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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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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Spin asymmetries for vector boson production in polarized p + p collisions

We study the cross section for vector boson (W ± /Z 0 /γ $\star$ ) production in polarized nucleon-nucleon collisions for low transverse momentum of the observed vector boson. For the case where one measures the transverse momentum and azimuthal angle of the vector bosons, we present the cross sections and the associated spin asymmetries in terms of transverse momentum dependent parton distribution functions (TMDs) at tree level within the TMD factorization formalism. To assess the feasibility of experimental measurements, we estimate the spin asymmetries forW ± /Z 0 boson production in polarized proton-proton collisions at the Relativistic Heavy Ion Collider by using current knowledge of the relevant TMDs. Here, we find that some of these asymmetries can be sizable if the suppression effect from TMD evolution is not too strong. The W program at RHIC can, thus, test and constrain spin theory by providing unique information on the universality properties of TMDs, TMD evolution, and the nucleon structure. For example, the single transverse spin asymmetries could be used to probe the well-known Sivers function f$⊥q\atop{1T}$, as well as the transversal helicity distribution g$q\atop{1T}$ via the parity-violating nature of W production.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Improving the Performance of Integrated Power-Hardware-in-the-Loop and Quasi-Static Time-Series Simulations

This paper introduces a novel multirate cosimulation architecture that overcomes previous challenges integrating faster real-time, microseconds-scale, power-hardware-in-the-loop (PHIL) with larger scale but slower, real-time, seconds-scale, quasi-static time-series (QSTS) simulation. Specifically, an intermediate reduced-equivalent electromagnetic transient (EMT) model duplicates the key power system topology to capture high-speed dynamics and converge hardware-power system interactions between QSTS updates. Exchanging multidimensional parameter vectors (loads, control status, etc.) between the QSTS and EMT models enables capturing the interactions of the rich, high-node-count (thousands of electrical nodes) QSTS model with the hardware. This architecture offers full spatial resolution from QSTS, including individual load dynamics, actual distribution management system controls, and nodal voltages. Simultaneously, the intermediate EMT model provides more detailed high-speed transients of key distributed energy resource hardware interactions. In addition, we use careful PHIL interface design and the exchange of complex power data, rather than current, to further improve performance. This cosimulation architecture is demonstrated by testing a simulated distribution system with an interconnected 500-kVA advanced photovoltaic (PV) inverter in PHIL. In conclusion, the architecture successfully captured PV local volt-volt ampere reactive (volt-VAR) control interactions with the larger network under time-varying electrical and weather conditions.

42 ENGINEERING↗
DOE OSTI2024

Vehicle Position Detection Based on Machine Learning Algorithms in Dynamic Wireless Charging

Dynamic wireless charging (DWC) has emerged as a viable approach to mitigate range anxiety by ensuring continuous and uninterrupted charging for electric vehicles in motion. DWC systems rely on the length of the transmitter, which can be categorized into long-track transmitters and segmented coil arrays. The segmented coil array, favored for its heightened efficiency and reduced electromagnetic interference, stands out as the preferred option. However, in such DWC systems, the need arises to detect the vehicle’s position, specifically to activate the transmitter coils aligned with the receiver pad and de-energize uncoupled transmitter coils. This paper introduces various machine learning algorithms for precise vehicle position determination, accommodating diverse ground clearances of electric vehicles and various speeds. Through testing eight different machine learning algorithms and comparing the results, the random forest algorithm emerged as superior, displaying the lowest error in predicting the actual position.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Application of visible and near-infrared spectroscopy to classification of Miscanthus species

Here, the feasibility of visible and near infrared (NIR) spectroscopy as tool to classify Miscanthus samples was explored in this study. Three types of Miscanthus plants, namely, M. sinensis , M. sacchariflorus and M. fIoridulus , were analyzed using a NIR spectrophotometer. Several classification models based on the NIR spectra data were developed using line discriminated analysis (LDA), partial least squares (PLS), least squares support vector machine regression (LSSVR), radial basis function (RBF) and neural network (NN). The principal component analysis (PCA) presented rough classification with overlapping samples, while the models of Line_LSSVR, RBF_LSSVR and RBF_NN presented almost same calibration and validation results. Due to the higher speed of Line_LSSVR than RBF_LSSVR and RBF_NN, we selected the line_LSSVR model as a representative. In our study, the model based on line_LSSVR showed higher accuracy than LDA and PLS models. The total correct classification rates of 87.79 and 96.51% were observed based on LDA and PLS model in the testing set, respectively, while the line_LSSVR showed 99.42% of total correct classification rate. Meanwhile, the lin_LSSVR model in the testing set showed correct classification rate of 100, 100 and 96.77% for M. sinensis , M. sacchariflorus and M. fIoridulus , respectively. The lin_LSSVR model assigned 99.42% of samples to the right groups, except one M. fIoridulus sample. The results demonstrated that NIR spectra combined with a preliminary morphological classification could be an effective and reliable procedure for the classification of Miscanthus species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Naturally light Dirac and pseudo-Dirac neutrinos from left-right symmetry

We develop a class of left-right symmetric theories based on the gauge group SU(3) c x SU(2) L x SU(2) R x U(1) with a generalized seesaw mechanism for generating the charged fermion masses. Neutrinos are naturally Dirac particles in this setup with their small masses arising from two-loop quantum corrections. We evaluate these two-loop diagrams exactly and analyze the flavor structure of the lepton sector. We find excellent fits to neutrino oscillation data, independent of the right-handed gauge symmetry breaking scale. We also explore the possibility that neutrinos are pseudo-Dirac particles in this framework, with the tiny mass splittings between active and sterile neutrinos arising from Planck-induced corrections and find possible realizations. These models can be tested in the near future with precision cosmological measurements of ΔN eff in CMB which is predicted to be ≃ 0.14. This class of models allows for a solution to the strong CP problem via parity symmetry without the need for an axion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Effect of neutron irradiation on defect evolution in Ti 3 SiC 2 and Ti 2 AlC

Here, we report on the characterization of defects formed in polycrystalline Ti 3 SiC 2 and Ti 2 AlC samples exposed to neutron irradiation – up to 0.1 displacements per atom (dpa) at 350 ± 40 °C or 695 ± 25 °C, and up to 0.4 dpa at 350 ± 40 °C. Black spots are observed in both Ti 3 SiC 2 and Ti 2 AlC after irradiation to both 0.1 and 0.4 dpa at 350 °C. After irradiation to 0.1 dpa at 695 °C, small basal dislocation loops, with a Burgers vector of b = 1/2 [0001] are observed in both materials. At 9 ± 3 and 10 ± 5 nm, the loop diameters in the Ti 3 SiC 2 and Ti 2 AlC samples, respectively, were comparable. At 1 × 10 23 loops/m 3 , the dislocation loop density in Ti 2 AlC was ≈1.5 orders of magnitude greater than in Ti 3 SiC 2 , at 3 x 10 21 loops/m3. After irradiation at 350 °C, extensive microcracking was observed in Ti 2 AlC, but not in Ti 3 SiC 2 . The room temperature electrical resistivities increased as a function of neutron dose for all samples tested, and appear to saturate in the case of Ti 3 SiC 2 . The MAX phases are unequivocally more neutron radiation tolerant than the impurity phases TiC and Al 2 O 3 . Based on these results, Ti 3 SiC 2 appears to be a more promising MAX phase candidate for high temperature nuclear applications than Ti 2 AlC.

36 MATERIALS SCIENCE↗
DOE OSTI2024

KiDS-1000 cosmology: Combined second- and third-order shear statistics

Aims.In this work, we perform the first cosmological parameter analysis of the fourth release of Kilo Degree Survey (KiDS-1000) data with second- and third-order shear statistics. This paper builds on a series of studies aimed at describing the roadmap to third-order shear statistics. Methods.We derived and tested a combined model of the second-order shear statistic, namely, the COSEBIs and the third-order aperture mass statistics 〈ℳ ap 3 〉 in a tomographic set-up. We validated our pipeline withN-body mock simulations of the KiDS-1000 data release. To model the second- and third-order statistics, we used the latest version of HMCODE2020 for the power spectrum and BIHALOFITfor the bispectrum. Furthermore, we used an analytic description to model intrinsic alignments and hydro-dynamical simulations to model the effect of baryonic feedback processes. Lastly, we decreased the dimension of the data vector significantly by considering only equal smoothing radii for the 〈ℳ ap 3 〉 part of the data vector. This makes it possible to carry out a data analysis of the KiDS-1000 data release using a combined analysis of COSEBIs and third-order shear statistics. Results.We first validated the accuracy of our modelling by analysing a noise-free mock data vector, assuming the KiDS-1000 error budget, finding a shift in the maximum of the posterior distribution of the matter density parameter, ΔΩ m < 0.02 σ Ω m , and of the structure growth parameter, ΔS 8 < 0.05 σ S 8 . Lastly, we performed the first KiDS-1000 cosmological analysis using a combined analysis of second- and third-order shear statistics, where we constrained Ω m = 0.248 −0.055 +0.062 andS 8 = σ 8 √(Ω m /0.3 )= 0.772 ± 0.022. The geometric average on the errors of Ω m andS 8 of the combined statistics decreases, compared to the second-order statistic, by a factor of 2.2.

Astronomy & Astrophysics↗
DOE OSTI2021

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗
DOE OSTI2015

Coherent optical transients observed in rubidium atomic line filtered Doppler velocimetry experiments

We report the first successful results from our novel Rubidium Atomic Line Filtered (RALF) Doppler velocimetry apparatus, along with unanticipated oscillatory signals due to coherent optical transients generated within pure Rb vapor cells. RALF is a high-velocity and high-acceleration extension of the well-known Doppler Global Velocimetry (DGV) technique for constructing multi-dimensional flow velocity vector maps in aerodynamics experiments [H. Komine, U.S. Patent No. 4,919,536 (24 April 1990)]. RALF exploits the frequency dependence of pressure-broadened Rb atom optical absorptions in a heated Rb/N{sub 2} gas cell to encode the Doppler shift of reflected near-resonant (λ{sub 0} ≈ 780.24 nm) laser light onto the intensity transmitted by the cell. The present RALF apparatus combines fiber optic and free-space components and was built to determine suitable operating conditions and performance parameters for the Rb/N{sub 2} gas cells. It yields single-spot velocities of thin laser-driven-flyer test surfaces and incorporates a simultaneous Photonic Doppler Velocimetry (PDV) channel [Strand et al., Rev. Sci. Instrum. 77, 083108 (2006)] for validation of the RALF results, which we demonstrate here over the v = 0 to 1 km/s range. Both RALF and DGV presume the vapor cells to be simple Beer's Law optical absorbers, so we were quite surprised to observe oscillatory signals in experiments employing low pressure pure Rb vapor cells. We interpret these oscillations as interference between the Doppler shifted reflected light and the Free Induction Decay (FID) coherent optical transient produced within the pure Rb cells at the original laser frequency; this is confirmed by direct comparison of the PDV and FID signals. We attribute the different behaviors of the Rb/N{sub 2} vs. Rb gas cells to efficient dephasing of the atomic/optical coherences by Rb-N{sub 2} collisions. The minimum necessary N{sub 2} buffer gas density ≈0.3 amagat translates into a smallest useful velocity range of 0 to 2 km/s, which can readily be extended to cover the 0 to 10 km/s range, and beyond. The recognition that coherent optical transients can be produced within low pressure vapor cells during velocimetry experiments may offer new insights into some quantitative discrepancies reported in earlier DGV studies. Future plans include “line-RALF” experiments with streak camera detection, and two-dimensional surface velocity mapping using pulsed laser illumination and/or gated intensified CCD camera detection.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Faxén form of time-domain force on a sphere in unsteady spatially varying viscous compressible flows

An explicit expression for the time-dependent force on a stationary, finite-sized spherical particle located in an unsteady inhomogeneous ambient flow is presented. The force expression accounts for both viscous and compressible effects. Towards this end, a time-harmonic plane travelling wave of a given frequency propagating in a viscous compressible flow over a sphere is considered. Linearized compressible Navier–Stokes equations are solved to obtain an analytical expression for the force exerted on the particle in the frequency domain. The force obtained in the Laplace space due to a travelling wave of a given frequency and wavenumber is then generalized to any arbitrary incoming flow. This is achieved by relating the radial and tangential velocity components in the Laplace space to the surface-averaged radial velocity and volume-averaged velocity vectors respectively in the time space. Moreover an expression relating the surface-averaged radial velocity and volume-averaged velocity vector has been provided. The total force is written as a summation of the undisturbed and disturbed force (quasi-steady, inviscid-unsteady and viscous-unsteady) contributions. The force contributions thus obtained are expressed as comprising of two parts – that arising due to spatial variation in the ambient flow and the other arising due to temporal variation. The current formulation is applicable to inhomogeneous ambient flows, however in the limit of negligible Reynolds and Mach numbers. The results are applicable even for particles of sizes larger than the acoustic wavelength. The accuracy of the explicit time-domain force expression is first tested by computing the force on an 80 mm diameter particle due to a weak planar expansion fan. Extension of this formulation when nonlinear effects become important is also proposed and tested by considering strong expansion fans. The results thus obtained are compared against corresponding axisymmetric numerical simulations.

Mechanics↗
DOE OSTI2014

GlueX: Meson Spectroscopy in Photoproduction

The goal of the GlueX experiment \cite{gluex} is to provide crucial data to help understand the soft gluonic fields responsible for binding quarks in hadrons. Hybrid mesons, and in particular exotic hybrid mesons, provide the ideal laboratory for testing QCD in the confinement regime since these mesons explicitly manifest the gluonic degrees of freedom. Photoproduction is expected to be effective in producing exotic hybrids but there is little data on the photoproduction of light mesons. GlueX will use the new 12-GeV electron beam at Jefferson Lab to produce a 9-GeV beam of linearly polarized photons using the technique of coherent bremsstrahlung. A solenoid-based hermetic detector is under construction, which will be used to collect data on meson production and decays. These data will also be used to study the spectrum of conventional mesons, including the poorly understood excited vector mesons. This talk will give an update on the experiment as well as describe theoretical developments \cite{Dudek:2011bn} to help understand how these data can provide insights into the fundamental theory of strong interactions.

Salgado, Carlos↗
DOE OSTI2022

Calibration and Localization of Optically Pumped Magnetometers Using Electromagnetic Coils

In this paper, we propose a method to estimate the position, orientation, and gain of a magnetic field sensor using a set of (large) electromagnetic coils. We apply the method for calibrating an array of optically pumped magnetometers (OPMs) for magnetoencephalography (MEG). We first measure the magnetic fields of the coils at multiple known positions using a well-calibrated triaxial magnetometer, and model these discreetly sampled fields using vector spherical harmonics (VSH) functions. We then localize and calibrate an OPM by minimizing the sum of squared errors between the model signals and the OPM responses to the coil fields. We show that by using homogeneous and first-order gradient fields, the OPM sensor parameters (gain, position, and orientation) can be obtained from a set of linear equations with pseudo-inverses of two matrices. The currents that should be applied to the coils for approximating these low-order field components can be determined based on the VSH models. Computationally simple initial estimates of the OPM sensor parameters follow. As a first test of the method, we placed a fluxgate magnetometer at multiple positions and estimated the RMS position, orientation, and gain errors of the method to be 1.0 mm, 0.2°, and 0.8%, respectively. Lastly, we calibrated a 48-channel OPM array. The accuracy of the OPM calibration was tested by using the OPM array to localize magnetic dipoles in a phantom, which resulted in an average dipole position error of 3.3 mm. The results demonstrate the feasibility of using electromagnetic coils to calibrate and localize OPMs for MEG.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Phylogenetic and ecological drivers of the avian lung mycobiome and its potentially pathogenic component

Vertebrate lungs contain diverse microbial communities, but little is known about the drivers of community composition or consequences for health. Microbiome assembly by processes such as dispersal, coevolution, and host-switching can be probed with comparative surveys; however, few studies exist for lung microbiomes, particularly for the fungal component, the mycobiome. Distinguishing among fungal taxa that are generalist or specialist symbionts, potential pathogens, or incidentally inhaled spores is urgent because of potential for emerging diseases. Here, we characterize the avian lung mycobiome and test the relative influences of environment, phylogeny, and functional traits. We used metabarcoding and culturing from 195 lung samples representing 32 bird species across 20 families. We identified 526 fungal taxa as estimated by distinct sequence types (zOTUs) including many opportunistic pathogens. These were predominantly from the phylum Ascomycota (79%) followed by Basidiomycota (16%) and Mucoromycota (5%). Yeast and yeast-like taxa (Malassezia, Filobasidium, Saccharomyces, Meyerozyma, and Aureobasidium) and filamentous fungi (Cladosporium, Alternaria, Neurospora, Fusarium, and Aspergillus) were abundant. Lung mycobiomes were strongly shaped by environmental exposure, and further modulated by host identity, traits, and phylogenetic affinities. Our results implicate migratory bird species as potential vectors for long-distance dispersal of opportunistically pathogenic fungi.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

J-PLUS: Support vector regression to measure stellar parameters

Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameter's regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account, the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Cyber-Attack Detection for Photovoltaic Farms Based on Power-Electronics-Enabled Harmonic State Space Modeling

Here in this paper, a physics-data-based detection method is proposed to detect a variety of cyber-attacks in Photovoltaic (PV) farms using the power electronics-enabled harmonic state space (HSS) models, which, to our knowledge, is original. At the device level, HSS-based detection is developed to monitor harmonic vectors of individual PV converter with minimum sensor measurements, thus improving accuracy and robustness compared to Kalman Filter-based detection. At the system level that involves multiple PV converters, a clustering approach is developed to investigate attack propagation and accurately locate attack sources within a PV farm. The proposed approach is one of the first attempts to address PV security through interaction between the device and system, maximizing the accuracy and robustness at different levels. To verify the feasibility, a comprehensive attacks model is built, including single attack, coordinated attacks, and replay attacks. Besides, the impacts of irradiance changes are taken into consideration in the test scenarios. With the real-time data acquisition and hardware-in-the-loop testbed, comprehensive test results are provided to verify the feasibility of the proposed detection methodology.

42 ENGINEERING↗
DOE OSTI2019

Using the Endogenous CRISPR-Cas System of Heliobacterium modesticaldum To Delete the Photochemical Reaction Center Core Subunit Gene

In Heliobacterium modesticaldum , as in many Firmicutes , deleting genes by homologous recombination using standard techniques has been extremely difficult. The cells tend to integrate the introduced plasmid into the chromosome by a single recombination event rather than perform the double recombination required to replace the targeted locus. Transformation with a vector containing only a homologous recombination template for replacement of the photochemical reaction center gene pshA produced colonies with multiple genotypes, rather than a clean gene replacement. To address this issue, we required an additional means of selection to force a clean gene replacement. In this study, we report the genetic structure of the type I-A and I-E CRISPR-Cas systems from H. modesticaldum , as well as methods to leverage the type I-A system for genome editing. In silico analysis of the CRISPR spacers revealed a potential consensus protospacer adjacent motif (PAM) required for Cas3 recognition, which was then tested using an in vivo interference assay. Introduction of a homologous recombination plasmid that carried a miniature CRISPR array targeting sequences in pshA (downstream of a naturally occurring PAM sequence) produced nonphototrophic transformants with clean replacements of the pshA gene with ~80% efficiency. Mutants were confirmed by PCR, sequencing, optical spectroscopy, and growth characteristics. This methodology should be applicable to any genetic locus in the H. modesticaldum genome. The heliobacteria are the only phototrophic members of the largely Gram-positive phylum Firmicutes , which contains medically and industrially important members, such as Clostridium difficile and Clostridium acetobutylicum . Heliobacteria are of interest in the study of photosynthesis because their photosynthetic system is unique and the simplest known. Since their discovery in the early 1980s, work on the heliobacteria has been hindered by the lack of a genetic transformation system. The problem of introducing foreign DNA into these bacteria has been recently rectified by our group; however, issues still remained for efficient genome editing. The significance of this work is that we have characterized the endogenous type I CRISPR-Cas system in the heliobacteria and leveraged it to assist in genome editing. Using the CRISPR-Cas system allowed us to isolate transformants with precise replacement of the pshA gene encoding the main subunit of the photochemical reaction center.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Development and Validation of a Polarimetric-MCScene 3D Atmospheric Radiation Model

Polarimetric measurements can substantially enhance the ability of both spectrally resolved and single band imagery to detect the proliferation of weapons of mass destruction, providing data for locating and identifying facilities, materials, and processes of undeclared and proliferant nuclear weapons programs worldwide. Unfortunately, models do not exist that efficiently and accurately predict spectral polarized signatures for the materials of interest embedded in complex 3D environments. Having such a model would enable one to test hypotheses and optimize both the enhancement of scene contrast and the signal processing for spectral signature extraction. The Phase I set the groundwork for development of fully validated polarimetric spectral signature and scene simulation models. This has been accomplished 1. by (a) identifying and downloading state-of-the-art surface and atmospheric polarimetric data sources, (b) implementing tools for generating custom polarimetric data, and (c) identifying and requesting US Government funded field measurement data for use in validation; 2. by formulating an approach for upgrading the radiometric spectral signature model MODTRAN to generate polarimetric intensities through (a) ingestion of the polarimetric data, (b) polarimetric vectorization of existing MODTRAN modules, and (c) integration of a newly developed algorithm for computing polarimetric multiple scattering contributions; 3. by generating an initial polarimetric model that demonstrates calculation of polarimetric solar and lunar single scatter intensities arising from the interaction of incoming irradiances with molecules and aerosols; 4. by developing a design and implementation plan to (a) automate polarimetric scene construction and (b) efficiently sample polarimetric scattering and reflection events, for use in a to be developed polarimetric version of the existing first-principles synthetic scene simulation model, MCScene; and 5. by planning a validation field measurement program in collaboration with the Remote Sensing and Exploitation group at Sandia National Laboratories (SNL) in which data from their ongoing polarimetric field and laboratory measurement program will be shared and, to the extent allowed, tailored for model validation in exchange for model predictions under conditions and for geometries outside of their measurement domain.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Huge ensembles – Part 1: Design of ensemble weather forecasts using spherical Fourier neural operators

Abstract. Simulating low-likelihood high-impact extreme weather events in a warming world is a significant and challenging task for current ensemble forecasting systems. While these systems presently use up to 100 members, larger ensembles could enrich the sampling of internal variability. They may capture the long tails associated with climate hazards better than traditional ensemble sizes. Due to computational constraints, it is infeasible to generate huge ensembles (comprised of 1000–10 000 members) with traditional, physics-based numerical models. In this two-part paper, we replace traditional numerical simulations with machine learning (ML) to generate hindcasts of huge ensembles. In Part 1, we construct an ensemble weather forecasting system based on spherical Fourier neural operators (SFNOs), and we discuss important design decisions for constructing such an ensemble. The ensemble represents model uncertainty through perturbed-parameter techniques, and it represents initial condition uncertainty through bred vectors, which sample the fastest-growing modes of the forecast. Using the European Centre for Medium-Range Weather Forecasts Integrated Forecasting System (IFS) as a baseline, we develop an evaluation pipeline composed of mean, spectral, and extreme diagnostics. With large-scale, distributed SFNOs with 1.1 billion learned parameters, we achieve calibrated probabilistic forecasts. As the trajectories of the individual members diverge, the ML ensemble mean spectra degrade with lead time, consistent with physical expectations. However, the individual ensemble members' spectra stay constant with lead time. Therefore, these members simulate realistic weather states during the rollout, and the ML ensemble passes a crucial spectral test in the literature. The IFS and ML ensembles have similar extreme forecast indices, and we show that the ML extreme weather forecasts are reliable and discriminating. These diagnostics ensure that the ensemble can reliably simulate the time evolution of the atmosphere, including low-likelihood high-impact extremes. In Part 2, we generate a huge ensemble initialized each day in summer 2023, and we characterize the simulations of extremes.

Mahesh, Ankur↗