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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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NASA NTRS1987

Automatic continuum analysis of reflectance spectra

A continuum algorithm based on a Segmented Upper Hull method (SUH) is described. An upper hull is performed on segments of a spectrum defined by local minima and maxima. The segments making a complete spectrum are then combined. The definition of the upper hull allows the continuum to be both concave and/or convex, adapting to the shape of the spectrum. The method performs multiple passes on a spectrum by segmenting each local maximum to minimum and performing an upper hull. The algorithm naturally adapts to the widths of absorption features, so that all features are found, including the nature of doublets, triplets, etc. The algorithm is also reasonably fast on common minicomputers so that it might be applied to the large data sets from imaging spectrometers.

Clark, Roger N.↗

NASA NTRS1991

Adaptive control of interface by temperature and interface profile feedback in transparent multi-zone crystal growth furnace

The objective of this research is to control the dynamics of multizone programmable crystal growth furnaces. Due to the inevitable heat exchange among different heating zones and the transient nature of the process, the dynamics of multizone furnaces is time varying, distributed, and therefore complex in nature. Electrical power to heating zones and the translational speed of the ampoule are employed as inputs to control the dynamics. Structural properties of the crystal is the ultimate aim of this adaptive control system. These properties can be monitored in different ways. Following an order of complexity, these may include: (1) on line measurement of the material optical properties such as the refractive index of crystal; (2) on line x-ray imaging of the interface topology; (3) on line optical quantification of the interface profile such as the determination of concavity or convexity of the interface shape; and (4) on line temperature measurement at points closest to the material such as measurements of the ampoule's outside and inside surface temperatures. The research performed makes use of the temperature and optical measurements, specified in (3) and (4) as the outputs of furnace dynamics. However, if the instrumentation is available, the proposed control methodology can be extended to the measurements listed in (1) and (2).

Batur, Celal↗

NASA NTRS2006

Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

Masek, Jeffrey G.↗

NASA NTRS2018

HabEx Space Telescope Optical System Overview: General Astrophysics Instruments

The HabEx (Habitable Exoplanet) concept study is defining a future space telescope with the primary mission of detecting and characterizing planetary systems around nearby stars. The telescope baseline design includes a high-contrast coronagraph and a starshade to enable the direct optical detection of exoplanets as close as 70 mas to their star. In addition to the study of exoplanets, HabEx carries two dedicated instruments for general astrophysics. The first instrument is a camera enabling imaging on a 3 arc minute field of view in two bands stretching from the UV at 150 nm to the near infrared at 1800 nm. The same instrument can also be operated as a multi-object spectrograph, with resolution of 2000. The second instrument is a high-resolution UV spectrograph operating from 300 nm down to 115 nm with up to 60,0000 resolution. HabEx would provide the highest resolution UV/optical images ever obtained. Diffraction limited at 0.4 µm, it would outperform all current and approved facilities, including the 30 m class ground-based extremely large telescopes (ELTs), which will achieve ~0.01 arcsecond resolution at near-infrared (IR) wavelengths with adaptive optics, but will be seeing-limited at optical wavelengths. HabEx would observe wavelengths inaccessible from the ground, including the UV and in optical/near-IR atmospheric absorption bands. Operating at L2, far above the Earth’s atmosphere and free from the large thermal swings inherent to HST’s low-Earth orbit, HabEx would provide an ultra-stable platform that will enable science ranging from precision astrometry to the most sensitive weak lensing maps ever obtained. Here we discuss the design concepts of the general astrophysics optical instruments for the proposed observatory.

Nissen, Joel↗

DOE OSTI2023

Simulation based inference with domain adaptation for strong gravitational lensing

Simulation based inference leverages machine learning to carry out Bayesian inference in systems with intractable likelihoods. However, transitioning a network trained on simulated data to real data runs the risk of encountering domain shift, leading to performance losses. We attempt to implement domain adaptation into the sbi neural posterior estimation framework using the Maximum Mean Discrepancy as an additional network loss, using masked autoregressive fow (MAF) as our density estimator. We test the network on a set of 400,000 simulated strong gravitational lensing images generated using deeplenstronomy. The source domain is defined as low noise whereas the target domain has a noise profile sampled from experimentally derived DES survey conditions. We find that SBI appears robust against small changes in the data with similar performance on source and target. Moreover, while DA does lead to performance improvements, they are marginal at 6% less inference error.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

EchemAMR (electro-chemical microsctructure scale models with adaptive meshing) [SWR-23-111]

A 3D microstructure resolving electrochemical transport and interfacial chemistry solver. Electrode microstructure plays an important role in determining the performance of an electrochemical system, e.g. lithium ion battery. EchemAMR is a microstructure scale model that solves the governing equations for ion transport, electrical current continuity, interfacial chemistry and structural mechanics. Complex microstructure geometries from imaging can be directly imported into EchemAMR. A volume fraction based description of the geometry on Cartesian grid with an immersed interface formulation enables simplified meshing and large-scale simulations with millions of degrees of freedom. EchemAMR has been tested against systems with analytic solutions for numerical convergence and highly resolved lithium ion battery microstructures. EchemAMR demonstrates excellent mass conversation and efficient scaling on heterogenous High-Performance Computing (HPC) with central and graphics processing units.

Sitaraman, Hariswaran↗

NASA NTRS1985

Acousto-optic techniques for real SAR imaging

Recent advancements in the development of the Real Time Acousto-optic SAR Processor are presented. In particular, the technique for introducing the azimuth reference function into the processor via an acousto-optic Bragg cell is discussed. This approach permits the reference function to be stored in electronic memory, thus giving the processor the flexibility needed to adapt rapidly to changes in the radar/target geometry. The architecture is described and results are presented which show the applicability of the technique to both spot-light and strip-map SAR.

Haney, M.↗

NASA NTRS2010

Simultaneous Spectral Temporal Adaptive Raman Spectrometer - SSTARS

Raman spectroscopy is a prime candidate for the next generation of planetary instruments, as it addresses the primary goal of mineralogical analysis, which is structure and composition. However, large fluorescence return from many mineral samples under visible light excitation can render Raman spectra unattainable. Using the described approach, Raman and fluorescence, which occur on different time scales, can be simultaneously obtained from mineral samples using a compact instrument in a planetary environment. This new approach is taken based on the use of time-resolved spectroscopy for removing the fluorescence background from Raman spectra in the laboratory. In the SSTARS instrument, a visible excitation source (a green, pulsed laser) is used to generate Raman and fluorescence signals in a mineral sample. A spectral notch filter eliminates the directly reflected beam. A grating then disperses the signal spectrally, and a streak camera provides temporal resolution. The output of the streak camera is imaged on the CCD (charge-coupled device), and the data are read out electronically. By adjusting the sweep speed of the streak camera, anywhere from picoseconds to milliseconds, it is possible to resolve Raman spectra from numerous fluorescence spectra in the same sample. The key features of SSTARS include a compact streak tube capable of picosecond time resolution for collection of simultaneous spectral and temporal information, adaptive streak tube electronics that can rapidly change from one sweep rate to another over ranges of picoseconds to milliseconds, enabling collection of both Raman and fluorescence signatures versus time and wavelength, and Synchroscan integration that allows for a compact, low-power laser without compromising ultimate sensitivity.

Blacksberg, Jordana↗

NASA NTRS1989

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗

DOE OSTI2024

Measurement of Photovoltaic Module Deformation Dynamics During Hail Impact Using Digital Image Correlation

Stereo high-speed video of photovoltaic modules undergoing laboratory hail tests was processed using digital image correlation to determine module surface deformation during and immediately following impact. The purpose of this work was to demonstrate a methodology for characterizing module impact response differences as a function of construction and incident hail parameters. Video capture and digital image analysis were able to capture out-of-plane module deformation to a resolution of ±0.1 mm at 11 kHz on an in-plane grid of 10 × 10 mm over the area of a 1 × 2 m commercial photovoltaic module. With lighting and optical adjustments, the technique was adaptable to arbitrary module designs, including size, backsheet color, and cell interconnection. Furthermore, impacts were observed to produce an initially localized dimple in the glass surface, with peak deflection proportional to the square root of incident energy. Subsequent deformation propagation and dissipation were also captured, along with behavior for instances when the module glass fractured. Natural frequencies of the module were identifiable by analyzing module oscillations postimpact. Limitations of the measurement technique were that the impacting ice ball obscured the data field immediately surrounding the point of contact, and both ice and glass fracture events occurred within 100 μs, which was not resolvable at the chosen frame rate. Increasing the frame rate and visualizing the back surface of the impact could be applied to avoid these issues. Applications for these data include validating computational models for hail impacts, identifying the natural frequencies of a module, and identifying damage initiation mechanisms.

14 SOLAR ENERGY↗

NASA NTRS2017

Performance of a Space-Based Wavelet Compressor for Plasma Count Data on the MMS Fast Plasma Investigation

Data compression has been a staple of imaging instruments for years. Recently, plasma measurements have utilized compression with relatively low compression ratios. The Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale (MMS) mission generates data roughly 100 times faster than previous plasma instruments, requiring a higher compression ratio to fit within the telemetry allocation. This study investigates the performance of a space-based compression standard employing a Discrete Wavelet Transform and a Bit Plane Encoder (DWT/BPE) in compressing FPI plasma count data. Data from the first 6 months of FPI operation are analyzed to explore the error modes evident in the data and how to adapt to them. While approximately half of the Dual Electron Spectrometer (DES) maps had some level of loss, it was found that there is little effect on the plasma moments and that errors present in individual sky maps are typically minor. The majority of Dual Ion Spectrometer burst sky maps compressed in a lossless fashion, with no error introduced during compression. Because of induced compression error, the size limit for DES burst images has been increased for Phase 1B. Additionally, it was found that the floating point compression mode yielded better results when images have significant compression error, leading to floating point mode being used for the fast survey mode of operation for Phase 1B. Despite the suggested tweaks, it was found that wavelet-based compression, and a DWT/BPE algorithm in particular, is highly suitable to data compression for plasma measurement instruments and can be recommended for future missions.

plasma↗

DOE OSTI2025

Point cloud-based diffusion models for the Electron-Ion Collider

At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standard Model, and inference tasks. In particular, it has been demonstrated that score-based diffusion models can generate high-fidelity and accurate samples of jets or collider events. This work expands on previous generative models in three distinct ways. First, our model is trained to generate entire collider events, including all particle species with complete kinematic information. We quantify how well the model learns event-wide constraints such as the conservation of momentum and discrete quantum numbers. We focus on the events at the future Electron-Ion Collider, but we expect that our results can be extended to proton-proton and heavy-ion collisions. Second, previous generative models often relied on image-based techniques. The sparsity of the data can negatively affect the fidelity and sampling time of the model. We address these issues using point clouds and a novel architecture combining edge creation with transformer modules called Point Edge Transformers. Third, we adapt the foundation model OmniLearn, to generate full collider events. This approach may indicate a transition toward adapting and fine-tuning foundation models for downstream tasks instead of training new models from scratch.

Araz, Jack Y. [Stony Brook Univ., NY (United State↗

DOE OSTI2022

Accelerating error correction in tomographic reconstruction

Abstract Spurred by recent advances in detector technology and X-ray optics, upgrades to scanning-probe-based tomographic imaging have led to an exponential growth in the amount and complexity of experimental data and have created a clear opportunity for tomographic imaging to approach single-atom sensitivity. The improved spatial resolution, however, is highly susceptible to systematic and random experimental errors, such as center of rotation drifts, which may lead to imaging artifacts and prevent reliable data extraction. Here, we present a model-based approach that simultaneously optimizes the reconstructed specimen and sinogram alignment as a single optimization problem for tomographic reconstruction with center of rotation error correction. Our algorithm utilizes an adaptive regularizer that is dynamically adjusted at each alternating iteration step. Furthermore, we describe its implementation in a software package targeting high-throughput workflows for execution on distributed-memory clusters. We demonstrate the performance of our solver on large-scale synthetic problems and show that it is robust to a wide range of noise and experimental drifts with near-ideal throughput.

Ali, Sajid (ORCID:0000000321864636)↗

DOE OSTI2023

A Versatile Fiber Coating Process for Efficient Fabrication of Multifunctional Composites

The objective of this research is to demonstrate the versatility of a dip coating process for the efficient integration of piezoelectric barium titanate (BaTiO3) microparticles on a wide variety of fibers to design passive self-sensing composites. The microparticles were deposited on glass, aramid, and basalt fiber weaves through the proposed dip coating technique. A computational framework is established to predict the deposition thickness on the fiber surfaces from the given microparticle concentration, size, coating velocity, and coating fluid viscosity. The deposition quality assessment was performed through scanning electron microscope imaging and subsequent image analysis. BaTiO3-coated fibers were directly used in composite preparation. After fabrication, the BaTiO3-enhanced composites were subjected to high-voltage poling. Finally, their passive self-sensing properties were characterized through experimental studies. The results show the adaptability of the proposed coating process to integrate BaTiO3 microparticles within different types of fiber-reinforced composites enabling passive self-sensing to attain subsurface damage characterization.

Gupta, Sumit↗

DOE OSTI2023

Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

Plant phenotyping is typically a time-consuming and expensive endeavor, requiring large groups of researchers to meticulously measure biologically relevant plant traits, and is the main bottleneck in understanding plant adaptation and the genetic architecture underlying complex traits at population scale. In this work, we address these challenges by leveraging few-shot learning with convolutional neural networks to segment the leaf body and visible venation of 2,906 Populus trichocarpa leaf images obtained in the field. In contrast to previous methods, our approach (a) does not require experimental or image preprocessing, (b) uses the raw RGB images at full resolution, and (c) requires very few samples for training (e.g., just 8 images for vein segmentation). Traits relating to leaf morphology and vein topology are extracted from the resulting segmentations using traditional open-source image-processing tools, validated using real-world physical measurements, and used to conduct a genome-wide association study to identify genes controlling the traits. In this way, the current work is designed to provide the plant phenotyping community with (a) methods for fast and accurate image-based feature extraction that require minimal training data and (b) a new population-scale dataset, including 68 different leaf phenotypes, for domain scientists and machine learning researchers. All of the few-shot learning code, data, and results are made publicly available.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1971

Analog video magnetograms in real time.

Description of a video differential photometer which is the result of an attempt to adapt television technology to the task of producing an electronic equivalent of the photographic subtraction technique. Advantages of electronic subtraction are potentially greater field sensitivity, immediate availability of the subtracted magnetograms (virtually in real time), and greater versatility in combining and comparing image data. Commercial television equipment was used in construction of the apparatus. All video subtraction, averaging, and other processing is done in analog form. The final magnetogram is displayed on an ordinary television monitor.

Smithson, R. C.↗

NASA NTRS1983

Some practical universal noiseless coding techniques, part 2

This report is an extension of earlier work (Part 1) which provided practical adaptive techniques for the efficient noiseless coding of a broad class of data sources characterized by only partially known and varying statistics (JPL Publication 79-22). The results here, while still claiming such general applicability, focus primarily on the noiseless coding of image data. A fairly complete and self-contained treatment is provided. Particular emphasis is given to the requirements of the forthcoming Voyager II encounters of Uranus and Neptune. Performance evaluations are supported both graphically and pictorially. Expanded definitions of the algorithms in Part 1 yield a computationally improved set of options for applications requiring efficient performance at entropies above 4 bits/sample. These expanded definitions include as an important subset, a somewhat less efficient but extremely simple "FAST' compressor which will be used at the Voyager Uranus encounter. Additionally, options are provided which enhance performance when atypical data spikes may be present.

Rice, R. F.↗

NASA NTRS1994

Effect of resistance training on muscle use during exercise

This study examined the effect of resistance training on exercise-induced contrast shift in magnetic resonance (MR) images. It was hypothesized that a given load could be lifted after training with less muscle showing contrast shift, thereby suggesting less muscle was used to perform the exercise. Nine males trained the left quadriceps femoris (QF) muscle 2 days/wk for 9 wk using 3-6 sets of 12 knee extensions each day. The right QF served as a control. Exercise-induced contrast shifts in MR images evoked by each of three bouts of exercise (5 sets of 10 knee extensions with a load equal to 50, 75, and 100% of the maximum pretraining load that could be lifted for 5 sets of 10 repetitions) were quantified pre- and posttraining. MR image contrast shift was quantified by determining QF cross-sectional area (CSA) showing increased spin-spin relaxation time. One repetition maximum increased 14% in the left trained QF and 7% in the right untrained QF. Left QF CSA increased 5%, with no change in right QSF CSA. Left QF CSA showing contrast shift was less after each bout of the exercise test posttraining. This was also true, to a lesser extent, for the right QF at the higher two loads. The results suggest that short-term resistance training reduces MR image contrast shift evoked by a given effort, thereby reflecting the use of less muscle to lift the load. Because this response was evident in both trained and contralateral untrained muscle, neural factors are suggested to be responsible. The consequence of this adaptation could be to increase 'stress' per unit area of active muscle during the course of training and thereby evoke hypertrophy.

Ploutz, Lori L.↗