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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 145 records · Page 8

Propagation of Noise Uncertainty Through Virtual Strain Gauge Formulations for 2D Digital Image Correlation

The effect of displacement uncertainty is examined on 2-dimensional strain, calculated using linear surfaces fitted to the displacement field. A classical engineering error propagation method is used to calculate uncertainty in Green-Lagrangian strain calculations. The derived uncertainty is compared to a Monte Carlo simulation and discrepancies under 2% are seen between these two methods. The effect of virtual strain gauge size, displacement uncertainty, and boundaries on the region of interest on the strain uncertainty are considered. Here, an exponential decay relationship is observed between strain uncertainty and virtual strain gauge size, while a linear relationship is seen between strain and displacement uncertainty. For boundaries in the region of interest, strain uncertainty is affected by the reduced number of points available to perform the regression.

42 ENGINEERING↗

Comparison of Machine Learning Approaches for Prediction of the Equivalent Alkane Carbon Number for Microemulsions Based on Molecular Properties

The chemical properties of oils are vital in the design of microemulsion systems. The hydrophilic–lipophilic difference equation used to predict microemulsions’ phase behavior expresses the oils’ physiochemical properties as the equivalent alkane carbon number (EACN). The experimental determination of EACN requires knowledge of the temperature dependence of the microemulsion system and the effects of different surfactant concentrations. Thus, the experimental determination is time-intensive and tedious, requiring days to months for proper separations. Furthermore, the experiments require high purity of chemicals because microemulsions are sensitive to impurities. Our work focuses on the quick and reliable predictions of the EACN with machine learning (ML) models. Due to the immaturity of ML chemical predictions, we compare three graph neural networks (GNNs) and a gradient-boosted tree algorithm, known as XGBoost. The GNNs use the molecular structures represented as simplified molecular-input line-entry system (SMILES) codes for the initial input, which allows us to assess whether geometry optimization is necessary for reliable results. The XGBoost model also begins with the SMILES representations of the molecules but uses molecular descriptors instead of geometry optimizations. As a result, the best model tested (crystal graph convolutional neural network with Merck molecular force field-94) has an error of 1.15 EACN units of the true EACN for unknown data with the errors skewed toward zero and an R² score of 0.9

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Investigating Tropical Versus Extratropical Influences on the Southern Hemisphere Tropical Edge in the Unified Model

Abstract Since the late 1970s, observations have shown a widening of the tropical Hadley cell (HC) circulation. State‐of‐the‐art climate models reproduce the general trend along with a projected continuous expansion. Discrepancies in expansion rates of observation‐ and model‐based studies have been attributed to differences in applied methods, natural variability and model shortcomings. Furthermore, the driving influence of tropical or extratropical processes on these changes is not well understood. All of this highlights the dynamical mechanisms and the region of origin controlling the tropical width are still insufficiently understood. Here we examine the influence of systematic model biases of the atmosphere‐only Unified Model (UM) onto the simulation of the Southern Hemisphere (SH) tropical edge. We utilize nudged experiments with prescribed sea surface temperatures, where potential temperature and horizontal winds are relaxed back to ERA‐Interim reanalysis for a 20‐year period in selected regions. Correcting model biases in the tropics and extratropics separately allows us to dissect the dominant remote impacts of present model errors onto the SH tropical edge simulation. The experiments are applied to established tropical width metrics ranging from near‐surface to upper‐level metrics capturing the poleward flank of the HC. We find both regions work remotely to reduce errors in the UM fields and location of the tropical edge. Surprisingly, correcting the extratropical biases, south of 45°S, more consistently improves the tropical width across the metrics and seasons than nudging the tropics (10°N–10°S). These findings demonstrate the substantial role of extratropical influences in locating the SH tropical edge.

54 ENVIRONMENTAL SCIENCES↗

A unified thermionic and thermionic-field emission (TE–TFE) model for ideal Schottky reverse-bias leakage current

We present a unified thermionic emission (TE) and thermionic-field emission (TFE) model for the ideal reverse-bias leakage current in Schottky junctions. The unified TE–TFE analytical model advances upon previous analytical TFE models by Murphy–Good and Padovani–Stratton, which are the two most widely adopted models by the community, in two major aspects: (i) the applicability of the TFE expression therein is extended to near-zero surface electric fields by an error-function correction, allowing for the calculation of the total current by a nontrivial sum of TE (over-the-barrier current) and TFE (below-the-barrier current) contributions; therefore, an accurate description of the TE-to-TFE transition region is captured analytically for the first time; (ii) image-force lowering is considered with much-simpler correction terms. Comparisons with the reference numerical model show that the unified TE–TFE model has excellent accuracy, as well as a 10 000× reduction in computation time. The unified model is further tested against experimental data from Schottky barrier diodes based on Si, 4H-SiC, GaN, and β-Ga 2 O 3 , revealing accurate extractions of barrier heights and correct descriptions of the ideal reverse leakage characteristics. With the extended applicable range, improved accuracy, and computational efficiency, the unified TE–TFE model is highly valuable for the design and analysis of devices based on Schottky junctions, as well as for potential integration in technology computer-aided design (TCAD) tools.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Linearised Fokker–Planck collision model for gyrokinetic simulations

We introduce a gyrokinetic, linearised Fokker–Planck collision model that satisfies conservation laws and is accurate at arbitrary collisionalities. The differential test-particle component of the operator is exact; the integral field-particle component is approximated using a spherical harmonic and a modified Laguerre polynomial expansion developed by Hirshman and Sigmar (1976 Phys. Fluids 19 1532). The numerical methods of the implementation in the δf-gyrokinetic code stella (Barnes et al 2019 J. Comput. Phys. 391 365–80) are discussed, and conservation properties of the operator are demonstrated. The collision model is then benchmarked against the collision model of the gyrokinetic solver GS2 in the limiting cases of a reduced test-particle collision operator and energy- and momentum-conserving operator. The accuracy of the full collision model is investigated by solving the parallel Spitzer-Härm problem for the transport coefficients. It is shown that retaining collisional energy flux and higher-order terms in the field-particle operator reduces errors in the transport coefficients from 10%–25% for a simple momentum- and energy-conserving model to under 1%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantum Simulation of the First-Quantized Pauli-Fierz Hamiltonian

We provide an explicit recursive divide-and-conquer approach for simulating quantum dynamics and derive a discrete first-quantized nonrelativistic QED Hamiltonian based on the many-particle Pauli-Fierz Hamiltonian. We apply this recursive divide-and-conquer algorithm to this Hamiltonian and compare it to a concrete simulation algorithm that uses qubitization. Our divide-and-conquer algorithm, using lowest-order Trotterization, scales for fixed grid spacing as O ~ ( Λ N 2 η 2 t 2 / ϵ ) for grid size N , η particles, simulation time t , field cutoff Λ , and error ϵ . Our qubitization algorithm scales as O ~ ( N ( η + N ) ( η + Λ 2 ) t log ( 1 / ϵ ) ) . This shows that even a naive partitioning and low-order splitting formula can yield, through our divide-and-conquer formalism, superior scaling to qubitization for large Λ . We compare the relative costs of these two algorithms on systems that are relevant for applications such as the spontaneous emission of photons and the photoionization of electrons. We observe that for different parameter regimes, one method can be favored over the other. Finally, we give new algorithmic and circuit-level techniques for gate optimization, including a new way of implementing a group of multicontrolled- X gates that can be used for better analysis of circuit cost. Published by the American Physical Society 2024

Mukhopadhyay, Priyanka (ORCID:0000000164639100)↗

Ambient-Frequency-Data Based System-Level Inertia Estimation Using Physical Equation and its Practice on Hawaii Islands

Here, in this paper, a practical ambient-frequency-data-based inertia estimation method using a physical equation is proposed and validated by real measurement data from Hawaii island grids. With high renewable penetration, accurate inertia estimation is important and urgent. Ambient frequency oscillation always exists in power grids, so the proposed method has advantages of real-time inertia estimation and no need for additional disturbances. This paper first developed the physical equation for inertia estimation to offer a clear mechanism for easy implementation in practice. To apply the proposed method in actual grids, a practical method to extract the ambient frequency oscillation from frequency measurement is further proposed. The inertia estimation using the physical equation is validated by KIUC simulation data and HECO field data, in which error rates are around 2% and 8%, respectively. Practical inertia estimation is challenging due to the large amounts of resources contributing to the power grid's effective inertia, but the method provided in this paper can offer a novel way for practical inertia estimation, which can help renewable penetration to boost carbon-free grid.

14 SOLAR ENERGY↗

BUQEYE guide to projection-based emulators in nuclear physics

The BUQEYE collaboration (Bayesian Uncertainty Quantification: Errors in Your effective field theory) presents a pedagogical introduction to projection-based, reduced-order emulators for applications in low-energy nuclear physics. The term emulator refers here to a fast surrogate model capable of reliably approximating high-fidelity models. As the general tools employed by these emulators are not yet well-known in the nuclear physics community, we discuss variational and Galerkin projection methods, emphasize the benefits of offline-online decompositions, and explore how these concepts lead to emulators for bound and scattering systems that enable fast and accurate calculations using many different model parameter sets. We also point to future extensions and applications of these emulators for nuclear physics, guided by the mature field of model (order) reduction. All examples discussed here and more are available as interactive, open-source Python code so that practitioners can readily adapt projection-based emulators for their own work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Truly conserving with conservative remapping methods

Abstract. Conservative mapping of data from one horizontal grid to another should preserve certain integral or mean properties of the original data. This may be essential in some model applications, including ensuring realistic exchange of energy and mass between coupled model components. It can also be essential for certain types of analysis, such as evaluating how far a system is from an equilibrium state. For some common grids, existing remapping algorithms may fail to perfectly represent the shapes and sizes of grid cells, which leads to errors in the remapped fields. A procedure is presented here that enables users to rely on the mapping weights generated by remapping algorithms but corrects for their deficiencies. With this procedure, for a given pair of source and destination grids, a single set of remapping weights can be applied to remap any variable, including those with grid cells that are partially or fully masked.

58 GEOSCIENCES↗

Dissipation Enables Strongly Detuning-Dependent Interference in Pulsed Dynamical Decoupling

One of the defining features of pulsed dynamical decoupling is its suppression of a driven qubit's sensitivity to static detuning errors between the drive field and qubit resonance. In this paper, we show that dissipation, in the form of excited-state decay, can change this behavior entirely, producing an interference signal with a strong detuning dependence. This signal arises from decay during driven evolution and relies on coherence retained by the qubit after such a decay event. We develop analytical and numerical models that capture the underlying mechanism and observe this same dissipation-induced detuning dependence experimentally in both a free-space strontium atom interferometer and a superconducting transmon qubit system. We also use this dissipation-induced detuning dependence as the basis for a new spectroscopic technique called Dissipative Carr-Purcell Spectroscopy (DCPS) and compare it with a traditional Ramsey sequence. Our results establish a regime of pulsed dynamical decoupling in which dissipation reshapes, rather than merely degrades, coherent control, and we expect these dynamics to be relevant to a wide range of quantum systems.

DeRose, Kenneth [Northwestern U.; Fermilab] (ORCID↗

Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models

Abstract. Strongly coupled nonlinear phenomena such as those described by Earth system models (ESMs) are composed of multiple component models with independent mesh topologies and scalable numerical solvers. A common operation in ESMs is to remap or interpolate component solution fields defined on their computational mesh to another mesh with a different combinatorial structure and decomposition, e.g., from the atmosphere to the ocean, during the temporal integration of the coupled system. Several remapping schemes are currently in use or available for ESMs. However, a unified approach to compare the properties of these different schemes has not been attempted previously. We present a rigorous methodology for the evaluation and intercomparison of remapping methods through an independently implemented suite of metrics that measure the ability of a method to adhere to constraints such as grid independence, monotonicity, global conservation, and local extrema or feature preservation. A comprehensive set of numerical evaluations is conducted based on a progression of scalar fields from idealized and smooth to more general climate data with strong discontinuities and strict bounds. We examine four remapping algorithms with distinct design approaches, namely ESMF Regrid (Hill et al., 2004), TempestRemap (Ullrich and Taylor, 2015), generalized moving least squares (GMLS) (Trask and Kuberry, 2020) with post-processing filters, and WLS-ENOR (Li et al., 2020). By repeated iterative application of the high-order remapping methods to the test fields, we verify the accuracy of each scheme in terms of their observed convergence order for smooth data and determine the bounded error propagation using challenging, realistic field data on both uniform and regionally refined mesh cases. In addition to retaining high-order accuracy under idealized conditions, the methods also demonstrate robust remapping performance when dealing with non-smooth data. There is a failure to maintain monotonicity in the traditional L2-minimization approaches used in ESMF and TempestRemap, in contrast to stable recovery through nonlinear filters used in both meshless GMLS and hybrid mesh-based WLS-ENOR schemes. Local feature preservation analysis indicates that high-order methods perform better than low-order dissipative schemes for all test cases. The behavior of these remappers remains consistent when applied on regionally refined meshes, indicating mesh-invariant implementations. The MIRA intercomparison protocol proposed in this paper and the detailed comparison of the four algorithms demonstrate that the new schemes, namely GMLS and WLS-ENOR, are competitive compared to standard conservative minimization methods requiring computation of mesh intersections. The work presented in this paper provides a foundation that can be extended to include complex field definitions, realistic mesh topologies, and spectral element discretizations, thereby allowing for a more complete analysis of production-ready remapping packages.

58 GEOSCIENCES↗

GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution during polycrystalline grain formation

High fidelity simulations of grain formation in alloys are an indispensable tool for process-to-mechanical-properties characterization. Such simulations, however, can be computationally expensive as they require fine spatial and temporal discretizations. Their cost becomes an obstacle to parametric studies and ensemble runs and ultimately makes downstream tasks like optimal control and uncertainty quantification challenging. To enable such downstream tasks, we introduce GrainNN, an efficient and accurate reduced-order model for epitaxial grain growth in additive manufacturing conditions. GrainNN is a sequence-to-sequence long-short-term-memory (LSTM) deep neural network that evolves the dynamics of manually crafted features. Its innovations are (1) an attention mechanism with grain-microstructure-specific transformer architecture; and (2) an overlapping combination of several clones of the network to generalize to grain configurations that are different from those used for training. This design enables GrainNN to predict grain formation for unseen physical parameters, grain number, domain size and geometry. Furthermore, GrainNN not only reconstructs the quantities of interest but also can be pointwise accurate. In our numerical experiments, we use a polycrystalline phase field method to both generate the training data and assess GrainNN. For multiparametric, ensemble simulations with many grains, GrainNN can be orders of magnitude faster than phase field simulations, while delivering 5%–15% pointwise error. Additionally, this speedup includes the cost of the phase field simulations for generating training data.

36 MATERIALS SCIENCE↗

Improved single-particle phase-space distributions for viscous fluid dynamic models of relativistic heavy ion collisions

Comparison of hydrodynamic calculations with experimental data inevitably requires a model for converting the fluid to particles. For shear viscous fluids, several different conversion models have been proposed, such as the quadratic Grad corrections, the Strickland-Romatschke (SR) ansatz, self-consistent shear corrections from linearized kinetic theory, or corrections from the relaxation time approach. We show, via comparison to nonlinear 2 → 2 kinetic theory evolution, that even for low specific shear viscosities 0.03 ≲ $\textit{η/s}$ ≲ 0.2 , these four models have varying accuracy and still significant errors in reproducing particle phase space densities from hydrodynamic fields. Moreover, we demonstrate that the overall reconstruction error of additive shear viscous $f = f_{eq} + δf$ models dramatically reduces by up to one order of magnitude, if one ensures through exponentiation that $\textit{f}$ is always positive. Further, we also illustrate how even more accurate viscous $\textit{δf}$ models can be constructed by incorporating the first time derivatives of hydrodynamic fields to account for the past evolution of the system. Such time derivatives are readily available in hydrodynamic simulations, though usually not included in the output. Though our comparisons are limited to a one-component massless system undergoing a (0 + 1)-dimensional (0 + 1D) longitudinal boost-invariant expansion, we expect that the improved models will be useful in 2 + 1D and 3 + 1D hydrodynamic studies as well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Application of radiochromic gel dosimetry to commissioning of a megavoltage research linear accelerator for small–field animal irradiation studies

To develop and implement an efficient and accurate commissioning procedure for small-field static beam animal irradiation studies on an MV research linear accelerator (Linatron-M9) using radiochromic gel dosimetry. The research linear accelerator (Linatron-M9) is a 9 MV linac with a static fixed collimator opening of 5.08 cm diameter. Lead collimators were manually placed to create smaller fields of 2 × 2 cm 2 , 1 × 1 cm 2 , and 0.5 × 0.5 cm 2 . Relative dosimetry measurements were performed, including profiles, percent depth dose (PDD) curves, beam divergence, and relative output factors using various dosimetry tools, including a small volume ionization chamber (A14), GAFCHROMIC™ EBT3 film, and Clearview gel dosimeters. The gel dosimeter was used to provide a 3D volumetric reference of the irradiated fields. The Linatron profiles and relative output factors were extracted at a reference depth of 2 cm with the output factor measured relative to the 2 × 2 cm 2 reference field. Absolute dosimetry was performed using A14 ionization chamber measurements, which were verified using a national standards laboratory remote dosimetry service. Absolute dosimetry measurements were confirmed within 1.4% (k = 2, 95% confidence = 5%). The relative output factor of the small fields measured with films and gels agreed with a maximum relative percent error difference between the two methods of 1.1 % for the 1 × 1 cm 2 field and 4.3 % for the 0.5 × 0.5 cm 2 field. These relative errors were primarily due to the variability in the collimator positioning. The measured beam profiles demonstrated excellent agreement for beam size (measured as FWHM), within approximately 0.8 mm (or less). Film measurements were more accurate in the penumbra region due to the film’s finer resolution compared with the gel dosimeter. Following the van Dyk criteria, the PDD values of the film and gel measurements agree within 11% in the buildup region starting from 0.5 cm depth and within 2.6 % beyond maximum dose and into the fall-off region for depths up to 5 cm. The 2D beam profile isodose lines agree within 0.5 mm in all regions for the 0.5 × 0.5 cm 2 and the 1 × 1 cm 2 fields and within 1 mm for the larger field of 2 × 2 cm 2 . The 2D PDD curves agree within approximately 2% of the maximum in the typical therapy region (1–4 cm) for the 1 × 1 cm 2 and 2 × 2 cm 2 and within 5% for the 0.5 × 0.5 cm 2 field. This work provides a commissioning process to measure the beam characteristics of a fixed beam MV accelerator with detailed dosimetric evaluation for its implementation in megavoltage small animal irradiation studies. Radiochromic gel dosimeters are efficient small-field relative dosimetry tools providing 3D dose measurements allowing for full representation of dose, dosimeter misalignment corrections and high reproducibility with low inter-dosimeter variability. Altogether, radiochromic gels are valuable for fast, full relative dosimetry commissioning in comparison to films for application in high-energy small-field animal irradiation studies.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Discrete modeling of a transformer with ALEGRA

We report progress on a task to model transformers in ALEGRA using the “Transient Magnetics” option. We specifically evaluate limits of the approach resolving individual coil wires. There are practical limits to the number of turns in a coil that can be numerically modeled, but calculated inductance can be scaled to the correct number of turns in a simple way. Our testing essentially confirmed this “turns scaling” hypothesis. We developed a conceptual transformer design, representative of practical designs of interest, and that focused our analysis. That design includes three coils wrapped around a rectangular ferromagnetic core. The secondary and tertiary coils have multiple layers. The tertiary has three layers of 13 turns each; the secondary has five layers of 44 turns; the primary has one layer of 20 turns. We validated the turns scaling of inductance for simple (one-layer) coils in air (no core) by comparison to available independent calculations for simple rectangular coils. These comparisons quantified the errors versus reduced number of turns modeled. For more than 3 turns, the errors are <5%. The magnetic field solver failed to converge (within 5000 iterations) for >10 turns. Including the core introduced some complications. It was necessary to capture the core surfaces in thin grid sheaths to minimize errors in computed magnetic energy. We do not yet have quantitative benchmarks with which to compare, but calculated results are qualitatively reasonable.

42 ENGINEERING↗

Correlation effects in magic-angle twisted bilayer graphene: An auxiliary-field quantum Monte Carlo study

Magic-angle twisted bilayer graphene (MATBG) presents a fascinating platform for investigating the effects of electron interactions in topological flat bands. The Bistritzer-MacDonald (BM) model provides a simplified quantitative description of the flat bands. Introducing long-range Coulomb interactions leads to an interacting BM (IBM) Hamiltonian, a momentum-space continuum description which offers a very natural starting point for many-body studies of MATBG. Accurate and reliable many-body computations in the IBM model are challenging, however, and have been limited mostly to special fillings or smaller lattice sizes. We employ a state-of-the-art auxiliary-field quantum Monte Carlo (AFQMC) method to study the IBM model, which constrains the sign problem to enable accurate treatment of large system sizes. We determine ground-state properties and quantify errors compared to mean-field theory calculations. Our calculations identify correlated metal states and their competition with the insulating Kramers intervalley-coherent state at both half-filling and charge neutrality. Additionally, we investigate one- and three-quarter fillings, and examine the effect of many-body corrections beyond single Slater determinant solutions. We discuss the effect that details of the IBM Hamiltonian have on the results, including different forms of double-counting corrections, and the need to establish and precisely specify many-body Hamiltonians to allow more direct and quantitative comparisons with experiments in MATBG. Published by the American Physical Society 2025

Xiao, Zhi-Yu (ORCID:0000000219531579)↗

Magnetic field mapping of inaccessible regions using physics-informed neural networks

A difficult problem concerns the determination of magnetic field components within an experimentally inaccessible region when direct field measurements are not feasible. In this paper, we propose a new method of accessing magnetic field components using non-disruptive magnetic field measurements on a surface enclosing the experimental region. Magnetic field components in the experimental region are predicted by solving a set of partial differential equations (Ampere’s law and Gauss’ law for magnetism) numerically with the aid of physics-informed neural networks (PINNs). Prediction errors due to noisy magnetic field measurements and small number of magnetic field measurements are regularized by the physics information term in the loss function. We benchmark our model by comparing it with an older method. The new method we present will be of broad interest to experiments requiring precise determination of magnetic field components, such as searches for the neutron electric dipole moment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗