Search NASA⌕ Search

SEARCH · Search NASA

Results for “Adaptivity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

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↗
NASA NTRS1996

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↗
NASA NTRS1995

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↗
DOE OSTI2024

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.↗
DOE OSTI2021

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.↗
NASA NTRS1988

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↗
NASA NTRS2002

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↗
NASA NTRS2016

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↗
DOE OSTI2023

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↗
DOE OSTI2020

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↗
NASA NTRS1972

Effects of incomplete adaption and disturbance in adaptive control

This investigation focused attention on the fact that the synthesis of adaptive control systems has often been discussed in the framework of idealizations which may represent over simplifications. A condition for boundedness of the tracking error has been derived for the case in which incomplete adaption and disturbance are present. When using Parks' design it is shown that instability of the adaptive gains can result due to the presence of disturbance. The theory has been applied to a nontrivial example in order to illustrate the concepts involved.

Lindorff, D. P.↗
NASA NTRS1972

Effects of incomplete adaptation and disturbance in adaptive control.

In this paper consideration is given to the effects of disturbance and incomplete parameter adaptation on the performance of adaptive control systems in which Liapunov theory is used in deriving the control law. A design equation for the bounded error is derived. It is further shown that parameters in the adaptive controller may not converge in the presence of disturbance unless the input signal has a rich enough frequency constant. Design examples are presented.

Lindorff, D. P.↗
NASA NTRS2003

An Adaptive Critic Approach to Reference Model Adaptation

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

Krishnakumar, K.↗
NASA NTRS2014

Adaptive Shape Functions and Internal Mesh Adaptation for Modelling Progressive Failure in Adhesively Bonded Joints

Enhanced finite elements are elements with an embedded analytical solution that can capture detailed local fields, enabling more efficient, mesh independent finite element analysis. The shape functions are determined based on the analytical model rather than prescribed. This method was applied to adhesively bonded joints to model joint behavior with one element through the thickness. This study demonstrates two methods of maintaining the fidelity of such elements during adhesive non-linearity and cracking without increasing the mesh needed for an accurate solution. The first method uses adaptive shape functions, where the shape functions are recalculated at each load step based on the softening of the adhesive. The second method is internal mesh adaption, where cracking of the adhesive within an element is captured by further discretizing the element internally to represent the partially cracked geometry. By keeping mesh adaptations within an element, a finer mesh can be used during the analysis without affecting the global finite element model mesh. Examples are shown which highlight when each method is most effective in reducing the number of elements needed to capture adhesive nonlinearity and cracking. These methods are validated against analogous finite element models utilizing cohesive zone elements.

computational mechanics↗
DOE OSTI2021

An adaptive adversarial domain adaptation approach for corn yield prediction

Recently, statistical machine learning and deep learning methods have been widely explored for corn yield prediction. Though successful, machine learning models generated within a specific spatial domain often lose their validity when directly applied to new regions. To address this issue, we designed an unsupervised adaptive domain adversarial neural network (ADANN). Specifically, through domain adversarial training, the ADANN model reduced the impact of domain shift by projecting data from different domains into the same subspace. Also, the ADANN model was designed to be trained in an adaptive way, which guaranteed the model can learn the domain-invariant features and perform accurate yield prediction simultaneously. Informative variables including time-series vegetation indices and sequential weather observations were first collected from multiple data sources and aggregated to the county level. Then, we trained the ADANN model with the extracted features and corresponding reported county-level corn yield from the U.S. Department of Agriculture (USDA). Finally, the trained model was evaluated in four testing years 2016–2019. The U.S. corn belt was used as the study area and counties under study were grouped into two diverse ecological regions. Overall, the experimental results showed that the developed ADANN model had better performance than three other state-of-the-art machine learning models in both local experiments (train and test in the same region) and transfer experiments (train and test in different regions). As the first study using adversarial learning for crop yield prediction, this research demonstrates a novel solution for improving model transferability on crop yield prediction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MultiSector Dynamics: Advancing the Science of Complex Adaptive Human-Earth Systems

The field of MultiSector Dynamics (MSD) explores the dynamics and co-evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state of knowledge, and describes ongoing activities to expand capacities for open science, leverage revolutions in data and computing, and grow and diversify the MSD workforce. Central to our vision is the ambition of advancing the next generation of complex adaptive human-Earth systems science to better address interconnected risks, increase resilience, and improve sustainability. This will require convergent research and the integration of ideas and methods from multiple disciplines. Understanding the tradeoffs, synergies, and complexities that exist in coupled human-Earth systems is particularly important in the context of energy transitions and increased future shocks.

Reed, Patrick↗
DOE OSTI2022

Adaptive Urban Traffic Signal Control for Multiple Intersections: An LQR Approach

Traffic congestion leads to severe problems especially in urban traffic networks. It increases the chance of accidents, energy waste, and social costs. In order to address these problems, an adaptive linear quadratic regulator (LQR) approach is developed for traffic signal control at multiple intersections in an urban area. The proposed method controls the green time of the traffic signals to reduce traffic congestion and smooth traffic flow. Real-world data from vision-based traffic sensors are used to build the traffic network model, which mimics the real-world traffic behavior. In addition, the proposed control utilizes recursive least square parameter estimation, which is capable of tracking dynamic changes in traffic conditions. Simulation of Urban MObility (SUMO) is used to analyze the efficacy of the proposed method. Results of the simulation show that the proposed method outperforms pretimed control in various aspects.

adaptive LQR control↗
DOE OSTI2023

An Adaptive Virtual Oscillator Control Structure for Grid-Forming Inverters

The electrical grid is facing unprecedented challenges due to the increasing penetration of inverter-based resources. Grid forming inverters (GFMIs) are a promising technology to address these challenges. Recently, the virtual oscillator based GFMI control is attracting more attention due to its superior performance over other control strategies. In this article, an adaptive control strategy is proposed to provide flexible operation and transition between grid-connected and islanded modes. The controller adapts the virtual oscillator's parameter values depending on the operation mode. It also provides a feedback signal using a measured frequency to account for any steady-state errors and to allow a seamless transition from grid-connected to islanded mode. Finally, to show the feasibility of the proposed controller, this article discusses the simulation results from the implementation of the controller on a single inverter system and on a group of inverters on a large practical utility feeder, the IEEE 13 node feeder, using the DIgSILENT simulation environment.

adaptive control↗