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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Development of the Microcalorimeter Detector for Athena/X-IFU

The X-ray Integral Field Unit (X-IFU) will be a microcalorimeter instrument on ESA’s Athena X-ray observatory, set to launch around 2037. Athena recently underwent a reformulation exercise resulting in a simplified X-IFU architecture, with a new baseline configuration featuring fewer pixels and readout channels. Newly developed transition edge sensor pixels that are slower and have reduced magnetic field sensitivity have helped enable the new instrument design whilst maintaining flagship quality science. In this paper, we report on the status and plan for continued development of the X-IFU microcalorimeter array. We describe details of the current pixel architecture and performance specifications. We will present the design of the first full scale microcalorimeter arrays that have the necessary flight like electrical and mechanical interfaces for X-IFU. These arrays will undergo testing in a focal-plane assembly (FPA) Development Model (DM) in Europe later in 2024 and serve as a precursor to the X-IFU Engineering Model detector.

Stephen J Smith↗
NASA NTRSDate not supplied

Objectively Identifying Transverse Cirrus Bands in Tropical Cyclones using a Convolutional Neural Network

Transverse cirrus bands (TCBs) are bands of upper-level clouds regularly seen in mesoscale and synoptic-scale weather systems. In tropical cyclones, their appearance has been subjectively linked to intensification and the diurnal cycle. However, these hypothesized relationships have not been rigorously tested due to the subjective nature of TCBs in satellite images. A machine learning technique that successfully identifies TCBs objectively in imagery from the GOES-16 Advanced Baseline Imager (ABI) has been developed to solve this problem. The technique uses a U-Net convolutional neural network (CNN) that assigns a probability to each pixel in an image based on the likelihood of the pixel being associated with a TCB. Using the U-Net CNN, a database of TCBs from 2019 to 2022 was developed for the Atlantic tropical cyclone basin by defining an appropriate probability threshold that defines the difference between TCB and non-TCB pixels. This threshold is where the Jaccard score, calculated using manually identified TCBs and model identified TCBs, is maximized. Statistics for TCB occurrence will also be presented, including the relationships between TCBs and storm relative motion, shear relative direction, cardinal direction, tropical cyclone intensity, tropical cyclone intensification rates, and time of day.

John Mark Mayhall↗
NASA NTRS2022

Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing

Hazard detection is critical for enabling autonomous landing on planetary surfaces. Current state-of-the-art methods leverage traditional computer vision approaches to automate the identification of safe terrain from input digital elevation models (DEMs). However, performance for these methods can degrade for input DEMs with increased sensor noise. In the last decade, deep learning techniques have been developed for various applications. Nevertheless, their applicability to safety-critical space missions has often been limited due to concerns regarding their outputs’ reliability. In response to these limitations, this paper proposes an application of the Bayesian deep learning segmentation method for hazard detection. The developed approach enables reliable, safe landing site detection by i) generating simultaneously a safety prediction map and its uncertainty map via Bayesian deep learning and semantic segmentation, and ii) using the uncertainty map to filter out the uncertain pixels in the prediction map so that the safe site identification is performed only based on the certain pixels (i.e., pixels for which the model is certain about its safety prediction). Experiments are presented with simulated data based on a Mars HiRISE digital terrain model by varying uncertainty threshold and noise levels to demonstrate the performance of the proposed approach.

Kento Tomita↗
DOE OSTI2015

Sparse sampling and reconstruction for electron and scanning probe microscope imaging

Systems and methods for conducting electron or scanning probe microscopy are provided herein. In a general embodiment, the systems and methods for conducting electron or scanning probe microscopy with an undersampled data set include: driving an electron beam or probe to scan across a sample and visit a subset of pixel locations of the sample that are randomly or pseudo-randomly designated; determining actual pixel locations on the sample that are visited by the electron beam or probe; and processing data collected by detectors from the visits of the electron beam or probe at the actual pixel locations and recovering a reconstructed image of the sample.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2015

Systems and methods that generate height map models for efficient three dimensional reconstruction from depth information

Methods of generating a three dimensional representation of an object in a reference plane from a depth map including distances from a reference point to pixels in an image of the object taken from a reference point. Weights are assigned to respective voxels in a three dimensional grid along rays extending from the reference point through the pixels in the image based on the distances in the depth map from the reference point to the respective pixels, and a height map including an array of height values in the reference plane is formed based on the assigned weights. An n-layer height map may be constructed by generating a probabilistic occupancy grid for the voxels and forming an n-dimensional height map comprising an array of layer height values in the reference plane based on the probabilistic occupancy grid.

42 ENGINEERING↗
DOE OSTI2017

AN INDUCTIVE MAPPING WITH CONVOLUTIONAL REPRESENTATIONS FOR HUMAN SETTLEMENT DETECTION: PRELIMINARY RESULTS

Undoubtedly, deep convolutional learning methods continue to improve performance in image-level classification for computer vision and remote sensing applications. However, the spatio-temporal nature of remote sensing imagery offers other interesting challenges in multiscale image understanding. Emerging opportunities include seeking fine-grained and neighborhood mapping with overhead imagery. Limitations due to lack of relevant scale ground-truth often mandates that these challenges are pursued as disjoint. We test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate surprising potential on multiscale experiments that incorporate edge-level details up to semantic-level informationWe test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a novel unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate a preliminary inductive transfer learning potential on multiscale experiments that incorporate edge-level details up to semantic-level informationWe test this premise and explore representation spaces from a single deep convolutional network and their visualization to argue for a novel unified feature extraction framework. The objective is to utilize and re-purpose trained feature extractors without the need for network retraining on three remote sensing tasks i.e. superpixel mapping, pixel-level segmentation and semantic based image visualization. By leveraging the same convolutional feature extractors and viewing them as visual information extractors that encode different image representation spaces, we demonstrate a preliminary inductive transfer learning potential on multiscale experiments that incorporate edge-level details up to semantic-level information.

Lunga, Dalton↗
DOE OSTI2017

Vertically Integrated Edgeless Photon Imaging Camera

The Vertically Integrated Photon Imaging Chip - Large, (VIPIC-L), is a large area, small pixel (65μm), 3D integrated, photon counting ASIC with zero-suppressed or full frame dead-time-less data readout. It features data throughput of 14.4 Gbps per chip with a full frame readout speed of 56kframes/s in the imaging mode. VIPIC-L contain 192 x 192 pixel array and the total size of the chip is 1.248cm x 1.248cm with only a 5μm periphery. It contains about 120M transistors. A 1.3M pixel camera module will be developed by arranging a 6 x 6 array of 3D VIPIC-L’s bonded to a large area silicon sensor on the analog side and to a readout board on the digital side. The readout board hosts a bank of FPGA’s, one per VIPIC-L to allow processing of up to 0.7 Tbps of raw data produced by the camera.

Fahim, Farah↗
DOE OSTI2018

Ultralow-dose, feedback imaging with laser-Compton X-ray and laser-Compton gamma ray sources

Ultralow-dose, x-ray or gamma-ray imaging is based on fast, electronic control of the output of a laser-Compton x-ray or gamma-ray source (LCXS or LCGS). X-ray or gamma-ray shadowgraphs are constructed one (or a few) pixel(s) at a time by monitoring the LCXS or LCGS beam energy required at each pixel of the object to achieve a threshold level of detectability at the detector. An example provides that once the threshold for detection is reached, an electronic or optical signal is sent to the LCXS/LCGS that enables a fast optical switch that diverts, either in space or time the laser pulses used to create Compton photons. In this way, one prevents the object from being exposed to any further Compton x-rays or gamma-rays until either the laser-Compton beam or the object are moved so that a new pixel location may be illumination.

43 PARTICLE ACCELERATORS↗
DOE OSTI2019

Portable COTS RGB Wavefront System for Real-time Turbulence Mitigation

Atmospheric effects reduce the ability to detect or identify objects of interest due to spatial and spectral scintillation. Algorithms alone cannot correct for turbulence over long-range horizontal paths. While adaptive optics methods work well for astronomical viewing, they are not readily adapted for complex imagery over long-range horizontal paths. At MSS Parallel in 2016, we presented our work for the red/green/blue (RGB) wavefront sensor. Since then, we have completed our system to combine an off-the-shelf high-frame-rate USB3 color camera with a compact 90 mm Maksutov-Cassegrain telescope and an OKO deformable mirror (DM) to create a portable, real-time RGB wavefront sensor and turbulence mitigation system. The telescope’s aperture is covered with an aluminum plate holding three separate narrowband color filters. These filters, specifically matched to the relative spectral response of the sensor’s Bayer mask, provide nearly complete separation of the three color images. This device enables portable imaging through atmospheric turbulence and analysis thereof, where relative motion of the three-color Bayer-pixel video provides real-time wavefront information on the second-order statistics of Kolmogorov turbulence. We measured relative RGB pixel shifts and controlled this mirror using an ODROID single-board computer. We developed a bench setup to calibrate the relationship between pixel shifts and the deformable mirror actuators. We demonstrated the feasibility of this system on a benchtop and on scenes at 700 meters showing real time correction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Smart-readout of the Skipper-CCD: Achieving Sub-electron Noise Levels in Regions of Interest

The skipper CCD is a special type of charge coupled device in which the readout noise can be reduced to sub-electron levels by averaging independent measurements of the same charge. Thus the charge in the pixels can be determined by counting the exact number of electrons. The total readout time is proportional to the number of measurements of the charge in each pixel. For some applications this time may be too long; however, researchers usually are interested only on certain region within the matrix of pixels. In this paper we present the development of a smart skipper readout technique that allows the user to specify regions of interest of the CCD matrix where an arbitrary (high) number of measurements of the same charge can taken to obtain the desired noise level, and far less measurements are performed in those regions that are less interesting to the researcher, therefore reducing the total readout time.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Achieving Single-Electron Sensitivity at Enhanced Speed in Fully-Depleted CCDs with Double-Gate MOSFETs

We introduce a new output amplifier for fully-depleted thick p-channel CCDs based on double-gate MOSFETs. The charge amplifier is an n-type MOSFET specifically designed and operated to couple the fully-depleted CCD with high charge-transfer efficiency. The junction coupling between the CCD and MOSFET channels has enabled high sensitivity, demonstrating sub-electron readout noise in one pixel charge measurement. We have also demonstrated the non-destructive readout capability of the device. Achieving single-electron and single-photon per pixel counting in the entire CCD pixel array has been made possible through the averaging of a small number of samples. We have demonstrated fully-depleted CCD readout with better performance than the floating diffusion and floating gate amplifiers available today, in both single and multisampling regimes, boasting at least six times the speed of floating gate amplifiers.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Multi-MGy Radiation Hardened Camera for Nuclear Facilities

There is an increasing interest in developing cameras for surveillance systems to monitor nuclear facilities or nuclear waste storages. Particularly, for today's and the next generation of nuclear facilities increasing safety requirements consecutive to Fukushima Daiichi's disaster have to be considered. For some applications, radiation tolerance needs to overcome doses in the MGy(SiO{sub 2}) range whereas the most tolerant commercial or prototypes products based on solid state image sensors withstand doses up to few kGy. The objective of this work is to present the radiation hardening strategy developed by our research groups to enhance the tolerance to ionizing radiations of the various subparts of these imaging systems by working simultaneously at the component and system design levels. Developing radiation-hardened camera implies to combine several radiation-hardening strategies. In our case, we decided not to use the simplest one, the shielding approach. This approach is efficient but limits the camera miniaturization and is not compatible with its future integration in remote-handling or robotic systems. Then, the hardening-by-component strategy appears mandatory to avoid the failure of one of the camera subparts at doses lower than the MGy. Concerning the image sensor itself, the used technology is a CMOS Image Sensor (CIS) designed by ISAE team with custom pixel designs used to mitigate the total ionizing dose (TID) effects that occur well below the MGy range in classical image sensors (e.g. Charge Coupled Devices (CCD), Charge Injection Devices (CID) and classical Active Pixel Sensors (APS)), such as the complete loss of functionality, the dark current increase and the gain drop. We'll present at the conference a comparative study between these radiation-hardened pixel radiation responses with respect to conventional ones, demonstrating the efficiency of the choices made. The targeted strategy to develop the complete radiation hard camera electronics will be exposed. Another important element of the camera is the optical system that transports the image from the scene to the image sensor. This arrangement of glass-based lenses is affected by radiations through two mechanisms: the radiation induced absorption and the radiation induced refractive index changes. The first one will limit the signal to noise ratio of the image whereas the second one will directly affect the resolution of the camera. We'll present at the conference a coupled simulation/experiment study of these effects for various commercial glasses and present vulnerability study of typical optical systems to radiations at MGy doses. The last very important part of the camera is the illumination system that can be based on various technologies of emitting devices like LED, SLED or lasers. The most promising solutions for high radiation doses will be presented at the conference. In addition to this hardening-by-component approach, the global radiation tolerance of the camera can be drastically improve by working at the system level, combining innovative approaches eg. for the optical and illumination systems. We'll present at the conference the developed approach allowing to extend the camera lifetime up to the MGy dose range. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Results with a micro-cavity plasma panel detector

During the three last years, a complete study of a radiation detector based on plasma panel technology (main component of plasma television display) has been completed using source, cosmic ray and beam. This studies showed a fast response (O(5 ns)), high spatial resolution detection of ionizing particle and minimum ionizing particles. It shows very promising results in term of pixel-to-pixel uniformity and time stability of both signal shapes and rates. The prototype has also demonstrated very low background over a wide range of applied high voltages, excellent pixel response isolation, time resolutions of a few nanoseconds, and efficiencies above 95% over a 100-volt range for beta particles emitted by a {sup 106}Ru radioactive source. A full report will be presented (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Image-Based Digital Twin for Assessing the Coupled Electro-Chemo-Mechanical Behavior of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The discrete nature of the images' pixel points is employed throughout the model and approximation construction. The mechanical model is verified using an image-based microstructure under tensile loading. A transient electro-chemo-mechanical coupled simulation is performed to evaluate the potential micro-cracking induced degradation of the battery cathode material subjected to charge/discharge cycling.

battery degradation↗
DOE OSTI2024

Astronomical Spectroscopy with Skipper CCDs: First Results from a Skipper CCD Focal Plane Prototype at SIFS

We present the first on-sky results from an ultra-low-readout-noise Skipper CCD focal plane prototype for the SOAR Integral Field Spectrograph (SIFS). The Skipper CCD focal plane consists of four 6k x 1k, 15 $\mu$m pixel, fully-depleted, p-channel devices that have been thinned to ~250 $\mu$m, backside processed, and treated with an anti-reflective coating. These Skipper CCDs were configured for astronomical spectroscopy, i.e., single-sample readout noise < 4.3 e- rms/pixel, the ability to achieve multi-sample readout noise $\ll$ 1 e- rms/pixel, full-well capacities ~40,000-65,000 e-, low dark current and charge transfer inefficiency (~2 x 10$^{-4}$ e-/pixel/s and 3.44 x 10$^{-7}$, respectively), and an absolute quantum efficiency of $\gtrsim$ 80% between 450 nm and 980 nm ($\gtrsim$ 90% between 600 nm and 900 nm). We optimized the readout sequence timing to achieve sub-electron noise (~0.5 e- rms/pixel) in a region of 2k x 4k pixels and photon-counting noise (~0.22 e- rms/pixel) in a region of 220 x 4k pixels, each with a readout time of $\lesssim$ 17 min. We observed two quasars (HB89 1159+123 and QSO J1621-0042) at redshift z ~ 3.5, two high-redshift galaxy clusters (CL J1001+0220 and SPT-CL J2040-4451), an emission line galaxy at z = 0.3239, a candidate member star of the Bo\"{o}tes II ultra-faint dwarf galaxy, and five CALSPEC spectrophotometric standard stars (HD074000, HD60753, HD106252, HD101452, HD200654). We present charge-quantized, photon-counting observations of the quasar HB89 1159+123 and show the detector sensitivity increase for faint spectral features. We demonstrate signal-to-noise performance improvements for SIFS observations in the low-background, readout-noise-dominated regime. We outline scientific studies that will leverage the SIFS-Skipper CCD data and new detector architectures that utilize the Skipper floating gate amplifier with faster readout times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Sensor Co-design for $\textit{smartpixels}$

Pixel tracking detectors at upcoming collider experiments will see unprecedented charged-particle densities. Real-time data reduction on the detector will enable higher granularity and faster readout, possibly enabling the use of the pixel detector in the first level of the trigger for a hadron collider. This data reduction can be accomplished with a neural network (NN) in the readout chip bonded with the sensor that recognizes and rejects tracks with low transverse momentum (p$_T$) based on the geometrical shape of the charge deposition (``cluster''). To design a viable detector for deployment at an experiment, the dependence of the NN as a function of the sensor geometry, external magnetic field, and irradiation must be understood. In this paper, we present first studies of the efficiency and data reduction for planar pixel sensors exploring these parameters. A smaller sensor pitch in the bending direction improves the p$_T$ discrimination, but a larger pitch can be partially compensated with detector depth. An external magnetic field parallel to the sensor plane induces Lorentz drift of the electron-hole pairs produced by the charged particle, broadening the cluster and improving the network performance. The absence of the external field diminishes the background rejection compared to the baseline by $\mathcal{O}$(10%). Any accumulated radiation damage also changes the cluster shape, reducing the signal efficiency compared to the baseline by $\sim$ 30 - 60%, but nearly all of the performance can be recovered through retraining of the network and updating the weights. Finally, the impact of noise was investigated, and retraining the network on noise-injected datasets was found to maintain performance within 6% of the baseline network trained and evaluated on noiseless data.

Shekar, Danush [Illinois U., Chicago]↗
DOE OSTI2024

The 4D Camera: An 87 kHz Direct Electron Detector for Scanning/Transmission Electron Microscopy

We describe the development, operation, and application of the 4D Camera—a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ~480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10–700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

mpfit: a robust method for fitting atomic resolution images with multiple Gaussian peaks

The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit, an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗