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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Dynamic sensing of 6-axis external force and moment applied to a robot end

A dynamic force sensing method is proposed for a robot manipulator. A 6-axis wrist force sensor which is commonly used for robot force sensing does not take the direct measurement of the force and moment applied to an end effector externally from the environment of the manipulator, but takes the resultant of the gravity, the inertial force and moment on the end effector, and the external force and moment. The separation of gravitational and inertial force and moment from the measurement of the force sensor is crucial to achieving dynamically accurate force sensing and fast manipulator motion under force feedback control. A mathematical model is derived for the force sensing process and the separation of the force and moment as a nonlinear optimal state estimation problem formulated. Then an approximate solution is given using extended Kalman filtering techniques.

Yokota, Masaru Uchiyama↗
DOE OSTI2020

Dynamic compressed sensing for real-time tomographic reconstruction

Electron tomography has achieved higher resolution and quality at reduced doses with recent advances in compressed sensing. Compressed sensing (CS) exploits the inherent sparse signal structure to efficiently reconstruct three-dimensional (3D) volumes at the nanoscale from undersampled measurements. However, the process bottlenecks 3D reconstruction with computation times that run from hours to days. Here we demonstrate a framework for dynamic compressed sensing that produces a 3D specimen structure that updates in real-time as new specimen projections are collected. Researchers can begin interpreting 3D specimens as data is collected to facilitate high-throughput and interactive analysis. Using scanning transmission electron microscopy (STEM), we show that dynamic compressed sensing accelerates the convergence speed by ~3-fold while also reducing its error by 27% for a Au/SrTiO 3 nanoparticle specimen. Before a tomography experiment is completed, the 3D tomogram has interpretable structure within ~33% of completion and fine details are visible as early as ~66%. Upon completion of an experiment, a high-fidelity 3D visualization is produced without further delay. Additionally, we report reconstruction parameters that tune data fidelity can be manipulated throughout the computation without re-running the entire process.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network-based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 min) with little drift. Prediction errors are on the order of the soft deflection sensor’s accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

Sabelhaus, Andrew P.↗
DOE OSTI2020

Recursive Dynamic Compressive Sensing in Smart Distribution Systems

With a transition to a smarter grid, we are witnessing a significant growth in smart metering infrastructure and sensor deployment in the distribution system. The underlying communication infrastructure is stressed due to the large volume of data that is generated by the smart meters/sensors. Furthermore, real time operations such as state estimation and control are impaired due to the lack of reliable aggregation of the data. In this paper, we exploit the underlying sparsity in grid data to implement two recursive dynamic compressive sensing (CS) approaches-streaming modified weighted-`1 CS and Kalman filtered CS. These approaches aim to reconstruct the sparse signal using the current underdetermined measurements and the prior information about the sparse signal and its support set. Slow signal and support change is in distribution grid data is validated using Pecan Street data. Both the IEEE 34 node test feeder system and PecanStreet data are considered as two examples to validate the superior performance of the two recursive CS techniques relative to classic CS.

Karimi, Hazhar Sufi↗
DOE OSTI2025

High-dynamic-range quantum sensing of magnons and their dynamics using a superconducting qubit

Magnons, the quanta of collective spin excitations in magnetic materials, may enable functionalities, such as nonreciprocity and transduction in hybrid quantum devices. To assess the potential of such applications, it is necessary to understand magnon dynamics beyond the simple harmonic oscillator regime, where theory predicts effects like population-dependent damping and quantum fluctuations in the form of magnon shot noise. Probing these phenomena requires sensors with high sensitivity and the ability to resolve magnon properties across different excitation regimes. Here, we demonstrate accurate and sensitive detection of magnon population and decay over a wide range of occupation numbers. We use a superconducting qubit to probe magnons in a ferrimagnet over approximately 2000 excitations. Using qubit control and parametrically induced qubit-magnon interactions, we demonstrate few-excitation sensitive detection of magnons with a dynamic range of approximately 30 dB, and are able to accurately resolve their decay with few-ns sensitivity. These capabilities offer a powerful and practical technique for probing magnon dynamics in or beyond the linear regime over a wide range of excitations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1976

System for measuring Reynolds in a turbulently flowing fluid

A system for measuring momentum flux in a turbulently flowing fluid includes: a sensing apparatus for dynamically sensing the mainstream and the cross velocity components of the fluid, a transducer operative to provide two electrical output signals representative of the velocity components in the mainstream and in the cross direction, and signal processors to derive the Reynolds stress wave and the Reynolds stress.

Cheng, D. Y.↗
NASA NTRS1977

System for measuring three fluctuating velocity components in a turbulently flowing fluid

A system is described for measuring fluid velocity in a turbulently flowing fluid including a sensing apparatus for dynamically sensing the mainstream and two orthogonal cross velocity components of the fluid. A transducer operative is included to provide three electrical output signals representative of the velocity components in the mainstream, and in the cross directions. Signal processors can be utilized to derive the Reynolds stress wave and the Reynolds stress.

Cheng, D. Y.↗
NASA NTRS2001

Demodulation System for Fiber Optic Bragg Grating Dynamic Pressure Sensing

Fiber optic Bragg gratings have been used for years to measure quasi-static phenomena. In aircraft engine applications there is a need to measure dynamic signals such as variable pressures. In order to monitor these pressures a detection system with broad dynamic range is needed. This paper describes an interferometric demodulator that was developed and optimized for this particular application. The signal to noise ratio was maximized through temporal coherence analysis. The demodulator was incorporated in a laboratory system that simulates conditions to be measured. Several pressure sensor configurations incorporating a fiber optic Bragg grating were also explored. The results of the experiments are reported in this paper.

Lekki, John D.↗
DOE OSTI2022

Dynamic, resilient sensing system for automatic cyber-attack neutralization

An industrial asset may have monitoring nodes that generate current monitoring node values. An abnormality detection computer may determine that an abnormal monitoring node is currently being attacked or experiencing fault. A dynamic, resilient estimator constructs, using normal monitoring node values, a latent feature space (of lower dimensionality as compared to a temporal space) associated with latent features. The system also constructs, using normal monitoring node values, functions to project values into the latent feature space. Responsive to an indication that a node is currently being attacked or experiencing fault, the system may compute optimal values of the latent features to minimize a reconstruction error of the nodes not currently being attacked or experiencing a fault. The optimal values may then be projected back into the temporal space to provide estimated values and the current monitoring node values from the abnormal monitoring node are replaced with the estimated values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Non-destructive evaluation and machine learning methods for inspection of spent nuclear fuel canisters: A state-of-the-art review

Nuclear energy is among the cleanest and most efficient energy sources currently available. The operation of nuclear power plants (NPPs) produces large amounts of high-level radioactive waste known as spent nuclear fuel (SNF). Currently, large amounts of SNF is stored in dry cask storage systems (DCSSs) for extended interim storage until a permanent disposal solution becomes available. During the extended interim storage, the DCSS, particularly the SNF canisters, may degrade and abnormal conditions may occur. Therefore, non-destructive evaluation (NDE) and machine learning (ML) approaches are necessary for inspection of SNF canisters. This paper presents a state-of-the-art review of literature by summarizing recent progress made on the applications of NDE and ML for inspection of SNF canisters. Sixteen NDE methods are examined and compared: visual inspection, ultrasonic guided waves (UGWs), laser-based approaches, acoustic emission (AE), eddy current testing (ECT), non-invasive acoustic sensing, dynamic modal testing, cosmic ray muons tomography, neutron imaging, gamma rays detection, fiber optical sensors, through-wall communications, X-ray computed tomography (CT), vibrothermography, monoenergetic photon sources, and surface acoustic wave (SAW) sensors. The technology readiness level (TRL) for each method is assessed and compared. Recent publications on ML-enhanced visual inspection, AE, non-invasive acoustic sensing, dynamic modal testing, and neutron imaging for SNF canisters are summarized and future research needs are identified. In conclusion, this review article provides a convenient reference on the state-of-the-art applications of NDE and ML methods for inspection of SNF canisters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Fabrication of Six Degrees-of-Freedom Hexflex Positioner With Integrated Strain Sensing Using Nonlithographically Based Microfabrication

In this study, a process flow is described for the low cost, flexible fabrication of metal micro-electromechanical systems (MEMS) with high performance integrated sensing. The process is capable of producing new designs in ≈1 week at an average unit cost of <$1 k/device even at batch sizes of ≈1–10, with expected sensing performance limits of about 135 dB over a 10 kHz sensor bandwidth. This is a ≈20× reduction in cost, ≈25× reduction in time, and potentially >30× increase in sensing dynamic range over comparable state-of-the-art compliant nanopositioners. The nonlithographically based microfabrication (NLBM) process is uniquely suited to create high performance nanopositioning architectures which are customizable to the positioning requirements of a range of nanoscale applications. These can significantly reduce the cost of nanomanufacturing research and development, as well as accelerate the development of new processes and the testing of fabrication process chains without excess capital investment. A six degrees-of-freedom (6DOF) flexural nanopositioner with integrated sensing for all 6DOF was fabricated using the newly developed process chain. The fabrication process was measured to have ≈30 μ m alignment. Sensor arm, flexure, and trace widths of 150 μ m, 150 μ m, and 800 μ m, respectively, were demonstrated. Process capabilities suggest lower bounds of 25 μ m, 50 μ m, and 100 μ m, respectively. Dynamic range sensing of 52 dB was demonstrated for the nanopositioner over a 10 kHz sensor bandwidth. Improvements are proposed to approach sensor performance of about 135 dB over a 10 kHz sensor bandwidth.

42 ENGINEERING↗
NASA NTRS1985

MSFC Data Analysis of the SAFE/DAE Experiment

The Solar Array Flight Experiment (SAFE) on-orbit experiment for measurement of large structures dynamics consists of a dynamic sensing system designed to record and analyze the dynamic characteristics of the SAFE. The early availability of the SAFE and its basic large space structure characteristics made it a logical candidate for verification of the sensing system and evaluation technique. The characteristics of the solar array which place it well within the generic class of large space structures are: (1) Large size; (2) Low natural frequencies; (3) Mechanical complexity of its extendable/retractable mast; and (4) The inability to dynamic test in Earth atmosphere and one g.

Schock, R. W.↗
NASA NTRS1983

Safe on-orbit experiment for measurement of large structures dynamics

The Solar Array Flight Experiment (SAFE) on-orbit experiment for measurement of large structures dynamics consists of a dynamic sensing system designed to record and analyze the dynamic characteristics of the SAFE. The early availability of the SAFE and its basic large space structure characteristics make it a logical candidate for verification of the sensing system and the evaluation technique. The characteristics of the solar array which place it well within the generic class of large space structures are: (1) large size, (2) low natural frequencies, (3) mechanical complexity of its extendable/retractable mast, and (4) the inability to dynamically test in the Earth's atmosphere and in one g. The fourth characteristic is due to its size, air damping dominance of the blanket, and structural instability in one g. The specific characteristics of the solar array are shown and the applicability to large space structures is illustrated.

Schock, R. W.↗
NASA NTRS2015

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

variability↗