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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 37 records · Page 2

Self-consistent simulation of resistive kink instabilities with runaway electrons

A new fluid model for runaway electron simulation based on fluid description is introduced and implemented in the magnetohydrodynamics code M3D-C1, which includes self-consistent interactions between plasma and runaway electrons. The model utilizes the method of characteristics to solve the continuity equation for the runaway electron density with large convection speed, and uses a modified Boris algorithm for pseudo particle pushing. The model was employed to simulate magnetohydrodynamics instabilities happening in a runaway electron final loss event in the DIII-D tokamak. Nonlinear simulation reveals that a large fraction of runaway electrons get lost to the wall when kink instabilities are excited and form stochastic field lines in the outer region of the plasma. Plasma current converts from runaway electron current to Ohmic current, and get pinched at the magnetic axis. Here, given the good agreement with experiment, the simulation model provides a reliable tool to study macroscopic plasma instabilities in existence of runaway electron current, and can be used to support future studies of runaway electron mitigation strategies in ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Active Learning of Microgrid Frequency Dynamics Using Neural Ordinary Differential Equations

Accurate frequency modelling of inverter‐based resource (IBR)‐dominated power systems is crucial for ensuring stable, reliable and resilient operations, particularly given their inherent low‐inertia characteristics and fast dynamics that traditional swing equation‐based models inadequately capture. This paper explores neural ordinary differential equations (Neural ODEs) as a computationally efficient, data‐driven framework for modelling power system frequency dynamics, specifically within microgrids integrating high penetrations of distributed energy resources (DERs). The developed neural ODEs framework incorporates a neural network architecture designed to capture input dynamics. By actively perturbing the system with a known signal, the Python‐based neural ODEs framework was trained using measured system states and inputs, without the need for detailed system information. The framework, tested on a model of the Cordova, AK, microgrid, achieved a goodness of fit ranging from 60% to 99% across different state variables and maintained a mean square error in the 10 -6 p.u. range under square and step excitation signals. The proposed approach demonstrated robustness to measurement noise and initial condition variations while maintaining low computational complexity suitable for real‐time power system control applications. Furthermore, transfer learning enabled the neural ODEs model to adapt to the following changes in system topology or generator dispatch, highlighting its effectiveness for dynamic microgrids with frequently evolving configurations and diverse DERs.

Aryal, Tara [South Dakota State Univ., Brookings, ↗

AWCC Simulations

Neutron well counters provide a means to measure fissile mass by detecting coincident neutrons, which is a unique signature to fission. For coincidence counting, mass is determined using a calibration curve established with items that have the same material characteristics. Multiplicity analysis solves the point model equations for mass using known detector parameters. In both cases, mass measurements may exhibit a bias due to item characteristics and should be corrected for. Experiments can be done to estimate bias and material effects, but they require having both the well counter and the material well defined. In pursuit of estimating measurement bias and uncertainty in a High Efficiency Neutron Counter (HENC), an MCNP simulation was matched to measurements performed with an Active Well Coincidence Counter (AWCC) to de ne a neutron source term. The neutron source term will be used to predict measurement performance of similar material types in a HENC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A New Method for Deriving Composition of S-type Asteroids from Noisy and Incomplete Near-infrared Spectra

The surface composition of S-type asteroids can be determined using band parameters extracted from their near-infrared (NIR) spectra (0.7–2.50 μm) along with spectral calibrations derived from laboratory samples. In the past, these empirical equations have been obtained by combining NIR spectra of meteorite samples with information about their composition and mineral abundance. For these equations to give accurate results, the characteristics of the laboratory spectra they are derived from should be similar to those of asteroid spectral data (i.e., similar signal-to-noise ratio (S/N) and wavelength range). Here we present new spectral calibrations that can be used to determine the mineral composition of ordinary chondrite-like S-type asteroids. Contrary to previous work, the S/N of the ordinary chondrite spectra used in this study has been decreased to recreate the S/N typically observed among asteroid spectra, allowing us to obtain more realistic results. In addition, the new equations have been derived for five wavelength ranges encompassed between 0.7 and 2.50 μm, making it possible to determine the composition of asteroids with incomplete data. The new spectral calibrations were tested using band parameters measured from the NIR spectrum of asteroid (25143) Itokawa, and comparing the results with laboratory measurements of the returned samples. We found that the spectrally derived olivine and pyroxene chemistry, which are given by the molar contents of fayalite (Fa) and ferrosilite (Fs), are in excellent agreement with the mean values measured from the samples (Fa{sub 28.6±1.1} and Fs{sub 23.1±2.2}), with a maximum difference of 0.6 mol% for Fa and 1.4 mol% for Fs.

79 ASTRONOMY AND ASTROPHYSICS↗

A High-Order Eulerian–Lagrangian Runge–Kutta Finite Volume (EL–RK–FV) Method for Scalar Nonlinear Conservation Laws

Abstract We present a class of high-order Eulerian–Lagrangian Runge–Kutta finite volume methods that can numerically solve Burgers’ equation with shock formations, which could be extended to general scalar conservation laws. Eulerian–Lagrangian (EL) and semi-Lagrangian (SL) methods have recently seen increased development and have become a staple for allowing large time-stepping sizes. Yet, maintaining relatively large time-stepping sizes post shock formation remains quite challenging. Our proposed scheme integrates the partial differential equation on a space-time region partitioned by linear approximations to the characteristics determined by the Rankine–Hugoniot jump condition. We trace the characteristics forward in time and present a merging procedure for the mesh cells to handle intersecting characteristics due to shocks. Following this partitioning, we write the equation in a time-differential form and evolve with Runge–Kutta methods in a method-of-lines fashion. High-resolution methods such as ENO and WENO-AO schemes are used for spatial reconstruction. Extension to higher dimensions is done via dimensional splitting. Numerical experiments demonstrate our scheme’s high-order accuracy and ability to sharply capture post-shock solutions with large time-stepping sizes.

Chen, Jiajie↗

The high-density equation of state in heavy-ion collisions: constraints from proton flow

Abstract A set of different equations of state is implemented in the molecular dynamics part of a non-equilibrium transport simulation (UrQMD) of heavy-ion collisions. It is shown how different flow observables are affected by the density dependence of the equation of state. In particular, the effects of a phase transition at high density are explored, including an expected reduction in mean $$m_T$$ m T . We also show that an increase in $$v_2$$ v 2 is characteristic for a strong softening of the equation of state. The phase transitions with a low coexistence density, $$n_{\text {CE}}<4 n_0$$ n CE < 4 n 0 , show a distinct minimum in the slope of the directed flow as a function of the beam energy, which would be a clear experimental signal. By comparing our results with experimental data, we can exclude any strong phase transition at densities below $$4n_0$$ 4 n 0 .

74 ATOMIC AND MOLECULAR PHYSICS↗

Recent progress on the APOLLO3 calculation scheme for the FLUOLE2 experiment

Studies of the neutron fluence on reactor pressure vessel and the correlated reactor lifetime issues require very good knowledge of the neutron source distribution in the reactor core and especially in the peripheral region. The FLUOLE2 experiment offers an appropriate starting configuration to investigate the possibility of using the APOLLO3 deterministic code with a two-step calculation scheme. It enables us to calculate a pin-by-pin neutron source distribution in the core, then to carry out the neutron propagation from the core to neutron detectors. In this paper, we focus on a calculation scheme dedicated to the determination of core neutron source distribution using APOLLO3 with the SHEM281 energy mesh, a Method of Characteristics (MOC) to solve the transport equation for the lattice computation step and a 20-groups 3D computation using the MINARET SN solver of APOLLO3. Reactivity and pin-by-pin reaction rate results have been analyzed. Results obtained with both lattice and core computations show a good agreement with those produced through a reference calculation using the TRIPOLI-4 Monte Carlo transport code. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Development and Validation of a Latent Thermal Energy Storage Model Using Modelica

An abundance of research has been performed to understand the physics of latent thermal energy storage with phase change material. Some analytical and numerical findings have been validated by experiments, but there are few free and open-source models available to the general public for use in systems simulation and analysis. The Modelica programming language is a good avenue to make such models available, because it is object-oriented, equation-based, declarative, and acausal. These characteristics have enabling the creation of component model libraries that can be used to build larger system simulations for design analysis. The authors have previously developed a numerical framework to model phase change thermal storage and have validated model predictions with experiments. The objectives of this paper are to describe the transfer of the numerical framework to an implementation in a Modelica component model and to validate the Modelica model with data from the experiment and the original numerical framework.

25 ENERGY STORAGE↗

Lectures on statistical mechanics

Presented here is a transcription of the lecture notes from Professor Allan N. Kaufman’s graduate statistical mechanics course Physics 212A and 212B at the University of California Berkeley from the 1972–1973 academic year. 212A addressed equilibrium statistical mechanics with topics: fundamentals (micro-canonical and sub-canonical ensembles, adiabatic law and action conservation, fluctuations, pressure, and virial theorem), classical fluids and other systems (equation of state, deviations from ideality, virial coefficients and van der Waals potential, canonical ensemble and partition function, quasistatic evolution, grand-canonical ensemble and partition function, chemical potential, simple model of a phase transition, quantum virial expansion, numerical simulation of equations of state, and phase transition), chemical equilibrium (systems with multiple species and chemical reactions, law of mass action, Saha equation, chemical equilibrium including ionization and excited states), and long-range interactions (including Coulomb, dipole, and gravitational interactions, Debye–Hückel theory, and shielding). 212B addressed nonequilibrium statistical mechanics with topics: fundamentals (definitions: realizations, moments, characteristic function, and discrete variables), Brownian motion (Langevin equation, fluctuation–dissipation theorem, spatial diffusion, Boltzmann’s H-theorem), Liouville and Klimontovich equations, Landau equation (derivation, elaboration, and H-theorem, and irreversibility), Markov processes and Fokker–Planck equation (derivations of the Fokker–Planck equation and a master equation), linear response and transport theory (linear Boltzmann equation, linear response theory of Kubo and Mori, relation of entropy production to electrical conductivity, transport relations and coefficients, normal mode solutions of the transport equations, sketch of a generalized Langevin equation method for transport theory), and an introduction to nonequilibrium quantum statistical mechanics.

plasma dynamics↗

Third-body stabilization of supercritical CO 2 in CO oxidation: development and application of a ReaxFF force field for the CO/O/CO 2 system

Supercritical CO 2 (scCO 2 ) plays a crucial role as a solvent in separation processes, advanced power cycles, and materials processing. Nonetheless, the atomistic comprehension of how the dense scCO 2 matrix influences the fundamental reaction of carbon monoxide (CO) is still insufficiently explored. Experimental studies and molecular dynamics (MD) simulations frequently fail to detect the highly reactive, transient intermediates, such as atomic oxygen (O), that drive these reactions. Here, to address this issue, we have developed a novel ReaxFF reactive force field for the CO 2 /CO/O system. The force field parameters were calibrated using density functional theory and second-order Møller-Plesset calculations to model CO 2 crystal properties, intermolecular interactions, bond dissociation curves, and reaction energy barriers. The force field reproduces the cohesive energy of the CO 2 crystal, the pressure characteristics of bulk scCO 2 , the equation-of-state behavior over a wide pressure–density range, the pressure dependence of the C–O bond length under compression, and the structural properties of liquid and scCO 2 , as documented by experiments, ab-initio MD, and prominent non-reactive models. The force field was subsequently applied to study the CO + O → CO 2 reaction. In a dilute environment, the reaction is inefficient as the newly formed CO 2 rapidly dissociates due to excess kinetic and potential energy acquired from the exothermic reaction. Conversely, in a dense scCO 2 environment, the surrounding matrix acts as an efficient third body, stabilizing the emerging CO2 product via molecular collisions. Statistical analysis confirms an average excess energy dissipation of 133.9 ± 3.6 kcal/mol over 112.4 ± 17.9 ps. Kinetic energy decomposition reveals that ∼ 92% of the excess kinetic energy is stored in internal (rotational and vibrational) degrees of freedom. This ReaxFF force field establishes a mechanistic foundation for third-body stabilization in dense reactive environments.

Chowdhury, Emdadul Haque [Pennsylvania State Univ.↗

Complementing a continuum thermodynamic approach to constitutive modeling with symbolic regression

Here, an interpretable machine learning method, physics-informed genetic programming-based symbolic regression (P-GPSR), is integrated into a continuum thermodynamic approach to developing constitutive models. The proposed strategy for combining a thermodynamic analysis with P-GPSR is demonstrated by generating a yield function for an idealized material with voids, i.e., the Gurson yield function. First, a thermodynamic-based analysis is used to derive model requirements that are exploited in a custom P-GPSR implementation as fitness criteria or are strongly enforced in the solution. The P-GPSR implementation improved accuracy, generalizability, and training time compared to the same GPSR code without physics-informed fitness criteria. The yield function generated through the P-GPSR framework is in the form of a composite function that describes a class of materials and is characteristically more interpretable than GPSR-derived equations. The physical significance of the input functions learned by P-GPSR within the composite function is acquired from the thermodynamic analysis. Fundamental explanations of why the implemented P-GPSR capabilities improve results over a conventional GPSR algorithm are provided.

42 ENGINEERING↗

A small heterocyclic molecule as a multistate transistor: a quantum many-body approach

Weakly coupled molecular junctions are an active and important field of research due to their non-linear charge carrier transport. In this study, we investigate transport properties in a weakly coupled molecule, B 2 C 2 N 2 H 6 , using a combined quantum many-body approach and kinetic (master) equations. Various non-linear current–voltage characteristics such as negative differential conductance (NDC), rectifications, and Coulomb staircase, which are the hallmarks of multistate transport devices, have been obtained. We further explore the effect of different perturbations such as gate voltage and perpendicular magnetic field on molecular transport. Depending on the strength of the applied perturbing field, several phenomena such as current switching, and suppression of NDC, have been realized in the device. This study demonstrates small molecules as promising components in next-generation nano-devices.

36 MATERIALS SCIENCE↗

Design of a 3rd Order Lumped-Element Filtering Attenuator

This paper presents a novel filtering attenuator (filtenuator) concept, which allows for adjustable passband attenuation and filtering characteristics in a single design. The mathematical equations relating the desired passband loss to required resistance values are provided and validated with ideal circuit simulations. A third-order Chebyshev static filtenuator is designed at 1 GHz with multiple values of attenuation using lumped-element components as a proof of concept. Simulated and measured results for a 3 dB filtenuator show good agreement and several attenuation levels are shown to validate the concept. The proposed static filtenuator has advantages of ease of modification, compact size, and low cost, which are necessities in meeting the needs of reducing size, weight, power, and cost (SWaP-C) in future radio frequency transceivers.

Filter, Attenuator, Band-pass Filter (BPF), Lumped↗

Parallel-in-Time Solution of Hyperbolic PDE Systems via Characteristic-Variable Block Preconditioning

We consider the parallel-in-time solution of both linear and nonlinear hyperbolic partial differential equation (PDE) systems in one spatial dimension. In the nonlinear setting, the discretized equations are solved with a preconditioned residual iteration based on a global linearization. The linear(ized) equation systems are approximately solved parallel-in-time using a block preconditioner applied in the characteristic variables of the underlying linear(ized) hyperbolic PDE. This change of variables is motivated by the observation that intervariable coupling between characteristic variables is weak, at least locally where spatio-temporal variations in the eigenvectors of the associated flux Jacobian are sufficiently small, while that between the original variables is not. For an ℓ-dimensional system of PDEs, applying the preconditioner consists of solving a sequence of ℓ scalar linear(ized)-advection-like problems, each associated with a different characteristic wave-speed in the underlying linear(ized) PDE. Furthermore, we approximately solve these linear advection problems using multigrid reduction-in-time (MGRIT); however, any other suitable parallel-in-time method could be used. Numerical examples are shown for the (linear) acoustics equations in heterogeneous media and for the (nonlinear) shallow water equations and Euler equations of gas dynamics with shocks and rarefactions. For many test problems, the solver converges in just a handful of iterations and with mesh-independent convergence rates.

97 MATHEMATICS AND COMPUTING↗

Charge Conservation beyond Uniformity: Spatially Inhomogeneous Electromagnetic Response in Periodic Solids

Nonlinear electromagnetic response functions have reemerged as a crucial tool for studying quantum materials, due to recently appreciated connections between optical response functions, quantum geometry, and band topology. Most attention has been paid to responses to spatially uniform electric fields, relevant to low-energy optical experiments in conventional solid state materials. However, magnetic and magnetoelectric phenomena are naturally connected by responses to spatially varying electric fields due to Maxwell’s equations. Furthermore, in the emerging field of moiré materials, characteristic lattice scales are much longer, allowing spatial variation of optical electric fields to potentially have a measurable effect in experiments. In order to address these issues, we develop a formalism for computing linear and nonlinear responses to spatially inhomogeneous electromagnetic fields. Starting with the continuity equation, we derive an expression for the second-quantized current operator that is manifestly conserved and model independent. Crucially, our formalism makes no assumptions on the form of the microscopic Hamiltonian and so is applicable to model Hamiltonians derived from tight-binding or calculations. We then develop a diagrammatic Kubo formalism for computing the wave vector dependence of linear and nonlinear conductivities, using Ward identities to fix the value of the diamagnetic current order by order in the vector potential. We apply our formula to compute the magnitude of the Kerr effect at oblique incidence for a model of a moiré-Chern insulator and demonstrate the experimental relevance of spatially inhomogeneous fields in these systems. We further show how our formalism allows us to compute the (orbital) magnetic multipole moments and magnetic susceptibilities in insulators. Turning to nonlinear response, we use our formalism to compute the second-order transverse response to spatially varying transverse electric fields in our moiré-Chern insulator model, with an eye toward the next generation of experiments in these systems. Published by the American Physical Society 2024

Physics↗

Secondary battery management system

A method and system for managing a battery system. The method including receiving at least one measured characteristic of the battery over a pre-defined time horizon from the at least one sensor, receiving at least one estimated characteristic of the battery from a electrochemical-based battery model based on differential algebraic equations, determining a cost function of a Moving Horizon Estimation based on the at least one measured characteristic and the at least one estimated characteristic, updating the electrochemical-based battery model based on the cost function, estimating at least one state of the at least one battery cell by applying the electrochemical-based battery model, and regulating at least one of charging or discharging of the battery based on the estimation of the at least one state of the at least one battery cell.

MirTabatabaei, Anahita↗

Mathematics of Gas Ingress of Hermetic Packages

Herein, we have derived a gas ingress and egress equation from the first principles of ideal gases. This work is intended to benefit the hermetic microelectronics packaging community, but it may be applied to other fields that require a deep understanding of gas ingress and egress dynamics. The equation outlined herein encompasses package material properties, package characteristics, hermetic testing conditions, and service conditions. It serves as a practical utility for calculating package pressure changes due to gas ingress and egress and, therefore, a power tool for component and system service life predictions.

42 ENGINEERING↗