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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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Plug and play: a general approach for the fusion of sensor and machine learning models
Regularized or Bayesian inversion has revolutionized our ability to reconstruct images from incomplete data.
Estimating groundwater use and demand in arid Kenya through assimilation of satellite data and in-situ sensors with machine learning toward drought early action
Groundwater is an important source of water for people, livestock, and agriculture during drought in the Horn of Africa. In this work, areas of high groundwater use and demand in drought-prone Kenya were identified and forecasted prior to the dry season. Estimates of groundwater use were extended from a sentinel network of 69 in-situ sensored mechanical boreholes to the region with satellite data and a machine learning model. The sensors contributed 756 site-month observations from June 2017 to September 2021 for model building and validation at a density of approximately one sensor per 3700 sq.km. An ensemble of 19 parameterized algorithms was informed by features including satellite-derived precipitation, surface water availability, vegetation indices, hydrologic land surface modeling, and site characteristics to dichotomize high groundwater pump utilization. Three operational definitions of high demand on groundwater infrastructure were considered: 1) mechanical runtime of pumps greater than a quarter of a day (6+ hr) and daily per capita volume extractions indicative of 2) domestic water needs (35+ L), and 3) intermediate needs including livestock (75+ L). Gridded interpolation of localized groundwater use and demand was provided from 2017 to 2020 and forecasted for the 2021 dry season, June–September 2021. Cross-validated skill for contemporary estimates of daily pump runtime and daily volume extraction to meet domestic and intermediate water needs was 68%, 69%, and 75%, respectively. Forecasts were externally validated with an accuracy of at least 56%, 70%, or 72% for each groundwater use definition. The groundwater maps are accessible to stakeholders including the Kenya National Drought Management Authority (NDMA) and the Famine Early Warning Systems Network (FEWS NET). These maps represent the first operational spatially-explicit sub-seasonal to seasonal (S2S) estimates of groundwater use and demand in the literature. Knowledge of historical and forecasted groundwater use is anticipated to improve decision-making and resource allocation for a range of early warning early action applications.
Surface accuracy measurement sensor test on a 50-meter antenna surface model
The Surface Accuracy Measurement Sensor (SAMS) is a telescope with a focal plane photo electric detector that senses the lateral position of light source targets in its field of view. After extensive laboratory testing the engineering breadboard sensor system was installed and tested on a 30 degree segment of a 50-meter diameter, mesh surface, antenna model. Test results correlated well with the laboratory tests and indicated accuracies of approximately 0.59 arc seconds at 21 meters range. Test results are presented and recommendations given for sensor improvements.
Design and test of an earth aspect sensor
Electronic breadboard model of solid state earth aspect attitude sensor for spin stabilized probes
SU-D-213-03: Towards An Optimized 3D Scintillation Dosimetry Tool for Quality Assurance of Dynamic Radiotherapy Techniques
Purpose: The purpose of this work is to simulate a multi-focus plenoptic camera used as the measuring device in a real-time three-dimensional scintillation dosimeter. Simulating and optimizing this realistic optical system will bridge the technological gap between concept validation and a clinically viable tool that can provide highly efficient, accurate and precise measurements for dynamic radiotherapy techniques. Methods: The experimental prototype, previously developed for proof of concept purposes, uses an off-the-shelf multi-focus plenoptic camera. With an array of interleaved microlenses of different focal lengths, this camera records spatial and angular information of light emitted by a plastic scintillator volume. The three distinct microlens focal lengths were determined experimentally for use as baseline parameters by measuring image-to-object magnification for different distances in object space. A simulated plenoptic system was implemented using the non-sequential ray tracing software Zemax: this tool allows complete simulation of multiple optical paths by modeling interactions at interfaces such as scatter, diffraction, reflection and refraction. The active sensor was modeled based on the camera manufacturer specifications by a 2048×2048, 5 µm-pixel pitch sensor. Planar light sources, simulating the plastic scintillator volume, were employed for ray tracing simulations. Results: The microlens focal lengths were determined to be 384, 327 and 290 µm. A realistic multi-focus plenoptic system, with independently defined and optimizable specifications, was fully simulated. A f/2.9 and 54 mm-focal length Double Gauss objective was modeled as the system’s main lens. A three-focal length hexagonal microlens array of 250-µm thickness was designed, acting as an image-relay system between the main lens and sensor. Conclusion: Simulation of a fully modeled multi-focus plenoptic camera enables the decoupled optimization of the main lens and microlens specifications. This work leads the way to improving the 3D dosimeter’s achievable resolution, efficiency and build for providing a quality assurance tool fully meeting clinical needs. M.R. is financially supported by a Master’s Canada Graduate Scholarship from the NSERC. This research is also supported by the NSERC Industrial Research Chair in Optical Design.
Online and Offline Identification of False Data Injection Attacks in Battery Sensors Using a Single Particle Model
The cells in battery energy storage systems are monitored, protected, and controlled by battery management systems whose sensors are susceptible to cyberattacks. False data injection attacks (FDIAs) targeting batteries’ voltage sensors affect cell protection functions and the estimation of critical battery states like the state of charge (SoC). Inaccurate SoC estimation could result in battery overcharging and over discharging, which can have disastrous consequences on grid operations. This paper proposes a three-pronged online and offline method to detect, identify, and classify FDIAs corrupting the voltage sensors of a battery stack. To accurately model the dynamics of the series-connected cells a single particle model is used and to estimate the SoC, the unscented Kalman filter is employed. FDIA detection, identification, and classification was accomplished using a tuned cumulative sum (CUSUM) algorithm, which was compared with a baseline method, the chi-squared error detector. Online simulations and offline batch simulations were performed to determine the effectiveness of the proposed approach. Throughout the batch simulations, the CUSUM algorithm detected attacks, with no false positives, in 99.83% of cases, identified the corrupted sensor in 97% of cases, and determined if the attack was positively or negatively biased in 97% of cases.
Daylight imagery of ocean surface waves for wave spectra
A simple second-order model is developed to describe the transformation between surface wave slope and radiance incident on an optical sensor. The model includes azimuth as well as elevation variations in the sky-radiance distribution and their effects on the imaging of wave slopes approaching the sensor azimuth from various directions. The model also includes upwelling radiance. Comparison between the exact transformation from wave slope to radiance and the second-order model suggests that they yield quantitatively similar results. The model is used in physical interpretations of how wave slopes are imaged and in indicating a way of optimizing the linearity and contrast of the transfer function relating wave slope to radiance for various sensor geometries, thereby minimizing sources of error. One-dimensional numerical simulations of the imaging of an analytically generated wave-slope profile demonstrate the utility of this technique in obtaining slope spectra.
Sensor-agnostic photogrammetric image registration with applications to population modeling
Photogrammetric registration of airborne and spaceborne imagery is a crucial prerequisite to many data fusion tasks. While embedded sensor models provide a rough geolocation estimate, these metadata may be incomplete or imprecise. Manual solutions are appropriate for small-scale projects, but for rapid streams of cross-modal, multi-sensor, multi-temporal imagery with varying metadata standards, an automated approach is required. We present a high-performance image registration workflow to address this need. This paper outlines the core development concepts and demonstrates its utility with respect to the 2016 data fusion contest imagery. In particular, Iris ultra-HD video is georeferenced to the Earth surface via registration to DEIMOS-2 imagery, which serves as a trusted control source. Geolocation provides opportunity to augment the video with spatial context, stereo-derived disparity, spectral sensitivity, change detection, and numerous ancillary geospatial layers. We conclude by leveraging these derivative data layers towards one such fusion application: population distribution modeling.
Free Drifting Buoys
Information was exchanged between people directly involved with the development, use, and/or potential use of free drifting buoys. Tracking systems and techniques, where methods and accuracy of optical, radio, radar, satellite, and sonic tracking of free-drifting buoys were discussed. Deployment and retrieval covering methods currently used or planned in the deployment and retrieval of free-drifting buoys from boats, ships, helicopters, fixed platforms, and fixed-wing aircraft were reported. Simulation, sensors, and data emphasizing the status of water circulation modeling, and sensors useful on free-drifting buoys, and data display and analysis were described.
Novel Optical Diagnostic Techniques for Studying Particle Deposition Upon Large Cylinders in a Sheared Suspension
On a twelve-month voyage to Mars, one astronaut will require at least two tons of potable water and two tons of pure oxygen. Efficient, reliable fluid reclamation is therefore necessary for manned space exploration. Space habitats require a compact, flexible, and robust apparatus capable of solid-fluid mechanical separation over a wide range of fluid and particle densities and particle sizes. In space, centrifugal filtration, where particles suspended in fluid are captured by rotating fixed-fiber mat filters, is a logical candidate for mechanical separation. Non-colloidal particles are deposited on the fibers due to inertial impaction or direct interception. Since rotation rates are easily adjustable, inertial effects are the most practical way to control separation rates for a wide variety of multiphase mixtures in variable gravity environments. Understanding how fluid inertia and differential fluid-particle inertia, characterized by the Reynolds and Stokes numbers, respectively, affect deposition is critical in optimizing filtration in a microgravity environment. This work will develop non-intrusive optical diagnostic techniques for directly visualizing where and when non-colloidal particles deposit upon, or contact, solid surfaces: 'particle proximity sensors'. To model particle deposition upon a single filter fiber, these sensors will be used in ground-based experiments to study particle dynamics as in the vicinity of a large (compared with the particles) cylinder in a simply sheared (i.e., linearly-varying, zero-mean velocity profile) neutrally-buoyant, refractive-index matched solid-liquid suspension.
3D Material Response Analysis of PICA Pyrolysis Experiments
Primarily interested in improving ablation modeling for use in inverse reconstruction of flight environments on ablative heat shields. Ablation model is essentially a component of the heat flux sensor, so model uncertainties lead to measurement uncertainties. Non-equilibrium processes have been known to be significant in low density ablators for a long time, but increased accuracy requirements of the reconstruction process necessitates incorporating this physical effect. Attempting to develop a pyrolysis model for implementation in material response based on the PICA data produced by Bessire and Minton. Pyrolysis gas species molar yields as a function of temperature and heating rate. Several problems encountered while trying to fit Arrhenius models to the data led to further investigation of the experimental setup.
Computational Electromagnetic Modeling of SansEC(Trade Mark) Sensors
This paper describes the preliminary effort to apply computational design tools to aid in the development of an electromagnetic SansEC resonant sensor composite materials damage detection system. The computational methods and models employed on this research problem will evolve in complexity over time and will lead to the development of new computational methods and experimental sensor systems that demonstrate the capability to detect, diagnose, and monitor the damage of composite materials and structures on aerospace vehicles.
Deposition Of Thin-Film Sensors On Glass-Fiber/Epoxy Models
Direct-deposition process devised for fabrication of thin-film sensors on three-dimensional, curved surfaces of models made of stainless steel covered with glass-fiber/epoxy-matrix composite material. Models used under cryogenic conditions, and sensors used to detect on-line transitions between laminar and turbulent flows in wind tunnel environments. Sensors fabricated by process used at temperatures from minus 300 degrees F to 175 degrees F.
Linear mixing model applied to coarse spatial resolution data from multispectral satellite sensors
A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55-3.95 micron channel was used with the two reflective channels 0.58-0.68 micron and 0.725-1.1 micron to run a constrained least squares model to generate fraction images for an area in the west central region of Brazil. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse spatial resolution data for global studies.
Evaluating the Accuracy of Various Irradiance Models in Detecting Soiling of Irradiance Sensors
We evaluate the feasibility of using various clear-sky models or purchased satellite data for estimating the soiling of a reference cell irradiance sensor. We find results to be more accurate for models that consider local meteorological conditions. We conclude that given the data sets considered, and depending on the requirements of the data analyst, choosing to use purchased satellite irradiance data from Solargis to estimate the soiling of a reference cell sensor tends to yield more accurate results, although there are instances where a clear-sky model performs better. The SOLIS clear-sky model in PVLIB with variable P wat provided useful soiling results, implying that the general method of using a clear-sky model with local meteorological data may provide a low-cost tool for detecting soiling of irradiance sensors.
Alpha-Particle Gas-Pressure Sensor
An approximate model was developed to establish design curves for the saturation region and a more complete model developed to characterize the current-voltage curves for an alpha-particle pressure sensor.
Virtual Deformation Control of the X-56A Model with Simulated Fiber Optic Sensors
A robust control law design methodology is presented to stabilize the X-56A model and command its wing shape. The X-56A was purposely designed to experience flutter modes in its flight envelope. The methodology introduces three phases: the controller design phase, the modal filter design phase, and the reference signal design phase. A mu-optimal controller is designed and made robust to speed and parameter variations. A conversion technique is presented for generating sensor strain modes from sensor deformation mode shapes. The sensor modes are utilized for modal filtering and simulating fiber optic sensors for feedback to the controller. To generate appropriate virtual deformation reference signals, rigid-body corrections are introduced to the deformation mode shapes. After successful completion of the phases, virtual deformation control is demonstrated. The wing is deformed and it is shown that angle-ofattack changes occur which could potentially be used to an advantage. The X-56A program must demonstrate active flutter suppression. It is shown that the virtual deformation controller can achieve active flutter suppression on the X-56A simulation model.