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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Green's functions provide a simple, yet effective, method to test and calibrate General-Circulation-Model(GCM) parameterizations, to study and quantify model and data errors, to correct model biases and trends, and to blend estimates from different solutions and data products.
The project has developed theory and computational tools to exploit active subspaces to reduce the dimension in statistical calibration problems. This dimension reduction enables MCMC methods to calibrate otherwise intractable models. The same theoretical and computational tools can also reduce the measurement dimension for calibration problems that use large stores of data.
Purpose: We present an improved method to calculate patient-specific calibration curves to convert X-ray computed tomography (CT) Hounsfield Unit (HU) to relative stopping powers (RSP) for proton therapy treatment planning. Methods: By optimizing the HU-RSP calibration curve, the difference between a proton radiographic image and a digitally reconstructed X-ray radiography (DRR) is minimized. The feasibility of this approach has previously been demonstrated. This scenario assumes that all discrepancies between proton radiography and DRR originate from uncertainties in the HU-RSP curve. In reality, external factors cause imperfections in the proton radiography, such as misalignment compared to the DRR and unfaithful representation of geometric structures (“blurring”). We analyze these effects based on synthetic datasets of anthropomorphic phantoms and suggest an extended optimization scheme which explicitly accounts for these effects. Performance of the method is been tested for various simulated irradiation parameters. The ultimate purpose of the optimization is to minimize uncertainties in the HU-RSP calibration curve. We therefore suggest and perform a thorough statistical treatment to quantify the accuracy of the optimized HU-RSP curve. Results: We demonstrate that without extending the optimization scheme, spatial blurring (equivalent to FWHM=3mm convolution) in the proton radiographies can cause up to 10% deviation between the optimized and the ground truth HU-RSP calibration curve. Instead, results obtained with our extended method reach 1% or better correspondence. We have further calculated gamma index maps for different acceptance levels. With DTA=0.5mm and RD=0.5%, a passing ratio of 100% is obtained with the extended method, while an optimization neglecting effects of spatial blurring only reach ∼90%. Conclusion: Our contribution underlines the potential of a single proton radiography to generate a patient-specific calibration curve and to improve dose delivery by optimizing the HU-RSP calibration curve as long as all sources of systematic incongruence are properly modeled.
This work develops a method to compare the radiometric calibration between a radiometer and imagers hosted on aircraft and satellites. The radiometer is the airborne Research Scanning Polarimeter (RSP), which takes multi-angle, photo-polarimetric measurements in several spectral channels. The RSP measurements used in this work were coincident with measurements made by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), which was on the same aircraft. These airborne measurements were also coincident with an overpass of the Landsat 8 Operational Land Imager (OLI). First we compare the RSP and OLI radiance measurements to AVIRIS since the spectral response of the multispectral instruments can be used to synthesize a spectrally equivalent signal from the imaging spectrometer data. We then explore a method that uses AVIRIS as a transfer between RSP and OLI to show that radiometric traceability of a satellite-based imager can be used to calibrate a radiometer despite differences in spectral channel sensitivities. This calibration transfer shows agreement within the uncertainty of both the various instruments for most spectral channels.
An approach for experimentally evaluating the radiometric calibration of the LANDSAT-4 band 6 data is described which draws on a method used to radiometrically calibrate the HCMR data which involved underflying the satellite with an infrared line scanner. By extending this technology to higher altitudes experimental radiance data suitable for radiometric calibration of the TM band 6 sensor can be generated. Repetition of this experiment can permit evaluation of long term drift in the sensor and provide a data base for evaluating atmospheric propagation models for radiation transfer. To date, efforts were concentrated on modifying the infrared line scanner to match the spectral response of the TM band 6 sensor. In addition, the LOWTRAN code corresponding to a satellite overpass of September 1982 was run to yield a plot of transmission and path radiance as a function of altitude.
A two-stage predictive method was developed for lossless compression of calibrated hyperspectral imagery. The first prediction stage uses a conventional linear predictor intended to exploit spatial and/or spectral dependencies in the data. The compressor tabulates counts of the past values of the difference between this initial prediction and the actual sample value. To form the ultimate predicted value, in the second stage, these counts are combined with an adaptively updated weight function intended to capture information about data regularities introduced by the calibration process. Finally, prediction residuals are losslessly encoded using adaptive arithmetic coding. Algorithms of this type are commonly tested on a readily available collection of images from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imager. On the standard calibrated AVIRIS hyperspectral images that are most widely used for compression benchmarking, the new compressor provides more than 0.5 bits/sample improvement over the previous best compression results. The algorithm has been implemented in Mathematica. The compression algorithm was demonstrated as beneficial on 12-bit calibrated AVIRIS images.
This is the presentation to follow conference paper of the same name. The adaptive compliant trailing edge (ACTE) flap experiment safety of flight requires that the flap to wing interface loads be sensed and monitored in real time to ensure that the wing structural load limits are not exceeded. This paper discusses the strain gage load calibration testing and load equation derivation methodology for the ACTE interface fittings. Both the left and right wing flap interfaces will be monitored and each contains four uniquely designed and instrumented flap interface fittings. The interface hardware design and instrumentation layout are discussed. Twenty one applied test load cases were developed using the predicted in-flight loads for the ACTE experiment.
This article investigates electron bunch density fluctuations in the 1 −10 μm wavelength range, focusing on their impact on coherent electron cooling (CEC) in hadron storage rings. In this study, we compare the shot-noise model with experimental observations using bandwidth-filtered near-infrared optical transition radiation (OTR) photodiode signals, where the transverse bunch size is much larger than the OTR wavelength of interest. The relativistic electron bunch (𝛾 ≈ 50) parameters are close to those proposed for the coherent electron cooler in the electron-ion collider (EIC) project. Preliminary feasibility experiments were conducted, and the noise factors are presented, supported by particle tracking. No major density fluctuations or effective cooling rate decrease were revealed for EIC CEC design parameters. Additionally, longitudinal-space-charge-induced microbunching for the chicane-compressed bunch was observed with coherent OTR enhancements up to 100 times, providing further calibration of the measurement method.
Many inter-consistency efforts force empirical agreement between sensors viewing a source nearly coincident in time and geometry that ensures consistency between sensors rather than obtain an SI-traceable calibration with documented error budgets. The method described here provides interconsistency via absolute radiometric calibration with defensible error budget avoiding systematic errors through prediction of at-sensor radiance for a site viewed by multiple sensors but not necessarily viewed at coincident times. The method predicts spectral radiance over a given surface site for arbitrary view and illumination angles and for any date dominated by clear-sky conditions. The foundation is a model-based, SI-traceable prediction of at-sensor radiance over selected sites based on physical understanding of the surface and atmosphere. The calibration of the ground site will include spatial, spectral, and sunview geometric effects based on satellite and ground-based data. The result is an interconsistency of hyperspectral and multispectral sensors spanning spatial resolutions from meters to kilometers all relative to the surface site rather than a single sensor. The source-centric philosophy of calibrating the site inherently accounts for footprint size mismatch, spectral band mismatch, and temporal and spatial sampling effects. The method for characterizing the test site allows its use for SI-traceable calibration of any sensor that can view the calibrated test site. Interconsistency is obtained through the traceability and error budget rather than coincident views. Such an approach to inter-consistency provides better understanding of biases between sensors as well producing more accurate results with documented SI-traceability that reduces the need for overlapping data sets.
This paper details the first complete, DOE approved, deployed and operational radiometry for robotic nondestructive assay (NDA) of holdup deposits in gaseous diffusion piping. Some features, like peak-finding, Compton correction, detector efficiency, and material properties are characteristic of typical manual methods. Most features are specific to in-pipe robotic deployment. These include in-motion radiometry, self-determined location, geometric modeling of thick deposits, bounding of self-attenuation thickness and auto-checking of replicate measurements. Significant are the means for determining all the properties, equations, and constants for automatically computing and displaying all the quantities, uncertainties and information needed for NDA reporting, analysis, and review. Earlier work by this team demonstrated rudimentary but convincing robotic in-pipe NDA of holdup deposits in pipes. Cold testing with high-enrichment mat sources and hot tests with low U-235 loadings together succeeded to exhibit convincing proof-of-principle. This research-grade radiometry implementation lacked accurate odometry, efficiency calibration, high-fidelity detector modeling, attenuation modeling, forward geometric modeling, auto-segmenting, uncertainty modeling, replicate checking, deconvolution and much more. This work explains the technical basis behind robotic in-pipe NDA. It includes discussion of a new method for modeling of self-attenuation using in-pipe deposit geometry information, detail of the method's total measurement uncertainty, and explanation of calibration methods and results. Beyond development of automation-specific radiometric elements, the paper highlights analyses, testing, and technical bases specific to and supportive of the methodology. Examples include collimation characterization, detector efficiency determination, auto-calibration methodology, and odometric replicate-checking. Results of this methodology are formalized in a DOE EM Technical Basis Document, implemented in software, formally verified in review and acceptance testing and proceduralized as a means for D and D NDA at the Portsmouth enrichment facility. Measurement of U-235 quantity is a well-known cost and schedule driver in D and D of every defunct gaseous diffusion enrichment facility in the world. The radiometry methodologies and results detailed in this paper were the high hurdles. Having established the technical basis for this automated NDA, the opportunity is to apply this to many sizes and robot forms for addressing holdup deposit NDA throughout the D and D community. (authors)
The National Ecological Observatory Network (NEON) is a continental-scale observatory with sites across the US collecting standardized ecological observations that will operate for multiple decades. To maximize the utility of NEON data, we envision edge computing systems that gather, calibrate, aggregate, and ingest measurements in an integrated fashion. Edge systems will employ machine learning methods to cross-calibrate, gap-fill and provision data in near-real time to the NEON Data Portal and to High Performance Computing (HPC) systems, running ensembles of Earth system models (ESMs) that assimilate the data. For the first time gridded EC data products and response functions promise to offset pervasive observational biases through evaluating, benchmarking, optimizing parameters, and training new machine learning parameterizations within ESMs all at the same model-grid scale. Leveraging open-source software for EC data analysis, we are already building software infrastructure for integration of near-real time data streams into the International Land Model Benchmarking (ILAMB) package for use by the wider research community. We will present a perspective on the design and integration of end-to-end infrastructure for data acquisition, edge computing, HPC simulation, analysis, and validation, where Artificial Intelligence (AI) approaches are used throughout the distributed workflow to improve accuracy and computational performance.
Specifications for shock testing of components that will be used on the Space Shuttle vehicles require very high acceleration levels. A special shock machine was built for testing of rocket components to determine if they can meet the specified accelerations. Calibrations of transducers and methods to monitor the shock tests raised several signature-analysis questions. In this report, calibration capabilities of shock accelerometers are found to be limited to 10,000g. Equivalency of the mechanical shock test and the rocket pyrotechnic shock are examined, and two simple relationships for equivalency are proposed. Five different pulse signature-analysis techniques are tested on analytical and experimental pulse data and recommendations are made for the signature technique which most clearly identifies the magnitude of the impulse applied to the test specimen.
Fission foil detectors (FFD's) are passive devices composed of heavy metal foils in contact with muscovite mica films. The heavy metal nuclei have significant cross sections for fission when irradiated with neutrons and protons. Each isotope is characterized by threshold energies for the fission reactions and particular energy-dependent cross sections. In the FFD's, fission fragments produced by the reactions are emitted from the foils and create latent particle tracks in the adjacent mica films. When the films are processed surface tracks are formed which can be optically counted. The track densities are indications of the fluences and spectra of neutrons and/or protons. In the past, detection efficiencies have been calculated using the low energy neutron calibrated dosimeters and published fission cross sections for neutrons and protons. The problem is that the addition of a large kinetic energy to the (n,nucleus) or (p,nucleus) reaction could increase the energies and ranges of emitted fission fragments and increase the detector sensitivity as compared with lower energy neutron calibrations. High energy calibrations are the only method of resolving the uncertainties in detector efficiencies. At high energies, either proton or neutron calibrations are sufficient since the cross section data show that the proton and neutron fission cross sections are approximately equal. High energy proton beams have been utilized (1.8 and 4.9 GeV, 80 and 140 MeV) for measuring the tracks of fission fragments emitted backward and forward.
A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.
Cryogenic Scanning/Transmission Electron Microscopy has been established as a leading method to image sensitive biological samples and is now becoming a powerful tool to understand materials' behavior at low temperatures. However, achieving precise local temperature calibration at low temperatures remains a challenge, which is especially crucial for studying phase transitions and emergent physical properties in quantum materials. In this study, we employ electron energy loss spectroscopy (EELS) to measure local cryogenic specimen temperatures. Here we use the temperature-dependent characteristics of aluminum's bulk plasmon peak in EEL spectra, which shifts due to changes in electron density caused by thermal expansion and contraction. We successfully demonstrate the versatility of this method by calibrating different liquid nitrogen cooling holders in various microscopes, regardless of whether a monochromated or non-monochromated electron beam is used. Temperature discrepancies between the actual temperature and the setpoint temperatures are identified across a range from room temperature to 100 K. This work demonstrates the importance of temperature calibrations at intermediate temperatures and presents a straightforward, robust method for calibrating local temperatures of cryogenically-cooled specimens in electron microscopes.
PowderSim is a calculation tool that combines a discrete-element method (DEM) module, including calibrated interparticle-interaction relationships, with a mesh-free, continuum, SPH (smoothed-particle hydrodynamics) based module that utilizes enhanced, calibrated, constitutive models capable of mimicking both large deformations and the flow behavior of regolith simulants and lunar regolith under conditions anticipated during in situ resource utilization (ISRU) operations. The major innovation introduced in PowderSim is to use a mesh-free method (SPH-based) with a calibrated and slightly modified critical-state soil mechanics constitutive model to extend the ability of the simulation tool to also address full-scale engineering systems in the continuum sense. The PowderSim software maintains the ability to address particle-scale problems, like size segregation, in selected regions with a traditional DEM module, which has improved contact physics and electrostatic interaction models.
Purpose: It is now commonplace to handle treatments of hyperthyroidism using iodine-131 as an outpatient procedure due to lower costs and less stringent federal regulations. The Nuclear Regulatory Commission has currently updated release guidelines for these procedures, but there is still a large uncertainty in the dose to the public. Current guidelines to minimize dose to the public require patients to remain isolated after treatment. The purpose of this study was to use a low-cost common device, such as a cell phone, to estimate exposure emitted from a patient to the general public. Methods: Measurements were performed using an Apple iPhone 3GS and a Cs-137 irradiator. The charge-coupled device (CCD) camera on the phone was irradiated to exposure rates ranging from 0.1 mR/hr to 100 mR/hr and 30-sec videos were taken during irradiation with the camera lens covered by electrical tape. Interactions were detected as white pixels on a black background in each video. Both single threshold (ST) and colony counting (CC) methods were performed using MATLAB®. Calibration curves were determined by comparing the total pixel intensity output from each method to the known exposure rate. Results: The calibration curve showed a linear relationship above 5 mR/hr for both analysis techniques. The number of events counted per unit exposure rate within the linear region was 19.5 ± 0.7 events/mR and 8.9 ± 0.4 events/mR for the ST and CC methods respectively. Conclusion: Two algorithms were developed and show a linear relationship between photons detected by a CCD camera and low exposure rates, in the range of 5 mR/hr to 100-mR/hr. Future work aims to refine this model by investigating the dose-rate and energy dependencies of the camera response. This algorithm allows for quantitative monitoring of exposure from patients treated with iodine-131 using a simple device outside of the hospital.
A hyperspectral sun photometer and associated methods have been developed and demonstrated. Accurate sun photometer calibration is critical to properly measure the solar irradiance and characterize the atmosphere. Traditional sun photometer calibration requires solar observations over several hours. In contrast, the procedures for operating this photometer entail less data acquisition time and embody a more direct approach to calibration. The scientific value of the measurement data produced by this instrument is not adversely affected by atmospheric instability. In addition, this instrument yields hyperspectral data covering a large spectral range (350-2,500 nm) not available from most traditional sun photometers. The hyperspectral sun photometer components include (1) a commercially available spectroradiometer that has been laboratory-calibrated and (2) a commercially available reflectance standard panel that exhibits nearly Lambertian 99% reflectance. The spectroradiometer is positioned above, and aimed downward at, the panel. The procedure for operating this instrument calls for a series of measurements: one in which the panel is fully illuminated by the sun, one in which a shade is positioned between the panel and the sun, and two in which the shade is positioned to cast a shadow to either side of the panel. The total sequence of measurements can be performed in less than a minute. From these measurements, the total radiance, the diffuse radiance, and the direct solar radiance are calculated. The direct solar irradiance is calculated from the direct solar radiance and the known reflectance factor of the panel as a function of the solar zenith angle. Atmospheric characteristics are estimated from the optical depth at various wavelengths calculated from (1) the direct solar irradiance obtained as described above, (2) the air mass along a column from the measurement position to the Sun, and (3) the top-of-atmosphere solar irradiance. The instrumentation used to implement the sun photometer is the same as that used to characterize targets used in radiometric vicarious calibrations. Utilizing this type of sun photometer thus reduces the amount of instrumentation and labor required to perform these studies.