Results for “inverse test” — Page 6

DOE OSTI2021

A Comparison of Exact and Model Exchange–Correlation Potentials for Molecules

Accurate exchange–correlation (XC) potentials for three-dimensional systems–via solution of the inverse density functional theory (DFT) problem–are now available to test the quality of DFT approximations. Herein, the exact XC potential for seven molecules–dihydrogen at four different bond-lengths, lithium hydride, water, and ortho-benzyne–are computed from full configuration interaction reference densities. These are compared to model XC potentials from nonlocal (B3LYP, HSE06, SCAN0, and M08-HX) and semilocal/local (SCAN, PBE, and PW92) XC functionals. Whereas for most systems, relative errors in the ground-state densities are O(10 –3 –10 –2 ) , the model XC potentials have much higher errors of O(10 –1 –10 0 ) . Among the model XC functionals, SCAN0 offers the best agreement with the exact XC potential, underlining the significance of satisfying exact conditions as well as including nonlocal effects in XC functionals. This work indicates that tests against the exact XC potential will provide a promising new direction for building more accurate XC functionals for DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗

DOE OSTI2025

Novel application of neutrinos to evaluate U.S. nuclear weapons performance

There is a growing realization that neutrinos can be used as a diagnostic tool to better understand the inner workings of a nuclear weapon. Robust estimates demonstrate that an Inverse Beta Decay (IBD) neutrino scintillation detector built at the Nevada Test Site with a 1000-ton active target mass at a standoff distance of 500 m would detect thousands of antineutrino events per nuclear test. This would provide less than 4% statistical error on the measured antineutrino rate and 5% error on antineutrino energy. Extrapolating this to an error on the test device explosive yield requires knowledge from evaluated nuclear databases, non-equilibrium fission rates, and assumptions on internal neutron fluxes. Initial calculations demonstrate that the total number of neutrinos emitted per fission in the first 10 3 s after a short pulse of 239 Pu fission is about a factor of two less than that from Pu fissioning under steady state conditions. Furthermore, there are significant energy spectral differences as a function of time after the pulse that must be considered. These and other model dependencies will be discussed in the paper. In the absence of nuclear weapons testing, many of the technical and theoretical challenges of a full nuclear test could be mitigated with a low cost smaller scale 20 ton fiducial mass IBD demonstration detector placed near a pulsed reactor. Potential reactors include the Texas A&M University TRIGA 1 GW–10 ms pulsed facility or the Sandia Annular Core Research Reactor. The short duty cycle and repeatability of pulses would provide critical real environment testing and measurements, which would be valuable for planning a possible real test shot in the future. Furthermore, the antineutrino rate as a function of time data would provide unique constraints on fission databases and model assumptions. Finally, there are impactful science drivers such as sensitive searches for ∼1 eV 2 sterile neutrinos and ∼MeV scale axions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems

Deep learning has been shown to be an effective tool in solving partial differential equations (PDEs) through physics-informed neural networks (PINNs). PINNs embed the PDE residual into the loss function of the neural network, and have been successfully employed to solve diverse forward and inverse PDE problems. However, one disadvantage of the first generation of PINNs is that they usually have limited accuracy even with many training points. Here, we propose a new method, gradient-enhanced physics-informed neural networks (gPINNs), for improving the accuracy of PINNs. gPINNs leverage gradient information of the PDE residual and embed the gradient into the loss function. We tested gPINNs extensively and demonstrated the effectiveness of gPINNs in both forward and inverse PDE problems. Our numerical results show that gPINN performs better than PINN with fewer training points. Additionally, we combined gPINN with the method of residual-based adaptive refinement (RAR), a method for improving the distribution of training points adaptively during training, to further improve the performance of gPINN, especially in PDEs with solutions that have steep gradients.

42 ENGINEERING↗

DOE OSTI2024

Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep-learning techniques

Using multiple geophysical methods has become a prevailing approach in numerous geophysical applications to investigate subsurface structures and parameters. These multimethod-based exploration strategies have the potential to greatly diminish uncertainties and ambiguities encountered during geophysical data analysis and interpretation. One of the applications is the cooperative inversion of airborne magnetic and gravity gradient data for the interpretation of data obtained in mineral, oil and gas, and geothermal explorations. In this paper, a unified cooperative inversion framework is designed by combining the standard separate inversions with a deep neural network (DNN), which serves as the link between different types of data. A well-trained DNN takes the separately inverted susceptibility and density models as the inputs and provides improved models that will be used as the initial models of deterministic inversions. A two-round iteration strategy is adopted to guarantee the reasonability of the recovered models and overall efficiency of the inversion. In addition, this deep-learning (DL)-based framework demonstrates excellent generalization abilities when tested on models that are entirely distinct from the training data sets. The framework can easily incorporate multiphysics without necessitating any structural changes to the network. Synthetic experiments validate that our DL-based method outperforms conventional separate inversions and cross-gradient-based joint inversion in view of the accuracy of the recovered models and inversion efficiency. Successful application to field data further verifies the effectiveness of our DL-based method.

Geochemistry & Geophysics↗

DOE OSTI2023

Recent Developments in Hydrogeologic Applications for Strain Tensor Analyses

Changes in fluid pressure deform porous media and this effect occurs in a variety of hydrogeologic processes, from the change in storage during pumping or injection to fluctuations in water levels caused by barometric pressure. We have developed instruments for measuring small strains in porous media, and we have used the resulting strain data to evaluate well testing, hydraulic fracturing, manual loading at the ground surface, and ambient hydrologic processes, like rainfall and evaporation. A particularly important application is the use of strain tensor data measured at shallow depths to analyze well tests or hydraulic fractures conducted at much greater depths. An early demonstration of this technique was conducted at the North Avant Field north of Tulsa, Oklahoma, where Pennsylvanian sandstone creates a confined aquifer and oil reservoir at a depth of 530m. We have showed that the strains caused by injecting into the aquifer could be measured at a depth of 30m and used to evaluate the properties of the aquifer. We recently expanded the array of strainmeters at the North Avant Field by deploying three more instruments at shallow depth (30m) along with a deep instrument at 520m depth in the winter, 2021. The deep instrument is deployed in shale caprock slightly above the aquifer. To our knowledge, the deep strainmeter at the North Avant Field is the deepest strainmeter ever deployed and this required refining methods originally developed for shallow deployments. The instrument was lowered to depth on oil field tubing and cemented in place using techniques and materials developed for use in oil wells. Optical fiber used to communicate with the instrument was cemented in the annulus on the outside of tubing. This is significant because the techniques we used could readily be extended to greater depth, suggesting that strainmeters can be deployed over a wide range of depths for monitoring critical subsurface processes. For example, it suggests that strainmeters could be deployed through the caprock to monitor for leaks from underlying CO2 storage reservoirs. The strainmeter array at the North Avant Field has been used to characterize deformation during a series of injection tests in the spring and summer, 2021. All the new strainmeters respond to pumping, and the strainmeters we installed earlier also responded. To our knowledge, this is the first application of well testing in a deep aquifer that was monitored by an array of strainmeters—our earlier work used strainmeters at a single location. We are currently analyzing the strain data using an analytical solution, a proxy-based Bayesian inversion algorithm, and other methods. Strainmeter data has also been used to characterize periodic pumping tests by us and Riley Blais. A periodically varying pumping rate causes both hydraulic head and strain signals that vary with the same period as the pumping. The peaks and troughs of the head in monitoring wells lag behind the peaks and troughs of the head in the pumping well, and this lag time increases with distance from the pumping well. The lag time of the pressure and the distance to the monitoring well can be used in a simple analysis to estimate the hydraulic diffusivity of the aquifer. The lag time determined from strain data can be used to estimate aquifer properties using the same analysis that works for the pressure only for strain data measured at particular locations. That is because the strain field in a confining unit advances upward, laterally and then downward even though the pressure in the underlying aquifer only advances laterally, according to our recent simulations. We have field data showing that a small periodic signal superimposed on an injection rate at the North Avant Field will create a periodic strain signal at shallow strainmeters. The field data and the recent simulations suggest that including a periodic component to injection or pumping and then monitoring the resulting strain signal could be a way to monitor the subsurface.

Murdoch, Larry↗

DOE OSTI2023

Recent Developments in Hydrogeologic Applications for Strain Tensor Analyses

Changes in fluid pressure deform porous media and this effect occurs in a variety of hydrogeologic processes, from the change in storage during pumping or injection to fluctuations in water levels caused by barometric pressure. We have developed instruments for measuring small strains in porous media, and we have used the resulting strain data to evaluate well testing, hydraulic fracturing, manual loading at the ground surface, and ambient hydrologic processes, like rainfall and evaporation. A particularly important application is the use of strain tensor data measured at shallow depths to analyze well tests or hydraulic fractures conducted at much greater depths. An early demonstration of this technique was conducted at the North Avant Field north of Tulsa, Oklahoma, where Pennsylvanian sandstone creates a confined aquifer and oil reservoir at a depth of 530m. We have showed that the strains caused by injecting into the aquifer could be measured at a depth of 30m and used to evaluate the properties of the aquifer. We recently expanded the array of strainmeters at the North Avant Field by deploying three more instruments at shallow depth (30m) along with a deep instrument at 520m depth in the winter, 2021. The deep instrument is deployed in shale caprock slightly above the aquifer. To our knowledge, the deep strainmeter at the North Avant Field is the deepest strainmeter ever deployed and this required refining methods originally developed for shallow deployments. The instrument was lowered to depth on oil field tubing and cemented in place using techniques and materials developed for use in oil wells. Optical fiber used to communicate with the instrument was cemented in the annulus on the outside of tubing. This is significant because the techniques we used could readily be extended to greater depth, suggesting that strainmeters can be deployed over a wide range of depths for monitoring critical subsurface processes. For example, it suggests that strainmeters could be deployed through the caprock to monitor for leaks from underlying CO2 storage reservoirs. The strainmeter array at the North Avant Field has been used to characterize deformation during a series of injection tests in the spring and summer, 2021. All the new strainmeters respond to pumping, and the strainmeters we installed earlier also responded. To our knowledge, this is the first application of well testing in a deep aquifer that was monitored by an array of strainmeters—our earlier work used strainmeters at a single location. We are currently analyzing the strain data using an analytical solution, a proxy-based Bayesian inversion algorithm, and other methods. Strainmeter data has also been used to characterize periodic pumping tests by us and Riley Blais. A periodically varying pumping rate causes both hydraulic head and strain signals that vary with the same period as the pumping. The peaks and troughs of the head in monitoring wells lag behind the peaks and troughs of the head in the pumping well, and this lag time increases with distance from the pumping well. The lag time of the pressure and the distance to the monitoring well can be used in a simple analysis to estimate the hydraulic diffusivity of the aquifer. The lag time determined from strain data can be used to estimate aquifer properties using the same analysis that works for the pressure only for strain data measured at particular locations. That is because the strain field in a confining unit advances upward, laterally and then downward even though the pressure in the underlying aquifer only advances laterally, according to our recent simulations. We have field data showing that a small periodic signal superimposed on an injection rate at the North Avant Field will create a periodic strain signal at shallow strainmeters. The field data and the recent simulations suggest that including a periodic component to injection or pumping and then monitoring the resulting strain signal could be a way to monitor the subsurface.

Murdoch, Larry↗

DOE OSTI2025

Field Testing of PID-p Susceptible Bifacial PERC Modules: Impact of Light, Voltage and Module History

This work investigates the potential induced degradation-polarization (PID-p) of bifacial passivated emitter and rear contact (PERC) modules installed in the field at the Florida Solar Energy Center. 22 modules were stressed over 1 year under various voltage (-1500V, -3500, +1500V) and mounting configurations (close to ground, 2 meters from ground, close to roof). The positively stressed modules were anticipated to have experiences PID-p on their front side. However, no degradation was observed, as the light-induced recovery effect effectively counteracted the degradation. The negatively stressed modules experienced Pmax drops during 2 weeks before stabilizing at 5-6% loss. I-V and EL characteristics suggest a PID-p degradation on the rear side. Lower degradation rates are observed with lower voltage and when the mounting configuration allows more albedo light on the rear side to compensate for the degradation. PID-p is observed to stabilize at similar level for the voltage and mounting configuration tested with slightly lower Pmax in winter. EL imaging reveals that cells are not degrading at the same rate across a module. Some cells get darker and then brighter which corresponds to the silicon/passivation interface going through depletion and then inversion when enough positive charges are accumulated. After full light-recovery, the modules were tested again along with 22 brand-new ones to assess the impact of the module history. Results confirmed the trends observed in the first year with PID-p occurring at voltage as low as -600V and recovered modules degrading faster than brand-new ones.

14 SOLAR ENERGY↗

DOE OSTI2020

Predictive Inverse Model for Advective Heat Transfer in a Short–Circuited Fracture: Dimensional Analysis, Machine Learning, and Field Demonstration

Identifying fluid flow maldistribution in planar geometries is a well–established problem in subsurface science/engineering. Of particular importance to the thermal performance of enhanced (or “engineered”) geothermal systems is identifying the existence of nonuniform (i.e., heterogeneous) permeability and subsequently predicting advective heat transfer. Here, machine learning via a genetic algorithm (GA) identifies the spatial distribution of an unknown permeability field in a two–dimensional Hele–Shaw geometry (i.e., parallel plates). The inverse problem is solved by minimizing the L2 norm between simulated residence time distribution (RTD) and measurements of an inert tracer breakthrough curve (BTC) (C–Dot nanoparticle). Principal component analysis (PCA) of spatially correlated permeability fields enabled reduction of the parameter space by more than a factor of 10 and restricted the inverse search to reservoir–scale permeability variations. Thermal experiments and tracer tests conducted at the mesoscale Altona Field Laboratory (AFL) demonstrate that the method accurately predicts the effects of extreme flow channeling on heat transfer in a single bedding–plane rock fracture. However, this is only true when the permeability distributions provide adequate matches to both tracer RTD and frictional pressure loss. Without good agreement to frictional pressure loss, it is still possible to match a simulated RTD to measurements, but subsequent predictions of heat transfer are grossly inaccurate. Here, the results of this study suggest that it is possible to anticipate the thermal effects of flow maldistribution, but only if both simulated RTDs and frictional pressure loss between fluid inlets and outlets are in good agreement with measurements.

42 ENGINEERING↗

DOE OSTI2026

Four ppm measurement of the antihydrogen ground-state hyperfine splitting

The hydrogen atom is a touchstone for the foundations, evolution and frontiers of quantum theory. Key spectral lines of this atom have been determined to remarkable precision. Our research focuses on the study of antihydrogen, the antimatter counterpart of hydrogen. We test fundamental symmetries of nature (such as simultaneous charge conjugation, parity inversion, and time reversal or CPT symmetry) through precision comparisons of these atomic systems. Recent 1S–2S spectroscopic measurements on trapped antihydrogen have achieved relative precisions of parts per trillion. However, the ground-state hyperfine splitting, which is sensitive to the internal structure of the antiproton, has only been measured to 400 parts per million (ppm). Here we report a 4 ppm measurement of the antihydrogen ground-state hyperfine splitting energy a 1S , advancing the state-of-the-art precision by two orders of magnitude. From microwave spectroscopy experiments with roughly 24,000 anti-atoms, we determine ${a}_{1{\rm{S}}}/h=\mathrm{1,420,404.8}\pm 1.1(\mathrm{stat.})\pm 5.6\,(\mathrm{sys.})\,\text{kHz}$ in a 1-T magnetic field, consistent with expectations for hydrogen. At this level, our measurement is sensitive to the internal structure of the antiproton, which contributes at about 40 ppm and is approaching the limit of existing theoretical analyses. The gains we report are the product of marked advances in magnetic trap field control, stabilization and characterization; anti-atom spin-state manipulation; and improved antihydrogen accumulation rate.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2019

Flat-field VLS spectrometer for a wavelength range of 50 – 275 Å

A flat-field VLS spectrograph for a wavelength range ∼50 – 275 Å with an average linear dispersion of 0.18 mm Å{sup −1}, which makes use of a grazing-incidence varied line-space (VLS) grating, was calculated and implemented (a spectrograph of Harada class). To fabricate the VLS grating by interference lithography technique, an algorithm was developed for calculating the writing configuration with an auxiliary aberrating mirror (the solution of the inverse problem of interference lithography). The spectrograph was put to a test and line spectra were recorded from the laser-produced plasma of lithium fluoride and teflon targets, which were excited by a focused laser beam (0.5 J, 8 ns, 1.06 μm). A resolving power λ/d l = 800 was demonstrated in a wavelength region of 135 Å. (x-ray spectrometry)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

β -delayed neutron emission of Mn 64 , Cr 62 , and Fe 65

The β-decay properties of nuclei near the second nuclear “island of inversion” around neutron rich nuclei with neutron number 40 are important tests of nuclear structure models and interactions. In particular, the β-delayed neutron emission branch (Ρ n ), is useful for investigating β-strength and neutron-γ competition above the neutron separation energies of the daughter nuclei. We report new constraints for Ρ n values for three nuclei in the region: 62 Cr (Ρ n <1%), 64 Mn (Ρ n = 1.5⁢(6)%), and 65 Fe (Ρ n < 1%), measured with the Neutron Emission Ratio Observer (NERO) neutron long counter system and the Beta Counting Station (BCS) at the National Superconducting Cyclotron Laboratory (NSCL). Our results resolve the large discrepancy between previous direct and indirect measurements for 64 Mn and confirm the predictions of global theoretical models when a statistical treatment of the γ and neutron decays of the daughter states is included. Here we also obtain improved half-lives for 62 Cr [206(5) ms] and the short-lived isomer in the 62 Fe daughter [112(7) ms] from β-delayed γ emission data obtained in the same experiment with the Summing NaI (SuN) total absorption spectrometer. Finally, we use γ emission data to obtain a new upper limit for the 62 Cr β-decay population of the long-lived isomeric state in 62 Mn.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

An extended trajectory-mechanics approach for calculating the path of a pressure transient: travel-time tomography

The application of a technique from quantum dynamics to the governing equation for hydraulic head leads to a trajectory-based solution that is valid for a general porous medium. The semi-analytic expressions for propagation path and velocity of a change in hydraulic head form the basis of a travel-time tomographic imaging algorithm. An application of the imaging algorithm to synthetic arrival times reveals that a cross-well inversion based upon the extended trajectories correctly reproduces the magnitude of a reference model, improving upon an existing asymptotic approach. An inversion of hydraulic head arrival times from cross-well slug tests at the Widen field site in northern Switzerland captures a general decrease in permeability with depth, which is in agreement with previous studies, but also indicates the presence of a high-permeability feature in the upper portion of the cross-well plane.

58 GEOSCIENCES↗

DOE OSTI2026

Experiments towards a neutron target for measurements in inverse kinematics

Neutron-induced reactions play an important role in fundamental nuclear physics, nuclear astrophysics, and applications. In the case of reactions on rare isotopes, there are limited options for direct experimental measurements. The Neutron Target Demonstrator project at Los Alamos National Laboratory seeks to test the feasibility of moderating spallation neutrons within a 1 m 3 graphite cube to create a standing neutron target for neutron-induced reaction measurements in inverse kinematics. This paper presents the results of experimental neutron flux distribution tests using neutron sources (ranging from 1 keV to 50 MeV) created by accelerators at the University of Notre Dame and Texas A&M University. Measurements were made with both the full graphite cube as well as a ”half cube” setup in which half of the graphite cube was removed. The measured distributions agree with simulated distributions in the case of the full cube moderator, although there remain discrepancies in certain cases for the half cube moderator. The results shown here will provide useful information for an upcoming experimental campaign to test the neutron target proof-of-principle.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Ultrasonic measurement of temperature distributions in extreme environments: Electrical power plants testing in utility-scale steam generators

Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.

42 ENGINEERING↗

DOE OSTI2021

Application of Markov Chain Monte Carlo Methods for Uncertainty Quantification in Inverse Transport Problems

Determination of the components of a radioactive source/shield system using the system’s radiation signature is of great importance in homeland security, material safeguards, and waste management. Although significant progress has been made toward solving this inverse transport problem in recent years, work remains to be done to quantify the uncertainty in reconstructed results. In this article we apply two Markov chain Monte Carlo (MCMC) approaches, the delayed rejection adaptive metropolis (DRAM) and differential evolution adaptive metropolis (DREAM) methods, to solve inverse problems and quantify uncertainty. The DRAM method uses delayed rejection combined with global adaptation of the proposal covariance matrix. Furthermore, the DREAM method hybridizes MCMC sampling with the differential evolution (DE) algorithm. In numerical test cases, the DRAM and DREAM methods are shown to be superior to a first-order inverse Hessian approach for problems with noisy data and multiple unknown quantities, with DREAM converging to the posterior distribution more quickly than DRAM. The DREAM and DRAM results indicate that a full posterior distribution is required to quantify uncertainty in many inverse transport problems.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2020

Reflections on the anomalous ANITA events: the Antarctic subsurface as a possible explanation

The Antarctic Impulsive Transient Antenna (ANITA) balloon experiment was designed to detect radio signals initiated by high-energy neutrinos and cosmic ray (CR) air showers. These signals are typically discriminated by the polarization and phase inversions of the radio signal. The reflected signal from CRs suffer phase inversion compared to a direct ‘tau neutrino’ event. In this paper, we study subsurface reflection, which can occur without phase inversion, in the context of the two anomalous up-going events reported by ANITA. It is found that subsurface layers and firn density inversions may plausibly account for the events, while ice fabric layers and wind ablation crusts could also play a role. This hypothesis can be tested with radar surveying of the Antarctic region in the vicinity of the anomalous ANITA events. Future experiments should not use phase inversion as a sole criterion to discriminate between down-going and up-going events, unless the subsurface reflection properties are well understood.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Correcting for digital image correlation speckle inversion at high temperature using color cameras

Digital image correlation (DIC) is a popular, noncontacting technique to measure full-field deformation by using cameras to track the motion of an applied surface pattern. Because it is noncontacting, DIC can be performed for extreme temperature applications (e.g., hot-fire rocket testing of carbon composite rocket nozzles) under harsh conditions during which bonded gauges are damaged. Speckle pattern inversion is a phenomenon that sometimes occurs while performing high-temperature DIC. During speckle pattern inversion, portions of the surface pattern that were initially darker at room temperature (e.g., graphite) may emit more light due to blackbody radiation than the portions that were initially paler, thereby producing images in which the pattern appears inverted at high temperature relative to the initial pattern at room temperature. This phenomenon can prevent the correlation algorithm from being able to resolve the displacements between images. This work compares three methods to mitigate speckle pattern inversion: (A) the subtraction method, a recently-published technique in which two high-temperature images are subtracted to remove unwanted light; (B) the filtering method, a popular technique in which optical bandpass filters screen out unwanted light; and (C) the histogram rescaling method, a proposed new method that pairs a color camera with a blue light source and uses information from the green sensor of the camera to correct against inversion in the blue sensor through postprocessing. The histogram rescaling method is shown to successfully eliminate speckle pattern inversion and has the added advantages that it does not require quasi-static loading to be able to compensate for speckle pattern inversion, nor does it impose thick-glass distortions caused by the optical filter.

Rowley, Lindsey J.↗