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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Binary pseudo-random array standards for calibration of 3D optical surface profilers used for metrology with significantly curved x-ray optics

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. The current capabilities and possibility for improvements in X-ray mirror manufacturing are limited by inherent imperfections of the integrated metrology tools. In the case of Fizeau interferometry, metrology tools are currently calibrated with super-polished flat test-standard/reference mirrors. This is acceptable for measuring slightly curved X-ray optics. However, for even moderately curved aspherical X-ray mirrors the flat-reference calibration is not sufficiently accurate and stitching Fizeau interferometer-based surface metrology is used to mitigate the problem. But still, the retrace and aberration errors, as well as the limited spatial resolution, described with the instrument transfer function (ITF), can be transferred into the optical surface topography of X-ray mirrors obtained in stitching metrology. For ITF calibration, we have developed an original technique, based on test standards structured as two-dimensional (2D) highly-randomized (HR) binary pseudo-random arrays (BPRAs). The technique employs the unique properties of the HR BPRA patterns in the spatial frequency domain., i.e. the inherent 2D power spectral density of the HR BPRA pattern has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. Here, we explore technological, metrological, and analytical aspects essential for calibration of the retrace and aberration errors of Fizeau interferometers using different types of tilted test samples, including a super-polished reference mirror for the re-trace calibration and the uniformly redundant array (URA) BPRA standards for the geometrical distortion (aberration) calibration. While the first method was previously demonstrated by researchers at DIAMOND Light Source, a method based on the URA BPRA is described and demonstrated here for the first time. We outline the design and fabrication process used in fabrication of URA BPRA test standards, and present the results of application of the URA BPRA standards demonstrating the high efficacy of our approach to geometrical distortion calibration of Fizeau interferometers. We also discuss the possible sources of unexpected peculiarities of the systematic errors, including an astigmatic character of the retrace error, observed with Fizeau interferometers at the Advanced Light Source X-Ray Optics Laboratory.

Munechika, Keiko↗
DOE OSTI2018

Energy scale calibration of the KEDR tagging system

The KEDR detector tagging system is a symmetric focusing magnetic spectrometer of small-angle electrons born in the interaction region of the VEPP-4M collider. Using this system, which is designed for studying the two-photon processes, the scattered electrons and positrons energy is measured with a resolution of ΔE/E{sub 0}= 0.03–0.6% where E{sub 0} is the beam energy. Two different methods are employed for calibrating the tagging system energy scale: the first one involves the electron/positron tagging by the energy of the singlebremsstrahlung photon measured in the BGO calorimeter, and the second one is based on the determination of the recoil electrons spectrum edge in the Compton backscattering of monochromatic laser radiation. The technical implementation and the present status of the calibration system are discussed in this paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Red Supergiants as Cosmic Abundance Probes: Massive Star Clusters in M83 and the Mass–Metallicity Relation of Nearby Galaxies

We present an abundance analysis of seven super star clusters in the disk of M83. The near-infrared spectra of these clusters are dominated by red supergiants, and the spectral similarity in the J-band of such stars at uniform metallicity means that the integrated light from the clusters may be analyzed using the same tools as those applied to single stars. Using data from VLT/KMOS, we estimate metallicities for each cluster in the sample. We find that the abundance gradient in the inner regions of M83 is flat, with a central metallicity of [Z]=0.21±0.11 relative to a solar value of Z {sub ⊙} = 0.014, which is in excellent agreement with the results from an analysis of luminous hot stars in the same regions. Compiling this latest study with our other recent work, we construct a mass–metallicity relation for nearby galaxies based entirely on the analysis of RSGs. We find excellent agreement with the other stellar-based technique—that of blue supergiants—as well as with temperature-sensitive (“auroral” or “direct”) H ii-region studies. Of all the H ii-region strong-line calibrations, those that are empirically calibrated to direct-method studies (N2 and O3N2) provide the most consistent results.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Evaluation of Long-Term Calibrations of the AVHRR Visible Radiances

Two systematic calibrations have been compiled for the visible radiances measured by the series of AVHRR instruments flown on the NOAA operational polar weather satellites: one by the International Satellite Cloud Climatology Project (ISCCP), anchored on NASA ER-2 underflights in the 1980s and early 1990s and covering the period 1981-2009, and one by the PATMOS-x project, anchored on comparisons to the MODIS instruments on the Aqua and Terra satellites in the 2000s and covering the period 1979-2010 (this result also includes calibration for the near-IR channels). Both methods have had to extend their anchor calibrations over a long series of instruments using different vicarious approaches, so a comparison provides an opportunity to evaluate how well this extension works by cross-checking the results at the anchor points. The basic result of this comparison is that for the ''afternoon'' series of AVHRRs, the calibrations agree to within their mutual uncertainties. However, this retrospective evaluation also shows that the representation of the time variations can be simplified. The ISCCP procedure had much more difficulty extending the calibration to the ''morning'' series of AVHRRs with the calibrations for NOAA-15 and NOAA-17 exceeding the estimated uncertainties. Given the general agreement, a new calibration for all AVHRR visible radiances (except TIROS-N, NOAA-6, NOAA-19, and MetOp-A) is proposed that is based on the average of the best linear fits to the two time records. The estimated uncertainty of these calibrations is 63% absolute (scaled radiance units).

Advanced Very High Resolution Radiometer↗
NASA NTRS2019

Smart power supply calibration system

This paper details the development of an automated procedure to conduct calibrations of power supplies at Jet Propulsion Laboratory, California Institute of Technology (JPL). The fundamentals of power supply calibrations is given, and discussion on the method by which this custom software handles that calibration. Additionally, this technique provides real time uncertainty quantification of the calibrations. This automated system has demonstrated a time savings over existing automated techniques in use today.

Umansky, Brandon M.↗
DOE OSTI2017

The use of minimal spanning trees in particle physics

Minimal spanning trees (MSTs) have been used in cosmology and astronomy to distinguish distributions of points in a multi-dimensional space. They are essentially unknown in particle physics, however. We briefly define MSTs and illustrate their properties through a series of examples. We show how they might be applied to study a typical event sample from a collider experiment and conclude that MSTs may prove useful in distinguishing different classes of events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Cosmic ray muon clustering for the MicroBooNE liquid argon time projection chamber using sMask-RCNN

In this article, we describe a modified implementation of Mask Region-based Convolutional Neural Networks (Mask-RCNN) for cosmic ray muon clustering in a liquid argon TPC and applied to MicroBooNE neutrino data. Our implementation of this network, called sMask-RCNN, uses sparse submanifold convolutions to increase processing speed on sparse datasets, and is compared to the original dense version in several metrics. The networks are trained to use wire readout images from the MicroBooNE liquid argon time projection chamber as input and produce individually labeled particle interactions within the image. These outputs are identified as either cosmic ray muon or electron neutrino interactions. We find that sMask-RCNN has an average pixel clustering efficiency of 85.9% compared to the dense network's average pixel clustering efficiency of 89.1%. We demonstrate the ability of sMask-RCNN used in conjunction with MicroBooNE's state-of-the-art Wire-Cell cosmic tagger to veto events containing only cosmic ray muons. The addition of sMask-RCNN to the Wire-Cell cosmic tagger removes 70% of the remaining cosmic ray muon background events at the same electron neutrino event signal efficiency. Furthermore, this event veto can provide 99.7% rejection of cosmic ray-only background events while maintaining an electron neutrino event-level signal efficiency of 80.1%. In addition to cosmic ray muon identification, sMask-RCNN could be used to extract features and identify different particle interaction types in other 3D-tracking detectors.

47 OTHER INSTRUMENTATION↗
NASA NTRS1974

Determination of left ventricular size and shape

Significant advances have occurred over the past 15 years in the ability to measure ventricular dimensions. Angiocardiography still remains the most reliable method for overall determination of chamber size and shape and serves as a standard for calibration or comparison for newer methods. Improvements in the use of radiographic methods over the next few years are anticipated with more extensive use of multiplane studies associated with repeated injections of improved contrast materials that produce fewer physiological effects or with substances that adhere to the endocardial surfaces. It is also anticipated that existing methods for automatically obtaining dimensional information from X rays will be continued and improved.

Sandler, H.↗
NASA NTRS1980

Low-speed airspeed calibration data for a single-engine research-support aircraft

A standard service airspeed system on a single engine research support airplane was calibrated by the trailing anemometer method. The effects of flaps, power, sideslip, and lag were evaluated. The factory supplied airspeed calibrations were not sufficiently accurate for high accuracy flight research applications. The trailing anemometer airspeed calibration was conducted to provide the capability to use the research support airplane to perform pace aircraft airspeed calibrations.

Holmes, B. J.↗
NASA NTRS2007

Implementation of Leak Test Methods for the International Space Station (ISS) Elements, Systems and Components

The International Space Station (ISS has Qualification and Acceptance Environmental Test Requirements document, SSP 41172 that includes many environmental tests such as Thermal vacuum & Cycling, Depress/Repress, Sinusoidal, Random, and Acoustic Vibration, Pyro Shock, Acceleration, Humidity, Pressure, Electromatic Interference (EMI)/Electromagnetic Compatibility (EMCO), etc. This document also includes (13) leak test methods for Pressure Integrity Verification of the ISS Elements, Systems, and Components. These leak test methods are well known, however, the test procedure for specific leak test method shall be written and implemented paying attention to the important procedural steps/details that, if omitted or deviated, could impact the quality of the final product and affect the crew safety. Such procedural steps/details for different methods include, but not limited to: - Sequence of testing, f or example, pressurization and submersion steps for Method I (Immersion); - Stabilization of the mass spectrometer leak detector outputs fo r Method II (vacuum Chamber or Bell jar); - Proper data processing an d taking a conservative approach while making predictions for on-orbit leakage rate for Method III(Pressure Change); - Proper Calibration o f the mass spectrometer leak detector for all the tracer gas (mostly Helium) Methods such as Method V (Detector Probe), Method VI (Hood), Method VII (Tracer Probe), Method VIII(Accumulation); - Usage of visibl ility aides for Method I (Immersion), Method IV (Chemical Indicator), Method XII (Foam/Liquid Application), and Method XIII (Hydrostatic/Visual Inspection); While some methods could be used for the total leaka ge (either internal-to-external or external-to-internal) rate requirement verification (Vacuum Chamber, Pressure Decay, Hood, Accumulation), other methods shall be used only as a pass/fail test for individual joints (e.g., welds, fittings, and plugs) or for troubleshooting purposes (Chemical Indicator, Detector Probe, Tracer Probe, Local Vacuum Chamber, Foam/Liquid Application, and Hydrostatic/Visual Inspection). Any isolation of SSP 41172 requirements have led to either retesting of hardware or accepting a risk associated with the potential system or component pressure integrity problem during flight.

Underwood, Steve↗
NASA NTRS2018

Regression Analysis and Calibration Recommendations for the Characterization of Balance Temperature Effects

Analysis and use of temperature-dependent wind tunnel strain-gage balance calibration data are discussed in the paper. First, three different methods are presented and compared that may be used to process temperature-dependent strain-gage balance data. The first method uses an extended set of independent variables in order to process the data and predict balance loads. The second method applies an extended load iteration equation during the analysis of balance calibration data. The third method uses temperature-dependent sensitivities for the data analysis. Physical interpretations of the most important temperature-dependent regression model terms are provided that relate temperature compensation imperfections and the temperature-dependent nature of the gage factor to sets of regression model terms. Finally, balance calibration recommendations are listed so that temperature-dependent calibration data can be obtained and successfully processed using the reviewed analysis methods.

wind tunnel test↗
DOE OSTI2022

Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology

Modeling real-world phenomena to any degree of accuracy is a challenge that the scientific research community has navigated since its foundation. Lack of information and limited computational and observational resources necessitate modeling assumptions which, when invalid, lead to model-form error (MFE). The work reported herein explored a novel method to represent model-form uncertainty (MFU) that combines Bayesian statistics with the emerging field of universal differential equations (UDEs). The fundamental principle behind UDEs is simple: use known equational forms that govern a dynamical system when you have them; then incorporate data-driven approaches – in this case neural networks (NNs) – embedded within the governing equations to learn the interacting terms that were underrepresented. Utilizing epidemiology as our motivating exemplar, this report will highlight the challenges of modeling novel infectious diseases while introducing ways to incorporate NN approximations to MFE. Prior to embarking on a Bayesian calibration, we first explored methods to augment the standard (non-Bayesian) UDE training procedure to account for uncertainty and increase robustness of training. In addition, it is often the case that uncertainty in observations is significant; this may be due to randomness or lack of precision in the measurement process. This uncertainty typically manifests as “noisy” observations which deviate from a true underlying signal. To account for such variability, the NN approximation to MFE is endowed with a probabilistic representation and is updated using available observational data in a Bayesian framework. By representing the MFU explicitly and deploying an embedded, data-driven model, this approach enables an agile, expressive, and interpretable method for representing MFU. In this report we will provide evidence that Bayesian UDEs show promise as a novel framework for any science-based, data-driven MFU representation; while emphasizing that significant advances must be made in the calibration of Bayesian NNs to ensure a robust calibration procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Calibrating uncertain parameters in melt pool simulations of additive manufacturing

Melt pool scale numerical modeling of additive manufacturing (AM) processes can provide predictive capabilities and theoretical insight into the process-property-structure-performance relationships for AM parts. Despite capabilities of numerical models to solve complex multi-physics problems, it is often important to consider a tradeoff between detailed physics and computational cost. Therefore, sources of uncertainty in both experimental conditions and the parameters needed for modeling require models to be validated against empirical evidence. Here, a method is proposed to calibrate uncertain parameters used in continuum-scale melt pool models for powder bed fusion (PBF) AM. Both a simplified heat transfer model and a heat transfer and fluid flow model were investigated. A surrogate model and Markov chain-based optimization algorithm calibrated melt pool geometry for models within experimental variation of the target melt pool width and depth from the NIST AM-Bench 2018-02 dataset. The melt pool temperature distributions, solidification parameters, and simulated multi-layer solidification microstructures were compared between the two models. Similar results from both models indicate that calibrated, lower fidelity numerical models may be used in place of higher fidelity models to generate melt pool solidification data. Finally, these calibrated models therefore enable lower computational cost melt pool simulations without a noticeable decrease in simulation accuracy for grain-scale microstructure simulations.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Application of Machine Learning Techniques in Calibration and Data Reduction of Multi-Hole Probes

This work presents procedures for implementing machine learning methods into existing algorithms for multi-hole probe calibration and data reduction. It demonstrates that using artificial neural networks (ANNs) can decrease the amount of calibration data needed to achieve a specific calibration uncertainty by over 50%, while also significantly reducing data reduction times. Instead of surface fitting methods, ANNs are employed. Initially, directional calibration coefficients related to flow angles are computed based on pressure measurements, and then these flow angles serve as input parameters for subsequent ANNs to iteratively define Mach number, static pressure, and total pressure. In an alternative approach, new calibration coefficients directly relate pressure measurements from the five-hole probe to the quantities of interest, thereby eliminating the need for iterative algorithms used in conventional surface fitting methods. This method offers several advantages: an average increase of less than 1%in calibration uncertainty for flow angles and a significant reduction in data reduction times to a few seconds on average. Additionally, the methodology is confirmed to avoid both over- and under-fitting.

Machine Learning↗
NASA NTRS2007

Development of Natural Flaw Samples for Evaluating Nondestructive Testing Methods for Foam Thermal Protection Systems

Low density polyurethane foam has been an important insulation material for space launch vehicles for several decades. The potential for damage from foam breaking away from the NASA External Tank was not realized until the foam impacts on the Columbia Orbiter vehicle caused damage to its Leading Edge thermal protection systems (TPS). Development of improved inspection techniques on the foam TPS is necessary to prevent similar occurrences in the future. Foamed panels with drilled holes for volumetric flaws and Teflon inserts to simulate debonded conditions have been used to evaluate and calibrate nondestructive testing (NDT) methods. Unfortunately the symmetric edges and dissimilar materials used in the preparation of these simulated flaws provide an artificially large signal while very little signal is generated from the actual defects themselves. In other words, the same signal are not generated from the artificial defects in the foam test panels as produced when inspecting natural defect in the ET foam TPS. A project to create more realistic voids similar to what actually occurs during manufacturing operations was began in order to improve detection of critical voids during inspections. This presentation describes approaches taken to create more natural voids in foam TPS in order to provide a more realistic evaluation of what the NDT methods can detect. These flaw creation techniques were developed with both sprayed foam and poured foam used for insulation on the External Tank. Test panels with simulated defects have been used to evaluate NDT methods for the inspection of the External Tank. A comparison of images between natural flaws and machined flaws generated from backscatter x-ray radiography, x-ray laminography, terahertz imaging and millimeter wave imaging show significant differences in identifying defect regions.

Workman, Gary L.↗
NASA NTRS1995

Initial vegetation species and senescience/stress indicator mapping in the San Luis Valley, Colorado using imaging spectrometer data

We analyzed AVIRIS data obtained over agricultural areas in the San Luis Valley of Colorado. The data were acquired on September 3, 1993. A combined method of radiative transfer modeling and ground calibration site reflectance was used to correct the flight data to surface reflectance. This method, called Radiative Transfer Ground Calibration, or RTGC, corrects for variable water vapor in the atmosphere and produces spectra free of artifacts with spectral channel to channel noise approaching the signal to noise of the raw data. The calibration site soil samples were obtained on the day of the overflight and measured on our laboratory spectrometer. The site was near the center of the AVIRIS scene and the spectra of the soil is spectrally bland, especially in the region of the chlorophyll absorption in the visible portion of the spectrum. The center of the scene is located at approximately 106 deg 03' longitude, 37 deg 23' latitude, and the scene covers about 92 square kilometers. This scene is one of 28 in the area for a general project to study the Summitville abandoned mine site, located in the mountains west of the San Luis Valley, and its effects on the surrounding environment.

Clark, Roger N.↗
NASA NTRS1988

Evaluation of platinum resistance thermometers

An evaluation procedure for the characterization of industrial platinum resistance thermometers (PRTs) for use in the temperature range -120 to 160 C was investigated. This evaluation procedure consisted of calibration, thermal stability and hysteresis testing of four surface measuring PRTs. Five different calibration schemes were investigated for these sensors. The IPTS-68 formulation produced the most accurate result, yielding average sensor systematic error of 0.02 C and random error of 0.1 C. The sensors were checked for thermal stability by successive and thermal cycling between room temperature, 160 C, and boiling point of nitrogen. All the PRTs suffered from instability and hysteresis. The applicability of the self-heating technique as an in situ method for checking the calibration of PRTs located inside wind tunnels was investigated.

Daryabeigi, Kamran↗
DOE OSTI2020

Prediction of gas hydrate saturation using machine learning and optimal set of well-logs

We report resistivity and acoustic logs are widely used to estimate gas hydrate saturation in various sedimentary systems using one of the two popular methods ((1) acoustic velocity and (2) electrical resistivity), but the limitations of these two methods are often overlooked, which include (i) well-specific calibration of empirical exponents in the electrical resistivity method, (ii) assumption of known pore morphology for gas hydrates in the acoustic velocity method, and (iii) presence of unknown mineralogy and bulk modulus terms in the acoustic velocity method. NMR-density porosity-derived gas hydrate saturation based on the analysis of the transverse magnetization relaxation time (T2) is considered the most precise method, but acquisition of NMR-based logs is limited at relatively recent drilled sites; additionally, its use in conventional oil and gas reservoirs is not that common due to higher cost and operational deployment limitations associated with acquiring NMR well-logs. This study proposes a new method that predicts gas hydrate saturation (S h ) for any well using porosity, bulk density, and compressional wave (P wave) velocity well-logs with neural network (or stochastic gradient descent regression) without any well-specific calibration and/or other aforementioned shortcomings of the existing methods. The method is developed by examining the underlying dependency between S h and different combinations of well-logs, chosen from 6 routine logs, with 12 different machine learning (ML) algorithms. The accuracy of the proposed method in predicting S h is ~ 84%, which is better than the accuracy of seismic and electrical resistivity methods (≤ 75%) per the results reported by three different studies. The robustness of the method in the specific case of permafrost-associated gas hydrates is demonstrated with well-log data from two wells drilled on the Alaska North Slope.

58 GEOSCIENCES↗