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An improved method of mapping the capacitive contribution to cross-talk among pixels in an imaging array of sensors (typically, an imaging photodetector array) has been devised for use in calibrating and/or characterizing such an array. The method involves a sequence of resets of subarrays of pixels to specified voltages and measurement of the voltage responses of neighboring non-reset pixels.
Impact cratering is an important geological process that occurs on every rocky body in the solar system. It alters the texture and mineralogy of rocks via shock metamorphism. The peak shock pressures experienced by a rock are traditionally evaluated using qualitative optical methods however, quantitative methods do exist. One such method was developed by Uchizono et al., who used X-ray Diffraction (XRD) to measure lattice strain (ε) in several artificially shocked olivine grains using XRD peak broadening as a function of tan θ, where θ is the diffraction angle. They plotted the ε values against the known peak shock pressures experienced by the olivine grains. Using this calibration curve, the precise shock pressure experienced by a grain of olivine can be determined using its measured ε value. Another method was developed by McCausland et al. and Izawa et al., who used in situ XRD to measure strain-related mosaicity (SRM) of olivine in several ordinary chondrites and enstatite in enstatite chondrites, respectively. They plotted these results against the shock stage estimates for these meteorites. Using these plots, meteorites can be assigned to shock stage bins by measuring the SRM of olivine and/or enstatite. Both methods are useful for evaluating shock metamorphism, however, they have limitations. Uchizono et al.’s calibration curve has been successfully applied to martian meteorites, however it can only be applied to olivine-bearing rocks. McCausland et al.’s and Izawa et al.’s SRM method is uncalibrated and is limited to binning meteorites by shock stage. This work aims to expand on both methods by creating calibration curves for clinopyroxene (CPX): one for ε, similar to Uchizono et al.’s calibration curve for olivine, and one for SRM. This will extend the application of shock calibration methods to a greater variety of rock types. Preliminary results are presented herein.
We present new constraints on the halo masses and matter density profiles of DESI galaxy groups by cross-correlating samples of luminous red galaxies (LRGs) and bright galaxy survey (BGS) galaxies with the publicly available CMB lensing convergence map from ACT DR6. This provides an independent, lensing-based calibration of halo masses, complementary to methods relying on clustering or dynamics. We derive constraints on the mean halo mass for three DESI-selected samples, finding log(𝑀 halo /(𝑀 ⊙ /ℎ)) ≈ 13.18, 13.03 and 13.02 for the main LRG, extended LRG, and BGS samples, respectively. Using a halo model approach, we also compare the projected galaxy-matter density profiles with previously reported gas profiles inferred from measurements of the kinematic Sunyaev-Zel’dovich (kSZ) effect. This work addresses one of the key uncertainties in interpreting kSZ signals—the unknown host halo mass distribution—by providing an independent and consistent mass calibration. The agreement between the gas and total mass profiles at large aperture suggests that sufficiently far from the group center (2–3 virial radii), we recover all the baryons, offering a resolution to the missing baryon problem. We further study the cumulative gas fractions for all galaxies as well as for the most massive galaxy groups in the sample [log(𝑀 halo /(𝑀 ⊙ /ℎ)) ≈ 13.5], finding values that are physically sensible and in agreement with previous findings using kSZ and x-ray data: compared to the TNG300 simulation, the observed gas fractions are systematically lower at fixed radius by ≳ 4𝜎, providing compelling, independent evidence for stronger baryonic feedback in the real Universe. These findings highlight the power of combining CMB lensing with galaxy surveys to probe the interplay between baryons and dark matter in group-sized halos.
Uplink antenna arrays have the potential to greatly increase the Deep Space Network s high-data-rate uplink capabilities as well as useful range, and to provide additional uplink signal power during critical spacecraft emergencies. While techniques for calibrating an array of receive antennas have been addressed previously, proven concepts for uplink array calibration have yet to be demonstrated. This article describes a method of utilizing the Moon as a natural far-field reflector for calibrating a phased array of uplink antennas. Using this calibration technique, the radio frequency carriers transmitted by each antenna of the array are optimally phased to ensure that the uplink power received by the spacecraft is maximized.
Accurate solar irradiance data are fundamental for determining the design and performance characteristics of photovoltaic systems. The uncertainty of solar irradiance measurements depends on many factors including radiometer design, calibration, installation, maintenance, and operational environment. The key contributors to this uncertainty can be classified as the measurement uncertainty of a particular radiometer and the operational uncertainty determined for the time of measurement. Radiometer measurement uncertainty estimates (U R ) can be based on well-established methods used as part of the radiometer calibration process. Estimates of operational uncertainties (U o ) require consideration of additional site-specific factors that affect data quality. A method is needed for establishing the accuracy of solar irradiance data by integrating an existing data quality process and measurement uncertainty estimates for specific radiometers. An algorithm has been developed to integrate data quality analyses and measurement uncertainty estimates for three-component solar irradiance data: global horizontal (total hemispheric) irradiance, direct normal (beam) irradiance, and diffuse horizontal (sky) irradiance collected at one- to 60-minute intervals. The algorithm has been tested using one-minute irradiance measurements. The goal of the project is to distribute a user-friendly software package based on the new algorithm.
This paper addresses two challenges in Bayesian calibration: 1) computational speed of existing sampling algorithms, and 2) calibration with spatio-temporal responses. The commonly used Markov Chain Monte Carlo (MCMC) approaches require many sequential model evaluations making the computational expense prohibitive. This paper proposes an efficient sampling algorithm: iterative importance sampling with genetic algorithm (IISGA). While iterative importance sampling enables computational efficiency, the genetic algorithm enables robustness by preventing sample degeneration and avoids getting stuck in multimodal search spaces. An inflated likelihood further enables robustness in high-dimensional parameter spaces by enlarging the target distribution. Spatio-temporal data complicate both surrogate modeling, which is necessary for expensive computational models, and the likelihood estimation. In this work, singular value decomposition is investigated for reducing the high-dimensional field data to a lower-dimensional space prior to Bayesian calibration. Then the likelihood is formulated and Bayesian inference is performed in the lower-dimension, latent space. An illustrative example is provided to demonstrate IISGA relative to existing sampling methods, and then IISGA is employed to calibrate a thermal battery model with 26 uncertain calibration parameters and spatio-temporal response data.
In electric propulsion (EP) systems, accurate measurement of the propellant mass flow rate of gas or liquid to the thruster and external cathode is a key input in the calculation of thruster efficiency and specific impulse. Although such measurements are often achieved with commercial mass flow controllers and meters integrated into propellant feed systems, the variability in potential propellant options and flow requirements amongst the spectrum of EP power regimes and devices complicates meter selection, integration, and operation. At the direction of the Committee on Standards for Electric Propulsion Testing, a guide was jointly developed by members of the electric propulsion community to establish a unified document that contains the working principles, methods of implementation and analysis, and calibration techniques and recommendations on the use of mass flow meters in laboratory and spacecraft electric propulsion systems. The guide is applicable to EP devices of all types and power levels ranging from microthrusters to high-power ion engines and Hall effect thrusters. The establishment of a community standard on mass flow metering will help ensure the selection of the proper meter for each application. It will also improve the quality of system performance estimates by providing comprehensive information on the physical phenomena and systematic errors that must be accounted for during the analysis of flow measurement data. This paper will outline the standard methods and recommended practices described in the guide titled "Flow Measurement for Electric Propulsion Systems."
Efficient selections of particle-scale contact parameters in discrete element modelling remain an open question. The purpose of this study is to provide a hybrid calibration framework to estimate linear contact stiffnesses (normal and tangential) for both two-dimensional and three-dimensional simulations. Analytical formulas linking macroscopic parameters (Young's modulus, Poisson's ratio) to mesoscopic particle parameters for granular systems are derived based on statistically isotropic packings under small-strain isotropic stress conditions. By taking the derived analytical solutions as initial approximations, the gradient descent algorithm automatically obtains a reliable numerical estimation. The introduced framework is validated with several numerical cases including randomly distributed monodisperse and polydisperse packings. The results show that this hybrid method practically reduces the time for artificial trials and errors to obtain reasonable stiffness parameters. The proposed framework can also be extended to other parameter calibration problems in DEM.
Purpose: Accounting for tumor motion during radiation therapy is important to ensure that the tumor receives the prescribed dose. Increasing the field size to account for this motion exposes the surrounding healthy tissues to unnecessary radiation. In contrast to using motion-encompassing techniques to treat moving tumors, conformal radiation therapy (RT) uses a smaller field to track the tumor and adapts the beam aperture according to the motion detected. This work investigates and compares the performance of three markerless, EPID based, optical flow methods to track tumor motion with conformal RT. Methods: Three techniques were used to track the motions of a 3D printed lung tumor programmed to move according to the tumor of seven lung cancer patients. These techniques utilized a multi-resolution optical flow algorithm as the core computation for image registration. The first method (DIR) registers the incoming images with an initial reference frame, while the second method (RFSF) uses an adaptive reference frame and the third method (CU) uses preceding image frames for registration. The patient traces and errors were evaluated for the seven patients. Results: The average position errors for all patient traces were 0.12 ± 0.33 mm, −0.05 ± 0.04 mm and −0.28 ± 0.44 mm for CU, DIR and RFSF method respectively. The position errors distributed within 1 standard deviation are 0.74 mm, 0.37 mm and 0.96 mm respectively. The CU and RFSF algorithms are sensitive to the characteristics of the patient trace and produce a wider distribution of errors amongst patients. Although the mean error for the DIR method is negatively biased (−0.05 mm) for all patients, it has the narrowest distribution of position error, which can be corrected using an offset calibration. Conclusion: Three techniques of image registration and position update were studied. Using direct comparison with an initial frame yields the best performance. The authors would like to thank Dr.YeLin Suh for making the Cyberknife dataset available to us. Scholarship funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) and CancerCare Manitoba Foundation is acknowledged.
In planetary sciences, in situ absolute geochronology is a scientific and engineering challenge. Currently, the age of the Martian surface can only be determined by crater density counting. However this method has significant uncertainties and needs to be calibrated with absolute ages. We are developing an instrument to acquire in situ absolute geochronology based on the K‐Ar method. The protocol is based on the laser ablation of a rock by hundreds of laser pulses. Laser Induced Breakdown Spectroscopy (LIBS) gives the potassium content of the ablated material and a mass spectrometer (quadrupole or ion trap) measures the quantity of 40Ar released. In order to accurately measure the quantity of released 40Ar in cases where Ar is an atmospheric constituent (e.g., Mars), the sample is first put into a chamber under high vacuum. The 40Arquantity, the concentration of K and the estimation of the ablated mass are the parameters needed to give the age of the rocks. The main uncertainties with this method are directly linked to the measures of the mass (typically some μg) and of the concentration of K by LIBS (up to 10%). Because the ablated mass is small compared to the mass of the sample, and because material is redeposited onto the sample after ablation, it is not possible to directly measure the ablated mass. Our current protocol measures the ablated volume and estimates the sample density to calculate ablated mass. The precision and accuracy of this method may be improved by using knowledge of the sample's geologic properties to predict its response to laser ablation, i.e., understanding whether natural samples have a predictable relationship between laser energy deposited and resultant ablation volume. In contrast to most previous studies of laser ablation, theoretical equations are not highly applicable. The reasons are numerous, but the most important are: a) geologic rocks are complex, polymineralic materials; b) the conditions of ablation are unusual (for example, variable vacuum pressure), and c) the ablation is made with hundreds of successive laser pulses. In this work, we aim to understand the effects that occur on LIBS spectra when a homogeneous rock or a mineral is ablated under high vacuum. Understanding these effects is important to define best practices for LIBS measurements and may lead to improved measurement (or possibly prediction) of the ablated volume. We will describe our laboratory approach and first results, and discuss its utility for situ absolute geochronology campaigns.
Liquid argon time projection chambers are often used in neutrino physics and dark-matter searches because of their high spatial resolution. The images generated by these detectors are extremely sparse, as the energy values detected by most of the detector are equal to 0, meaning that despite their high resolution, most of the detector is unused in a particular interaction. Instead of representing all of the empty detections, the interaction is usually stored as a sparse matrix, a list of detection locations paired with their energy values. Traditional machine learning methods that have been applied to particle reconstruction such as convolutional neural networks (CNNs), however, cannot operate over data stored in this way and therefore must have the matrix fully instantiated as a dense matrix. Operating on dense matrices requires a lot of memory and computation time, in contrast to directly operating on the sparse matrix. We propose a machine learning model using a point set neural network that operates over a sparse matrix, greatly improving both processing speed and accuracy over methods that instantiate the dense matrix, as well as over other methods that operate over sparse matrices. Compared to competing state-of-the-art methods, our method improves classification performance by 14%, segmentation performance by more than 22%, while taking 80% less time and using 66% less memory. Compared to state-of-the-art CNN methods, our method improves classification performance by more than 86%, segmentation performance by more than 71%, while reducing runtime by 91% and reducing memory usage by 61%.
The effort to understand the Earth's climate system requires a complete integration of remote sensing imager data across time and multiple countries. Such an integration necessarily requires ensuring inter-consistency between multiple sensors to create the data sets needed to understand the climate system. Past efforts at inter-consistency have forced agreement between two sensors using sources that are viewed by both sensors at nearly the same time, and thus tend to be near polar regions over snow and ice. The current work describes a method that would provide an absolute radiometric calibration of a sensor rather than an inter-consistency of a sensor relative to another. The approach also relies on defensible error budgets that eventually provides a cross comparison of sensors without systematic errors. The basis of the technique is a model-based, SI-traceable prediction of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The effort effectively works to characterize the sites as sources with known top-of-atmosphere radiance allowing accurate intercomparison of sensor data that without the need for coincident views. Data from the Advanced Spaceborne Thermal Emission and Reflection and Radiometer (ASTER), Enhanced Thematic Mapper Plus (ETM+), and Moderate Resolution Imaging Spectroradiometer (MODIS) are used to demonstrate the difficulties of cross calibration as applied to current sensors. Special attention is given to the differences caused in the cross-comparison of sensors in radiance space as opposed to reflectance space. The radiance comparisons lead to significant differences created by the specific solar model used for each sensor. The paper also proposes methods to mitigate the largest error sources in future systems. The results from these historical intercomparisons provide the basis for a set of recommendations to ensure future SI-traceable cross calibration using future missions such as CLARREO and TRUTHS. The paper describes a proposed approach that relies on model-based, SI-traceable predictions of at-sensor radiance over selected sites. The predicted radiance would be valid for arbitrary view and illumination angles and for any date of interest that is dominated by clear-sky conditions. The basis of the method is highly accurate measurements of at-sensor radiance of sufficient quality to understand the spectral and BRDF characteristics of the site and sufficient historical data to develop an understanding of temporal effects from changing surface and atmospheric conditions.
The two magnetometers recently replaced on the Hubble Space Telescope during the STS-61 Servicing Mission are now being used successfully for Coarse Attitude Determination during spacecraft vehicle safemode recovery operation. The magnetometer alignments relative to the spacecraft's vehicle's reference frame and the magnetic coupling of the sensors to the four magnetic torquer bars were determined. Coarse Attitude determination errors are now reduced to an average of 0.6 deg. Magnetometer Sensing System calibration and Coarse Attitude determination testing with the new calibration parameters is a geometrical problem. Telemetered earth magnetic field data was collected at twenty-six different vehicle attitudes. The spacecraft attitudes selected were distributed as widely apart as possible throughout the Geocentric Inertial Coordinate reference frame. It is also desirable to sample the Earth's magnetic field over as many different locations of the spacecraft's passage over the Earth as possible, within the limitation of the +/- 28.5 deg orbital inclination. A full range of magnetic moment outputs from the torquer bars needs to be sampled, +/- 3600 ampmeters squared, as well as data when the torquer bars have zero current. Graphic utilities were also developed to visually aid in optimizing the data collection process. Finally, a brief discussion of a method for collecting data for future calibrations is suggested.
Here, we investigate and compare the spatial (lateral) resolution, or more generally, the optical/instrumental transfer function (OTF/ITF) of surface slope measuring profilometers of two different types that are commonly used for high accuracy characterization of x-ray optics at the long-spatial-wavelength range. These are an autocollimator based profiler, Optical Surface Measuring System (OSMS), and a long trace profiler, LTP-II, both available at the Advanced Light Source (ALS) X-Ray Optics Lab (XROL). In the OSMS, an ELCOMAT-3000 electronic auto-collimator, vertically mounted to the translation carriage and equipped with an aperture of 2.5 mm diameter, is scanned along the surface under test. The LTP-II OTF has been measured for two different configurations, a classical two-beam pencil-beam-interferometry and a single-Gaussian-beam deflectometry. For the ITF calibration, we apply a recently developed method based on test surfaces with one-dimensional (1D) linear chirped height profiles of constant slope amplitude. Analytical expressions for the OTFs, empirically deduced based on the experimental results, are presented. We also discuss the application of the results of the ITF measurements and modeling to improve the surface slope metrology with state-of-the-art x-ray mirrors.
Holdup is the residual amount of special nuclear material (SNM) remaining in a processing facility after the bulk materials have been cleaned out. In commercial uranium processing facilities, quantification of holdup is a major challenge because of the highly variable shapes and sizes of the deposits. Any method that attempts to generalize and calibrate deposit shapes in order to quantify holdup will be prone to high uncertainties. Uncertainties on the order of ±50% are typical in holdup results. In international safeguards applications, a ±50% uncertainty can result in a large amount of material unaccounted for (MUF) thereby increasing the difficulty of detecting material diversion and facility misuse. An imaging-based methodology has been developed with the objective of significantly reducing this uncertainty by using the true deposit shape, instead of relying on oversimplified geometric assumptions. The project is a collaboration between ORNL, Y-12, and the University of Tennessee, Knoxville, TN. Uranium sources of known masses were measured using the Germanium Gamma-ray Imager (GeGI), a high-resolution imaging spectrometer, creating a pixelated map for each spectral bin. Two different gamma imaging methods are employed in this work: coded aperture imaging and Compton imaging. A validated MonteCarlo model of the detector has been developed using the GEANT4 code for determining the intrinsic response of the detector, its enclosure, and the coded aperture mask. An inverse transport solver based on the Markov Chain Monte-Carlo approach known as Differential Evolution Adaptive Metropolis (DREAM) is employed to use the measurement data from the image pixels (coded aperture or Compton) to solve for the mass of 235 U in the deposit. A reliable method based on the DREAM solver has been developed to flag the infinite thickness condition of a uranium deposit. The project team is working towards improving the image reconstruction for Compton imaging so that a better localization of the source can be achieved. Besides treating the coded aperture and Compton imaging methods independently, the project is also evaluating a combined method that uses the Compton scatter data from a coded aperture measurement. GEANT4 simulations are being performed to evaluate the combined approach. The impact on the DREAM optimization as the source thickness progressively approaches infinite thickness is being evaluated. A number of uranium sources available at ORNL have been measured, and the DREAM results have been tested and validated for the coded aperture imaging. A similar effort will be carried out to validate the Compton based method once the development of algorithms for better localization are complete. The imaging based quantification is very amenable to unattended monitoring of holdup accumulation at key measurement points. A proof of concept measurement has been completed to demonstrate this capability The current work used the high energy resolution imager GeGI. However, the approach and methodologies are applicable to other imagers such as the cadmium zin telluride (CZT) based imager manufactured by H3D, Inc.
The paper discusses the selection of regression model terms for the analysis of wind tunnel strain-gage balance calibration data. Different function class combinations are presented that may be used to analyze calibration data using either a non-iterative or an iterative method. The role of the intercept term in a regression model of calibration data is reviewed. In addition, useful algorithms and metrics originating from linear algebra and statistics are recommended that will help an analyst (i) to identify and avoid both linear and near-linear dependencies between regression model terms and (ii) to make sure that the selected regression model of the calibration data uses only statistically significant terms. Three different tests are suggested that may be used to objectively assess the predictive capability of the final regression model of the calibration data. These tests use both the original data points and regression model independent confirmation points. Finally, data from a simplified manual calibration of the Ames MK40 balance is used to illustrate the application of some of the metrics and tests to a realistic calibration data set.
The present conference on remote sensing instrumentation considers topics in water resources research, planetary remote sensing and mathematical geophysics, sea ice behavior in view of the Cold Regions Research and Engineering Laboratories pond measurements, Shuttle Imaging Radar-B (SIR-B) system performance and calibration results, geological applications of remote sensing, and microwave scattering from vegetation. Further attention is given to atmospheric probing with lasers, image processing for remote sensing, forest inventory and condition assessment, atmospheric remote sensing, SIR-B geological results, the reflectance, emission, and scattering characteristics of vegetation, sea ice sensing, multipolarization SAR results, the theoretical modeling of surfaces and volumes, crop condition assessment and productivity estimates, and SIR-B results for vegetation cover. Also considered are the microwave remote sensing of soil moisture, advanced sensors, advanced information extraction, wind and wave remote observations, results from the ESA Remote Sensing satellite, large area crop and land cover statistics, SIR-B results for directional ocean wave spectra, seasonal snow cover, ice sheets, and lake ice, fundamental research in terrain remote sensing, image classification methods, vegetation stress detection, remote sensing of coastal processes, SAR systems and calibration, electromagnetic geophysical methods and signal processing, image processing techniques, and SAR internal wave measurements.
The present work reports on the development of techniques for in-field fast-neutron radiography measurements using the associated-particle imaging (API) method. The API method employs alpha-neutron coincidences from the d+t→α+n reaction to enable fast neutron transmission imaging with excellent contrast using a wide cone beam. However, for field radiography applications, the API method is burdened by the need for the relative positions of the source and detector to be known. Fortunately, these relative positions can be inferred from transmission data. The inferred positions also enable accurate stitching of multiple images into a composite image even when using a low-resolution detector panel and acquiring images having few overlapping pixels. The developed techniques address analysis of measurements where (1) the source and detector panel are separately hand positioned rather than held in registration by a gantry, (2) multiple detector panel positions within the “coincident cone” of tagged neutrons are required to piece together an image of an item of interest, and (3) normalization measurements that have identical source-detector positioning but without the inspected object are not possible. The present work will describe the system calibrations (including timing calibrations and neutron direction calibrations) necessary for subsequent analyses, the method of locating the detector in the coincident cone of neutrons with millimeter precision using the timing and directions of coincident neutrons, the method of calculating a normalization image for a given detector panel position, and the method used to project multiple images into a common image.
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