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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 OSTI2019

Magnetohydrodynamical equilibria with current singularities and continuous rotational transform

We revisit the Hahm–Kulsrud–Taylor (HKT) problem, a classic prototype problem for studying resonant magnetic perturbations and 3D magnetohydrodynamical equilibria. We employ the boundary-layer techniques developed by Rosenbluth, Dagazian, and Rutherford (RDR) for the internal m = 1 kink instability, while addressing the subtle difference in the matching procedure for the HKT problem. Pedagogically, the essence of RDR's approach becomes more transparent in the reduced slab geometry of the HKT problem. We then compare the boundary-layer solution, which yields a current singularity at the resonant surface, to the numerical solution obtained using a flux-preserving Grad–Shafranov solver. The remarkable agreement between the solutions demonstrates the validity and universality of RDR's approach. Additionally, we show that RDR's approach consistently preserves the rotational transform, which hence stays continuous, contrary to a recent claim that RDR's solution contains a discontinuity in the rotational transform.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Ultrafast processing of pixel detector data with machine learning frameworks

Modern photon science performed at high repetition rate free-electron laser (FEL) facilities and beyond relies on 2D pixel detectors operating at increasing frequencies (towards 100 kHz at LCLS-II) and producing rapidly increasing amounts of data (towards TB/s). This data must be rapidly stored for offline analysis and summarized in real time for online feedback to the scientists. While at LCLS all raw data has been stored, at LCLS-II this would lead to a prohibitive cost; instead, enabling real time processing of pixel detector data (dark, gain, common mode, background, charge summing, subpixel position, photon counting, data summarization) allows reducing the size and cost of online processing, offline processing and storage by orders of magnitude while preserving full photon information. This could be achieved by taking advantage of the compressibility of sparse data typical for LCLS-II applications. Faced with a similar big data challenge a decade ago, computer vision stimulated revolutionary advances in machine learning hardware and software. We investigated if these developments are useful in the field of data processing for high speed pixel detectors and found that typical deep learning models and autoencoder architectures failed to yield useful noise reduction while preserving full photon information, presumably because of the very different statistics and feature sets in computer vision and radiation imaging. However, the raw performance of modern frameworks like Tensorflow inspired us to redesign in Tensorflow mathematically equivalent versions of the state-of-the-art, “classical” algorithms used at LCLS. The novel Tensorflow models resulted in elegant, compact and hardware agnostic code, gaining 1 to 2 orders of magnitude faster processing on an inexpensive consumer GPU, reducing by 3 orders of magnitude the projected cost of online analysis and compression without photon loss at LCLS-II. The novel Tensorflow models also enabled ongoing development of a pipelined hardware system expected to yield an additional 3 to 4 orders of magnitude speedup, necessary for meeting the data acquisition and storage requirements at LCLS-II, potentially enabling acquiring every single FEL pulse at full speed. Computer vision a decade ago was dominated by hand-crafted filters; their structure inspired the deep learning revolution resulting in modern deep convolutional networks; similarly, our novel Tensorflow filters provide inspiration for designing future deep learning models for ultrafast and efficient processing and classification of pixel detector images at FEL facilities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil

Fluid flow in the transonic regime finds relevance in aerospace engineering, particularly in the design of commercial air transportation vehicles. Computational fluid dynamics models of transonic flow for aerospace applications are computationally expensive to solve because of the high degrees of freedom as well as the coupled nature of the conservation laws. While these issues pose a bottleneck for the use of such models in aerospace design, computational costs can be significantly minimized by constructing special, structure-preserving surrogate models called reduced-order models. In this work, we propose a machine learning method to construct reduced-order models via deep neural networks and we demonstrate its ability to preserve accuracy with a significantly lower computational cost. In addition, our machine learning methodology is physics-informed and constrained through the utilization of an interpretable encoding by way of proper orthogonal decomposition. Application to the inviscid transonic flow past the RAE2822 airfoil under varying freestream Mach numbers and angles of attack, as well as airfoil shape parameters with a deforming mesh, shows that the proposed approach adapts to high-dimensional parameter variation well. Notably, the proposed framework precludes the knowledge of numerical operators utilized in the data generation phase, thereby demonstrating its potential utility in the fast exploration of design space for diverse engineering applications. Comparison against a projection-based nonintrusive model order reduction method demonstrates that the proposed approach produces comparable accuracy and yet is orders of magnitude computationally cheap to evaluate, despite being agnostic to the physics of the problem.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Servo-aero-gravo-elastic (SAGE) scaling and its application to a 13-MW downwind turbine

Reduced scale wind turbines can be extremely cost-effective to test new rotor concepts since prototype costs are heavily dependent on the rotor diameter. Ideally, the scaled model would have the same non-dimensional deflections, dynamics, and control behavior as the full-scale model. This would provide a high-fidelity demonstration of the full-scale performance, which is ideal if the full-scale turbine has significant aeroelastic interactions. To this end, servo-aero-gravo-elastic (SAGE) scaling is developed and applied to a 13-MW turbine that is scaled to a 20% scale model. The scaling preserves the tip-speed ratio, the rotor speed normalized by the flapping frequency, and the tip deflections normalized by the blade length. In addition, the controller employs the same control structure (gain-scheduled pitch control and variable speed torque control) and is scaled dynamically (e.g., matching non-dimensional time constant of the pitch angle, etc.). Furthermore, the thrust, gravity, and centrifugal moments are scaled such that the load angles are preserved as a function of a non-dimensional wind speed. However, the environmental scaling must consider differences in Reynolds number (since this parameter cannot be held constant) and subsequent changes in the axial induction factor. While the presented results showcase these differences during operational conditions, the non-dimensional tip deflections remain comparable through all wind speed ranges, indicating the viability of the SAGE scaling method in matching full-scale aeroelastic responses.

Kaminski, Meghan (ORCID:0000000322334784)↗
DOE OSTI2022

Restored Passivation after Complete Removal of Front Poly-Si Between the Grid in Poly-Si/SiO2 Front/Back Cells

This work explores the use of wet chemical etching to completely remove the front poly-Si layer between grid lines of a front/back poly-Si/SiO2 passivated contact device. The purpose of the work is to provide excellent passivation under the metal grid, but to also maximize Jsc by eliminating optical absorption in the front poly-Si. We show that after a high temperature anneal to distribute carriers in the poly-Si/SiO2/c-Si interface all of the poly-Si can be removed selectively with TMAH, using the SiO2 as an etch-stop layer. The etched surface can be repassivated back to its original level with the addition of a SiNx/Al2O3 stack grown on the preserved tunnelling oxide layer followed by a short forming gas anneal. Using symmetric 100 - 200 nm intrinsically doped poly-Si/SiO2 on textured n-type wafer templates we show absolute device efficiency enhancement from 15% to 21% by increasing the Jsc by 12 mA/cm2 after removing the front poly-Si and repassivating while effectively preserving the Voc, and FF of the device. IQE values are similar to PERC devices in the short wavelength range.

etching↗
DOE OSTI2022

Surface stability of SrNbO 3+δ grown by hybrid molecular beam epitaxy

4d transition metal oxides have emerged as promising materials for numerous applications including high mobility electronics. SrNbO 3 is one such candidate material, serving as a good donor material in interfacial oxide systems and exhibiting high electron mobility in ultrathin films. However, its synthesis is challenging due to the metastable nature of the d 1 Nb 4+ cation and the limitations in the delivery of refractory Nb. To date, films have been grown primarily by pulsed laser deposition (PLD), but development of a means to grow and stabilize the material via molecular beam epitaxy (MBE) would enable studies of interfacial phenomena and multilayer structures that may be challenging by PLD. To that end, SrNbO 3 thin films were grown using hybrid MBE for the first time using a tris(diethylamido)(tert-butylimido) niobium precursor for Nb and an elemental Sr source on GdScO 3 substrates. Varying thicknesses of insulating SrHfO 3 capping layers were deposited using a hafnium tert-butoxide precursor for Hf on top of SrNbO 3 films to preserve the metastable surface. Grown films were transferred in vacuo for x-ray photoelectron spectroscopy to quantify elemental composition, density of states at the Fermi energy, and Nb oxidation state. Ex situ studies by x-ray absorption near edge spectroscopy and scanning transmission electron microscopy illustrate that the SrHfO 3 capping plays an important role in preserving the crystalline quality of the material and the Nb 4d 1 metastable charge state under atmospheric conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Scalable learning of potentials to predict time-dependent Hartree–Fock dynamics

We propose a framework to learn the time-dependent Hartree–Fock (TDHF) inter-electronic potential of a molecule from its electron density dynamics. Although the entire TDHF Hamiltonian, including the inter-electronic potential, can be computed from first principles, we use this problem as a testbed to develop strategies that can be applied to learn a priori unknown terms that arise in other methods/approaches to quantum dynamics, e.g., emerging problems such as learning exchange–correlation potentials for time-dependent density functional theory. We develop, train, and test three models of the TDHF inter-electronic potential, each parameterized by a four-index tensor of size up to 60 × 60 × 60 × 60. Two of the models preserve Hermitian symmetry, while one model preserves an eight-fold permutation symmetry that implies Hermitian symmetry. Across seven different molecular systems, we find that accounting for the deeper eight-fold symmetry leads to the best-performing model across three metrics: training efficiency, test set predictive power, and direct comparison of true and learned inter-electronic potentials. All three models, when trained on ensembles of field-free trajectories, generate accurate electron dynamics predictions even in a field-on regime that lies outside the training set. To enable our models to scale to large molecular systems, we derive expressions for Jacobian-vector products that enable iterative, matrix-free training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A fractional calculus framework for open quantum dynamics: From Liouville to Lindblad to memory kernels

Open quantum systems exhibit dynamics ranging from unitary evolution to irreversible dissipation. While the Gorini–Kossakowski–Sudarshan–Lindblad equation uniquely characterizes Markovian completely positive and trace-preserving (CPTP) evolution, many physical platforms display non-Markovian features such as algebraic relaxation and coherence backflow. Fractional calculus provides a natural way to model such long-memory behavior through power-law temporal kernels introduced by fractional time derivatives. Here, we develop a unified framework that embeds fractional master equations within the broader hierarchy of open-system formalisms. The fractional equation forms a structured subclass of memory-kernel models, reduces to the Lindblad form at unit order, and, through Bochner–Phillips subordination, admits a CPTP representation as an average over Lindblad semigroups. Its resolvent structure further connects fractional dynamics to established non-Markovian approaches, including Nakajima–Zwanzig kernels and hierarchical equations of motion, providing a compact surrogate for long-memory effects. This formulation positions fractional calculus as a rigorous and practical language for modeling non-Markovian quantum dynamics in chemical physics and physical chemistry, providing a CPTP-preserving, computationally efficient surrogate for structured condensed-phase environments where long-time memory and dissipation play a central role.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Novel approach to general curvilinear coordinates for plasma fluid applications

In general geometry, plasma fluid equations include nonlinear geometric sources associated with fictitious forces, which pose significant challenges to computer simulations. We reformulate the plasma fluid hierarchy to rigorously preserve geometry and conservation properties critical to numerical simulations, while concealing the geometric sources. In their discrete form, the reformulated models conserve mass, angular momentum, and energy naturally, by simple analogy with the continuum equations. These conservation properties have minimal requirements in discrete space, namely, the anti-symmetry of the first derivative and the orthogonality of the scalar and cross products. By decoupling magnetic geometry, coordinate systems, and numerical discretization, this enables maximum flexibility while preserving physics fidelity. As a testbed, we apply the novel representation to the resistive magnetohydrodynamic system, which involves a complete set of curvilinear operations. We verify the correctness of the approach using steady state liquid metal flows and the classic Orszag–Tang vortex.

Halpern, Federico D. [General Atomics, San Diego, ↗
DOE OSTI2017

Deep melting reveals liquid structural memory and anomalous ferromagnetism in bismuth

As an archetypal semimetal with complex and anisotropic Fermi surface and unusual electric properties (e.g., high electrical resistance, large magnetoresistance, and giant Hall effect), bismuth (Bi) has played a critical role in metal physics. In general, Bi displays diamagnetism with a high volumetric susceptibility (~10 -4 ). Here in this paper, we report unusual ferromagnetism in bulk Bi samples recovered from a molten state at pressures of 1.4–2.5 GPa and temperatures above ~1,250 K. The ferromagnetism is associated with a surprising structural memory effect in the molten state. On heating, low-temperature Bi liquid (L) transforms to a more randomly disordered high-temperature liquid (L') around 1,250 K. By cooling from above 1,250 K, certain structural characteristics of liquid L' are preserved in L. Bi clusters with characteristics of the liquid L' motifs are further preserved through solidification into the Bi-II phase across the pressure-independent melting curve, which may be responsible for the observed ferromagnetism.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Elastocaloric signatures of symmetric and antisymmetric strain-tuning of quadrupolar and magnetic phases in DyB 2 C 2

The adiabatic elastocaloric effect measures the temperature change of a given system with strain and provides a thermodynamic probe of the entropic landscape in the temperature-strain space. Here, we demonstrate that the DC bias strain-dependence of AC elastocaloric effect allows decomposition of the latter into symmetric (rotation-symmetry-preserving) and antisymmetric (rotation-symmetry-breaking) strain channels, using a tetragonal f -electron intermetallic DyB 2 C 2 —whose antiferroquadrupolar order breaks local fourfold rotational symmetries while globally remaining tetragonal—as a showcase example. We capture the strain evolution of its quadrupolar and magnetic phase transitions using both singularities in the elastocaloric coefficient and its jumps at the transitions, and the latter we show follows a modified Ehrenfest relation. We find that antisymmetric strain couples to the underlying order parameter in a biquadratic (linear-quadratic) manner in the antiferroquadrupolar (canted antiferromagnetic) phase, which are attributed to a preserved (broken) global tetragonal symmetry, respectively. The broken tetragonal symmetry in the magnetic phase is further evidenced by elastocaloric strain-hysteresis and optical birefringence. Additionally, within the staggered quadrupolar order, the observed elastocaloric response reflects a quadratic increase of entropy with antisymmetric strain, analogous to the role magnetic field plays for Ising antiferromagnetic orders by promoting pseudospin flips. Our results demonstrate AC elastocaloric effect as a compact and incisive thermodynamic probe into the coupling between electronic degrees of freedom and strain in free energy, which holds the potential for investigating and understanding the symmetry of a wide variety of ordered phases in broader classes of quantum materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Preventing Reverse Engineering of Critical Industrial Data with DIOD

Business analytics augmented by artificial intelligence and machine learning (AI/ML) have revolutionized the role of data in the modern world. In recent years, businesses have incorporated data into their decision-making process for better prediction, risk-assessment, content creation, etc. While such businesses often seek to leverage the full use of their data through third-party AI/ML services, they are often hampered by the risks of data leaks, reverse-engineering, stolen technology, etc. that often have disastrous consequences for businesses and their stakeholders alike. Thus, there arises a need for data masking prior to its transmission that obfuscates proprietary information while preserving the information relevant for AI/ML applications. In order to meet the needs of industrial data which are significantly different from those of data warehouses, previous work proposed an efficient time and space-scalable data masking paradigm known as the deceptive infusion of data (DIOD) methodology. The present work expands upon this work by leveraging existing reverse-engineering capabilities to facilitate the decomposition of industrial data into its proprietary and AI/ML-relevant parts, referred to as fundamental and inference metadata respectively. Both sets of metadata are further obfuscated in accordance with the DIOD methodology to create the DIOD rendition of the industrial data, which is rendered immune to reverse-engineering by discarding proprietary information and only preserving AI/ML-relevant information. Additionally, constraints of the original DIOD manuscript are relaxed using mutual information by configuring the methodology to the target AI/ML application to unlock the full potential of the DIOD methodology. As an example, data from a nuclear reactor is transformed into that from a nonlinear spring-mass system with different levels of data masking as required by the generic system and the target application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Comparison of two Galerkin quadrature methods

Here, we compare two methods for generating Galerkin quadratures. In method 1, the standard S N method is used to generate the moment-to-discrete matrix and the discrete-to-moment matrix is generated by inverting the moment-to-discrete matrix. This is a particular form of the original Galerkin quadrature method. In method 2, which we introduce here, the standard S N method is used to generate the discrete-to-moment matrix and the moment-to-discrete matrix is generated by inverting the discrete-to-moment matrix. With an N-point quadrature, method 1 has the advantage that it preserves N eigenvalues and N eigenvectors of the scattering operator in a pointwise sense. With an N-point quadrature, method 2 has the advantage that it generates consistent angular moment equations from the corresponding S N equations while preserving N eigenvalues of the scattering operator. Our computational results indicate that these two methods are quite comparable for the test problem considered.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

The Legendre Polynomial Axial Expansion Method

This work presents a new formulation of the axial expansion transport method explicitly using Legendre polynomials for arbitrarily high-order expansions. This new formulation also features an alternative method of axial leakage calculation to allow for nonextruded flat source region meshes. This alternative axial leakage is introduced alongside a balance equation requirement to ensure that neutron balance is preserved in the coarse mesh for a given axial leakage formulation, which allows for effective coarse mesh finite difference acceleration. A matrix exponential table method is derived to allow for fast computations of arbitrarily high-order matrix exponentials for this work and precludes the need for further research into matrix exponential calculations for this method. Numerical results are presented that demonstrate the stability of the axial expansion method in systems with voidlike regions, showcase the speedup from matrix exponential tables, and investigate the axial convergence of the method in terms of both expansion order and mesh size.

Herring, Nicholas↗
DOE OSTI2014

The effect of radial migration on galactic disks

We study the radial migration of stars driven by recurring multi-arm spiral features in an exponential disk embedded in a dark matter halo. The spiral perturbations redistribute angular momentum within the disk and lead to substantial radial displacements of individual stars, in a manner that largely preserves the circularity of their orbits and that results, after 5 Gyr (∼40 full rotations at the disk scale length), in little radial heating and no appreciable changes to the vertical or radial structure of the disk. Our results clarify a number of issues related to the spatial distribution and kinematics of migrators. In particular, we find that migrators are a heavily biased subset of stars with preferentially low vertical velocity dispersions. This 'provenance bias' for migrators is not surprising in hindsight, for stars with small vertical excursions spend more time near the disk plane, and thus respond more readily to non-axisymmetric perturbations. We also find that the vertical velocity dispersion of outward migrators always decreases, whereas the opposite holds for inward migrators. To first order, newly arrived migrators simply replace stars that have migrated off to other radii, thus inheriting the vertical bias of the latter. Extreme migrators might therefore be recognized, if present, by the unexpectedly small amplitude of their vertical excursions. Our results show that migration, understood as changes in angular momentum that preserve circularity, can strongly affect the thin disk, but cast doubts on models that envision the Galactic thick disk as a relic of radial migration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

MPI-AMRVAC FOR SOLAR AND ASTROPHYSICS

In this paper, we present an update to the open source MPI-AMRVAC simulation toolkit where we focus on solar and non-relativistic astrophysical magnetofluid dynamics. We highlight recent developments in terms of physics modules, such as hydrodynamics with dust coupling and the conservative implementation of Hall magnetohydrodynamics. A simple conservative high-order finite difference scheme that works in combination with all available physics modules is introduced and demonstrated with the example of monotonicity-preserving fifth-order reconstruction. Strong stability-preserving high-order Runge-Kutta time steppers are used to obtain stable evolutions in multi-dimensional applications, realizing up to fourth-order accuracy in space and time. With the new distinction between active and passive grid cells, MPI-AMRVAC is ideally suited to simulate evolutions where parts of the solution are controlled analytically or have a tendency to progress into or out of a stationary state. Typical test problems and representative applications are discussed with an outlook toward follow-up research. Finally, we discuss the parallel scaling of the code and demonstrate excellent weak scaling up to 30, 000 processors, allowing us to exploit modern peta-scale infrastructure.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Experimental studies of a high-gradient X-band welded hard-copper split accelerating structure

We report on recent research on high-gradient radio frequency (RF) accelerating structures indicates that the use of hard copper alloys provides improvement in high gradient performance over annealed copper. Such structures are made by bonding individually manufactured parts. However, there are no well-established bonding techniques that preserve the hardness, surface finish and cleanliness required for high gradient operation. To preserve the copper hardness, RadiaBeam has developed a novel high-gradient split accelerating structure, based on electron beam welding joining technique. This technique provides efficient bonding with strong, clean welds and minimal thermal loading, while maintaining a clean inner RF environment. Our RF design and fabrication methodology limits the small heat affected zone to the outer cavity envelop, with virtually no distortions or thermal loading of critical RF surfaces. It also incorporates provisions to precisely control the gap despite conventional issues with weld joint shrinkage. To date we have manufactured and validated an RF accelerating structure joined by electron-beam welding that incorporates a novel open split design to significantly reduce the assembly complexity and cost. In this paper, we will present the electromagnetic design of this structure, discuss bonding, and present the results of high-power tests, where the accelerating gradients of 140 MV m -1 with surface peak fields of 400 MV m -1 were achieved for flat-top pulse length of 600 ns with an RF breakdown rate of 10 -4 1/(pulsecm).

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Atomic structure and Mott nature of the insulating charge density wave phase of 1T-TaS 2

Here, using x-ray pair distribution function (PDF) analysis and computer modeling, we explore structure models for the complex charge density wave (CDW) phases of layered 1T-TaS 2 that both well capture their atomic-level features and are amenable to electronic structure calculations. The models give the most probable position of constituent atoms in terms of 3D repetitive unit cells comprising a minimum number of Ta–S layers. Structure modeling results confirm the emergence of star-of-David (SD) like clusters of Ta atoms in the high-temperature incommensurate (IC) CDW phase and show that, contrary to the suggestions of recent studies, the low-temperature commensurate (C) CDW phase expands upon cooling thus reducing lattice strain. The C-CDW phase is also found to preserve the stacking sequence of Ta–S layers found in the room temperature, nearly commensurate (NC) CDW phase to a large extent. DFT based on the PDF refined model shows that bulk C-CDW 1T-TaS 2 also preserves the insulating state of individual layers of SD clusters, favoring the Mott physics description of the metal-to-insulator (NC-CDW to C-CDW) phase transition in 1T-TaS 2 . Our work highlights the importance of using precise crystal structure models in determining the nature of electronic phases in complex materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗