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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Sensory-Feedback Exoskeletal Arm Controller

An electromechanical exoskeletal arm apparatus has been designed for use in controlling a remote robotic manipulator arm. The apparatus, called a force-feedback exoskeleton arm master (F-EAM) is comfortable to wear and easy to don and doff. It provides control signals from the wearer s arm to a robot arm or a computer simulator (e.g., a virtual-reality system); it also provides force and torque feedback from sensors on the robot arm or from the computer simulator to the wearer s arm. The F-EAM enables the wearer to make the robot arm gently touch objects and finely manipulate them without exerting excessive forces. The F-EAM features a lightweight design in which the motors and gear heads that generate force and torque feedback are made smaller than they ordinarily would be: this is achieved by driving the motors to power levels greater than would ordinarily be used in order to obtain higher torques, and by providing active liquid cooling of the motors to prevent overheating at the high drive levels. The F-EAM (see figure) includes an assembly that resembles a backpack and is worn like a backpack, plus an exoskeletal arm mechanism. The FEAM has five degrees of freedom (DOFs) that correspond to those of the human arm: 1. The first DOF is that of the side-to-side rotation of the upper arm about the shoulder (rotation about axis 1). The reflected torque for this DOF is provided by motor 1 via drum 1 and a planar four-bar linkage. 2. The second DOF is that of the up-and-down rotation of the arm about the shoulder. The reflected torque for this DOF is provided by motor 2 via drum 2. 3. The third DOF is that of twisting of the upper arm about its longitudinal axis. This DOF is implemented in a cable remote-center mechanism (CRCM). The reflected torque for this DOF is provided by motor 3, which drives the upper-arm cuff and the mechanism below it. A bladder inflatable by gas or liquid is placed between the cuff and the wearer s upper arm to compensate for misalignment between the exoskeletal mechanism and the shoulder. 4. The fourth DOF is that of flexion and extension of the elbow. The reflected torque for this DOF is provided by motor 4 and drum 4, which are mounted on a bracket that can slide longitudinally by a pin-and-slot engagement with the upper-arm cuff to compensate for slight variations in the position of the kinematic center of the elbow. Attached to drum 4 is an adapter plate to which is attached a CRCM for the lower arm. 5. The lower-arm CRCM implements the fifth DOF, which is the twist of the forearm about its longitudinal axis. Motor 5 provides the reflected torque for this DOF by driving the lower-arm cuff. A rod transmits twist and torsion between the lower-arm cuff and the hand cuff. With this system, the motion of the wearer s joints and the reflected torques applied to these joints can be measured and controlled in a relatively simple manner. This is because the anthropomorphic design of the mechanism imitates the kinematics of the human arm, eliminating the need for kinematic conversion of joint-torque and joint-angle data.

An, Bin↗
NASA NTRS2009

Testing of an Integrated Reactor Core Simulator and Power Conversion System with Simulated Reactivity Feedback

A Direct Drive Gas-Cooled (DDG) reactor core simulator has been coupled to a Brayton Power Conversion Unit (BPCU) for integrated system testing at NASA Glenn Research Center (GRC) in Cleveland, OH. This is a closed-cycle system that incorporates an electrically heated reactor core module, turbo alternator, recuperator, and gas cooler. Nuclear fuel elements in the gas-cooled reactor design are replaced with electric resistance heaters to simulate the heat from nuclear fuel in the corresponding fast spectrum nuclear reactor. The thermodynamic transient behavior of the integrated system was the focus of this test series. In order to better mimic the integrated response of the nuclear-fueled system, a simulated reactivity feedback control loop was implemented. Core power was controlled by a point kinetics model in which the reactivity feedback was based on core temperature measurements; the neutron generation time and the temperature feedback coefficient are provided as model inputs. These dynamic system response tests demonstrate the overall capability of a non-nuclear test facility in assessing system integration issues and characterizing integrated system response times and response characteristics.

Bragg-Sitton, Shannon M.↗
NASA NTRS2013

Dusty Feedback from Massive Black Holes in Two Elliptical Galaxies

Far-infrared dust emission from elliptical galaxies informs us about galaxy mergers, feedback energy outbursts from supermassive black holes and the age of galactic stars. We report on the role of AGN feedback observationally by looking for its signatures in elliptical galaxies at recent epochs in the nearby universe. We present Herschel observations of two elliptical galaxies with strong and spatially extended FIR emission from colder grains 5-10 kpc distant from the galaxy cores. Extended excess cold dust emission is interpreted as evidence of recent feedback-generated AGN energy outbursts in these galaxies, visible only in the FIR, from buoyant gaseous outflows from the galaxy cores.

Galaxies↗
NASA NTRS2016

Single-Mode, Distributed Feedback Interband Cascade Lasers

Single-mode, distributed feedback interband cascade lasers (ICLs) using distributed-feedback gratings (e.g., lateral Bragg gratings) and methods of fabricating such ICLs are provided. The ICLs incorporate distributed-feedback gratings that are formed above the laser active region and adjacent the ridge waveguide (RWG) of the ICL. The ICLs may incorporate a double-ridge system comprising an optical confinement structure (e.g., a RWG) disposed above the laser active region that comprises the first ridge of the double ridge system, a DFB grating (e.g., lateral Bragg grating) disposed above the laser active region and adjacent the optical confinement structure, and an electric confinement structure that passes at least partially through the laser active region and that defines the boundary of the second ridge comprises and the termination of the DFB grating.

Frez, Clifford F.↗
NASA NTRS2021

Soil Moisture–Atmosphere Feedbacks Dominate Land Carbon Uptake Variability

Year-to-year changes in carbon uptake by terrestrial ecosystems play an essential role in determining atmospheric carbon dioxide concentrations. It remains uncertain to what extent temperature and water availability can explain these variations at the global scale. Here we use factorial climate model simulations and show that variability in soil moisture drives 90% of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture–atmosphere feedbacks amplify temperature and humidity anomalies, and enhance the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate a dominant role of soil moisture which is not readily apparent in land surface model simulations and observational analyses. These findings highlight the need to account for feedbacks between soil and atmospheric dryness when estimating the carbon cycle’s response to climatic change globally, as well as when conducting field-scale investigations of the ecosystem response to droughts. Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects which are controlled by soil moisture.

Atmospheric dynamics↗
NASA NTRSDate not supplied

The Surface Albedo of Sea Ice in CMIP6 and the Implications for the Surface Albedo Feedback

The Arctic has experienced rapid sea ice loss and a substantial decline in surface albedo, significantly impacting its radiation budget. Climate models from the Coupled Model Intercomparison Project (CMIP6) reproduce these changes. However, inconsistencies remain among models regarding the magnitude, spatial distribution, and seasonal patterns of Arctic surface albedo evolution. This study investigates these discrepancies by comparing model outputs with observation from the Clouds and the Earth's Radiant Energy System (CERES). We develop a decomposition method to assess the contributions of sea ice albedo, sea ice concentration, and sea ice extent to Arctic surface albedo. Over land, differences in snow cover account for the substantial inter-model spread in surface albedo, while over the ocean, sea ice albedo, concentration, and extent all contribute. Comparisons between CMIP6 and the Atmospheric Model Intercomparison Project (AMIP) simulations, which use identically prescribed sea ice concentrations, reveals considerable inter-model spread in Arctic Ocean surface albedo due to differences in sea ice albedo. Applying the decomposition method to projections shows that models predicting larger decreases in sea ice concentration and extent, especially in the Central Arctic, exhibit lower surface albedo and stronger sea ice albedo feedback. Beyond 2050, Arctic Ocean surface albedo decline is mainly influenced by sea ice extent indicating that the retreat of the ice edge is the most important process to constrain the surface albedo feedback. This study provides insights into factors contributing to the spread and changes in Arctic surface albedo and the associated sea ice albedo feedback.

Patrick C Taylor↗
DOE OSTI2025

CHEMREASONER: Heuristic Search over a Large Language Model’s Knowledge Space using Quantum-Chemical Feedback

The discovery of new catalysts is essential for the design of new and more efficient chemical processes in order to transition to a sustainable future. We introduce an AI-guided computational screening framework unifying linguistic reasoning with quantum-chemistry based feedback from 3D atomistic representations. Our approach formulates catalyst discovery as an uncertain environment where an agent actively searches for highly effective catalysts via the iterative combination of large language model (LLM)-derived hypotheses and atomistic graph neural network (GNN)-derived feedback. Identified catalysts in intermediate search steps undergo structural evaluation based on spatial orientation, reaction pathways, and stability. Scoring functions based on adsorption energies and barriers steer the exploration in the LLM's knowledge space toward energetically favorable, high-efficiency catalysts. We introduce planning methods that automatically guide the exploration without human input, providing competitive performance against expert-enumerated chemical descriptor-based implementations. By integrating language-guided reasoning with computational chemistry feedback, our work pioneers AI-accelerated, trustworthy catalyst discovery.

artificial intelligence↗
DOE OSTI2024

Implications of a Pervasive Climate Model Bias for Low‐Cloud Feedback

Abstract How low clouds respond to warming constitutes a key uncertainty for climate projections. Here we observationally constrain low‐cloud feedback through a controlling factor analysis based on ridge regression. We find a moderately positive global low‐cloud feedback (0.45 W , 90% range 0.18–0.72 W ), about twice the mean value (0.22 W ) of 16 models from the Coupled Model Intercomparison Project. We link this discrepancy to a pervasive model mean‐state bias: models underestimate the low‐cloud response to warming because (a) they systematically underestimate present‐day tropical marine low‐cloud amount, and (b) the low‐cloud sensitivity to warming is proportional to this present‐day low‐cloud amount. Our results hence highlight the importance of reducing model biases in both the mean state of clouds and their sensitivity to environmental factors for accurate climate change projections.

58 GEOSCIENCES↗
DOE OSTI2026

Recent Weakening of the Global Radiative Feedback

Earth's climate stability, characterized by the global radiative feedback parameter (𝜆), varies decadally due to changing surface temperature patterns. Recent variations in 𝜆 are poorly understood as coordinated model simulations typically end in 2014. We apply a convolutional neural network trained on climate model simulations to observation-based surface temperature reconstructions to estimate variations in 𝜆 up to 2025. We find that 𝜆 reached a minimum (maximum stability) around the mid 1990s (𝜆 ≃ −3 Wm −2 /K), but has since weakened significantly (𝜆 ≃ −2 Wm −2 /K). We confirm these results with climate model simulations extended to 2022. The recent 𝜆 weakening is not significantly affected by El Niño Southern Oscillation or Pacific Decadal Oscillation. Attribution reveals that warming in the subtropical Northeast Pacific is an important driver of the recently weakened feedback, confirmed by targeted experiments in E3SMv2. Our approach enables near real-time monitoring of Earth's climate stability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

In-Field Testing of Components for Feedback and Control of the ITER Disruption Mitigation System

Here, the shattered pellet injection (SPI) method has been chosen as the disruption mitigation system (DMS) for ITER. To protect the device from plasma disruptions that cause damaging heat and electromagnetic loads, SPI is used to inject high-Z material into the plasma. The process of SPI utilizes cryogenic cooling to form solid pellets. Pellets are accelerated down a barrel and into an angled surface, causing the pellet to shatter prior to entering the tokamak chamber. For the DMS to function reliably, the 27 separate shattered pellet injectors planned for ITER must rely on many components to provide accurate feedback data and for control functions. Each component in the DMS is exposed to an elevated background magnetic field depending on its placement and proximity to the plasma chamber. A Helmholtz coil test stand that is operated at Oak Ridge National Laboratory was utilized to test the components in relevant background field levels to assess component performance. This paper details the test design and results for in-field component operation for a variety of components. This list includes the following components: two different network switches for camera connectivity, a VAT fast shutter valve intended to reduce the flow of SPI propellant gas into the torus, a solenoid control valve intended for use in the pellet formation process, pressure/vacuum switches to be used for feedback and control, a printed circuit board piezo pressure sensor to be used to measure breech pressure, and various relays for the high-voltage pulsed power supply used to drive the SPI propellant valve.

Disruption mitigation↗
DOE OSTI2024

Feedback-based quantum algorithm inspired by counterdiabatic driving

In recent quantum algorithmic developments, a feedback-based approach has shown promise for preparing quantum many-body system ground states and solving combinatorial optimization problems. This method utilizes quantum Lyapunov control to iteratively construct quantum circuits. Here, we propose a substantial enhancement by implementing a protocol that uses ideas from quantum Lyapunov control and the counterdiabatic driving protocol, a key concept from quantum adiabaticity. Our approach introduces an additional control field inspired by counterdiabatic driving. We apply our algorithm to prepare ground states in one-dimensional quantum Ising spin chains. Comprehensive simulations demonstrate a remarkable acceleration in population transfer to low-energy states within a significantly reduced time frame compared to conventional feedback-based quantum algorithms. This acceleration translates to a reduced quantum circuit depth, a critical metric for potential quantum computer implementation. We validate our algorithm on the IBM cloud computer, highlighting its efficacy in expediting quantum computations for many-body systems and combinatorial optimization problems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Advocating Feedback Control for Human-Earth System Applications

This paper proposes a feedback control perspective for Human-Earth Systems (HESs) which essentially are complex systems that capture the interactions between humans and nature. Recent attention in HES research has been directed towards devising strategies for climate change mitigation and adaptation, aimed at achieving environmental and societal objectives. However, existing approaches heavily rely on HES models, which inherently suffer from inaccuracies due to the complexity of the system. Moreover, overly detailed models often prove impractical for optimization tasks. We propose a framework inheriting from feedback control strategies the robustness against model errors, because inaccuracies are mitigated using measurements retrieved from the field. The framework comprises two nested control loops. The outer loop computes the optimal inputs to the HES, which are then implemented by actuators controlled in the inner loop. Potential fields of applications are also identified and a numerical example is provided.

biological system modeling↗
DOE OSTI2024

The Role of Deep Convection and Large-scale Circulation in Driving Model Spread in Low Cloud Feedback and Equilibrium Climate Sensitivity

This project aims to advance the understanding of the processes that drive the large uncertainties in climate change projections, use observations to constrain model physics and reduce the inter-model spread in equilibrium climate sensitivity (ECS). There are three major goals: 1) Characterize the representation of the physical pathways that link deep convection, large-scale circulation and low cloud feedback in CMIP6 model simulations and determine the relative contribution of each pathway to the CMIP6 model spread in low cloud feedback and ECS; 2) Use process-oriented diagnostics and multiple observations to evaluate CMIP6 model performance in capturing the observed cloud-circulation relation and deep convection characteristics including convective transition statistics and the bulk properties of mesoscale convective systems (MCSs). Error decomposition in CMIP6 models will be performed. 3) Conduct E3SM short-range hindcasts following the DOE Cloud-Associated Parameterizations Testbed (CAPT) protocol to pinpoint specific model parameters/processes that are crucial to the representation of deep convection, circulation, clouds and the pathways that connect them. We will modify convective parameters in E3SM and analyze the perturbed physics experiments (PPEs) to isolate model parameters that are critical to the uncertainty of ECS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A Proof for the Unbiased Nature of Range-Doppler Measurements in Coarse-Resolution Dechirp-on-Receive Feedback Synthetic Aperture Radar Navigation

In feedback synthetic aperture radar (SAR) navigation, observables extracted from SAR range-Doppler images correct position and velocity errors accumulated within an associated navigation system. Unlike most other sensors, which produce measurements without input from a navigation system, SARs require a prior estimate of the radar’s position and velocity to adjust the radar’s matched filter during range-Doppler image formation. Consequently, it is possible for position and velocity errors within a navigation system to manifest as additional errors (biases) in the range-Doppler measurement observables. Prior work has not tackled this possibility in the context of feedback SAR navigation with a dechirp-on-receive radar. This paper offers a proof demonstrating that range-Doppler observables extracted from coarse-resolution vertical SAR images formed with a dechirp-on-receive radar may be safely modeled as unbiased measurements of the radar’s true position and velocity despite the presence of moderate navigation errors.

dechirp-on-receive↗
NASA NTRS2002

Adaptation to Coriolis force perturbation of movement trajectory; role of proprioceptive and cutaneous somatosensory feedback

Subjects exposed to constant velocity rotation in a large fully-enclosed room that rotates initially make large reaching errors in pointing to targets. The paths and endpoints of their reaches are deviated in the direction of the transient lateral Coriolis forces generated by the forward velocity of their reaches. With additional reaches, subjects soon reach in straighter paths and become more accurate at landing on target even in the absence of visual feedback about their movements. Two factors contribute to this adaptation: first, muscle spindle and golgi tendon organ feedback interpreted in relation to efferent commands provide information about movement trajectory, and second, somatosensory stimulation of the fingertip at the completion of a reach provides information about the location of the fingertip relative to the torso.

Non-NASA Center↗
NASA NTRS1988

The effects of feedback lighting on the circadian rhythm of locomotor activity and the reproductive maturation of the male Djungarian hamster (Phodopus sungorus)

The non-parametric model of entrainment suggests that brief pulses of light, delivered between dusk and dawn can simulate the phasing effects of full photoperiods or even constant light (LL). Feedback lighting (LDFB) is a lighting condition where individual animals, otherwise in constant darkness (DD), are exposed to light in response to a monitored behavior. The specific purpose of this type of illumination is to expose the circadian cycle to light only during the subjective night. LDFB has been used to support this hypothesis in several species of nocturnal rodents and one species of diurnal primate by producing similar free-running periods in LDFB as in LL. This lighting condition has also been used to test the hypothesis that exposing the subjective night to even short duration light pulses will maintain reproductive function in long day breeders. In the Syrian hamster (Mesocricetus auratus), however, LDFB is not as photostimulatory as LL despite extensive light exposure during the subjective night. In the experiments presented here, a group of immature male Djungarian hamsters (Phodopus sungorus) were placed in individual light-tight sound attenuated chambers where they had free access to food, water and an activity wheel. The animals were exposed to one of four lighting conditions [DD, LL, LDFB or a neighbor control of feedback lighting (LDFB NC)] for approximately 30 days shortly after weaning. LDFB NC is a lighting condition where a neighbor control hamster receives the identical lighting regime as a paired animal exposing itself to LDFB, yet the neighbor has no control over it. A fifth group was exposed to a light-dark cycle of 16 hours of light and 8 hours of dark (LD16:8). This group was housed in cages in a colony room and did not have access to a running wheel. The free-running periods of the locomotor activity rhythms for hamsters exposed to LDFB and LL were not similar, unlike the results for rats, Syrian hamsters, mice, monkeys and even mature Djungarian hamsters. Immature hamsters exposed to DD and LDFB NC developed more slowly than animals exposed to LL or LD16:8, while hamsters in LDFB developed at an intermediate rate. Thus, it appears that LDFB, although capable of inducing reproductive function in immature Djungarian hamsters, is not as photostimulatory as may have been expected from current photoperiodic models, despite substantial light exposure during the subjective night. Furthermore, this data may suggest that the circadian system of 18-48 day old Djungarian hamsters are still undergoing organizational maturation.

NASA Program Space Biology↗
NASA NTRS2001

Exploring new frontiers in multi-rater feedback

The presentation provides an overview of the Upward Feedback Program used at JPL to provide feedback to managers on their employees' perceptions of their management effectiveness.

upward feedback leadership employee assessment↗