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NASA NTRS2017

Quantitative Image Analysis Techniques with High-Speed Schlieren Photography

Optical flow visualization techniques such as schlieren and shadowgraph photography are essential to understanding fluid flow when interpreting acquired wind tunnel test data. Output of the standard implementations of these visualization techniques in test facilities are often limited only to qualitative interpretation of the resulting images. Although various quantitative optical techniques have been developed, these techniques often require special equipment or are focused on obtaining very precise and accurate data about the visualized flow. These systems are not practical in small, production wind tunnel test facilities. However, high-speed photography capability has become a common upgrade to many test facilities in order to better capture images of unsteady flow phenomena such as oscillating shocks and flow separation. This paper describes novel techniques utilized by the authors to analyze captured high-speed schlieren and shadowgraph imagery from wind tunnel testing for quantification of observed unsteady flow frequency content. Such techniques have applications in parametric geometry studies and in small facilities where more specialized equipment may not be available.

Pollard, Victoria J.↗
NASA NTRS2016

Quantitative Validation of the Integrated Medical Model (IMM) for ISS Missions

Lifetime Surveillance of Astronaut Health (LSAH) provided observed medical event data on 33 ISS and 111 STS person-missions for use in further improving and validating the Integrated Medical Model (IMM). Using only the crew characteristics from these observed missions, the newest development version, IMM v4.0, will simulate these missions to predict medical events and outcomes. Comparing IMM predictions to the actual observed medical event counts will provide external validation and identify areas of possible improvement. In an effort to improve the power of detecting differences in this validation study, the total over each program ISS and STS will serve as the main quantitative comparison objective, specifically the following parameters: total medical events (TME), probability of loss of crew life (LOCL), and probability of evacuation (EVAC). Scatter plots of observed versus median predicted TMEs (with error bars reflecting the simulation intervals) will graphically display comparisons while linear regression will serve as the statistical test of agreement. Two scatter plots will be analyzed 1) where each point reflects a mission and 2) where each point reflects a condition-specific total number of occurrences. The coefficient of determination (R2) resulting from a linear regression with no intercept bias (intercept fixed at zero) will serve as an overall metric of agreement between IMM and the real world system (RWS). In an effort to identify as many possible discrepancies as possible for further inspection, the -level for all statistical tests comparing IMM predictions to observed data will be set to 0.1. This less stringent criterion, along with the multiple testing being conducted, should detect all perceived differences including many false positive signals resulting from random variation. The results of these analyses will reveal areas of the model requiring adjustment to improve overall IMM output, which will thereby provide better decision support for mission critical applications.

validation↗
NASA NTRS2018

The Advantages of Synergy-Quantitative Earth Science Data Visualization and Analysis with Giovanni, Panoply, and Excel

The NASA Giovanni data analysis system provides a multitude of basic analysis capabilities for numerous Earth science data products which are available in the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) archive, as well as for additional selected data products provided by other NASA Distributed Active Archive Center (DAAC) archives. In Giovanni, users can easily generate time-averaged data maps, area-averaged time-series, Latitude-Time and Longitude-Time Hovmoeller diagrams, correlation maps, accumulation maps, and map animations (22 analysis options are available in total). While ASCII text output is available for time-series plots, it is not included as an option for data maps. In order to provide a quantitative, easy-to-use numerical output in ASCII text form, the NetCDF file output from a Giovanni visualization is downloaded and then opened with the free NASA visualization software package Panoply. Panoply provides the capability of translating the Giovanni file into comma-separated-variable (CSV) output. Panoply also provides additional visualization options, including the facile calculation of difference maps and quasi-anomaly maps using Giovanni output files. The CSV files from Panoply can then be imported into an Excel spreadsheet, where an Excel macro converts the CSV files. The output consists of latitude-longitude-data value triads in text form for maps, and either longitude-time-data value or latitude-time-data value triads in text form for Hovmoeller diagrams. This presentation will explicate the basic procedure for the conversion, and then provide several examples where the procedure is applied to Giovanni output from different analysis options.

Earth science↗
NASA NTRS2019

Quantitative Comparison of Proprietary and Open-Source Georeferencing Tools for Use with Astronaut Photography

The Crew Earth Observations (CEO) Facility within the Earth Science and Remote Sensing Unit at NASA’s Johnson Space Center supports the acquisition, analysis, and curation of astronaut photography of Earth’s surface and atmosphere. Astronauts on the International Space Station (ISS) respond to requests from CEO to acquire imagery of scientific and education targets, to include high profile targets in response to activations from the International Charter for Space & Major Disasters (also known as the International Disaster Charter, or IDC) and NASA’s Disasters Program. CEO facilitates the acquisition of astronaut photography in response to IDC events and delivers georeferenced data products to the United States Geological Survey (USGS) for distribution to the disaster community. Using GeoRef, an internal web-based tool developed in collaboration with NASA’s Ames Research Center, CEO generates data packages of georeferenced imagery, uncertainty images for assessing control and tie point accuracy, and metadata documenting raw and processed data. Operational experience with the Georef software identified vulnerabilities to internal code and server errors that can significantly increase time of data production. As such, CEO developed a backup procedure in case the GeoRef software experiences front-end or back-end errors. A system using OSGEO’s open-source QGIS software combined with a semi-automated pipeline using the object-oriented Python language and the Geospatial Abstract Library for generating metadata is quantitatively compared to GeoRef’s data package for quality and productivity. Root Mean Square Error (RMSE) provides a standard measurement of data quality as it relates to ground error. Assessing RMSE measurements generated from georeferenced astronaut photographs acquired with different obliquity and focal length offers a comprehensive accuracy assessment of the software’s transformation algorithms. This assessment will indicate the software's ability to produce data products with the least ground-error or highest data quality regarding ground accuracy. In addition, a comparison of the software’s efficiency in generating a data package that includes georeferenced images, metadata, and uncertainty images for measuring tie/ground point error was performed. Initial results, based on the comparison of three nadir-facing astronaut photographs acquired with a 95mm focal length, reveal the QGIS-based system's average RMSE is 2.36 (pixels) suggesting its georectification system produces data products that meet and perhaps improve upon Georef solution's average RMSE of 32.99 (pixels). However, the QGIS system was unable to reproduce two unique Georef data products, uncertainty images for measuring tie and control point errors and a translated unwrapped image. In addition, the Georef software is designed to accept handheld camera pose information from a hardware component (Geosens) scheduled for deployment on the ISS in late 2018; this information is intended to provide increased accuracy and auto-registration capability for astronaut photographs. Future work is expected to determine the QGIS-based georectification system’s potential as an open-source alternative (and operational backup) to Georef for georeferencing the full range of resolutions and viewing angles unique to handheld digital camera imagery in support of ISS disaster response activities.

Jagge, Amy M.↗
NASA NTRS2018

Quantitative Analysis of Planar Laser-Induced Fluorescence Measurements in a Hypersonic Boundary Layer

Several quantitative measurements extracted from nitric oxide (NO) planar laser-induced fluorescence (PLIF) data obtained in a hypersonic boundary layer are reported: (a) off-body NO mole fraction; (b) surface heat flux; and (c) near-wall static temperature. The experimental data was obtained at NASA Langley Research Center’s 31 in. Mach 10 air tunnel. NO was seeded into the flow through a spanwise slot on the surface of the 10 degree half-angle wedge model. An ultraviolet planar laser sheet was positioned perpendicular to the wedge surface, downstream of the seeding slot, to excite six fluorescence transitions. A method for extracting the relative NO mole fraction, based on spatial variations of the J”= 0.5 PLIF signal, is presented. Combined with the principle of mass conservation, the absolute NO mole fraction is determined. These measurements were used to assess CFD diffusion modelling, correct previously reported PLIF thermometry results, and develop methods for NO-PLIF heat transfer measurements.

McDougall, Connor C.↗
NASA NTRS2019

Benefits and Challenges of Model-based Software Engineering: Lessons Learned based on Qualitative and Quantitative Findings

Even though Model-based Software Engineering (MBSwE) techniques and Autogenerated Code (AGC) have been increasingly used to produce complex software systems, there is only anecdotal knowledge about the state-of-thepractice. Furthermore, there is a lack of empirical studies that explore the potential quality improvements due to the use of these techniques. This paper presents in-depth qualitative findings about development and Software Assurance (SWA) practices and detailed quantitative analysis of software bug reports of a NASA mission that used MBSwE and AGC. The mission’s flight software is a combination of handwritten code and AGC developed by two different approaches: one based on state chart models (AGC-M) and another on specification dictionaries (AGC-D). The empirical analysis of fault proneness is based on 380 closed bug reports created by software developers. Our main findings include: (1) MBSwE and AGC provide some benefits, but also impose challenges. (2) SWA done only at a model level is not sufficient. AGC code should also be tested and the models and AGC should always be kept in-sync. AGC must not be changed manually. (3) Fixes made to address an individual bug report were spread both across multiple modules and across multiple files. On average, for each bug report 1.4 modules, that is, 3.4 files were fixed. (4) Most bug reports led to changes in more than one type of file. The majority of changes to auto-generated source code files were made in conjunction to changes in either file with state chart models or XML files derived from dictionaries. (5) For newly developed files, AGC-M and handwritten code were of similar quality, while AGC-D files were the least fault prone.

Goseva-Popstojanova, Katerina↗
NASA NTRSDate not supplied

Quantitative Radiation Thermometry Using Commercially Available High-Speed Video Cameras

In order to understand the risk posed to astronauts by electric arc-generated particles, high-speed, high-resolution, quantitative thermal imaging was needed. The measurement requirements appeared to be beyond the capabilities of commercial thermal imaging systems, but the particles were known to have a significant amount of emission in the visible spectrum. This led to the use of commercially available, high-speed video cameras as imaging radiometers. Measured particle temperatures were consistent with predictions and other measurement data. The optical temperature measurement method, results, and conclusions are presented, along with recommendations for further work.

Thermal imaging↗
NASA NTRS2021

Quantitative Investigation of Radiometric Interactions between Snowfall, Snow Cover, and Cloud Liquid Water over Land

Falling snow alters its own microwave signatures when it begins to accumulate on the ground, making retrieval of snowfall challenging. This paper investigates the effects of snow-cover depth and cloud liquid water content on microwave signatures of terrestrial snowfall using reanalysis data and multi-annual observations by the Global Precipitation Measurement (GPM) core satellite with particular emphasis on the 89 and 166 GHz channels. It is found that over shallow snow cover (snow water equivalent (SWE) ≤100 kg/sq. m) and low values of cloud liquid water path (LWP 100–150 g/sq. m), the scattering of light snowfall (intensities ≤0.5 mm/ h) is detectable only at frequency 166 GHz, while for higher snowfall rates, the signal can also be detected at 89 GHz. However, when SWE exceeds 200 kg/sq. m and the LWP is greater than 100–150 g/sq. m, the emission from the increased liquid water content in snowing clouds becomes the only surrogate microwave signal of snowfall that is stronger at frequency 89 than 166 GHz. The results also reveal that over high latitudes above 60°N where the SWE is greater than 200 kg/sq. m and LWP is lower than 100–150 g/sq. m, the snowfall microwave signal could not be detected with GPM without considering a priori data about SWE and LWP. Our findings provide quantitative insights for improving retrieval of snowfall in particular over snow-covered terrain.

Zeinab Takbiri↗
NASA NTRS2022

A Quantitative Damage Tolerance Comparison of High Strength and High Modulus Carbon Fiber Sandwich Structure

This study presents experimental results of the compression after impact (CAI) testing of sandwich structure with face sheets made either with IM7/8552 high strength fiber or HM63/8552 high modulus fiber. While the HM63/8552 face sheet sandwich specimens would not be as damage tolerant as the IM7/8552 face sheet sandwich specimens, a quantitative measure of how much more damage tolerant the IM7/8552 face sheets were than the HM63/8552 face sheets was sought. Due to the IM7/8552 face sheets being 28% thicker than the HM63/8552 face sheets, the impact energies used needed to be adjusted for a fair comparison. The results show that the modulus is 35% lower for the IM7/8552 face sheet sandwich structure while the CAI strength

High modulus carbon fiber↗
NASA NTRS2018

Quantitative validation of Ames IR intensity and new line lists for (32/33/34)S(16)O2, (32)S(18)O2 and (16)O(32)S(18)O

The quality of Ames-296K SO2 Infrared (IR) line list intensities is first validated by quantitative exploration of several dipole moment surfaces (DMSs) and partition sum convergence. The DMSs are computed with several of Dunning’s correlation-consistent basis sets and their vibrational dependence are compared to the empirical model derived from Stark effect experiments reported by D. Patel, D. Margolese, and T.R. Dykea [J.Chem.Phys. 70, 2740 (1979)]. The effective dipole deviations from the DMS adopted in the Ames IR lists is 0.2-0.4% for vibrational states up to 3v3. The vibrational dependence of the dipole moment is also in good agreement, except for nv1. Partition sum convergence at 296K is confirmed by new calculations with rotational quantum number J up to 150 and upper state E’ up to 8000 cm-1. The isotopologue consistency of the Ames IR line lists is superior relative to the regular Effective Hamiltonian (EH) models and Effective Dipole Moment (EDM) models. The v1+v2 and v2+v3 intensity consistency check reveals the recently reported experimental intensities need significant improvement or re-analysis. After the accuracy, convergence, and isotopologue consistency have been confirmed, the theoretical Ames-296K intensities are combined with the experimental line positions or EH models that experimental spectroscopists published after 2009. Three high-resolution IR line sets are reported for the (32/33/34)S(16)O2, (32)S(18)O2 and (16)O(32)S(18)O isotopologues: (1) the “New Lines Sets” include experimentally measured line positions; (2) the “Expanded Line Sets” include possible transitions among new rovibrational levels assigned in experiments and ground state (GS) levels predicted by reliable EH models; (3) the “Ames + MARVEL Sets” include possible transitions among all those levels reported in a recent MARVEL analysis. [Tóbiás et al, JQSRT 208, 152 (2018)]. Compared to the limited data in High-resolution TRANsmission molecular absorption database (HITRAN), these line sets have significantly improved the data coverage up to 4000 cm-1. Some missing bands can be traced to the unpublished experimental data. The isotopologue consistency of these line sets will help identify the uncertainties and defects in the experimental EH and EDM models. These line sets are good candidates for the next HITRAN update, if line shape parameters are available. The line sets can be downloaded from supplementary files or from the Ames Molecular Spectroscopic Database at http://huang.seti.org.

Xinchuan Huang↗
NASA NTRS2023

Quantitative Gas Property Measurements By Filtered Rayleigh Scattering: A Review

Filtered Rayleigh scattering (FRS) is a laser-based diagnostic technique used to nonintrusively quantify various thermodynamic properties of a light-scattering gas. The backbone of FRS is the molecular filtering of Rayleigh scattered light. This concept was initially introduced by the atmospheric LIDAR community before being adopted within the aerospace research field in the early 1990s. Since then, FRS has matured into a versatile quantitative diagnostic tool and has found use in a variety of flow regimes ranging from sub- to supersonic speeds in both reacting and nonreacting environments. This adoption can be attributed to the wealth of information that can be obtained via FRS, including the gas density, pressure, temperature, velocity, species composition, or, in some cases, several of these properties at once. This article reviews the current state of FRS methodology in recovering such gas properties. As knowledge of the fundamentals of Rayleigh scattering and spectral light filtering is crucial to the design of an FRS experiment, we begin by briefly reviewing these areas. Subsequently, we conduct a survey of experimental design strategies, assumptions, and data reduction methods used to measure different gas properties using FRS. We conclude the review with a short discussion on quantification of experimental uncertainty and future trends in FRS.

filtered Rayleigh scattering↗
NASA NTRSDate not supplied

Quantitative Assessment of the HLS Surface Reflectance Consistency

The Harmonized Landsat and Sentinel-2 (HLS) project produces compatible surface reflectance (SR) from observations acquired by Landsat-8/9 OLI and Sentinel-2A/2B MSI. The HLS harmonization procedures include atmosphere correction, cloud masking, view angle normalization, and bandpass adjustment. The objective of this study is to quantitatively assess the reflectance consistency between Landsat and Sentinel-2 within the Version 2 HLS data. We collected 545 pairs of same-day Landsat/Sentinel-2 images across the globe to represent a wide range of vegetation types and climate regimes. The mean absolute difference (MAD) in reflectance between Landat and Sentinel-2 was calculated as a consistency indicator for each harmonization step. The MAD generally increased after the atmosphere correction, and then greatly decreased after the BRDF and bandpass adjustments, to smaller than the top-of-atmosphere MAD values. The MAD ranged from 0.0048 to 0.0093 for the six common spectral bands (blue, green, red, NIR, SWIR1, and SWIR2) in the final products, only slightly greater than the difference between Landsat and Sentinel-2 calibrations.. An evaluation on a few commonly used vegetation indices also showed good agreement between Landsat and Sentinel-2 reflectance. All these evaluations demonstrate that the HLS project produces a consistent SR dataset from Landsat-OLI and Sentinel-MSI, which will be a valuable resource for a wide range of remote sensing applications.

Qiang Zhou↗
NASA NTRSDate not supplied

Progress on Quantitative Infrared Thermography at the NASA Langley Aerothermodynamic Laboratory

A quantitative infrared thermography technique is being developed for accurate and high-resolution measurements of surface temperature and heat flux in the hypersonic wind tunnels at NASA Langley Research Center. A hemisphere test campaign was carried out in the Langley Aerothermodynamic Laboratory 20-Inch Mach 6 Air Tunnel to assess the current performance of the technique and to identify remaining challenges. Measurements were obtained for three different model materials over a range of freestream Reynolds numbers. The raw infrared images were converted to temperature via a radiometric calibration of the camera sensor. Corrections were made for losses due to test article emissivity and window transmissivity. A preliminary uncertainty analysis yielded an estimated accuracy within 4 K at moderate viewing angles, similar to that of a standard thermocouple. Surface heat flux was obtained from the measured surface temperatures via a finite-difference solution of the one-dimensional heat equation that modeled thermal variation of the material properties. Comparisons of the measured heating to both computational and theoretical predictions demonstrated agreement within the expected uncertainty of the technique. The heat transfer measurement near the stagnation point was found to be highly sensitive to the test article emissivity, which establishes the need for improved characterization of the wind tunnel model materials for high temperature applications.

infrared thermography↗
DOE OSTI2024

Detection and Quantitation of Hydrogen Emissions Role and Status of Detection Technology

Hydrogen is a critical strategy to decarbonize energy and manufacturing industries. Hydrogen is nontoxic and can be handled safely, but potential for secondary greenhouse impacts. Hydrogen releases arise from a variety of mechanisms (process, design features, "leaks") that contribute to total hydrogen releases. Detection methodologies will be critical to detect and quantify hydrogen emissions. Detection is to be integrated with advanced analytics (AI) and behavior modelling to effectively identify, quantify, and source locate hydrogen releases. Modelling of emissions will contribute to facility safety and reliability. DOE is committed to develop the tools to model and mitigate the impact of hydrogen releases which include: Support modeling to elucidate released hydrogen degradation; Support the development of tools for emissions quantitation; and Support engineering advancements to minimize hydrogen losses along the value chain (including process, design features, and leaks).

detection↗
DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

The Myth of Fungible FTE: A Quantitative Assessment of Matrixed Resource Allocation

Matrix organizations allow scientific facilities to share specialized personnel across projects, operations, maintenance, and strategic initiatives. Nominal staffing allocations, however, may not capture the schedule consequences of fragmented individual commitments, limited access to specialist groups, and intermittent availability of key decision makers. We developed a stochas- tic, daily-time-step simulation of a hypothetical medium-sized accelerator-facility project com- prising sequential phases and parallel tasks. Each task requires role-specific work measured in FTE-days. Ordinary personnel may be unavailable because they contribute concurrently to other institutional activities, while designated key roles have independently specified daily un- availability probabilities. An organization-wide priority factor scales the number of people from each functional group who can effectively contribute to the project. It is interpreted as a composite proxy for project access and workforce fragmentation across competing commit- ments. We examined project completion time as a function of this factor and Project Lead unavailability using 100 Monte Carlo runs per condition. Increasing priority factor from 0.1 to 1.0 reduced median completion time from 1708.5 days (interquartile range 1681.5–1735.25) to 390 days (interquartile range 379–399). At priority factor = 0.1, increasing Project Lead unavailability from 0.5 to 0.9 increased median completion time from 1713.5 days (interquartile range 1691–1733.25) to 4,417 days (interquartile range 4271.75–4550.5). The model quantifies the commonly expected sensitivity of project schedules to fragmented resource commitments and limited coordination availability. Within this model, the results also indicate a possible threshold regime in which small increases in workforce availability yield only modest sched- ule improvements until sufficient capacity becomes accessible, after which project performance improves sharply. With further validation and calibration, this quantitative framework could support resource-allocation decisions during initial project planning and subsequent schedule rebaselining.

Bai, Mei [SLAC National Accelerator Laboratory (SL↗