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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Possible Observation of Sigma-nn Continuum Structures and A Bound Sigma-NN State Using the (e, e 'K+) Reaction

The E12-17-003 (e, e'K+) experiment was carried out in the experimental Hall A facility of Jefferson Lab in November 2018. The experiment aimed at providing the experimental data for the unknown Lambda-n interaction by measuring the bound state or the resonance state as indicated by the HypHI experiment. The so obtained Lambda-n interaction was assumed to solve the existing charge symmetry breaking problem in the case of Lambda-N interaction. The experiment used Hall A high resolution spectrometers (both left and right spectrometers) positioned symmetrically at constant angle 13.2 deg. each. A 25 cm long aluminum cylinder filled with H-3 gas was used as a production target. The major calibration data were taken with the H target contained in an identical aluminum cylinder. The electroproduction of Lambda and Sigma^0 via p(e, e'K+)Lambda, Sigma^0 reactions was used to calibrate the absolute energy scale with the known masses of the Lambda and Sigma^0. Then by using the (e, e'K+) Sigma-reaction, two possible Lambda-nn resonance states and one NN bound state were observed. The observed states have the energy resolution about 1.6 MeV (FWHM), however, great r statistics are required to solidly confirm the observed states. The A = 3 and 4 Sigma bound states have been predicted long ago but only the A = 4 Sigma hypernucleus, that is He-4/Sigma, was found in the (K-, pi-) reaction. A careful Monte Carlo study was conducted to study the A (nuclear mass number) dependence on the missing mass resolution by using the identical experimental conditions. The simulated and experimentally obtained Lambda and Sigma^0 channels agreed within 100 keV in sigma, where sigma is the standard deviation. The intrinsic missing mass resolution of A = 3 (3/Lambda-n) resonance was predicted about sigma = 0.67 MeV with a natural width of about 0.6 MeV. However, due to the low statistics the precision does not permit sufficient constrain on the determination of the Lambda-n interaction. The reason of having such low statistics is due to the use of unoptimized Hall A system which was definitely feasible but not ideal for this experiment. In addition, the cross section was found to be much smaller than expected.

Pandey, Bishnu↗
DOE OSTI2024

Optimization and Experimental Validation of Annular Finned PCM-HX for a Domestic Hot Water Heater Application

The load profile for domestic water heating is time-dependent and can result in high energy demand during peak operating times. Shifting this peak load can have significant environmental and economic impacts. Phase change material (PCM)-based thermal energy storage (TES) is a potentially useful technology for peak load shifting in domestic hot water (DHW) applications thanks to its high latent heat and energy density. In this study, an annular finned-tube PCM-HX design concept was optimized for a load-shifting TES unit to meet the Department of Energy standard for a medium-usage DHW heater using a resistance-capacitance model (RCM) integrated with a Multi-Objective Genetic Algorithm. The optimized design comprised 70 identical annular finned-tube PCM-HX units connected in parallel and utilizing RT62HC as the PCM. A single PCM-HX unit was prototyped and tested in a vertically oriented setup with upward heat transfer fluid (HTF) flow. The hot water supply time was defined based on a cutoff temperature of 51.7°C. The as-designed mass flow rate (1.5 g/s) was tested to assess the performance of the prototyped PCM-HX unit for RCM validation. For the experimental investigation, RTD sensor bundles measured HTF temperature at the PCM-HX inlet and outlet, and a Coriolis flow meter accurately measured the HTF mass flow rate. The simulated discharging power underpredicted the experimental result by about 12%, and the simulated hot water supply time underpredicted the experimental result by approximately 13% for the as-designed mass flow rate (1.5 g/s). The average deviation of the hot water supply temperature between the experimental and RCM results during the complete PCM solidification process was 1.3 K for the as-designed mass flow rate. The overall good agreement between the experimental and RCM results provides confidence that computationally efficient models such as RCM can be utilized for design optimization of PCM-HXs.

42 ENGINEERING↗
DOE OSTI2021

Machine Learning Driven Contouring of High-Frequency Four-Dimensional Cardiac Ultrasound Data

Automatic boundary detection of 4D ultrasound (4DUS) cardiac data is a promising yet challenging application at the intersection of machine learning and medicine. Using recently developed murine 4DUS cardiac imaging data, we demonstrate here a set of three machine learning models that predict left ventricular wall kinematics along both the endo- and epi-cardial boundaries. Each model is fundamentally built on three key features: (1) the projection of raw US data to a lower dimensional subspace, (2) a smoothing spline basis across time, and (3) a strategic parameterization of the left ventricular boundaries. Model 1 is constructed such that boundary predictions are based on individual short-axis images, regardless of their relative position in the ventricle. Model 2 simultaneously incorporates parallel short-axis image data into their predictions. Model 3 builds on the multi-slice approach of model 2, but assists predictions with a single ground-truth position at end-diastole. To assess the performance of each model, Monte Carlo cross validation was used to assess the performance of each model on unseen data. For predicting the radial distance of the endocardium, models 1, 2, and 3 yielded average R2 values of 0.41, 0.49, and 0.71, respectively. Monte Carlo simulations of the endocardial wall showed significantly closer predictions when using model 2 versus model 1 at a rate of 48.67%, and using model 3 versus model 2 at a rate of 83.50%. These finding suggest that a machine learning approach where multi-slice data are simultaneously used as input and predictions are aided by a single user input yields the most robust performance. Subsequently, we explore the how metrics of cardiac kinematics compare between ground-truth contours and predicted boundaries. We observed negligible deviations from ground-truth when using predicted boundaries alone, except in the case of early diastolic strain rate, providing confidence for the use of such machine learning models for rapid and reliable assessments of murine cardiac function. To our knowledge, this is the first application of machine learning to murine left ventricular 4DUS data. Future work will be needed to strengthen both model performance and applicability to different cardiac disease models.

4D ultrasound↗
DOE OSTI2020

A deep insight on the coal ash-to-slag transformation behavior during the entrained flow gasification process

Recent research provided deep insight on the coal ash-to-slag transformation characterization during the entrained flow gasification process, with experimentation on a 40 kg/hr (dry basis) coal-fed opposed multi-burner (OMB) entrained flow gasifier and simulation via FactSage™ software. A general mechanism is presented to relate the gasifier design temperature, ash fluid temperature, and operating temperature with the degree of the slag polymerization. The change of the high temperature zone, the corresponding particle residence time in the high temperature zone, and syngas composition have obvious effects on the slag mineral transformation behavior. Mineral types formed on the wall of the gasifier chamber were mainly anorthite (CaAl 2 Si 2 O 8 ), aluminum oxide (Al 2 O 3 ), and calcium sulfide (CaS). These minerals transformed to anorthite and diopside (CaMgSi 2 O 6 ) at the slag hole zone, while the minerals at the lock hopper were anorthite, orthoclase (KAlSi 3 O 8 ), quartz (SiO 2 ), gypsum (CaSO 4 ), calcite (CaCO 3 ), and halite (NaCl). FactSage™ predicted minerals as anorthite, diopside, orthoclase, and albite (NaAlSi 3 O 8 ), etc., where the slag temperature was below the ash fluid temperature and when the ratios of CO/CO 2 and (CO + H 2 )/CO 2 were lower than 1.0 and 2.0, respectively. By simulation, residual carbon was found to be the dominant factor over syngas composition to cause mineral transformation, and this was verified experimentally. The Ca-based crystals, typically anorthite, was shifted to diopside, near the slag hole zone, and a linear relationship was found between the content ratios of diopside/(anorthite + diopside), CaO/SiO 2 , and (CaO + MgO)/SiO 2 . A dimensionless number, θ, was defined to characterize the changing chemical composition and the degree of slag polymerization, with temperature deviation from the design condition. Three zones of θ were identified and related to the deviation between the actual gasification condition from the design condition. Finally, a low slag polymerization degree corresponded with a higher temperature deviation between the actual condition and design condition, and this proved that increased residual carbon content and changing iron valence state increased the mineral types when the slag temperature was below the ash fluid temperature.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

An asymmetric electron-scattering photosphere around optical tidal disruption events

We report a star crossing the tidal radius of a supermassive black hole will be spectacularly ripped apart with an accompanying burst of radiation. A few tens of such tidal disruption events have now been identified in optical wavelengths, but the exact origin of the strong optical emission remains inconclusive. Here we report polarimetric observations of three tidal disruption events. The continuum polarization appears independent of wavelength, while emission lines are partially depolarized. These signatures are consistent with photons being scattered and polarized in an envelope of free electrons. An almost axisymmetric photosphere viewed from different angles is in broad agreement with the data, but there is also evidence for deviations from axial symmetry before the peak of the flare and significant time evolution at early times, compatible with the rapid formation of an accretion disk. By combining a super-Eddington accretion model with a radiative transfer code, we simulate the polarization degree as a function of disk mass and viewing angle and we show that the predicted levels are compatible with the observations for extended reprocessing envelopes of ~1,000 gravitational radii. Spectropolarimetry therefore constitutes a new observational test for tidal disruption event models, and opens an important new line of exploration in the study of tidal disruption events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Improved Cumulative Fission Yield Measurements with Fission Spectrum Neutrons on 238U

Two isotopically-characterized targets of high-purity (99.961±0.002%) 238U metal and a neutron dosimetry package were exposed to a pulsed neutron irradiation using the Godiva IV critical assembly at the National Criticality Experiments Research Center to measure the integral fission product yields produced in a Watt fission neutron-energy spectrum. Following irradiation, the fissioned targets were counted with two broad energy germanium detectors. Estimates of the total fissions for each target were made using measurements of well-known fission products. The total number of fissions in each target were then used to measure the fission yields of 33 fission products, 18 of which are published as new measurements. Twelve of the 18 isotopes were in agreement with ENDF/B- VIII.0 using the zeta test and treating ENDF/B-VIII.0 as the true mean: 84mBr, 93Y, 94Y, 104Tc, 134I, 135I, 138Xe, 141Ba, 142Ba, 142La, 146Ce, and 149Nd. The ENDF/B-VIII.0 fission yield for 139Ba was only slightly outside of 1-s relative to the uncertainty measured in this work. Uncertainties for 5 fission product yields were markedly improved over those reported in ENDF/B-VIII.0: 128Sn, 129Sb, 130gSb, 131mTe, and 133I. The fission yields measured for 128Sn, 131mTe, and 133I were in good agreement with the ENDF/B-VIII.0 predicted fission yields. However, fission yields measurements of the isotopes 129Sb, and 130gSb deviated from the ENDF/B-VIII.0 value. Both of these isotopes reside near the doubly magic nuclear shell closures of 50 protons and 82 neutrons. These fission yields may be suppressed because of the odd-odd nuclear structure of 130gSb and the odd-even structure of 129Sb and isomer splitting. Comparisons to other recent work and a brief review with citations are included to support this conclusion.

Fission Yields↗
DOE OSTI2020

Longitudinal coherence and short-term wind speed prediction based on a nacelle-mounted Doppler lidar

The spatial structure of turbulence in atmospheric boundary layer flows is highly relevant to wind energy. In particular, wind turbine control strategies based on inflow preview measurements require knowledge of the longitudinal evolution of turbulent flow as it approaches the rotor. These upstream measurements are usually obtained with nacelle-mounted wind lidars. In contrast to traditional in situ anemometry, lidars collect measurements within a probe volume which varies in size depending on the technology of the commercial system being used. Here, we address two issues related to the use of wind lidar to measure the incoming flow to a wind turbine: (i) whether existing longitudinal coherence models can be used to predict flow at the rotor, based on measurements performed at a distance away from the rotor; and (ii) what effect probe-volume averaging has on the inflow predictions. These two questions are critical to the design and implementation of robust wind turbine control strategies. To address these questions, we perform field measurements and large-eddy simulations to determine which incoming flow structures can be readily predicted with existing coherence models, and which require additional corrections to account for lidar volumetric averaging effects. Results reveal that the wind turbine induction zone has a negligible impact on the longitudinal coherence and first-order turbulence quantities, such as the standard deviation of velocity fluctuations. However, the phase of the signal, from which advection time periods of the turbulent structures are derived, is affected by the rotor blockage effect.

17 WIND ENERGY↗
DOE OSTI2020

Photo response of 164 Dy

Background: Little data is available for the pygmy dipole resonance (PDR) in axially deformed nuclei. Photon-scattering experiments are complicated by high level densities in the PDR region and the small energy difference of transitions to the ground state and to excited states. Purpose: In this work, we report on an experimental study of the low-energy dipole strength distribution of the well-deformed nucleus 164 Dy between 4.0–7.7 MeV. Methods: The low-lying photoresponse of 164 Dy has been investigated using the method of nuclear resonance fluorescence using a quasimonochromatic linearly polarized $\textit{γ}$-ray beam in the energy range of 4.0–7.7 MeV in steps of 0.2 MeV. Results: For excitation energies between 4 MeV and 5 MeV, sufficiently low level densities allow for the identification of individual states, including level energies, reduced transition widths and branching ratios. Energy-averaged mean decay branching ratios, mean population ratios and partial absorption cross sections were determined above 5 MeV up to the neutron-separation threshold at 7.7 MeV. A Lorentzian-shaped enhancement of the partial photo absorption cross section followed by decays back to the ground-state band is found at 6.10(5) MeV with a width of 0.77(23) MeV. A comparison with results from complementary measurements is performed using the framework of the statistical model. Conclusions: The experimental results for the mean population ratios deviate systematically from the statistical model simulation by 30(6)%. However, they are in agreement within one standard deviation of the simulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP): Quantifying Uncertainties in Atmospheric River Climatology

Atmospheric rivers (ARs) are now widely known for their association with high-impact weather events and long-term water supply in many regions. Researchers within the scientific community have developed numerous methods to identify and track of ARs—a necessary step for analyses on gridded data sets, and objective attribution of impacts to ARs. These different methods have been developed to answer specific research questions and hence use different criteria (e.g., geometry, threshold values of key variables, and time dependence). Furthermore, these methods are often employed using different reanalysis data sets, time periods, and regions of interest. The goal of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is to understand and quantify uncertainties in AR science that arise due to differences in these methods. This paper presents results for key AR-related metrics based on 20+ different AR identification and tracking methods applied to Modern-Era Retrospective Analysis for Research and Applications Version 2 reanalysis data from January 1980 through June 2017. We show that AR frequency, duration, and seasonality exhibit a wide range of results, while the meridional distribution of these metrics along selected coastal (but not interior) transects are quite similar across methods. Furthermore, methods are grouped into criteria-based clusters, within which the range of results is reduced. AR case studies and an evaluation of individual method deviation from an all-method mean highlight advantages/disadvantages of certain approaches. For example, methods with less (more) restrictive criteria identify more (less) ARs and AR-related impacts. Finally, this paper concludes with a discussion and recommendations for those conducting AR-related research to consider.

Rutz, Jonathan J.↗
DOE OSTI2020

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗
DOE OSTI2022

Development of a water source heat pump hardware-in-the-loop (HIL) testing facility for smart building applications

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while maintaining the thermal comfort of building occupants. As the pivotalpoint between building electricity consumption and indoor thermal comfort, high-efficiency electrical heatpumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on the heatpump operation andperformance under different weather, building load, and grid requests calls for investigation and verification via experimental tests with actual heat pumps integrated with real-time building and grid responses. This study presents a Water-Source Heat Pump Hardware-in-The-Loop (HIL) Test Facility developed with the capability to perform such tests. The hardware configuration for this testfacility introduces a hydronic system that emulates the conditions for the heat pump water-side, and a duct system that emulates conditions for the heat pump airside. Both data acquisition and emulator control are implemented through the National Instruments (NI) LabVIEW software running on an NI PXIplatform. The HIL mechanism based on the hardware-software integration that allows the testbed to communicate with a generic simulation environment is also discussed. Currently, the test facility setup includes a single heatpump and virtual building model in EnergyPlus coupled with an occupant behavioral model in MATLAB. Preliminary test results of the current setup demonstrate the building load emulator's ability to track the simulated gone temperature with a Root Mean Square Deviation (RSME) below 0.12°C (0.216°F). An uncertainty analysis based on sensor accuracies shows that the heat pump coefficient of performance (COP) can be measured with a relative uncertainty of 10.4% in cooling and 3.7% in heating. Apartfrom the current testing on a single heat pump, the test facility also provides the flexibility to include additional heat pumps to form a heat pump cluster, as well as coupling the heat pump with active thermal storage to provide enhanced demandflexibility.

Calfa, Caleb↗
DOE OSTI2023

A Multi-Objective Bayesian Optimized Human Assessed Multi-Target Generated Spectral Recommender System for Rapid Pareto Discoveries of Material Properties

Optimization for different tasks like material characterization, synthesis, and functional properties for desired applications over multi-dimensional control parameter and function spaces need a rapid strategic search through active learning. However, in all cases prior to optimization, the target material properties are assumed known and fixed, which mostly deviates from real-world scenarios in material synthesis. This can be critical for running expensive experiments on new materials, when the experimental results are fuzzy for any scientific outcomes due to improper target setting, ultimately wasting time and cost. The failure rate and cost are even higher over exploring on multi-target space, where we want to learn the pareto among multiple properties, to jointly optimize during material synthesis for desired applications. To address the challenge, here we introduce the human-operator attempt flexibility in the active learning based automated experiment framework, with generating multiple human assessed targets through a voting-based recommender system during real-time microscope measurements over the large material image space, sequentially learn/update multiple desired targets through a weighting system, and adaptively search in multiple material properties functional space for non-dominated pareto discoveries to maximize the custom structural similarity based acquisition function. We term this a multi-objective Bayesian optimized human assessed multi-target generated spectral recommender systems (MOBO-HAM-SRS). The approach has been demonstrated to peizoresponse force spectroscopy of a ferroelectric thin film, exploring with different kernels and acquisition functions. This work shows an advancement towards human-AI collaborated automated experiments, steering optimization trajectories through human overpowering AI at the early stage when uncertainty is high and AI overpowering human at the later stage with rapid exploration towards optimal goal, following human-assessed multiple targets properties.

Biswas, Arpan↗
DOE OSTI2026

ZTF-SEDm Type Ia supernova sample for Twins Embedding spectrophotometric standardization

Aims. This paper has two aims: the first aim is to build a large homogeneous spectrophotometric sample of Type Ia supernovae (SNe Ia) from the second data release of the Zwicky Transient Facility (ZTF DR2). We used the spectrum sample from the low-resolution ( R ∼ 100) SEDmachine (SEDm) Integral Field Spectrograph (IFS) that gathered 3069 spectra. This is one of the largest samples of such collections that can attempt to reproduce the Twins Embedding (TE) spectrophotometric standardization method. This is our second objective. The method was developed based on high-quality spectra from 200 SNe Ia of the Nearby Supernova factory (SNfactory) and led to an exceptionally low value of 0.073 mag for the intrinsic scatter. Methods. As the SEDm is not designed as a spectrophotometric instrument, we first improved the flux-calibration accuracy of the SN Ia spectrum sample using the ZTF photometric data, which were calibrated at the percent level. We corrected the spectra for second-order polynomials, fitted by comparing the synthetic photometry in the ZTF g , r , i filters with the light-curve (LC) data. We then applied the three steps of the TE parameterization to a subset of 783 ZTF SN spectra near maximum light while comparing results from SNfactory and ZTF. We finally analyzed the standardization methods based on the TE parameters. Results. The precision of the phase-correction model, which is the first step of the TE, is estimated at 0.01 mag in g band based on ZTF data. Despite the challenge posed by the spectrum-extraction pipeline associated with the SEDm (flux calibration, leftover host signal, low signal-to-noise ratio, and low resolution), we applied a first standardization in color based on the second step of the TE, called read between the lines (RBTL), to the ZTF sample. We reached a Hubble residual scatter of 0.153 mag, all in normalized median absolute deviation, which is to be compared to the ∼0.11 mag obtained with the SNfactory data. The SALT color and stretch standardization reaches a scatter of 0.164 mag for the same ZTF SN Ia sample, and its host steps are ∼0.1 mag and zero for RBTL. When considering the scatter due to the redshift error and flux calibration error, we estimated a RBTL scatter of ∼0.129 mag for this ZTF sample as an upper limit because we identified an additional contribution from a systematic error in color. We tested the standardization based on the nonlinear TE parameters, and, as expected from the low spectrum quality, it did not improve the overall dispersion. Conclusions. We release 1897 flux calibrated spectra of 1607 SNe Ia with an estimated photometric accuracy of 0.07 mag. We further demonstrate that some amount of spectrophotometric SN Ia standardization can be done with limited-quality spectra. The RBTL standardization is more efficient than that of SALT with one parameter less, and the resulting host steps are consistent with zero. This makes it less prone to astrophysical bias. For future spectroscopic surveys, targeting the extraction pipeline for a thorough flux calibration and good signal-to-noise ratio would enable us to compute the full TE standardization, which would further reduce the scatter in the distance estimate.

Ganot, C↗
DOE OSTI2024

Modifying the Asynchronous Jacobi Method for Data Corruption Resilience

Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing environments can operate on data in situ, offering enticing benefits over data aggregation to HPC and CC facilities that include avoiding costs of transmission, increased data privacy, and real-time data analysis. Because of the inherent unreliability of edge computing environments, new fault-tolerant approaches must be developed before the benefits of edge computing can be realized. Motivated by algorithm-based fault tolerance, a variant of the asynchronous Jacobi (ASJ) method is developed that achieves resilience to data corruption by rejecting solution approximations from neighbor devices according to a bound derived from convergence theory. Numerical results on a two-dimensional Poisson problem show that the new rejection criterion, along with a novel approximation to the shortest path length on which the criterion depends, restores convergence for the ASJ variant in the presence of certain types data corruption. Numerical results are obtained for when the singular values in the analytic bound are approximated. Additional linear systems are also explored, one with a more dense sparsity pattern and one that includes advection. All results indicate that successful resilience to data corruption depends on whether the bound tightens fast enough to reject corrupted data before the iteration evolution deviates significantly from that predicted by the convergence theory defining the bound. This observation generalizes to future work on algorithm-based fault tolerance for other asynchronous algorithms, including upcoming approaches that leverage Krylov subspaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

3D Deep Learning Joint Inversion of Active Seismic Full Waveform and Passive Seismic Traveltime Data for Reservoir Imaging and Uncertainty Quantification

Here, we present deep learning (DL) networks for three-dimensional (3D) joint inversion of active seismic full waveform and passive seismic traveltime data to image reservoirs and their properties and quantify imaging uncertainties. Active seismic full-waveform data can provide high-resolution monitoring images but are collected only intermittently because of their high acquisition cost. In contrast, passive seismic data can be gathered at relatively low cost between regular active surveys, although their imaging quality can be compromised by factors such as low signal-to-noise ratios and limited ray coverage of the target. Although these datasets are routinely acquired together at CO 2 storage sites, their combined inversion within a 3D DL framework has not been previously demonstrated. To our knowledge, this is the first study to address this gap, combining the strength of both data types. For efficient data storage and DL training with large 3D seismic datasets, we use a 3D data matrix in which a random number of passive seismic traveltime data are stored as parabolic envelopes using one-hot encoding and a 3D full-waveform data matrix in which multiple shot gathers are summed. Two network architectures are evaluated: a single-encoder U-Net for single-data type inversion and a dual-encoder U-Net for joint inversion of active and passive seismic data. We also evaluate the single-encoder U-Net for joint inversion by concatenating full-waveform data and traveltime data. We propose a systematic approach for selecting an optimal dropout rate that balances regularization during training and Monte Carlo dropout-based uncertainty quantification during prediction by examining the correlation coefficient between standard deviation and prediction error, along with the training misfit, across a range of dropout rates. 3D DL inversion experiments include five different network configurations, with evaluations under ideal, noisy and dropout-enabled conditions. Both model and data uncertainties are assessed, as well as their combined effects. Across all conditions, the networks consistently predict accurate CO 2 saturation models with low prediction errors, such as a structural similarity index of 0.993 and CO 2 difference of 1.1%. Uncertainty estimates show strong spatial correlation with prediction errors, confirming the effectiveness of the proposed dropout selection approach. The results demonstrate that our DL approach, utilizing compact data representations and appropriate uncertainty quantification, yields accurate subsurface images under various inversion conditions and provides valuable insights into the reliability of predictions.

Um, Evan Schankee [Lawrence Berkeley National Labo↗
DOE OSTI2021

Analysis of the EMCCD point-source response using x-rays

Electron Multiplying Charge Coupled Devices, EMCCD are used as x-ray detectors. The NSLS-II Soft Inelastic x-ray Scattering (SIX) beam line has two EMCCDs for x-ray detection in the spectrometer arm. The spectrometer with high resolving power disperses x-rays vertically. The x-ray vertical position on the sensor plane is related to its energy. This allows for very accurate x-ray energy measurements through x-ray coordinates. X-rays interact with silicon and create a number of electron-hole pairs proportional to the x-ray energy. Electrons drift and diffuse toward pixel gates and are collected there. The diffused electrons form a charge cloud distributed over several neighboring pixels. This charge sharing enables coordinate measurements with accuracy better than the pixel pitch. The charge distribution shape has to be taken into account to achieve ultimate accuracy in coordinate measurements. In this paper, we present a method of the charge distribution shape analysis and demonstrate its applications. The drift and diffusion of electrons ftom the point of generation to pixel gates results in the bell-shaped electron cloud usually approximated by Gaussian shape. The number of electrons collected under a pixel is proportional to the shape function integral. These electron packets get transferred to the sense node of the output amplifier. The transfer process could introduce distortions to the original charge distribution. For example, during transfers, electrons in the packet could be exposed to traps if they are present in the sensor. The trapping and later the release processes distort the apparent shape of the charge distribution. Therefore, deviations of the charge distribution shape ftom the originally symmetrical form can indicate the presence of trap centers in the sensor and can be used for sensor diagnostics.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Anisotropic neutron response of trans-stilbene and impact on a handheld dual particle imager

Here this manuscript details measurements of the anisotropic light-output response of trans-stilbene, henceforth referred to as stilbene, along the three primary crystal planes and analyzes how this anisotropic response impacts neutron image reconstruction in a handheld dual particle imager (H2DPI). A prototype H2DPI composed of stilbene pillars (6 x 6 x 50 mm 3 ) coupled to silicon photomultipliers was built and is capable of imaging both fast neutrons and gamma rays from kilogram quantities of special nuclear material. Stilbene was chosen as the scintillating medium for the imager because of its pulse shape discrimination capability, time resolution and relatively high light output. A drawback to using stilbene, however, is the anisotropic response. A recoiling proton from a neutron elastic-scattering event in stilbene will yield different amounts of scintillation light depending on the direction of the recoiling proton with respect to the crystal lattice. This manuscript analyzes how this anisotropic response impacts neutron image reconstruction in 4π. The light output in the three primary crystal planes of stilbene were independently measured 6–7 times for proton recoil energies ranging from 0.5–5.0 MeV using a quasi-monoenergetic time-of-flight neutron source. The measured light-output data in the three crystal planes were fit with a semi-empirical function based on Birks’ formula. These fits were used to reconstruct the location of a 252 Cf source in front of the imager (0°, -0.8°), to the left of the imager (-90°, -0.8°) and directly above the imager (0°, 90°) to determine if it is necessary to apply the directionally-dependent response of stilbene to accurately reconstruct source locations. A bootstrapping technique was applied to the measured data sets to produce 1000 images composed of 2000 cone projections for each source location and each measured light-output curve. List-mode maximum likelihood expectation maximization was applied to each image; the highest pixel location and the full width at half maximum (FWHM) were then recorded. The average and standard deviations of these parameters were taken for each set of images. The maximum difference in the average azimuthal pixel location when varying between the appropriate and incorrect light-output curves for the source locations at (0°, -0.8°) and (-90°, -0.8°) were respectively found to be 1.85 ± 1.39° and 2.03 ± 1.78°. All other pixel locations and FWHMs were within a single standard deviation of uncertainty. Taken together, the anisotropic response of stilbene has negligible impact on the neutron image reconstruction capability of the H2DPI.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Primary $\gamma$-ray intensities and $\gamma$-strength functions from discrete two-step $\gamma$-ray cascades in radiative proton-capture experiments

Background: Reaction rates of radiative capture reactions can play a crucial role in the nucleosynthesis of heavy nuclei in explosive stellar environments. These reaction rates depend strongly on $\gamma$-ray decay widths in the reaction products, which are, for nonresonant capture reactions at high excitation energies, derived from the $\gamma$-ray strength function and the nuclear level density. Recently, the ratio method was applied to primary $\gamma$ rays observed from ($\textit{d, p}$) reactions and nuclear resonance fluorescence measurements to extract the dipole strength in atomic nuclei and to test the generalized Brink-Axel hypothesis. Purpose: The purpose of this work is to apply the ratio method to primary $\gamma$-ray intensities of the 63,65 Cu($\textit{p},\gamma$) reactions to extract $\gamma$-ray strength information on the nuclei 64,66 Zn. Here, the impact of spin distribution, total $\gamma$-ray decay widths, level densities, and width fluctuations on the application of the ratio method will be discussed. Additionally, by comparing the relative $\gamma$-ray strength at different excitation energies, conclusions on the validity of the generalized Brink-Axel hypothesis can be made. Method: The radiative proton capture reaction measurements have been performed at the HORUS $\gamma$-ray spectrometer of the University of Cologne at one excitation energy for each reaction. Primary $\gamma$-ray intensities have been determined by normalizing secondary $\gamma$-ray transitions in two-step cascades using their absolute branching ratio. The ratio method was applied to the measured primary $\gamma$-ray intensities as well as to previous measurements by Erlandsson et al. at different excitation energies. Results: The relative strength function curve for 64 Zn from our measurement shows no significant deviation from the previous measurement at a different excitation energy. The same is true for 66 Zn where both measurements were at almost the same excitation energy. Absolute $\gamma$-strength function values have been obtained by normalizing the relative curves to quasiparticle random phase approximation calculations because of the absence of experimental data in the respective energy region. Conclusion: The generalized Brink-Axel hypothesis, i.e., the independence of the strength function on the excitation energy, seems to hold in the studied energy region and nuclei. The method to obtain primary $\gamma$-ray intensities from two-step cascade spectra was shown to be a valuable and sensitive tool although its uncertainties are connected to the knowledge of the low-energy level scheme of the investigated nucleus. The scaling in the ratio method should be taken with care, because the relative strength is not a simple sum of $f_{E1}$ and $f_{M1}$ but a somewhat complex linear combination dependent on the excitation energy of the nucleus.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗