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84 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

Safta, Cosmin [Sandia National Laboratories (SNL-C↗
DOE OSTI2021

Deployment of salt sample extraction system at an engineering-scale electrorefiner

The goal of the salt sampling program at Argonne is to develop and deploy automated molten salt sampling approaches for interfacing relevant unit operations with salt analysis to improve the timeliness of sampling-based accountancy measurements. Two technologies under development in support of this goal are a vacuum sampling loop module and a high-throughput pneumatic sample generator module. Compared to traditional point sampling approaches (i.e., dip probes), the vacuum sampling loop facilitates the collection of a larger cross-section of the bulk salt in order to collect more representative samples. The vacuum sampling approach also eliminates the risk of dross contamination of samples and avoids the use of moving parts in the salt. The pneumatic sample generator module is used to facilitate high-throughput sample analysis to improve the measurement precision of any given analytical technique by averaging out random sampling and measurement errors. In FY21, two methods for integrating these two modules were tested including direct fluidic coupling and coupling using a solid salt transfer mechanism. Solid salt transfer was ultimately selected over fluidic coupling, primarily to enable the transport of samples over longer distances to support automated at-line integration with high-precision techniques (such as microcalorimetry) that cannot withstand the conditions near an electrorefining process. To facilitate rapid solid salt coupling, new mechanisms were developed for rapidly charging and discharging salt sample tubes at the vacuum sampling loop and pneumatic sample generator modules, respectively. While the charging mechanism will be deployed in FY22, the discharge mechanism was tested in FY21 and is described here. The solid salt tube transfer method was deployed at one of Argonne’s engineering-scale electrorefiners to implement at-line high-throughput pneumatic micro-sample generation capabilities. The approach was used to generate precise uranium- and lanthanide-bearing electrorefiner micro-samples with the specific dimensions requested by researchers at Los Alamos National Laboratory for use in testing their novel microcalorimeter x-ray techniques. The solid salt transfer mechanism proved not only to be an effective means of integrating the precision sample generator with vacuum sampling, but also improved the performance of the sampler generator. To discharge salt from the sample tubes at the sampler generator, tube segments were inserted directly into the sample generator’s Helmholtz chamber and pressure pulse actuations were used to generate precision molten salt samples directly from the tube segments. The direct insertion of sample tubes into the sample generator enabled rapid loading of the salt and prevented salt from contacting most of the interior surfaces of the sample generator, which eliminated cross-contamination between runs. The vacuum sampling-loop tube charging mechanism will support high-throughput tube sampling operations by employing a dynamic vacuum filling process to fill short charge tubes that are configured to be rapidly connected and disconnected from the loop. The dynamic vacuum sampling operation will be automated, and sample tube handling can be executed with simple overhead actuation. Because the modular sampling approach described here eliminates the need for new high-radiation sample handling capabilities, salt-wetted seals, salt-wetted moving parts, and heated transfer lines outside the electrorefiner, it will address most of the remaining technical challenges for the at-line deployment of high-precision analytical techniques which will enable significant reductions in the time delay for sampling-based high-precision accountancy measurements.

42 ENGINEERING↗
DOE OSTI2025

Multifrequency Models of Black Hole Photon Rings from Low-luminosity Accretion Disks

Images of black holes encode both astrophysical and gravitational properties. Detecting highly lensed features in images can differentiate between these two effects. We present an accretion disk emission model coupled to the Adaptive Analytical Ray Tracing (AART) code that allows a fast parameter space exploration of black hole photon ring images produced from synchrotron emission from 10 to 670 GHz. As an application, we systematically study several disk models and compute their total flux density, average radii, and optical depth. The model parameters are chosen around fiducial values calibrated to general relativistic magnetohydrodynamic (GRMHD) simulations and observations of M87*. For the parameter space studied, we characterize the transition between optically thin and thick regimes and the frequency at which the first photon ring is observable. Our results highlight the need for careful definitions of photon ring radius in the image domain, as in certain models the highly lensed photon ring is dimmer than the direct emission at certain angles. We find that at low frequencies the ring radii are set by the electron temperature, while at higher frequencies the magnetic field strength plays a more significant role, demonstrating how multifrequency analysis can also be used to infer plasma parameters. Lastly, we show how our implementation can qualitatively reproduce multifrequency black hole images from GRMHD simulations when adding time variability to our disk model through Gaussian random fields. This approach provides a new method for simulating observations from the Event Horizon Telescope and the proposed Black Hole Explorer space mission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Modeling the spectral modification of lower hybrid wave in the presence of drift-wave type density fluctuation in the scrape-off-layer of the EAST tokamak

In this work, the spectrum change of the lower hybrid (LH) waves caused by a low-frequency density fluctuation in the scrape-off-layer is studied by applying the wave scattering model developed by Bonoli and Ott [Phys. Fluids 25, 359 (1982)] via a Monte Carlo method. A ray-tracing model specific to this purpose is developed to evaluate the probability distribution of both the poloidal refractive index (N θ ) and the parallel refractive index (N ∥ ) of the LH wave at the last closed flux surface (LCFS).The probability distributions of N ∥ and N θ at the LCFS are studied using the EAST parameters as a function of wave frequency, the initial N ∥ , and the polar injection position, which may influence the lower hybrid current drive efficiency.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Quasiparticle random-phase approximation calculations for M 1 transitions with the noniterative finite-amplitude method and application to neutron radiative capture cross sections

Here, we derive the equations of quasiparticle random-phase approximation (QRPA) based on the finite amplitude method with the Hartree-Fock+Bardeen–Cooper–Schrieffer (HF+BCS) single-particle states, and calculate the magnetic dipole (M⁢1) transition for deformed gadolinium isotopes. Our QRPA calculation shows both large spin-flip transitions in the 5 to 10 MeV excitation energy and the low energy orbital transition that would correspond to the M⁢1 scissors mode observed in nuclear experiments. Then, we calculate neutron capture reactions based on the statistical Hauser-Feshbach theory with the photoabsorption cross sections of even-even nuclei given by QRPA. We find that the capture cross section is enhanced due to the contribution from the low energy M⁢1 transition although the calculated capture cross section still underestimates the experimental data. This issue in the calculated capture cross section could be improved by uncertainties of the low energy E⁢1 transition neglected in our QRPA calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Randomized Algorithms for Scientific Computing (RASC)

Randomized algorithms have propelled advances in artificial intelligence (AI) and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. Advances in data collection and numerical simulation have changed the dynamics of scientific research and motivate the need for randomized algorithms. For instance, advances in imaging technologies such as X-ray ptychography, electron microscopy, electron energy loss spectroscopy, or adaptive optics lattice light-sheet microscopy collect hyperspectral imaging and scattering data in terabytes, at breakneck speed enabled by state-of-the-art detectors. The data collection is exceptionally fast compared with its analysis. Likewise, advances in high-performance architectures have made exascale computing a reality and changed the economies of scientific computing in the process. Floating-point operations that create data are essentially free in comparison with data movement. Thus far, most approaches have focused on creating faster hardware. Ironically, this faster hardware has exacerbated the problem by making data still easier to create. Under such an onslaught, scientists often resort to heuristic deterministic sampling schemes (e.g., low-precision arithmetic, sampling every nth element) and sacrifice potentially valuable accuracy. Dramatically better results can be achieved via randomized algorithms, reducing the data size as much as or more than naive deterministic subsampling can achieve, while retaining the high accuracy of computing on the full data set. By randomized algorithms we mean those algorithms that employ some form of randomness in internal algorithmic decisions to accelerate time to solution, increase scalability, or improve reliability. Examples include matrix sketching for solving large-scale least-squares problems (see Figure 1) and stochastic gradient descent for training machine learning models. We are not recommending heuristic methods but rather randomized algorithms that have certificates of correctness and probabilistic guarantees of optimality and near-optimality. Such approaches can be useful beyond acceleration, for example, in understanding how to avoid measure zero worst-case scenarios that plague methods such as QR matrix factorization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Elucidating the Atomic Structures of the Gel Layer Formed during Aluminoborosilicate Glass Dissolution: An Integrated Experimental and Simulation Study

The altered glasses produced during aqueous dissolution of silicate and borosilicate glasses are among the most complex structures to understand at the atomic level due to their amorphous nature, random porosity and various levels of hydration. In this study, we gained insights of the complex atomic structures of altered aluminoborosilicate glasses by combining a range of experimental and computational approaches. The altered glasses were prepared by dissolution of three glasses with varying level of alumina in acid for 7 days. A comprehensive set of experimental [elemental analysis, high-energy X-ray diffraction, 29 Si and 27 Al solid-state nuclear magnetic resonance (NMR), and O 1s X-ray photoelectron spectroscopy (XPS)] and modeling (molecular dynamics (MD) simulations using non-reactive and reactive force fields) were used to study the atomic structures of these altered glasses. Elemental analysis showed that most of the B in the pristine glasses was leached into the solution and was not contained in the altered glass. The 29 Si and 27 Al solid-state NMR spectra revealed that the altered glasses have more polymerized silicate network as compared to those in the pristine glasses due to the reformation of linkages among Si and Al oxygen polyhedral in the altered glasses. The bridging and non-bridging (or hydroxyl O) atoms in the altered glasses were also quantified from their O 1s XPS spectra. Atomic structure models of the altered glasses were constructed by using MD simulations using the reactive force field based on the compositional information obtained from experiments. Various pore structures were generated using the charge-scaling (CS) method by using different initial densities and CS temperatures; the best CS parameters of each alternated glass were then determined by comparing with the experimental structure factors obtained from high energy X-ray diffraction. Pore and the atomic structures and vibrational properties around these pore surfaces were analyzed. Furthermore, these results from this comprehensive study thus provides a realistic insight into the pore morphology, atomic structure, and vibrational properties of altered glasses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Polytypism in semi-disordered lizardite and amesite by low-dose HAADF-STEM

Serpentine minerals exert important controls on the physical properties of ultramafic rocks and have the potential to influence deformation phenomena in fault zones and to control the release of water in subducted slabs. Sheet serpentine generally, and lizardite and amesite specifically, can adopt alternative crystallographic stacking arrangements called polytypes. Polytypism has been extensively studied in fully ordered crystals, but it remains largely enigmatic in the more common semi-disordered crystals that in long-range analyses such as X-ray diffraction only exhibit random combinations of 0b and ±1/3b interlayer shifts. To date, atomic-resolution imaging to identify locally ordered polytypes has been precluded by the beam-sensitive nature of this hydrous magnesium silicate mineral. Here, in this study, we employed low-dose high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to study the polytypic structure of semi-disordered lizardite and amesite. Because the electron dose was as low as ~6000 e–/Å 2 , it was possible to directly resolve oxygen atomic columns and all the cations with a resolution of ~1 Å and reveal the short-range order. For lizardite, we identified long-period non-standard polytypes, including examples with 3, 4, 8, and 9 layers stemming from the ordering of the octahedral tilt along the a-axis. For amesite, we found short-range ordered polytypes with periodicities of up to 42 Å stemming from the ordering of interlayer shifts along the b-axis. The resolution was sufficient to determine the relative abundance of 6R 2 , 6R 1 , 2H 1 , and 2H 2 polytypes in amesite to be 46.1, 29.6, 7.7, and 1.9%, respectively. This is contrary to the expectation that the most common form of amesite is the 2H 2 polytype, which may be more likely to form macroscopic crystals suitable for conventional X-ray diffraction-based studies. We conclude that HAADF-STEM methods open the way for the characterization of beam-sensitive minerals and to resolve the structural details of less well-ordered (but possibly more abundant) minerals at a unit-cell scale.

58 GEOSCIENCES↗
DOE OSTI2026

TCAD-Machine Learning Enabled TID Compact Model Development for Commercial SiC MOSFET

We propose a TCAD (Technology Computer Aided Design)-machine learning coupled approach that combines a TCAD tool (Charon), optimization/uncertainty quantification tool (Dakota), surrogate models, and Bayesian learning capabilities. The coupling approach is used for accurate modeling and calibration of total ionizing dose (TID) induced threshold voltage (V th ) shifts in Commercial-Off-The-Shelf (COTS) semiconductor devices and to develop physics-informed TID compact models. This versatile approach is applied to model the TID effect in an exemplar COTS 3.3 kV SiC power MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor). With the Charon-Dakota coupling, we can determine key device geometry and doping values based on device physics, which are difficult to obtain or not available for COTS devices but important for TCAD simulation; additionally, we can efficiently generate thousands of simulation results in a large parameter space, which makes it possible to develop data-driven surrogate models and perform Bayesian calibration. Utilizing the full tool-coupling approach, we achieve calibrated TCAD simulation models that accurately capture the average TID-induced V th shifts behavior with total doses and V th shifts saturation at high doses as observed in experimental data. More importantly, the calibrated TCAD simulations are obtained with determined TID model parameters (e.g., hole trap density and capture cross section) values that contain well quantified uncertainties. Furthermore, we can isolate and quantify the noises that are not captured by the TCAD models but exist in the measured data due to measurements and devices variabilities. Lastly, the calibrated surrogate models are used to develop physics-informed TID compact models. The method is generalizable to other devices and/or radiation conditions with few modifications and can provide well-determined uncertainties.

COTS↗
DOE OSTI2021

Removal of spurious data in Bragg coherent diffraction imaging: an algorithm for automated data preprocessing

Bragg coherent diffraction imaging (BCDI) provides a powerful tool for obtaining high-resolution structural information from nanocrystalline materials. Here a BCDI sample consisting of a large number of randomly oriented nanoscale crystals is considered. Ideally, only one crystal is oriented to produce a Bragg peak on the detector. However, diffraction from other crystals often produces additional signals on the detector. Before the measured diffraction patterns can be processed into structural images, scientists routinely need to manually identify and remove the `alien' intensities from sources other than the intended crystal. With the development of modern high-coherence storage rings, such as the upgraded Advanced Photon Source (APS), the already slow process of manual preprocessing will be untenable for the large volumes of data that will be produced. An automated method of identifying and deleting alien intensities is proposed. This method exploits the fact that BCDI of a perfect crystal produces diffraction data with inversion symmetry around the Bragg peak. This approach uses the machine learning clustering method DBSCAN to distinguish between diffraction from multiple sources, and then calculates cluster size and inversion symmetry to assess whether clusters of intensity belong to desired data or alien signals. This approach can dramatically reduce the amount of time spent manually processing data, allowing BCDI data processing capabilities to keep pace with the technological advances of fourth-generation synchrotron light sources.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accelerating full-waveform inversion using source stacking: synthetic experiments at the global scale in a realistic 3-D earth model

SUMMARY The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform ‘data’ for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ, and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for.

Geochemistry & Geophysics↗
DOE OSTI2025

Deviations from the Porter-Thomas Distribution due to Nonstatistical 𝛾 Decay below the 150 Nd Neutron Separation Threshold

We introduce a new method for the study of fluctuations of partial transition widths based on nuclear resonance fluorescence experiments with quasimonochromatic linearly polarized photon beams below particle separation thresholds. It is based on the average branching of decays of 𝐽=1 states of an even-even nucleus to the 2$^{+}_{1}$ state in comparison to the ground state. Between 5 and 7 MeV, a constant average branching ratio for 𝛾 decays from 1 − states of 0.490(16) is observed for the nuclide 150 Nd. Assuming 𝜒 2 -distributed partial transition widths, this average branching ratio is related to a degree of freedom of 𝜈 = 1.93⁢(12), rejecting the validity of the Porter-Thomas distribution, requiring 𝜈 = 1. The observed deviation can be explained by nonstatistical effects in the 𝛾-decay behavior with contributions in the range of 9.4(10)% up to 94(10)%.

150 ≤ A ≤ 189↗