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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Distributed Optimization for Nonrigid Nano-Tomography

Resolution level and reconstruction quality in nano-computed tomography (nano-CT) are in part limited by the stability of microscopes, because the magnitude of mechanical vibrations during scanning becomes comparable to the imaging resolution, and the ability of the samples to resist radiation induced deformations during data acquisition. In such cases, there is no incentive in recovering the sample state at different time steps like in time-resolved reconstruction methods, but instead the goal is to retrieve a single reconstruction at the highest possible spatial resolution and without any imaging artifacts. Here we propose a distributed optimization solver for tomographic imaging of samples at the nanoscale. Our approach solves the tomography problem jointly with projection data alignment, nonrigid sample deformation correction, and regularization. Projection data consistency is regulated by dense optical flow estimated by Farneback's algorithm, leading to sharp sample reconstructions with less artifacts. Synthetic data tests show robustness of the method to Poisson and low-frequency background noise. We accelerated the solver on multi-GPU systems and validated the method on three nano-imaging experimental data sets.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Assessing the Oxygen Permeability of Candidate Asteroid Sample Containers With Optochemical Sensors

The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center currently curates 500 mg (10%) of carbonaceous asteroid Ryugu regolith collected by the Japan Aerospace and Exploration Agency’s Hayabusa II spacecraft and returned to Earth in 2021. In September 2023, NASA’s OSIRIS-REx spacecraft returned at least 70 grams of regolith collected from the surface of Carbonaceous Asteroid Bennu. These new astromaterials collections are stored and handled in gloveboxes and desiccators that are continuously purged with ultrapure nitrogen in order to minimize contamination and alteration of extraterrestrial samples from terrestrial environments, e.g., reaction with terrestrial oxygen and water. Ito et al. have previously reported on the development of containers to transport samples between facilities in inert, sealed environments; Hayabusa2 samples allocated to investigators by JAXA’s Extraterrestrial Sample Curation Center (ESCuC) are shipped in these Facility-to-Facility Transfer Containers (FFTCs). NASA curation has also been investigating sealed containers for storage, transportation, and allocation of Bennu and Ryugu regolith in sealed anoxic environments. In order to assess the ability of candidate sample containers to maintain nitrogen environments, we have utilized optochemical sensors to measure trace oxygen levels within sealed volumes.

C J Snead↗

DOE OSTI2020

Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data

High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genotypes with respect to the trait(s) of interest. In this paper, the potential of accurate and reliable sorghum biomass prediction using visible and near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data as well as light detection and ranging (LiDAR) data acquired by sensors mounted on UAV platforms is investigated. Predictive models are developed using classical regression-based machine learning methods for nine experiments conducted during the 2017 and 2018 growing seasons at the Agronomy Center for Research and Education (ACRE) at Purdue University, Indiana, USA. The impact of the regression method, data source, timing of RS and field-based biomass reference data acquisition, and the number of samples on the prediction results are investigated. R2 values for end-of-season biomass ranged from 0.64 to 0.89 for different experiments when features from all the data sources were included. Geometry-based features derived from the LiDAR point cloud to characterize plant structure and chemistry-based features extracted from hyperspectral data provided the most accurate predictions. Evaluation of the impact of the time of data acquisition during the growing season on the prediction results indicated that although the most accurate and reliable predictions of final biomass were achieved using remotely sensed data from mid-season to end-of-season, predictions in mid-season provided adequate results to differentiate between promising varieties for selection. The analysis of variance (ANOVA) of the accuracies of the predictive models showed that both the data source and regression method are important factors for a reliable prediction; however, the data source was more important with 69% significance, versus 28% significance for the regression method.

09 BIOMASS FUELS↗

DOE OSTI2026

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Apollo Lunar Sample Photographs: Digitizing the Moon Rock Collection

The Acquisition and Curation Office at JSC has undertaken a 4-year data restoration project effort for the lunar science community funded by the LASER program (Lunar Advanced Science and Exploration Research) to digitize photographs of the Apollo lunar rock samples and create high resolution digital images. These sample photographs are not easily accessible outside of JSC, and currently exist only on degradable film in the Curation Data Storage Facility

Lofgren, Gary E.↗

NASA NTRS2016

An Interdisciplinary Method for the Visualization of Novel High-Resolution Precision Photography and Micro-XCT Data Sets of NASA's Apollo Lunar Samples and Antarctic Meteorite Samples to Create Combined Research-Grade 3D Virtual Samples for the Benefit of Astromaterials Collections Conservation, Curation, Scientific Research and Education

New technologies make possible the advancement of documentation and visualization practices that can enhance conservation and curation protocols for NASA's Astromaterials Collections. With increasing demands for accessibility to updated comprehensive data, and with new sample return missions on the horizon, it is of primary importance to develop new standards for contemporary documentation and visualization methodologies. Our interdisciplinary team has expertise in the fields of heritage conservation practices, professional photography, photogrammetry, imaging science, application engineering, data curation, geoscience, and astromaterials curation. Our objective is to create virtual 3D reconstructions of Apollo Lunar and Antarctic Meteorite samples that are a fusion of two state-of-the-art data sets: the interior view of the sample by collecting Micro-XCT data and the exterior view of the sample by collecting high-resolution precision photography data. These new data provide researchers an information-rich visualization of both compositional and textural information prior to any physical sub-sampling. Since January 2013 we have developed a process that resulted in the successful creation of the first image-based 3D reconstruction of an Apollo Lunar Sample correlated to a 3D reconstruction of the same sample's Micro- XCT data, illustrating that this technique is both operationally possible and functionally beneficial. In May of 2016 we began a 3-year research period during which we aim to produce Virtual Astromaterials Samples for 60 high-priority Apollo Lunar and Antarctic Meteorite samples and serve them on NASA's Astromaterials Acquisition and Curation website. Our research demonstrates that research-grade Virtual Astromaterials Samples are beneficial in preserving for posterity a precise 3D reconstruction of the sample prior to sub-sampling, which greatly improves documentation practices, provides unique and novel visualization of the sample's interior and exterior features, offers scientists a preliminary research tool for targeted sub-sample requests, and additionally is a visually engaging interactive tool for bringing astromaterials science to the public.

Blumenfeld, E. H.↗

NASA NTRS1972

Automated Microbial Metabolism Laboratory

The Automated Microbial Metabolism Laboratory (AMML) 1971-1972 program involved the investigation of three separate life detection schemes. The first was a continued further development of the labeled release experiment. The possibility of chamber reuse without inbetween sterilization, to provide comparative biochemical information was tested. Findings show that individual substrates or concentrations of antimetabolites may be sequentially added to a single test chamber. The second detection system which was investigated for possible inclusion in the AMML package of assays, was nitrogen fixation as detected by acetylene reduction. Thirdly, a series of preliminary steps were taken to investigate the feasibility of detecting biopolymers in soil. A strategy for the safe return to Earth of a Mars sample prior to manned landings on Mars is outlined. The program assumes that the probability of indigenous life on Mars is unity and then broadly presents the procedures for acquisition and analysis of the Mars sample in a manner to satisfy the scientific community and the public that adequate safeguards are being taken.

Source record↗

DOE OSTI2020

Design and implementation of a J -coupled spectrometer for multidimensional structure and relaxation detection at low magnetic fields

In recent years, it has been realized that low and ultra-low field (mT-nT magnetic field range) nuclear magnetic resonance (NMR) spectroscopy can be used for molecular structural analysis. However, spectra are often hindered by lengthy acquisition times or require large sample volumes and high concentrations. Here, we report a low field (50 µT) instrument that employs a linear actuator to shuttle samples between a 1 T prepolarization field and a solenoid detector in a laboratory setting. The current experimental setup is benchmarked using water and 13 C-methanol with a single scan detection limit of 2x10 20 spins (3 μL, 55 M H 2 O) and detection of 2.9x10 19 (200 μL, 617 mM 13 C-methanol) spins with signal averaging. The system has a dynamic range of >3 orders of magnitude. Investigations of room-temperature relaxation dynamics of 13Cmethanol show that sample dilution can be used in lieu of sample heating to acquire spectra with linewidths comparable to high-temperature spectra. These results indicate that the T 1 and T 2 mechanisms are governed by both the proton exchange rate and the dissolved oxygen in the sample. Finally, a 2D correlation spectroscopy (COSY) experiment is reported, performed in the strong coupling regime that resolves the multiple resonances associated with the heteronuclear Jcoupling. The spectrum was collected using 10 times less sample and in less than half the time from previous reports in the strong coupling limit.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Simple, compact, high-resolution monochromatic x-ray source for characterization of x-ray calorimeter arrays

X-ray calorimeters routinely achieve very high spectral resolution, typically a few eV full width at half maximum (FWHM). Measurements of calorimeter line shapes are usually dominated by the natural linewidth of most laboratory calibration sources. This compounds the data acquisition time necessary to statistically sample the instrumental line broadening and can add systematic uncertainty if the intrinsic line shape of the source is not well known. To address these issues, we have built a simple, compact monochromatic x-ray source using channel cut crystals. A commercial x-ray tube illuminates a pair of channel cut crystals that are aligned in a dispersive configuration to select the Kα1 line of the x-ray tube anode material. The entire device, including the x-ray tube, can be easily hand-carried by one person and may be positioned manually or using a mechanical translation stage. The output monochromatic beam provides a collimated image of the anode spot with magnification of unity in the dispersion direction (typically 100 μm–200 μm for the x-ray tubes used here) and is unfocused in the cross-dispersion direction so that the source image in the detector plane appears as a line. We measured output count rates as high as 10 count/s/pixel for the Hitomi soft x-ray spectrometer, which had 819 μm square pixels. We implemented different monochromator designs for energies of 5.4 keV (one design) and 8.0 keV (two designs), which have effective theoretical FWHM energy resolution of 0.125 eV, 0.197 eV, and 0.086 eV, respectively; these are well-suited for optimal calibration measurements of state-of-the art x-ray calorimeters. We measured an upper limit for the energy resolution of our Cr Kα1 monochromator of 0.7 eV FWHM at 5.4 keV, consistent with the theoretical prediction of 0.125 eV.

47 OTHER INSTRUMENTATION↗

NASA NTRS1973

Results of the 1971 Corn Blight Watch experiment.

The objective of the experiment was to evaluate the use of advanced remote sensing techniques to detect the development and spread of southern corn leaf blight during the growing season across the Corn Belt region. The sampling plan involved the selection of the study area, the determination of the flightline, and the determination of a field sample design. Aspects of data acquisition are discussed, giving attention to ground data collection and aerial data collection. Details of data flow are considered along with data analysis procedures and corn blight records. The experiment results are examined, taking into account photointerpretation results, the machine analysis of multispectral scanner data results, the influence of blight on yields, and questions of crop identification.

Macdonald, R. B.↗

NASA NTRS1986

A survey of the state-of-the-art and focused research in range systems, task 1

This final report presents the latest research activity in voice compression. We have designed a non-real time simulation system that is implemented around the IBM-PC where the IBM-PC is used as a speech work station for data acquisition and analysis of voice samples. A real-time implementation is also proposed. This real-time Voice Compression Board (VCB) is built around the Texas Instruments TMS-3220. The voice compression algorithm investigated here was described in an earlier report titled, Low Cost Voice Compression for Mobile Digital Radios, by the author. We will assume the reader is familiar with the voice compression algorithm discussed in this report. The VCB compresses speech waveforms at data rates ranging from 4.8 K bps to 16 K bps. This board interfaces to the IBM-PC 8-bit bus, and plugs into a single expansion slot on the mother board.

Omura, J. K.↗

NASA NTRS1987

Combined optimization of image-gathering and image-processing systems for scene feature detection

The relationship between the image gathering and image processing systems for minimum mean squared error estimation of scene characteristics is investigated. A stochastic optimization problem is formulated where the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled and noisy image data. An analytical solution for the optimal characteristic image processor is developed. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristic is scene restoration. Optimal edge detection is investigated using the Laplacian operator x G as the desired characteristic, where G is a two dimensional Gaussian distribution function. It is shown that the optimal edge detector compensates for the blurring introduced by the image gathering optics, and notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition. The optimal image gathering optical transfer function is also investigated and the results of a sensitivity analysis are shown.

Halyo, Nesim↗

NASA NTRS1986

Combined optimization of image-gathering optics and image-processing algorithm for edge detection

This paper investigates the relationships between the image-gathering and image-processing systems for minimum mean-squared error estimation of scene characteristics. A stochastic optimization problem is formulated in which the objective is to determine a spatial characteristic of the scene rather than a feature of the already blurred, sampled, and noisy image data. The Wiener filter for the sampled image case is obtained as a special case, where the desired characteristics is scene restoration. Optimal edge detection is investigated. It is shown that the optimal edge detector compensates for the blurring introduced by the image-gathering optics, and, notably, that it is not circularly symmetric. The lack of circular symmetry is largely due to the geometric effects of the sampling lattice used in image acquisition.

Halyo, N.↗

NASA NTRS2004

Quasi-Uniform High Speed Foam Crush Testing Using a Guided Drop Mass Impact

A relatively simple method for measuring the dynamic crush response of foam materials at various loading rates is described. The method utilizes a drop mass impact configuration with mass and impact velocity selected such that the crush speed remains approximately uniform during the entire sample crushing event. Instrumentation, data acquisition, and data processing techniques are presented, and limitations of the test method are discussed. The objective of the test method is to produce input data for dynamic finite element modeling involving crash and energy absorption characteristics of foam materials.

Jones, Lisa E.↗

NASA NTRS2007

Real-Time Data Display

RT-Display is a MATLAB-based data acquisition environment designed to use a variety of commercial off-the-shelf (COTS) hardware to digitize analog signals to a standard data format usable by other post-acquisition data analysis tools. This software presents the acquired data in real time using a variety of signal-processing algorithms. The acquired data is stored in a standard Operator Interactive Signal Processing Software (OISPS) data-formatted file. RT-Display is primarily configured to use the Agilent VXI (or equivalent) data acquisition boards used in such systems as MIDDAS (Multi-channel Integrated Dynamic Data Acquisition System). The software is generalized and deployable in almost any testing environment, without limitations or proprietary configuration for a specific test program or project. With the Agilent hardware configured and in place, users can start the program and, in one step, immediately begin digitizing multiple channels of data. Once the acquisition is completed, data is converted into a common binary format that also can be translated to specific formats used by external analysis software, such as OISPS and PC-Signal (product of AI Signal Research Inc.). RT-Display at the time of this reporting was certified on Agilent hardware capable of acquisition up to 196,608 samples per second. Data signals are presented to the user on-screen simultaneously for 16 channels. Each channel can be viewed individually, with a maximum capability of 160 signal channels (depending on hardware configuration). Current signal presentations include: time data, fast Fourier transforms (FFT), and power spectral density plots (PSD). Additional processing algorithms can be easily incorporated into this environment.

Pedings, Marc↗

NASA NTRS2018

More Efficient Precipitation Rate Data Acquisition with the STORM Swath-Based Analysis Tool

A multitude of locations exist for acquiring satellite-derived precipitation rate data. Because the volume of data exceeds what can reasonably be analyzed manually, online tools have been developed to help researchers make more informed data acquisition decisions. Some interfaces provide sample images generated from prioritized variables to enable efficient visual inspection, while others include the ability to subset geographically to reduce the volume of the data to the area of interest. Building upon such value-added services is the STORM (the NASA Precipitation Processing System (PPS) data product ordering system) Swath-Based Analysis Tool (https://storm.pps.eosdis.nasa.gov/storm/Analysis.jsp). With it, users can compare overflights of multiple precipitation satellites simultaneously and from this make determinations about which swaths will best serve their research. They can preview these overflights with two distinct visualization tools. Finally, they can then download geographically subset swaths that have precipitation rate characteristics matching their research needs. A user starts by making up to six selections. They then select their date range of interest going back to 1997. Finally, they select a geographical region either by inputting latitude-longitude corners of a rectangle or drawing that rectangle on an interactive map. The system processes each file, determining aggregate statistics about the precipitation rates within the selected region as observed by each instrument. These statistical values are added to a time series graph as a "time remaining" counter is continuously updated. The chart is fully interactive, with detailed values displayed upon mouseover, and numerous options available upon clicking each point. Since the user is likely to need the relevant files for their own research, they can generate an order from their request. All files are geographically subset to the region of interest, and the user can use the statistical values to limit which files are added to the order. This flexibility helps to ensure researchers are only downloading the files they need for their work, making for a more efficient process both from a time-consumption and a storage perspective. This paper will introduce the Swath-Based Analysis Tool and explore its numerous features. It will discuss several use cases for precipitation scientists.

remote sensing↗

NASA NTRS2020

Simple, Compact, High-Resolution Monochromatic X-Ray Source for Characterization of X-Ray Calorimeter Arrays

M A Leutenegger↗

NASA NTRS2023

Electronic Nose Development and Preliminary Human Breath Testing for Rapid, Non-Invasive COVID-19 Detection

We adapted an existing, spaceflight-proven, robust “electronic nose” (E-Nose) that uses an array of electrical resistivity-based nanosensors mimicking aspects of mammalian olfaction to conduct on-site, rapid screening for COVID-19 infection by measuring the pattern of sensor responses to volatile organic compounds (VOCs) in exhaled human breath. We built and tested multiple copies of a hand-held prototype E-Nose sensor system, composed of 64 chemically sensitive nanomaterial sensing elements tailored to COVID-19 VOC detection; data acquisition electronics; a smart tablet with software (App) for sensor control, data acquisition and display; and a sampling fixture to capture exhaled breath samples and deliver them to the sensor array inside the E-Nose. The sensing elements detect the combination of VOCs typical in breath at parts-per-billion (ppb) levels, with repeatability of 0.02% and reproducibility of 1.2%; the measurement electronics in the E-Nose provide measurement accuracy and signal-to-noise ratios comparable to benchtop instrumentation. Preliminary clinical testing at Stanford Medicine with 63 participants, their COVID-19-positive or COVID-19-negative status determined by concomitant RT-PCR, discriminated between these two categories of human breath with a 79% correct identification rate using “leave-one-out” training-and-analysis methods. Analyzing the E-Nose response in conjunction with body temperature and other non-invasive symptom screening using advanced machine learning methods, with a much larger database of responses from a wider swath of the population, is expected to provide more accurate on-the-spot answers. Additional clinical testing, design refinement, and a mass manufacturing approach are the main steps toward deploying this technology to rapidly screen for active infection in clinics and hospitals, public and commercial venues, or at home.

COVID-19↗