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NASA NTRS2018

Applications of the Dynamic N-Dimensional K-Vector

The n-dimensional k-vector (NDKV) is an appealing alternative to binary tress for resolving complex queries in large relational databases. The method has excelled in several applications involving static databases. The present paper extends the theory supporting the NDKV to handle dynamic databases, where the data is updated frequently. This includes deleting records, adding new entries, or editing existing elements. The merit of this new version of the NDKV, the dynamic n-dimensional k-vector (DNDKV), is that it is no longer necessary to recompute the entire k-vector (the main structure that indexes the data) every time a record changes. The algorithm updates the four constituents of the standard NDKV on the ﬂy: the database, sorted database, index, and k-vector tables. As a result, the DNDKV becomes comparable in terms of capabilities and ﬂexibility to stateof-the-art storage engines relying on structured query languages (SQL). The performance of the DNDKV is assessed by running typical read/write operations on a database that contains millions of pre-computed missions to celestial bodies. This database requires frequent updates whenever an orbit solution is reﬁned or new bodies are discovered. The DNDKV is faster than rebuilding the k-vector tables completely, provided that the number of elements being added or removed is not excessively large. Direct runtime comparisons with MySQL suggest that the DNDKV is several times faster for reading but might be slower for writing and updating the database. One limit of the technique is the elements being added must be within the range of the current k-vector tables. If this is not the case, the technique cannot be used and the k-vector tables must be rebuilt from scratch.

Mortari, Daniele↗

DOE OSTI2021

Ruling Out the Onset of Color Transparency up to Q2 = 14.2 GeV2 in Quasielastic 12C(e,e'p) Scattering

Color Transparency (CT) is a prediction of QCD that at high momentum transfer Q2, a system of quarks which would normally interact strongly with nuclear matter could form a small color-neutral object whose compact transverse size would be maintained for some distance, passing through the nucleus undisturbed. A clear signature of CT would be a dramatic rise in nuclear transparency T with increasing Q2. CT emerges as a deviation from Glauber multiple scattering theory, which predicts constant T. While a rise in nuclear transparency would provide an unequivocal validation of QCD factorization theorems, the complex nature of nuclear interactions renders its observation difficult to predict. The E12-06-107 experiment at JLab measured T in quasielastic electron-proton scattering with carbon-12 and liquid hydrogen targets, for Q2 between 8.0 and 14.2 GeV2 , a range over which models of CT predicted that T might differ appreciably from Glauber calculations. Supported in part by US DOE grant DE-FG02-03ER41240.

Matter, John↗

NASA NTRS1996

Interface Configuration Experiments (ICE) Explore the Effects of Microgravity on Fluids

The Interface Configuration Experiment (ICE) is actually a series of experiments that explore the striking behavior of liquid-vapor interfaces (i.e., fluid surfaces) in a low gravity environment under which major shifts in liquid position can arise from small changes in container shape or contact angle. Although these experiments are designed to test current mathematical theory, there are numerous practical applications that could result from these studies. When designing fluid management systems for space-based operations, it is important to be able to predict the locations and configurations that fluids will assume in containers under low-gravity conditions. The increased ability to predict, and hence control, fluid interfaces is vital to systems and/or processes where capillary forces play a significant role both in space and on the Earth. Some of these applications are in general coating processes (paints, pesticides, printing, etc.), fluid transport in porous media (ground water flows, oil recovery, etc.), liquid propellant systems in space (liquid fuel and oxygen), capillary-pumped loops and heat pipes, and space-based life-support systems. In space, almost every fluid system is affected, if not dominated, by capillarity. Knowledge of the liquid-vapor interface behavior, and in particular the interface shape from which any analysis must begin, is required as a foundation to predict how these fluids will react in microgravity and on Earth. With such knowledge, system designs can be optimized, thereby decreasing costs and complexity, while increasing performance and reliability. ICE has increased, and will continue to increase this knowledge, as it probes the specific peculiarities of current theory upon which our current understanding of these effects is based. Several versions of ICE were conducted in NASA Lewis Research Center's drop towers and on the space shuttle during the first and second United States Microgravity Laboratory missions (USML-1 and USML-2). Additional tests are planned for the space shuttle and for the Russian Mir space station. These studies will focus on interfacial problems concerning surface existence, uniqueness, configuration, stability, and flow characteristics.

Source record↗

DOE OSTI2023

Antiferromagnetic Fe Te 2 1 T - phase formation at the Sb 2 Te 3 / Ni 80 Fe 20 interface

Bilayer topological insulator/ferromagnet (TI/FM) heterostructures are promising for spintronic applications due to their low switching energy and therefore power efficiency. Until recently, the reactivity of TI with FM films was overlooked in the spin orbit-torque literature, even though there are reports that it is energetically favorable for TIs to react with transition metals and form interfacial layers. Here, in this study we fabricated a TI/FM heterostructure comprised of molecular beam epitaxy grown Sb 2 Te 3 and DC sputtered Ni 80 Fe 20 . Broadband ferromagnetic resonance revealed spin-pumping evident by the significant enhancement in Gilbert damping, which is likely a signature of the topological surface states or the presence of large spin-orbit-coupling in the adjacent Sb 2 Te 3 . With low-temperature magnetometry, an exchange bias is observed which indicates an exchange interaction between an antiferromagnet (AFM) and an adjacent FM. Cross-section high-angle annular dark field scanning transmission electron microscopy (HAADF-STEM) characterization of the Sb 2 Te 3 - Ni 80 Fe 20 bilayer revealed a complex interface showing diffusion of Fe and Ni into the Sb 2 Te 3 film yielding the formation of a FeTe 2 1T-type structural phase. Furthermore, density functional theory calculations revealed that the FeTe 2 1T-phase has an AFM ground state. Due to experimental limitations in the electron energy loss spectroscopy measurements precise chemistry of the interfacial phase could not be determined, therefore it is possible that the FeTe 2 1T and/or an intermixed (Fe 1-x Ni x )Te 2 1T is the AFM interfacial phase contributing to exchange bias in the system. This work emphasizes the chemical complexity of TI/FM interfaces that host novel, metastable magnetic topological phases and require more in-depth studies of other similar interfaces.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1995

Large HAWT wake measurement and analysis

From the theoretical fluid dynamics point of view, the wake region of a large horizontal-axis wind turbine has been defined and described, and numerical models of wake behavior have been developed. Wind tunnel studies of single turbine wakes and turbine array wakes have been used to verify the theory and further refine the numerical models. However, the effects of scaling, rotor solidity, and topography on wake behavior are questions that remain unanswered. In the wind tunnel studies, turbines were represented by anything from scaled models to tea strainers or wire mesh disks whose solidity was equivalent to that of a typical wind turbine. The scale factor compensation for the difference in Reynolds number between the scale model and an actual turbine is complex, and not typically accounted for. Though it is wise to study the simpler case of wakes in flat topography, which can be easily duplicated in the wind tunnel, current indications are that wind turbine farm development is actually occurring in somewhat more complex terrain. Empirical wake studies using large horizontal-axis wind turbines have not been thoroughly composited, and, therefore, the results have not been applied to the well-developed theory of wake structure. The measurement programs have made use of both in situ sensor systems, such as instrumented towers, and remote sensors, such as kites and tethered, balloonborne anemometers. We present a concise overview of the work that has been performed, including our own, which is based on the philosophy that the MOD-2 turbines are probably their own best detector of both the momentum deficit and the induced turbulence effect downwind. Only the momentum deficit aspects of the wake/machine interactions have been addressed. Both turbine power output deficits and wind energy deficits as measured by the onsite meteorological towers have been analyzed from a composite data set. The analysis has also evidenced certain topographic influences on the operation of spatially diverse wind turbines.

Miller, A. H.↗

NASA NTRS1989

Analytic theory for the selection of 2-D needle crystal at arbitrary Peclet number

An accurate analytic theory is presented for the velocity selection of a two-dimensional needle crystal for arbitrary Peclet number for small values of the surface tension parameter. The velocity selection is caused by the effect of transcendentally small terms which are determined by analytic continuation to the complex plane and analysis of nonlinear equations. The work supports the general conclusion of previous small Peclet number analytical results of other investigators, though there are some discrepancies in details. It also addresses questions raised on the validity of selection theory owing to assumptions made on shape corrections at large distances from the tip.

Tanveer, Saleh↗

NASA NTRS1989

Analytic theory for the selection of a two-dimensional needle crystal at arbitrary Peclet number

Tanveer, S.↗

DOE OSTI2021

Hydro-chemo-mechanical phase field formulation for corrosion induced cracking in reinforced concrete

Steel corrosion induced cracking in reinforced concrete structures is often caused by volumetric straining at the steel-concrete interface. This volumetric strain is mainly controlled by the rate of generation of corrosion product, which depends on the diffusion of Cl{sup −} and dissolved O{sub 2} as well as the chemical reaction at the steel-concrete interface. While many numerical modeling techniques have been proposed to tackle this complex phenomenon, most have been limited to using staggered solution schemes, where the diffusion, chemical reaction, mechanical strain, and crack fields are solved for separately. Unfortunately, such approaches introduce numerical errors that can lead to unrealistic predictions. Therefore, a coupled solution, is needed to remove the formulation induced errors and understand this complex phenomenon. To provide a unifying solution framework for corrosion induced cracking in reinforced concrete, a phase field formulation is presented and implemented with FEM algorithms. The governing equations are derived from the system's free energy and Fick's law of diffusion. The proposed formulation was first validated in 1D by comparing the modeling results with the semi-analytical solution approximated via Laurent series to avoid singularities in the complex domain. 2D plane strain solutions to the embedded rebar undergoing corrosion induced cracking with pre-cracks are also presented and compared with the approximated solutions from linear elastic fracture mechanics theory (LEFM). The modeling of crack propagation enabled by the proposed formulation is also presented along with parametric studies to reveal the roles of the fracture toughness and permeability of the concrete on the corrosion induced cracking. A case study was also conducted on H-pile steel with concrete jackets to demonstrate the feasibility of modeling corrosion induced fracture in reinforced concrete structures with complex steel-concrete interfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Role of Hydrogen-bonded Bimolecular Formic Acid–Formate Complexes for Formic Acid Decomposition on Copper: A Combined First-Principles and Microkinetic Modeling Study

Hydrogen bonding interactions alter the nanoscale reaction mechanisms of many chemistries. Yet, it remains unclear how they affect heterogeneously catalyzed decomposition of formic acid (FA), a reaction of intense interest since FA is a promising hydrogen carrier. In this work, we elucidate how hydrogen bonding affects the reaction mechanisms for FA decomposition on Cu(111) by combining first-principles density functional theory calculations to calculate reaction energetics, Latin-hypercube sampling to elucidate stable high-coverage adsorbate configurations, and coverage self-consistent mean-field microkinetic models to predict reaction kinetics. We demonstrate that hydrogen-bonded complexes of FA with formate (bimolecular FA–HCOO complexes) can play a dominant role in FA decomposition. Specifically, our first-principles calculations show that hydrogen bonding of FA with HCOO may stabilize the crucial monodentate HCOO intermediate and the transition states for HCOO decomposition, especially at low coverages. We predict that, depending on the reaction conditions, 40–80% of the reaction flux goes through pathways involving the bimolecular FA–HCOO complexes. Additionally, the active site for FA decomposition on Cu(111) involves a high coverage (~0.4 monolayers (ML)) of these complexes, which unexpectedly stabilize intermediates and transition states via van der Waals interactions. Our work provides molecular insights consistent with previous experimental observations on supported Cu/Al 2 O 3 catalysts. This paves the way toward the development of novel catalysts for FA decomposition as well as for other industrially important chemistries with intermediates capable of hydrogen bonding, such as ammonia electrooxidation and CO 2 hydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

An effective field theory for muon conversion and muon decay-in-orbit

Muon conversion is one of the best probes of charged lepton flavor violation. The experimental limit is soon expected to improve by four orders of magnitude, thus calling for precise predictions of the shape of the signal spectrum. Equally important are precise predictions for muon decay-in-orbit, the main background for muon conversion. While the calculation of electromagnetic corrections to the two processes above the nuclear scale does not involve significant challenges, it becomes substantially more complex below that scale due to multiple scales, bound-state effects and experimental setup. Here, we present a systematic framework that addresses these challenges by resorting to a series of effective field theories. Combining Heavy Quark Effective Theory (HQET), Non-Relativistic QED (NRQED), potential NRQED, Soft-Collinear Effective Theory I and II, and boosted HQET, we derive a factorization theorem and present the renormalization group equations. Our framework allows for the proper calculation of precise predictions for the rates of the two processes, with crucial implications for the upcoming muon conversion searches. We also provide the most accurate prediction of the signal shape for those searches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Probing the Electronic Structure of a Thorium Nitride Complex by Solid-State 15N NMR Spectroscopy

The solid-state 15N NMR powder spectra of the thorium nitride complex, [K(18-crown-6)(THF)2][(R2N)3Th(m-15N)(Th(NR2)3] ([K][1-15N], R = SiMe3), and the thorium amide complex, [Th(NR2)3(15NH2)] (2-15N) were recorded. The spectrum for [K][1-15N] represents the first reported solid-state 15N NMR data for an actinide nitride complex. The experimentally measured tensor spans are 847 ppm for [K][1-15N] and 237 ppm for 2-15N. Both shielding tensors exhibit a near-zero asymmetry parameter, which for [K][1-15N] is consistent with a local rotational symmetry of its 15N-labelled nitride ligand. For 2-15N, the lack of asymmetry can be rationalized by a quasi-free Th-NH2 bond rotation in the solid-state. DFT calculations overestimate the tensor span somewhat for [K][1-15N], but provide isotropic shifts in good agreement with both the solid-state and solution values for both complexes. Natural localized molecular orbital (NLMO) analyses of the nuclear shielding reveal that the larger tensor span in [K][1-15N] vs. 2-15N is primarily a consequence of more pronounced covalency of the N-Th bonds, and large spin-orbit coupling due to significant Th 5f orbital contribution to those bonds, impacting the principal components of the shielding tensor perpendicular to the Th-N-Th axis. Overall, our analysis confirms the involvement of the 5f orbitals in Th-N multiple bonds, and further demonstrates the value of solid-state NMR spectroscopy for interrogating actinide-ligand bonding.

actinides, covalent bonding, Nuclear Magnetic Reso↗

DOE OSTI2020

Parsimonious Inference Information-Theoretic Foundations for a Complete Theory of Machine Learning (CIS-LDRD Project 218313 Final Technical Report)

This work examines how we may cast machine learning within a complete Bayesian framework to quantify and suppress explanatory complexity from first principles. Our investigation into both the philosophy and mathematics of rational belief leads us to emphasize the critical role of Bayesian inference in learning well-justified predictions within a rigorous and complete extended logic. The Bayesian framework allows us to coherently account for evidence in the learned plausibility of potential explanations. As an extended logic, the Bayesian paradigm regards probability as a notion of degrees of truth. In order to satisfy critical properties of probability as a coherent measure, as well as maintain consistency with binary propositional logic, we arrive at Bayes' Theorem as the only justifiable mechanism to update our beliefs to account for empiracle evidence. Yet, in the machine learning paradigm, where explanations are unconstrained algorithmic abstractions, we arrive at a critical challenge: Bayesian inference requires prior belief. Conventional approaches fail to yield a consistent framework in which we could compare prior plausibility among the infinities of potential choices in learning architectures. The difficulty of articulating well-justified prior belief over abstract models is the provinence of memorization in traditional machine learning training practices. This becomes exceptionally problematic in the context of limited datasets, when we wish to learn justifiable predictions from only a small amount of data.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Model Parameter Development for Complex Materials: Species-Specific Diffusion Barriers in 316 Stainless Steel from Systematic DFT Calculations

Vacancy-mediated diffusion barriers in 316 stainless steel have been systematically calculated using density functional theory to provide essential parameters for mesoscale microstructure evolution models. A statistical sampling approach employing 210 nudged elastic band calculations across multiple special quasi-random structures captures the effects of local chemical environments in this concentrated alloy. The computational methodology addresses challenges specific to chemically disordered systems, including proper magnetic treatment throughout multi-step calculations and validation against experimental structural properties. The calculated activation barriers reveal clear species-dependent diffusion behavior with the hierarchy Ni >> Fe ˜ Cr >> Mo. Nickel exhibits the highest barriers (0.74–1.31 eV, mean 1.045 eV), confirming its role as the slowest-diffusing major component. Iron and chromium show similar moderate barriers averaging 0.587 eV and 0.522 eV, respectively. Remarkably, molybdenum demonstrates exceptionally low barriers (0.12–0.28 eV, mean 0.194 eV), suggesting much higher mobility than previously recognized and potentially significant implications for precipitation kinetics and microstructure evolution. The barrier ranges remain consistent across different 316 SS compositions, supporting parameter transferability for modeling applications. The overall mean barrier of 0.64 eV provides a practical approximation for phase field simulations, while species-specific values enable detailed treatments of diffusion-controlled processes. This systematic approach establishes a validated framework for generating diffusion parameters in other concentrated alloys where experimental data are limited, while providing the first systematic set of species-specific barriers for predictive modeling of 316 stainless steel microstructure evolution.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Theoretical Operational Model for Complex Experiments and its Invariance Theorems

We develop and systematize the Theoretical–Operational Model (TOM), a framework that treats preparation and measurement —including their operational residues— as intrinsic structures of physical theory. The central contribution is a principled geometric–algebraic organization of admissible operational deformations, formulated using quantum channels, renormalization-style flows, and information-geometric tools. Within this structure, operational residues and background processes are represented as effective morphisms attached to these operational components, whose invariants yield constraints on how theoretical parameters vary under specified classes of deformations. Illustrations drawn from muon–electron conversion, long-baseline neutrino oscillations, and quark–gluon-plasma phenomenology show how TOM maps operational effects into inferences about theoretical parameters, enables systematic cross-experimental comparisons, and stabilizes parameter estimation against defined deformation families. By embedding the operational layer—together with its residues—within a structured theoretical setting, TOM supports both theory testing and theory development, clarifying the conceptual relation between experimental realization and the physical quantities represented by the theory.

Pronskikh, Vitaly [Fermilab] (ORCID:00000002518174↗

DOE OSTI2020

$\testit{d}$-wave superconductivity and Bogoliubov-Fermi surfaces in Rarita-Schwinger-Weyl semimetals

In this work, we uncover the properties of complex tensor ($\textit{d}$-wave) superconducting order in three-dimensional Rarita-Schwinger-Weyl semimetals that host pseudospin-$\frac{3}{2}$ fermions at a fourfold linear band-crossing point. Although the general theory of $\textit{d}$-wave order was originally developed for materials displaying quadratic band touching, it directly applies to the case of semimetals with linear dispersion, several candidate compounds of which have been discovered experimentally very recently. The spin-$\frac{3}{2}$ nature of the fermions allows for the formation of spin-2 Cooper pairs which may be described by a complex second-rank tensor order parameter. In the case of linear dispersion, for the chemical potential at the Fermi point and at strong coupling, the energetically preferred superconducting state is the uniaxial nematic state, which preserves time-reversal symmetry and provides a full (anisotropic) gap for quasiparticle excitations. In contrast, at a finite chemical potential, we find that the usual weak-coupling instability is toward the “cyclic state,” well known from the studies of multicomponent Bose-Einstein condensates, which breaks time-reversal symmetry maximally, has vanishing average value of angular momentum, and features 16 small Bogoliubov-Fermi surfaces. The Rarita-Schwinger-Weyl semimetals provide therefore the first example of weakly coupled, three-dimensional, isotropic $\textit{d}$-wave superconductors where the $\textit{d}$-wave superconducting phase is uniquely selected by the quartic expansion of the mean-field free energy, and is not afflicted by the accidental degeneracy first noticed by Mermin over 40 years ago. We discuss the appearance and stability of the Bogoliubov-Fermi surfaces in absence of inversion symmetry in the electronic Hamiltonian, as in the case at hand.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

GFiRe—Gauge Field integrator for Reheating

We present a new numerical algorithm and code, GFiRe, for solving the nonlinear evolution of Abelian gauge fields coupled to complex scalar fields in homogeneous and isotropic spacetimes. We adopt a hybrid approach to solving the system: the spatial derivatives are discretized using standard Lattice Gauge Field Theory techniques, whereas the time evolution of the fields and scale factor is implemented with explicit, composite, symplectic integrators. An important property of our compound algorithm is that the discretized Gauss constraint is respected exactly, regardless of the order of the symplectic integrator. This remains true even when the background expansion is computed “self-consistently”; that is, when the expansion history is computed using spatial averaged components of the energy momentum tensor in the simulation volume. Hence, our code can also be used in cases where the fields dominate the energy density of the universe, for example, during reheating after inflation. We test the algorithm in scenarios of reheating where the inflaton is a complex scalar field with a potential ∝(2|Φ| 2 - v 2 ) 2 and is coupled to an Abelian gauge field. Tracing the evolution of the system through complex dynamics (including resonant excitation of fields, backreaction, formation of solitons, and changes in the equation of state) in a self-consistently expanding universe, we find the energy conservation violation (<10 -4 ) to be very stable and the Gauss constraint violation (<10 -6 ) to be dominated by differencing noise.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1993

LinAir: A multi-element discrete vortex Weissinger aerodynamic prediction method

LinAir is a vortex lattice aerodynamic prediction method similar to Weissinger's extended lifting-line theory, except that the circulation around a wing is represented by discrete horseshoe vortices, not a continuous distribution of vorticity. The program calculates subsonic longitudinal and lateral/directional aerodynamic forces and moments for arbitrary aircraft geometries. It was originally written by Dr. Ilan Kroo of Stanford University, and subsequently modified by the author to simplify modeling of complex configurations. The Polhamus leading-edge suction analogy was added by the author to extend the range of applicability of LinAir to low aspect ratio (i.e., fighter-type) configurations. A brief discussion of the theory of LinAir is presented, and details on how to run the program are given along with some comparisons with experimental data to validate the code. Example input and output files are given in the appendices to aid in understanding the program and its use. This version of LinAir runs in the VAX/VMS, Cray UNICOS, and Silicon Graphics Iris workstation environments at the time of this writing.

Durston, Donald A.↗

DOE OSTI2023

Machine Learning for First Principles Calculations of Material Properties for Ferromagnetic Materials

The investigation of finite temperature properties using Monte-Carlo (MC) methods requires a large number of evaluations of the system’s Hamiltonian to sample the phase space needed to obtain physical observables as function of temperature. DFT calculations can provide accurate evaluations of the energies, but they are too computationally expensive for routine simulations. To circumvent this problem, machine-learning (ML) based surrogate models have been developed and implemented on high-performance computing (HPC) architectures. In this paper, we describe two ML methods (linear mixing model and HydraGNN) as surrogates for first principles density functional theory (DFT) calculations with classical MC simulations. These two surrogate models are used to learn the dependence of target physical properties from complex compositions and interactions of their constituents. We present the predictive performance of these two surrogate models with respect to their complexity while avoiding the danger of overfitting the model. An important aspect of our approach is the periodic retraining with newly generated first principles data based on the progressive exploration of the system’s phase space by the MC simulation. The numerical results show that HydraGNN model attains superior predictive performance compared to the linear mixing model for magnetic alloy materials.

Eisenbach, Markus↗