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At least 757 records · Page 42

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DOE OSTI2019

In-depth evaluation of 252 Cf absolute calibration by passive neutron correlation counting method

252 Cf neutron sources are particularly convenient, and therefore widely used, to characterize and calibrate many kinds of neutron detectors for both scientific and technological applications. An emerging interest is the use of 252 Cf to calibrate neutron correlation counters for the verification and assay of Pu-items as part of the international effort to safeguard nuclear materials. Passive neutron correlation counting (PNCC) methods, combined with knowledge of the fission neutron multiplicity distribution, can be used as an absolute technique to determine the neutron emission rate of 252 Cf sources. This means that common equipment used by the safeguards community can, in principle, be used to self-certify, to high accuracy, the strength of physically small 252 Cf sealed sources for use in calibration. This is the first step in using 252Cf in place of extensive Pu reference materials for experimental calibration by the safeguards community. The theoretical foundation is already clear but the present work presents the first systematic attempt at demonstrating the practical utility of the concept across a variety of typical instruments. We compare four emission rate estimators for four detector configurations on a common source previously certified by the MnSO 4 -bath technique. We find that the estimator based on the singles to doubles rate ratio provides consistent and precise results across all of the instruments and that these agree with the MnSO 4 -bath technique within combined uncertainties. This success suggests that the absolute PNCC method could become a technically defensible and commonly used, method capable of sub 1% accuracy for routine calibration work.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Modeling Soot Oxidation and Gasification with Bayesian Statistics

This paper presents a statistical method for model calibration using data collected from literature. The method is used to calibrate parameters for global models of soot consumption in combustion systems. This consumption is broken into two different submodels: first for oxidation where soot particles are attacked by certain oxidizing agents; second for gasification where soot particles are attacked by H 2 O or CO 2 molecules. Rate data were collected from 19 studies in the literature and evaluated using Bayesian statistics to calibrate the model parameters. Bayesian statistics are valued in their ability to quantify uncertainty in modeling. The calibrated consumption model with quantified uncertainty is presented here along with a discussion of associated implications. The oxidation results are found to be consistent with previous studies. Significant variation is found in the CO 2 gasification rates.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS1985

Preliminary Evaluation of the Radiometric Calibration of LANDSAT-4 Thematic Mapper Data by the Canada Centre for Remote Sensing

The radiometric characteristics of the LANDSAT-4 TM sensor are being studied with a view to developing absolute and relative radiometric calibration procedures. Preliminary results from several different approaches to the relative correction of all detectors within each band are reported. Topics covered include: the radiometric correction method; absolute calibration; the relative radiometric calibration algorithm; relative gain and offset calibration; relative gain and offset observations; and residual radiometric stripping.

Murphy, J.↗

DOE OSTI2025

Development of a forced advection sampling technique (FAST) for quantification of methane emissions from orphaned wells

Abstract. Orphaned wells, meaning unplugged and non-producing wells lacking responsible owners, pose a significant and undersampled environmental challenge due to their vast number and unknown associated emissions. We propose, develop and test an alternative method for estimating emissions from orphaned wells using a forced advection sampling technique (FAST) that can overcome many of the limitations in current methods (cost, accuracy, safety). In contrast to existing ambient Gaussian plume methods, our approach uses a fan-generated flow to force advection between the emission source and a point methane (CH4) sensor. The fan flow field is characterized using a colocated sonic anemometer to measure the 3D wind profile generated by the fan. Using time-series measurements of CH4 concentration and wind, a simple estimate of the CH4 emission rate of the source can be inferred. The method was calibrated using outdoor controlled-release experiments and then tested on four orphaned wells in Lufkin, TX, and Osage County, OK. Our results suggest that the FAST method can provide a low-cost, portable, fast and safe alternative to existing methods with reasonable estimates of orphaned well emissions over a range of leak rates below 40 g h−1 and within certain geometric and atmospheric constraints.

Dubey, Mohit L↗

DOE OSTI2018

Parameter covariance and non-uniqueness in material model calibration using the Virtual Fields Method

Traditionally, material identification is performed using global load and displacement data from simple boundary-value problems such as uni-axial tensile and simple shear tests. More recently, however, inverse techniques such as the Virtual Fields Method (VFM) that capitalize on heterogeneous, full-field deformation data have gained popularity. In this work, we have written a VFM code in a finite-deformation framework for calibration of a viscoplastic (i.e. strain-rate dependent) material model for 304L stainless steel. Using simulated experimental data generated via finite-element analysis (FEA), we verified our VFM code and compared the identified parameters with the reference parameters input into the FEA. The identified material model parameters had surprisingly large error compared to the reference parameters, which was traced to parameter covariance and the existence of many essentially equivalent parameter sets. This parameter non-uniqueness and its implications for FEA predictions is discussed in detail. Lastly, we present two strategies to reduce parameter covariance – reduced parametrization of the material model and increased richness of the calibration data – which allow for the recovery of a unique solution.

304L stainless steel↗

NASA NTRS1976

High Temperature Strain Gage Calibration Fixture

An apparatus and method are described for calibrating high temperature strain gases which serve for both dead weight and constant deflection measurements. A cantilever support arm allows the test unit to slide into a furnace while one end is subjected to bending strain either by hanging weights upon it or by deflecting it with a push rod. The dual nature of the fixture permits both tests to be run without change of the test specimen or removal from the furnace.

Vranas, T.↗

NASA NTRS2001

Solar-Reflectance-Based Calibration of Spectral Radiometers

A method by which to calibrate a spectral radiometer using the sun as the illumination source is discussed. Solar-based calibrations eliminate several uncertainties associated with applying a lamp-based calibration to field measurements. The procedure requires only a calibrated reflectance panel, relatively low aerosol optical depth, and measurements of atmospheric transmittance. Further, a solar-reflectance-based calibration (SRBC), by eliminating the need for extraterrestrial irradiance spectra, reduces calibration uncertainty to approximately 2.2% across the solar-reflective spectrum, significantly reducing uncertainty in measurements used to deduce the optical properties of a system illuminated by the sun (e.g., sky radiance). The procedure is very suitable for on-site calibration of long-term field instruments, thereby reducing the logistics and costs associated with transporting a radiometer to a calibration facility.

Cattrall, Christopher↗

DOE OSTI2017

Automated calibration of multistatic arrays

A method is disclosed for calibrating a multistatic array having a plurality of transmitter and receiver pairs spaced from one another along a predetermined path and relative to a plurality of bin locations, and further being spaced at a fixed distance from a stationary calibration implement. A clock reference pulse may be generated, and each of the transmitters and receivers of each said transmitter/receiver pair turned on at a monotonically increasing time delay interval relative to the clock reference pulse. Ones of the transmitters and receivers may be used such that a previously calibrated transmitter or receiver of a given one of the transmitter/receiver pairs is paired with a subsequently un-calibrated one of the transmitters or receivers of an immediately subsequently positioned transmitter/receiver pair, to calibrate the transmitter or receiver of the immediately subsequent transmitter/receiver pair.

42 ENGINEERING↗

DOE OSTI2017

Effects of self-calibration of intrinsic alignment on cosmological parameter constraints from future cosmic shear surveys

Intrinsic alignments (IA) of galaxies have been recognized as one of the most serious contaminants to weak lensing. These systematics need to be isolated and mitigated in order for ongoing and future lensing surveys to reach their full potential. The IA self-calibration (SC) method was shown in previous studies to be able to reduce the GI contamination by up to a factor of 10 for the 2-point and 3-point correlations. The SC method does not require the assumption of an IA model in its working and can extract the GI signal from the same photo-z survey offering the possibility to test and understand structure formation scenarios and their relationship to IA models. In this paper, we study the effects of the IA SC mitigation method on the precision and accuracy of cosmological parameter constraints from future cosmic shear surveys LSST, WFIRST and Euclid. We perform analytical and numerical calculations to estimate the loss of precision and the residual bias in the best fit cosmological parameters after the self-calibration is performed. We take into account uncertainties from photometric redshifts and the galaxy bias. We find that the confidence contours are slightly inflated from applying the SC method itself while a significant increase is due to the inclusion of the photo-z uncertainties. The bias of cosmological parameters is reduced from several-σ, when IA is not corrected for, to below 1-σ after SC is applied. These numbers are comparable to those resulting from applying the method of marginalizing over IA model parameters despite the fact that the two methods operate very differently. We conclude that implementing the SC for these future cosmic-shear surveys will not only allow one to efficiently mitigate the GI contaminant but also help to understand their modeling and link to structure formation.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1985

Comparison of the calibration of ionospheric delay in VLBI data by the methods of dual frequency and Faraday rotation

When both S-band and X-band data are recorded for a signal which has passed through the ionosphere, it is possible to calculate the ionospheric contribution to signal delay. In Very Long Baseline Interferometry (VLBI) this method is used to calibrate the ionosphere. In the absence of dual frequency data, the ionospheric content measured by Faraday rotation, using a signal from a geostationary satellite, is mapped to the VLBI observing direction. The purpose here is to compare the ionospheric delay obtained by these two methods. The principal conclusions are: (1) the correlation between delays obtained by these two methods is weak; (2) in mapping Faraday rotation measurements to the VLBI observing direction, a simple mapping algorithm which accounts only for changes in hour angle and elevation angle is better than a more elaborate algorithm which includes solar and geomagnetic effects; (3) fluctuations in the difference in total electron content as seen by two antennas defining a baseline limit the application of Faraday rotation data to VLBI.

Scheid, J. A.↗

DOE OSTI2020

Quality Control of Additively Manufactured Metallic Structures with Machine Learning of Thermography Images

Additive manufacturing (AM) of high-strength metals is currently based on the laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Quality control (QC) requires nondestructive evaluation of actual AM structures. Flash thermography is a potentially promising QC technique because it is scalable to arbitrary structure size. However, the detection sensitivity of this method is limited by noise. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatial–temporal blind source separation and spatial–temporal sparse dictionary learning methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced by the LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, the ML methods with higher accuracy require a longer runtime. However, this runtime is sufficiently short to perform QC within a realistic time frame.

36 MATERIALS SCIENCE↗

DOE OSTI2015

SU-E-T-470: Importance of HU-Mass Density Calibration Technique in Proton Pencil Beam Dose Calculation

Purpose: Stoichiometric calibration of Hounsfield Units (HUs) for conversion to proton relative stopping powers (RStPs) is vital for accurate dose calculation in proton therapy. However proton dose distributions are not only dependent on RStP, but also on relative scattering power (RScP) of patient tissues. RScP is approximated from material density but a stoichiometric calibration of HU-density tables is commonly neglected. The purpose of this work was to quantify the difference in calculated dose of a commercial TPS when using HU-density tables based on tissue substitute materials and stoichiometric calibrated ICRU tissues. Methods: Two HU-density calibration tables were generated based on scans of the CIRS electron density phantom. The first table was based directly on measured HU and manufacturer quoted density of tissue substitute materials. The second was based on the same CT scan of the CIRS phantom followed by a stoichiometric calibration of ICRU44 tissue materials. The research version of Pinnacle{sup 3} proton therapy was used to compute dose in a patient CT data set utilizing both HU-density tables. Results: The two HU-density tables showed significant differences for bone tissues; the difference increasing with increasing HU. Differences in density calibration table translated to a difference in calculated RScP of −2.5% for ICRU skeletal muscle and 9.2% for ICRU femur. Dose-volume histogram analysis of a parallel opposed proton therapy prostate plan showed that the difference in calculated dose was negligible when using the two different HU-density calibration tables. Conclusion: The impact of HU-density calibration technique on proton therapy dose calculation was assessed. While differences were found in the calculated RScP of bony tissues, the difference in dose distribution for realistic treatment scenarios was found to be insignificant.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Detection of Defects in Additively Manufactured Metallic Materials with Machine Learning of Pulsed Thermography Images

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Control and Calibration of GlueX Central Drift Chamber Using Gaussian Process Regression

The Gluonic Excitations (GlueX) experiment is designed to search for exotic hybrid mesons using photoproduction, and to study the hybrid meson spectrum predicted from Lattice Quantum Chromodynamics. For the first time, the GlueX Central Drift Chamber was controlled autonomously using machine learning (ML) to calibrate in real time while recording cosmic ray tracks. We demonstrate the ability of a Gaussian Process to predict the gain correction calibration factor used to determine a high voltage setting that will stabilize the CDC gain in response to changing environmental conditions; this is in contrast to the traditional, computationally expensive method of calibrating raw data after data collection is complete.

McSpadden, Helen↗

NASA NTRS1978

Results of the 1974 through 1977 NASA/JPL balloon flight solar cell calibration program

From 1974 through 1977, seven solar cell calibration flights and two R&D flights with a spectroradiometer as a payload were attempted. There were two R&D flights, and one calibration flight that failed. Each calibration flight balloon was designed to carry its payload to an altitude of 36.6 km (120 kft). The R&D flight balloons were designed for a payload altitude of 47.5 km (150 kft). At the end of the flight period, the upper (solar cell calibration system) and lower (consolidated instrument package (DIP) payloads were separated from the balloon and descend via parachutes. The calibrated solar cells recovered in this manner were used as primary intensity reference standards during solar simulator testing of solar cells and solar arrays with similar spectral response characteristics. This method of calibration has become the most widely accepted technique for developing space standard solar cells.

Sidwell, L. B.↗

NASA NTRSDate not supplied

TPSAS-NF1676L-32020-DND

The Earth Polychromatic Imaging Camera (EPIC) instrument aboard the Deep Space Climate Observatory (DSCOVR) satellite has a constant unique view of the sunlit disk of the Earth from the Lagrange-1 (L1) point nearly a million miles away from the Earth. The DSCOVR EPIC team released the version 2 dataset last year which included many enhancements, such as improved navigation, stray-light correction, and flat-fielding. Since there is no on-board calibration for EPIC, its 10 spectral channels must be calibrated using other methods, such as inter-calibrating with sensors with on-board calibration hardware. VIIRS is a well-calibrated instrument with similar spectral channels as EPIC. Spectral band induced radiance differences between VIIRS and EPIC are mitigated using Spectral Band Adjustment Factor (SBAF). We will extend the previous calibrations from prior studies to include more recent data by ray-matching EPIC with VIIRS over all-sky tropical ocean (ATO) and deep convective cloud (DCC) conditions. In addition to ATO and DCC ray-matching, we will validate these results by utilizing DCC as invariant targets to monitor sensor degradation. DCC behave as solar diffusers in the tropics and when collectively analyzed can be used to monitor the degradation of the EPIC sensor. Improvement to our dynamic navigation adjustment algorithm, as well as exploring the view angle response of the EPIC CCD array, will be examined for their effectiveness and presented at the conference.

C O Haney↗

NASA NTRS2013

Advances in Digital Calibration Techniques Enabling Real-Time Beamforming SweepSAR Architectures

Real-time digital beamforming, combined with lightweight, large aperture reflectors, enable SweepSAR architectures, which promise significant increases in instrument capability for solid earth and biomass remote sensing. These new instrument concepts require new methods for calibrating the multiple channels, which are combined on-board, in real-time. The benefit of this effort is that it enables a new class of lightweight radar architecture, Digital Beamforming with SweepSAR, providing significantly larger swath coverage than conventional SAR architectures for reduced mass and cost. This paper will review the on-going development of the digital calibration architecture for digital beamforming radar instrument, such as the proposed Earth Radar Mission's DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice) instrument. This proposed instrument's baseline design employs SweepSAR digital beamforming and requires digital calibration. We will review the overall concepts and status of the system architecture, algorithm development, and the digital calibration testbed currently being developed. We will present results from a preliminary hardware demonstration. We will also discuss the challenges and opportunities specific to this novel architecture.

TR (Transmit/Receive)↗