo-ocular reflex (VOR) depends upon central neural mechanisms that couple the canals to the muscles with the appropriate functional gains in order to generate a response that rotates the eye the correct amount and around the correct axis. A consequence of these neural connections is a cross-axis adaptive capability, which can be stimulated experimentally when head rotation is around one axis and visual motion about another. From this visual-vestibular conflict the brain infers that the slow-phase eye movement is rotating around the wrong axis. We explored the capability of human cross-axis adaptation, using a short-term training paradigm, to determine if torsional eye movements could be elicited by yaw (horizontal) head rotation (where torsion is normally inappropriate). We applied yaw sinusoidal head rotation (+/-10 degrees, 0.33 Hz) and measured eye movement responses in the dark, and before and after adaptation. The adaptation paradigm lasted 45-60 min, and consisted of the identical head motion, coupled with a moving visual scene that required one of several types of eye movements: (1) torsion alone (-Roll); (2) horizontal/torsional, head right/CW torsion (Yaw-Roll); (3) horizontal/torsional, head right/CCW torsion (Yaw+Roll); (4) horizontal, vertical, torsional combined (Yaw+Pitch-Roll); and (5) horizontal and vertical together (Yaw+Pitch). The largest and most significant changes in torsional amplitude occurred in the Yaw-Roll and Yaw+Roll conditions. We conclude that short-term, cross-axis adaptation of torsion is possible but constrained by the complexity of the adaptation task: smaller torsional components are produced if more than one cross-coupling component is required. In contrast, vertical cross-axis components can be easily trained to occur with yaw head movements.

Non-NASA Center

Context-specific adaptation of the gain of the oculomotor response to lateral translation using roll and pitch head tilts as contexts

Previous studies established that vestibular and oculomotor behaviors can have two adapted states (e.g., gain) simultaneously, and that a context cue (e.g., vertical eye position) can switch between the two states. The present study examined this phenomenon of context-specific adaptation for the oculomotor response to interaural translation (which we term "linear vestibulo-ocular reflex" or LVOR even though it may have extravestibular components). Subjects sat upright on a linear sled and were translated at 0.7 Hz and 0.3 gpeak acceleration while a visual-vestibular mismatch paradigm was used to adaptively increase (x2) or decrease (x0) the gain of the LVOR. In each experimental session, gain increase was asked for in one context, and gain decrease in another context. Testing in darkness with steps and sines before and after adaptation, in each context, assessed the extent to which the context itself could recall the gain state that was imposed in that context during adaptation. Two different contexts were used: head pitch (26 degrees forward and backward) and head roll (26 degrees or 45 degrees, right and left). Head roll tilt worked well as a context cue: with the head rolled to the right the LVOR could be made to have a higher gain than with the head rolled to the left. Head pitch tilt was less effective as a context cue. This suggests that the more closely related a context cue is to the response being adapted, the more effective it is.

Non-NASA Center

Adaptation, plant evolution, and the fossil record

The importance of adaptation in determining patterns of evolution has become an important focus of debate in evolutionary biology. As it pertains to paleobotany, the issue is whether or not adaptive evolution mediated by natural selection is sufficient to explain the stratigraphic distributions of taxa and character states observed in the plant fossil record. One means of addressing this question is the functional evaluation of stratigraphic series of plant organs set in the context of paleoenvironmental change and temporal patterns of floral composition within environments. For certain organ systems, quantitative estimates of biophysical performance can be made on the basis of structures preserved in the fossil record. Performance estimates for plants separated in time or space can be compared directly. Implicit in different hypotheses of the forces that shape the evolutionary record (e.g. adaptation, mass extinction, rapid environmental change, chance) are predictions about stratigraphic and paleoenvironmental trends in the efficacy of functional performance. Existing data suggest that following the evolution of a significant structural innovation, adaptation for improved functional performance can be a major determinant of evolutionary changes in plants; however, there are structural and development limits to functional improvement, and once these are reached, the structure in question may no longer figure strongly in selection until and unless a new innovation evolves. The Silurian-Devonian paleobotanical record is consistent with the hypothesis that the succession of lowland floodplain dominants preserved in the fossil record of this interval was determined principally by the repeated evolution of new taxa that rose to ecological importance because of competitive advantages conferred by improved biophysical performance. This does not seem to be equally true for Carboniferous-Jurassic dominants of swamp and lowland floodplain environments. In these cases, environmental disruption appears to have been a major factor in shaping the fossil record. This does not mean that continuing adaptation was not important during this interval, but it may indicate that adaptive evolution was strongest in environments other than those best represented in the paleobotanical record.

NASA Discipline Exobiology

Adaptation of the phase of the human linear vestibulo-ocular reflex (LVOR) and effects on the oculomotor neural integrator

The phase of the translational linear VOR (LVOR) can be adaptively modified by exposure to a visual-vestibular mismatch. We extend here our earlier work on LVOR phase adaptation, and discuss the role of the oculomotor neural integrator. Ten subjects were oscillated laterally at 0.5 Hz, 0.3 g peak acceleration, while sitting upright on a linear sled. LVOR was assessed before and after adaptation with subjects tracking the remembered location of a target at 1 m in the dark. Phase and gain were measured by fitting sine waves to the desaccaded eye movements, and comparing sled and eye position. To adapt LVOR phase, the subject viewed a computer-generated stereoscopic visual display, at a virtual distance of 1 m, that moved so as to require either a phase lead or a phase lag of 53 deg. Adaptation lasted 20 min, during which subjects were oscillated at 0.5 Hz/0.3 g. Four of five subjects produced an adaptive change in the lag condition (range 4-45 deg), and each of five produced a change in the lead condition (range 19-56 deg), as requested. Changes in drift on eccentric gaze suggest that the oculomotor velocity-to-position integrator may be involved in the phase changes.

Non-NASA Center

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Task Performance and Analysis

Comparing Unstructured Adaptive Mesh Solutions for the High Lift Common Research Model Airfoil

Discretization error is a common source of uncertainty in Computational Fluid Dynamics (CFD) analyses. Traditional means of controlling discretization error through fixed-mesh refinement studies has proven to be difficult particularly when modeling complex geometries and flow fields. One reason for this is that mesh generation in today’s production CFD workflow is often a labor intensive process that is heavily dependent on user judgment. Unstructured mesh adaptation is known to be an efficient way to control discretization errors in CFD. Adaptive methods replace user based decision making with automated processes that optimize a mesh to reduce discretization error. This paper compares the application of multiple solution adaptive techniques in combination with multiple flow solvers to solve for the flow field about a 2D airfoil section of the NASA High-Lift Common Research Model (HL-CRM). By driving the adaptive mesh processes to a similar level of mesh convergence, the ability to achieve consistent results between multiple adaptive techniques and flow solvers is demonstrated. Mesh convergence for the various adaptive mesh approaches is compared identifying potential areas for improvement and providing mesh generation guidance for future workshops.

mesh adaptation high-lift 2D airfoil

Comparing Unstructured Adaptive Mesh Solutions for the High Lift Common Research Model Airfoil

Discretization error is a common source of uncertainty in Computational Fluid Dynamics (CFD) analyses. Traditional means of controlling discretization error through fixed-mesh refinement studies has proven to be difficult particularly when modeling complex geometries and flow fields. One reason for this is that mesh generation in today’s production CFD workflow is often a labor intensive process that is heavily dependent on user judgment. Unstructured mesh adaptation is known to be an efficient way to control discretization errors in CFD. Adaptive methods replace user based decision making with automated processes that optimize a mesh to reduce discretization error. This paper compares the application of multiple solution adaptive techniques in combination with multiple flow solvers to solve for the flow field about a 2D airfoil section of the NASA High-Lift Common Research Model (HL-CRM). By driving the adaptive mesh processes to a similar level of mesh convergence, the ability to achieve consistent results between multiple adaptive techniques and flow solvers is demonstrated. Mesh convergence for the various adaptive mesh approaches is compared identifying potential areas for improvement and providing mesh generation guidance for future workshops.

mesh adaptation