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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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At least 37 records · Page 2

A Moving Embedded Boundary Approach for the Compressible Navier-Stokes Equations in a Block-Structured Adaptive Refinement Framework

A computational technique has been developed to perform compressible flow simulations involving moving boundaries using an embedded boundary approach within the block-structured adaptive mesh refinement (SAMR) framework of AMReX [1], [91], [92]. We leverage the SAMR capability to obtain quantitatively accurate results whilst using robust, second-order finite volume schemes. A conservative, unsplit, cut-cell approach is utilized and a ghost-cell approach is developed for computing the flux on the moving, embedded boundary faces. A third-order least-squares formulation has been developed to compute the wall velocity gradients, and was found to significantly improve the performance of the solver in terms of the quantitative comparison of surface quantities such as the skin friction coefficient. Various test cases are performed to validate the method, and compared with analytical, experimental, and other numerical results in literature. Inviscid and viscous test cases are performed that span a wide regime of flow speeds - acoustic (harmonically pulsating sphere), smooth flows (expansion fan created by a receding piston) and flows with shocks (shock-cylinder interaction, shock-wedge interaction, pitching NACA 0012 airfoil and shock-cone interaction). A closed system with moving boundaries - an oscillating piston in a cylinder, showed that the percentage error in mass within the system decreases with refinement, demonstrating that the numerical scheme is conservative with grid refinement, but is not discretely conservative. Viscous test cases involve that of a horizontally moving cylinder at Re = 40, an inline oscillating cylinder at Re = 100, and a transversely oscillating cylinder at Re = 185. The judicious use of adaptive mesh refinement with appropriate refinement criteria to capture the regions of interest leads to well-resolved flow features, and good quantitative comparison is observed with the results available in literature.

adaptive refinement↗

A novel approach for adaptive skeleton toolpath generation

Industry 4.0 is revolutionizing manufacturing through the integration of automation and real-time data sharing in cyber-physical systems. At the forefront of this revolution is large-format additive manufacturing. In large-format printing, parts are often designed to be an even number of beads wide to produce a completely dense part. However, voids can still arise. This is often due to the part not being an even number of bead widths wide in some areas, or in geometry containing acute angles, as the process of generating closed contours cannot completely fill the space. Voids can be tolerated in smaller models, but in large-format additive manufacturing they may cause mechanical defects. To fill these voids, open loop paths called skeletons are often used, but they are typically limited by the physical constraints defined in the slicing software. To address this, researchers at Oak Ridge National Laboratory have extended skeleton toolpaths via an adaptive methodology. These adaptive skeletons were found to better fill void spaces through manipulation of physical parameters of the build process and were calculated as part of the slicing process.

42 ENGINEERING↗

Real-Time Model-Adaptive Relaying Applied to Microgrid Protection

In microgrids, the short-circuit current magnitude is significantly limited by more than an order of magnitude due to the relatively small inverter-based resources. Commercially available protective devices for distribution cannot reliably protect a microgrid due to their dependence on the magnitude of the fault current. Moreover, overcurrent relays typically cannot function properly for a microgrid because they are incapable of detecting faults and/or performing the coordination between the relays in inverter-based microgrids operated in the islanded mode. This paper proposes a model-adaptive relay designed to adjust the relay curves based on the available generation and the network topology. The proposed method runs a real-time model of the microgrid, which gathers information from the network to calculate the available short-circuit current in the specified node. The fault current from the model is then used for the adaptive algorithm to calculate the relay settings, considering coordination with the downstream fuses and upstream reclosers. This work presents the validation of the proposed method in Hardware-in-the-Loop, in a hardware testbed as well as field deployed in a real microgrid in East-Tennessee.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Adaptation of primate vestibuloocular reflex to altered peripheral vestibular inputs. II Spatiotemporal properties of the adapted slow-phase eye velocity

1. The ability of the vestibuloocular reflex (VOR) to undergo adaptive modification after selective changes in the peripheral vestibular system was investigated in rhesus monkeys by recording three-dimensional eye movements before and after inactivation of selective semicircular canals. In the preceding paper we showed that the horizontal VOR gain evoked by passive yaw oscillations after lateral semicircular canal inactivation recovers gradually over time in a frequency-specific manner. Here we present the spatial tuning of the adapted slow-phase eye velocity and describe its spatiotemporal properties as a function of time after canal inactivation. 2. The spatial organization of the VOR was investigated during oscillations at different head positions in the pitch, roll, and yaw planes, as well as in the right anterior/left posterior and left anterior/right posterior canal planes. Acutely after bilateral inactivation of the lateral semicircular canals, a small horizontal response could still be elicited that peaked during rotations in pitched head positions that would maximally stimulate vertical semicircular canals. In addition, the phase of horizontal slow-phase velocity abruptly reversed through 180 degrees at positions close to upright, similarly to torsional slow-phase velocity. These spatial response properties suggest that the small, residual horizontal response components that are present acutely after plugging of both lateral canals originate from vertical semicircular canal signals. 3. As the horizontal response amplitude increased over time, consistent changes were also observed in the spatiotemporal tuning of horizontal slow-phase velocity. 1) The spatiotemporal response properties of horizontal slow-phase velocity acquired noncosine tuning characteristics, primarily in the pitch plane, in the right anterior/left posterior and left anterior/right posterior canal planes. Accordingly, horizontal response amplitude was nonzero during rotation in any head position in these planes and response phase varied significantly as a function of head orientation. 2) The peak horizontal response amplitude shifted spatially over time, such that 5-10 mo after plugging it was maximal during rotations at head positions close to upright. 4. In parallel to these unique spatiotemporal response properties characterizing the adapted horizontal VOR, torsional slow-phase velocity also exhibited small spatiotemporal changes after lateral canal inactivation that tended to precede in time the changes associated with the horizontal response components. In contrast, vertical slow-phase velocity in the plugged animals was unaltered and continued to be characterized by cosine-tuned spatial properties in three dimensions. 5. Recovery of the horizontal response gain during yaw oscillations in upright position, as well as the unique, noncosine spatiotemporal characteristics of the adapted horizontal VOR, were also observed in an animal with all but one vertical semicircular canals inactivated. There was, however, no sign of VOR gain recovery up to 2 mo after all semicircular canals were inactivated. These results suggest that the observed recovery of horizontal VOR is at least partly due to signals originating from the remaining intact vertical canal(s). Even in the presence of a single intact vertical canal, the improvement in horizontal gaze stability is at least partly restored through spatiotemporal changes in the processing of vestibuloocular signals that improve the gain and spatial tuning of horizontal VOR at the expense of temporal response properties.

NASA Discipline Number 16-10↗

Motor adaptation to Coriolis force perturbations of reaching movements: endpoint but not trajectory adaptation transfers to the nonexposed arm

1. Reaching movements made in a rotating room generate Coriolis forces that are directly proportional to the cross product of the room's angular velocity and the arm's linear velocity. Such Coriolis forces are inertial forces not involving mechanical contact with the arm. 2. We measured the trajectories of arm movements made in darkness to a visual target that was extinguished at the onset of each reach. Prerotation subjects pointed with both the right and left arms in alternating sets of eight movements. During rotation at 10 rpm, the subjects reached only with the right arm. Postrotation, the subjects pointed with the left and right arms, starting with the left, in alternating sets of eight movements. 3. The initial perrotary reaching movements of the right arm were highly deviated both in movement path and endpoint relative to the prerotation reaches of the right arm. With additional movements, subjects rapidly regained straight movement paths and accurate endpoints despite the absence of visual or tactile feedback about reaching accuracy. The initial postrotation reaches of the left arm followed straight paths to the wrong endpoint. The initial postrotation reaches of the right arm had paths with mirror image curvature to the initial perrotation reaches of the right arm but went to the correct endpoint. 4. These observations are inconsistent with current equilibrium point models of movement control. Such theories predict accurate reaches under our experimental conditions. Our observations further show independent implementation of movement and posture, as evidenced by transfer of endpoint adaptation to the nonexposed arm without transfer of path adaptation. Endpoint control may occur at a relatively central stage that represents general constraints such as gravitoinertial force background or egocentric direction relative to both arms, and control of path may occur at a more peripheral stage that represents moments of inertia and muscle dynamics unique to each limb. 5. Endpoint and path adaptation occur despite the absence both of mechanical contact cues about the perturbing force and visual or tactile cues about movement accuracy. These findings point to the importance of muscle spindle signals, monitoring of motor commands, and possibly joint and tendon receptors in a detailed trajectory monitoring process. Muscle spindle primary and secondary afferent signals may differentially influence adaptation of movement shape and endpoint, respectively.

Non-NASA Center↗

A Consistent Spatially Adaptive Smoothed Particle Hydrodynamics Method for fluid-structure interactions

A new consistent, spatially adaptive, smoothed particle hydrodynamics (SPH) method for Fluid-Structure Interactions (FSI) is presented. The method combines several attributes that have not been simultaneously satisfied by other SPH methods. Specifically, it is second-order convergent; it allows for resolutions spatially adapted with moving (translating and rotating) boundaries of arbitrary geometries; and, it accelerates the FSI solution as the adaptive approach leads to fewer degrees of freedom without sacrificing accuracy. The key ingredients in the method are a consistent discretization of differential operators, a posteriori error estimator/distance-based criterion of adaptivity, and a particle-shifting technique. The method is applied in simulating six different flows or FSI problems. The new method's convergence, accuracy, and efficiency attributes are assessed by comparing the results it produces with analytical, finite element, and consistent SPH uniform high-resolution solutions as well as experimental data.

Hu, Wei↗

The fungus that came in from the cold: dry rot’s pre-adapted ability to invade buildings

Many organisms benefit from being pre-adapted to niches shaped by human activity, and have successfully invaded man-made habitats. One such species is the dry rot fungus Serpula lacrymans, which has a wide distribution in buildings in temperate and boreal regions, where it decomposes coniferous construction wood. Comparative genomic analyses and growth experiments using this species and its wild relatives revealed that S. lacrymans evolved a very effective brown rot decay compared to its wild relatives, enabling an extremely rapid decay in buildings under suitable conditions. Adaptations in intracellular transport machineries promoting hyphal growth, and nutrient and water transport may explain why it is has become a successful invader of timber in houses. Further, we demonstrate that S. lacrymans has poor combative ability in our experimental setup, compared to other brown rot fungi. In sheltered indoor conditions, the dry rot fungus may have limited encounters with other wood decay fungi compared to its wild relatives. Overall, our analyses indicate that the dry rot fungus is an ecological specialist with poor combative ability against other fungi.

fungal biology↗

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗

Nonparallel transcriptional divergence during parallel adaptation

Abstract How underlying mechanisms bias evolution toward predictable outcomes remains an area of active debate. In this study, we leveraged phenotypic plasticity and parallel adaptation across independent lineages of Trinidadian guppies ( Poecilia reticulata ) to assess the predictability of gene expression evolution during parallel adaptation. Trinidadian guppies have repeatedly and independently adapted to high‐ and low‐predation environments in the wild. We combined this natural experiment with a laboratory breeding design to attribute transcriptional variation to the genetic influences of population of origin and developmental plasticity in response to rearing with or without predators. We observed substantial gene expression plasticity, as well as the evolution of expression plasticity itself, across populations. Genes exhibiting expression plasticity within populations were more likely to also differ in expression between populations, with the direction of population differences more likely to be opposite those of plasticity. While we found more overlap than expected by chance in genes differentially expressed between high‐ and low‐predation populations from distinct evolutionary lineages, the majority of differentially expressed genes were not shared between lineages. Our data suggest alternative transcriptional configurations associated with shared phenotypes, highlighting a role for transcriptional flexibility in the parallel phenotypic evolution of a species known for rapid adaptation.

Fischer, Eva K.↗

Towards adaptive spiking label propagation

Graph algorithms are a new class of applications for neuromorphic hardware. Rather than adapting deep learning and standard neural network approaches to a low-precision spiking environment, we use spiking neurons to analyze undirected graphs (e.g., the underlying modular structure). While fully connected spin glass implementations of spiking label propagation have shown promising results on graphs with dense communities, identifying sparse communities remains difficult. This work focuses on steps towards an adaptive spike-based implementations of label propagation, utilizing sparse embeddings and synaptic plasticity. Sparser embeddings reduce the number of inhibitory connections, and synaptic plasticity is used to simultaneously amplify spike responses between neurons in the same community, while impeding spike responses across different communities. We present results on identifying communities in sparse graphs with very small communities.

Hamilton, Kathleen↗

An adaptive human response mechanism controlling the V/STOL aircraft. Appendix 3: The adaptive control model of a pilot in V/STOL aircraft control loops

Importance of the role of human operator in control systems has led to the particular area of manual control theory. Human describing functions were developed to model human behavior for manual control studies to take advantage of the successful and safe human operations. A single variable approach is presented that can be extended for multi-variable tasks where a low order human response model is used together with its rules, to adapt the model on-line, being capable of responding to the changes in the controlled element dynamics. Basic control theory concepts are used to combine the model, constrained with the physical observations, particularly, for the case of aircraft control. Pilot experience is represented as the initial model parameters. An adaptive root-locus method is presented as the adaptation law of the model where the closed loop bandwidth of the system is to be preserved in a stable manner with the adjustments of the pilot handling qualities which relate the latter to the closed loop bandwidth and damping of the closed loop pilot aircraft combination. A Kalman filter parameter estimator is presented as the controlled element identifier of the adaptive model where any discrepancies of the open loop dynamics from the presented one, are sensed to be compensated.

Kucuk, Senol↗

Understanding How Astronauts Adapt to Space and to Earth: Anatomical Studies of Central Vestibular Adaptation

Significant changes take place in the nervous systems of astronauts during and following exposure to microgravity. These changes, particularly in the part of the brain that controls balance, the vestibular system, can cause sensations of rotation, dizziness, and vertigo, as well as space adaptation syndrome. Adaptation to the microgravity environment usually occurs within one week, and a subsequent re-adaptation period of several days is often required upon return to Earth. In order to realize long-term spaceflight, effective countermeasures for these symptoms must be developed. The structural changes that take place in one of the vestibular regions of the brain (the cerebellar cortex) during the process of adaptation to Earth's gravity remain unclear and are the subject of an experiment being conducted on STS-107 by Dr. Gay Holstein of the Mount Sinai School of Medicine in New York. Using the rat as a model, Dr. Holstein and her team will seek to identify the cellular changes underlying the vestibular changes experienced by astronauts.

Holstein, Gay↗

Using Remotely Sensed Data for Climate Change Mitigation and Adaptation: A Collaborative Effort Between the Climate Change Adaptation Science Investigators Workgroup (CASI), NASA Johnson Space Center, and Jacobs Technology

With ever changing landscapes and environmental conditions due to human induced climate change, adaptability is imperative for the long-term success of facilities and Federal agency missions. To mitigate the effects of climate change, indicators such as above-ground biomass change must be identified to establish a comprehensive monitoring effort. Researching the varying effects of climate change on ecosystems can provide a scientific framework that will help produce informative, strategic and tactical policies for environmental adaptation. As a proactive approach to climate change mitigation, NASA tasked the Climate Change Adaptation Science Investigators Workgroup (CASI) to provide climate change expertise and data to Center facility managers and planners in order to ensure sustainability based on predictive models and current research. Generation of historical datasets that will be used in an agency-wide effort to establish strategies for climate change mitigation and adaptation at NASA facilities is part of the CASI strategy. Using time series of historical remotely sensed data is well-established means of measuring change over time. CASI investigators have acquired multispectral and hyperspectral optical and LiDAR remotely sensed datasets from NASA Earth Observation Satellites (including the International Space Station), airborne sensors, and astronaut photography using hand held digital cameras to create a historical dataset for the Johnson Space Center, as well as the Houston and Galveston area. The raster imagery within each dataset has been georectified, and the multispectral and hyperspectral imagery has been atmospherically corrected. Using ArcGIS for Server, the CASI-Regional Remote Sensing data has been published as an image service, and can be visualized through a basic web mapping application. Future work will include a customized web mapping application created using a JavaScript Application Programming Interface (API), and inclusion of the CASI data for the NASA Johnson Space Center into a NASA-Wide GIS Institutional Portal.

Jagge, Amy↗

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification

Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation.

36 MATERIALS SCIENCE↗

An Adaptive Reduced Basis Collocation Method Based on PCM ANOVA Decomposition for Anisotropic Stochastic PDEs

The combination of reduced basis and collocation methods enables efficient and accurate evaluation of the solutions to parameterized PDEs. Here, we study the stochastic collocation methods that can be combined with reduced basis methods to solve high-dimensional parameterized stochastic PDEs. We also propose an adaptive algorithm using a probabilistic collocation method (PCM) and ANOVA decomposition. This procedure involves two stages. First, the method employs an ANOVA decomposition to identify the effective dimensions, i.e., subspaces of the parameter space in which the contributions to the solution are larger, and sort the reduced basis solution in a descending order of error.Then, the adaptive search refines the parametric space by increasing the order of polynomials until the algorithm is terminated by a saturation constraint. We demonstrate the effectiveness of the proposed algorithm for solving a stationary stochastic convection-diffusion equation, a benchmark problem chosen because solutions contain steep boundary layers and anisotropic features. Lastly, we show that two stages of adaptivity are critical in a benchmark problem with anisotropic stochasticity.

97 MATHEMATICS AND COMPUTING↗

TBASS: A Robust Adaptation of Bayesian Adaptive Spline Surfaces

The R package TBASS is an extension of the BASS package created by Francom and Sansó (2019). The package is used to fit a Bayesian multivariate adaptive spline to a dataset that either follows a Student’s t-distribution or has outliers. Much of the framework for TBASS is adapted from the concepts of Bayesian Multivariate Adaptive Regression Splines (BMARS), specifically the work done by Denison, Mallick, and Smith (1998). The spline function is fit using a Reversible-Jump Markov Chain Monte Carlo algorithm,. By including this more robust generalization, a dataset with outliers can be accurately fit using the BMARS model, without the possibility of overfitting or variance inflation.

97 MATHEMATICS AND COMPUTING↗