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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

DRACO: An Overview [Slides]

DRACO (Diffusion ReACtiOn) is a diffusion and chemistry code designed to: 1) Operate on 3D with an unstructured grid defining an arbitrary geometry of interacting parts. 2) Generate its own meshes and use meshes created by other software. 3)Model the transport of any number of diffusing quantities: Concentrations, pressures, temperature, etc. 4) Allow diffusion coefficients to depend in an arbitrary way on concentration, temperature, position, time, etc. 5) Model general chemistry between concentrations with arbitrary reaction rates. 6) Allow arbitrary initial conditions, boundary conditions, and sources/sinks. 7) Allow all of the above to be specified by the user.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

FSEN Reaction Rate Calculations in MCNP [Slides]

FSEN provides an opportunity to quickly calculate sensitivities to orthogonal measurements during integral experiments. Toy problem has been deployed to expand on verification of FSEN for reaction rate ratios. While there is decent agreement, further investigation must be done on multiplication’s impact on sensitivity vector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Scientific Discovery with Physics-Informed System Identification (Abbreviated Report)

My fellowship research focused on making physics-based simulations faster and more useful through machine learning. Many problems in science and engineering are governed by partial differential equations, but high-fidelity simulations are often too expensive to run repeatedly. I worked on improving Latent Space Dynamics Identification (LaSDI), a reduced-order modeling framework that compresses large simulation data sets into a smaller representation and then learns how that representation evolves over time. The motivation was to develop reduced models that remain accurate for more challenging systems, especially when predictions must remain reliable over long time intervals or when the underlying dynamics are more complicated than standard methods can easily handle. I also contributed to related work on Quandary, a high-performance software effort for simulation and control of open quantum systems, before focusing primarily on Latent Space Dynamics Identification methods. The main outcomes of the fellowship were two new algorithms (both of which were published), Rollout-LaSDI and Higher-Order LaSDI, together with supporting work on multi-stage Latent Space Dynamics Identification. Rollout-LaSDI improved long-term prediction by training the model to stay accurate over extended time horizons, and Higher-Order LaSDI broadened the method so it could model systems with higher-order time dynamics. My contributions to multistage Latent Space Dynamics Identification also helped show that its later training stages could be simplified without losing effectiveness, and that this behavior held across different model architectures and training strategies. Taken together, these advances improved the accuracy, flexibility, and practical value of reduced-order modeling tools for computational science.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Advancing Molecular Weight Determination of Lignin by Multi-Angle Light Scattering

Due to the complexity and recalcitrance of lignin, its chemical characterization is a key factor preventing the valorization of this abundant material. Multi-angle light scattering (MALS) is becoming a sought-after technique for absolute molecular weight (MW) determination of polymers and proteins. Lignin is a suitable candidate for MW determination via MALS, yet further investigation is required to confirm its absolute MW values and molecular size. Studies aiming to break down lignin into a variety of renewable products will benefit greatly from a simple and reliable determination method like MALS. Recent pioneering studies, discussed in this review, addressed several key challenges in lignin’s MW characterization. Nevertheless, some lignin-specific issues still need to be considered for in-depth characterization. This study explores how MALS instrumentation manages the complexities of determining lignin’s MW, e.g., with simultaneous fractionation and fluorescence interference mitigation. Additionally, we rationalize the importance of a more detailed light scattering analysis for lignin characterization, including aspects like the second virial coefficient and radius of gyration.

differential refractive index increment↗
NASA NTRS1980

Grid evolution in time asymptotic problems

A technique for generating systems of coordinates for solving time asymptotic problems is described which provides a simple way of moving the mesh points in physical space and reduces the error in the solution relative to that obtained using a fixed mesh. First order partial differential equations are formulated for the grid point velocity in transient problems. Local flow information and boundary motion are used to determine the interior grid point motion.

Rai, M. M.↗
NASA NTRS1983

Solar wind and coronal structure

Spectroscopic diagnostic techniques used to determine the coronal source region of the solar wind, and results of preliminary applications are examined. The topics reviewed are magnetic fields, coronal mass ejections, coronal holes, flow velocities, coronal temperatures, fine spatial structure, and future observational programs. The physical mechanisms responsible for plasma heating, solar-wind acceleration, the transport of mass momentum and energy, and the spatial differentiation of chemical abundances are also discussed. Among the data presented are Skylab's white-light coronagraph photograph of a coronal transient, X-ray photographs of the corona, and spectroheliograms showing bright points overlying polar plumes, and macrospicules.

Withbroe, G. L.↗
NASA NTRS1985

Fire-retardant decorative inks for aircraft interiors

Commercial and experimental fire retardants were screened as potential fire retardants for acrylic printing inks used on aircraft interior sandwich panels. The fire retardants are selected according to their physical properties and their thermostabilities. A criterion for selecting a more stable fire retardant is established. Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) are used to determine thermostabilities. Results show that the fire retardant formulations are more thermally stable than the acrylic ink control. It is determined that an ink formulation containing a brominated phenol and carboxy-terminated butadiene acrylonitrile which has been modified with a brominated polymeric additive (BPA), yields the highest limiting oxygen index (LOI) of all the compounds tested. All of the fire-retardant formulations have a higher oxygen index than the baseline acrylic ink.

Kourtides, D. A.↗
NASA NTRS1986

Physical and numerical sources of computational inefficiency in integration of chemical kinetic rate equations: Etiology, treatment and prognosis

The design of a very fast, automatic black-box code for homogeneous, gas-phase chemical kinetics problems requires an understanding of the physical and numerical sources of computational inefficiency. Some major sources reviewed in this report are stiffness of the governing ordinary differential equations (ODE's) and its detection, choice of appropriate method (i.e., integration algorithm plus step-size control strategy), nonphysical initial conditions, and too frequent evaluation of thermochemical and kinetic properties. Specific techniques are recommended (and some advised against) for improving or overcoming the identified problem areas. It is argued that, because reactive species increase exponentially with time during induction, and all species exhibit asymptotic, exponential decay with time during equilibration, exponential-fitted integration algorithms are inherently more accurate for kinetics modeling than classical, polynomial-interpolant methods for the same computational work. But current codes using the exponential-fitted method lack the sophisticated stepsize-control logic of existing black-box ODE solver codes, such as EPISODE and LSODE. The ultimate chemical kinetics code does not exist yet, but the general characteristics of such a code are becoming apparent.

Pratt, D. T.↗
NASA NTRS1995

Preliminary control system design and analysis for the Space Station Furnace Facility thermal control system

This report presents the Space Station Furnace Facility (SSFF) thermal control system (TCS) preliminary control system design and analysis. The SSFF provides the necessary core systems to operate various materials processing furnaces. The TCS is defined as one of the core systems, and its function is to collect excess heat from furnaces and to provide precise cold temperature control of components and of certain furnace zones. Physical interconnection of parallel thermal control subsystems through a common pump implies the description of the TCS by coupled nonlinear differential equations in pressure and flow. This report formulates the system equations and develops the controllers that cause the interconnected subsystems to satisfy flow rate tracking requirements. Extensive digital simulation results are presented to show the flow rate tracking performance.

Jackson, M. E.↗
NASA NTRS2024

Accelerating Continuous Variable Coherent Ising Machines Via Momentum

The Coherent Ising Machine (CIM) is a non-conventional architecture that takes inspiration from physical annealing processes to solve Ising problems heuristically. Its dynamics are naturally continuous and described by a set of ordinary differential equations that have been proven to be useful for the optimization of continuous variables nonconvex quadratic optimization problems. The dynamics of such Continuous Variable CIMs (CV-CIM) encourage optimization via optical pulses whose amplitudes are determined by the negative gradient of the objective; however, standard gradient descent is known to be trapped by local minima and hampered by poor problem conditioning. In this work, we propose to modify the CV-CIM dynamics using more sophisticated pulse injections based on tried-and-true optimization techniques such as momentum and Adam. Through numerical experiments, we show that the momentum and Adam updates can significantly speed up the CV-CIM’s convergence and improve sample diversity over the original CV-CIM dynamics. We also find that the Adam-CV-CIM’s performance is more stable as a function of feedback strength, especially on poorly conditioned instances, resulting in an algorithm that is more robust, reliable, and easily tunable. More broadly, we identify the CIM dynamical framework as a fertile opportunity for exploring the intersection of classical optimization and modern analog computing.

Ising Model↗
DOE OSTI2025

Status of the PrimEx $\eta$ experiment at Jefferson Lab

The GlueX detector in the experimental Hall D at Jefferson Lab offers a unique opportunity to perform a measurement of the decay width of eta mesons through the Primakoff effect. The experiment complements the physics program at Jefferson Lab on measuring the decay width of light pseudoscalar mesons via the Primakoff process. The goal of the experiment is to measure differential cross sections of eta mesons at forward angles using a beam of tagged photons incident on a liquid 4He target, which will be used for the extraction of the decay width. This measurement is vital for understanding fundamental properties like the ratios of the light quark masses and the eta - eta' mixing angle, and will provide an important test of chiral symmetry breaking in QCD. Our experimental results will help reduce uncertainties on partial widths of all other eta decays. The experiment collected data during three physics runs between 2019 and 2022. We will give an overview of the PrimEx eta experiment and the current status of our data analyses. We will also discuss the feasibility of conducting future Primakoff measurements in light of the recent upgrade of the GlueX forward calorimeter and the potential accelerator energy upgrade to 22 GeV.

Somov, Alexander↗
DOE OSTI2021

nn-PINNs: Non-Newtonian physics-informed neural networks for complex fluid modeling

Time- and rate-dependent material functions in non-Newtonian fluids in response to different deformation fields pose a challenge in integrating different constitutive models into conventional computational fluid dynamic platforms. Considering their relevance in many industrial and natural settings alike, robust data-driven frameworks that enable accurate modeling of these complex fluids are of great interest. The main goal is to solve the coupled Partial Differential Equations (PDEs) consisting of the constitutive equations that relate the shear stress to the deformation and fully capture the behavior of the fluid under various flow protocols with different boundary conditions. Here, in this work, we present non-Newtonian physics-informed neural networks (nn-PINNs) for solving systems of coupled PDEs adopted for complex fluid flow modeling. The proposed nn-PINN method is employed to solve the constitutive models in conjunction with conservation of mass and momentum by benefiting from Automatic Differentiation (AD) in neural networks, hence avoiding the mesh generation step. nn-PINNs are tested for a number of different complex fluids with different constitutive models and for several flow protocols. These include a range of Generalized Newtonian Fluid (GNF) empirical constitutive models, as well as some phenomenological models with memory effects and thixotropic timescales. nn-PINNs are found to obtain the correct solution of complex fluids in spatiotemporal domains with good accuracy compared to the ground truth solution. We also present applications of nn-PINNs for complex fluid modeling problems with unknown boundary conditions on the surface, and show that our approach can successfully recover the velocity and stress fields across the domain, including the boundaries, given some sparse velocity measurements.

42 ENGINEERING↗
DOE OSTI2023

Correspondence between open bosonic systems and stochastic differential equations

Bosonic mean-field theories can approximate the dynamics of systems of $n$ bosons provided that $n \gg 1$. Here, we show that there can also be an exact correspondence at finite $n$ when the bosonic system is generalized to include interactions with the environment and the mean-field theory is replaced by a stochastic differential equation. When the $n \to \infty$ limit is taken, the stochastic terms in this differential equation vanish, and a mean-field theory is recovered. Besides providing insight into the differences between the behavior of finite quantum systems and their classical limits given by $n \to \infty$, the developed mathematics can provide a basis for quantum algorithms that solve some stochastic nonlinear differential equations. We discuss conditions on the efficiency of these quantum algorithms, with a focus on the possibility for the complexity to be polynomial in the log of the stochastic system size. A particular system with the form of a stochastic discrete nonlinear Schrödinger equation is analyzed in more detail.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Minijet quenching in a concurrent jet + hydro evolution and the nonequilibrium quark-gluon plasma

Minijets, created by perturbative hard QCD collisions at moderate energies, can represent a significant portion of the total multiplicity of a heavy-ion collision event. Since their transverse momenta are initially larger than the typical saturation scale describing the bulk of the equilibrating quark-gluon plasma (QGP), they ought to be described through the physics of parton energy loss. Indeed, their typical stopping distances are larger than the usual hydrodynamization time, so they do not in general hydrodynamize at the same pace than the bulk of the collision. Therefore, in general minijets cannot be described solely by a unique preequilibrium stage that bridges the initial, overoccupied glasma state, with the hydrodynamical evolution. In this work we make use of a new concurrent minijet+hydrodynamic framework in which the properties of the hydrodynamically evolving QGP are modified due to the injection of energy and momentum from the minijets. We study the system for different choices of the minimum transverse momentum associated with minijet production. In order to achieve a realistic description of charged particle multiplicity, the amount of entropy associated to the low- x initial state needs to be reduced. Moreover, the fact that the injected momentum from the randomly oriented minijets is not correlated with the spatial gradients of the system reduces overall flow, and the value of the QGP transport coefficients needs to be reduced accordingly in order to describe the measured flow coefficients in experiments. They are, in effect, an important new source of fluctuations, resulting in a spikier, notably modified hydrodynamical evolution when compared to the scenario in which the presence of minijets is ignored. We avow that their abundance makes it necessary to include their physics in holistic descriptions of heavy-ion collisions. We discuss the impact of the minijets on a number of observables, such as p T spectra and p T -differential flow v n for a wide range of centrality classes. In contrast to elliptic, triangular or quadrangular flow, here we find that directed flow, v 1 , has the strongest potential to discriminate between different minijet production rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Rindler fluids from gravitational shockwaves

We study a correspondence between gravitational shockwave geometry and its fluid description near a Rindler horizon in Minkowski spacetime. Utilizing the Petrov classification that describes algebraic symmetries for Lorentzian spaces, we establish an explicit mapping between a potential fluid and the shockwave metric perturbation, where the Einstein equation for the shockwave geometry is equivalent to the incompressibility condition of the fluid, augmented by a shockwave source. Then we consider an Ansatz of a stochastic quantum source for the potential fluid, which has the physical interpretation of shockwaves created by vacuum energy fluctuations. Under such circumstance, the Einstein equation, or equivalently, the incompressibility condition for the fluid, becomes a stochastic differential equation. By smearing the quantum source on a stretched horizon in a Lorentz invariant manner with a Planckian width (similarly to the membrane paradigm), we integrate fluctuations near the Rindler horizon to find an accumulated effect of the variance in the round-trip time of a photon traversing the horizon of a causal diamond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

From clutter to clarity: Emergent neural operators via questionnaire metrics

Real-world datasets in chemical engineering and bioengineering processes—such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials—can often be unlabeled or disorganized, rendering the training of existing supervised learning models ineffective at learning the underlying dynamics. To salvage these datasets for decision-making, we first seek to obtain clarity from the cluttered data. Here, we present a framework for developing “structural” generative models, discovering emergent equations, and constructing efficient emulators from scrambled datasets by integrating unsupervised organizational learning techniques (Questionnaires) with advanced deep learning architectures (Deep Hidden Physics Models and Deep Operator Networks). Our approach is demonstrated on two illustrative model systems: (a) a 1D advection–diffusion partial differential equation representing a winding underground pipe and (b) an ensemble of Stuart–Landau oscillators, an agent-based system of coupled ordinary differential equations. In both cases, we successfully reconstruct meaningful spatial, temporal, and parameter embeddings from scrambled data, enabling good predictions of system dynamics. As a result, we highlight the framework’s potential for broader applications, enabling data-driven system identification in fields with inherently disorganized or hidden parameter spaces.

42 ENGINEERING↗
DOE OSTI2025

InAs sidewall tunnel diodes enabled by surface states

Negative differential resistance (NDR), where the device current decreases with increasing bias voltage, is a representative phenomenon where quantum mechanics induces counterintuitive physical behavior and offers promising applications such as high-frequency oscillators, amplifiers, and multilevel logic circuits. While the NDR behavior has been extensively studied in various materials and devices, the role of surface properties in NDR, particularly in InAs-based diodes, remains underexplored. In this work, we report the observation of NDR in vertically structured InAs p + n diodes that exhibit a peak-valley current ratio of ∼6, which is suitably high for applications. Circumference-normalized current–voltage characterization revealed that the NDR originates from band-to-band tunneling between the valence band of p + -InAs and the conduction band of an n + -InAs surface, where the n + surface is due to surface states on otherwise n − -InAs. In addition, by comparing devices with various surface passivation methods (without intentional passivation, benzocyclobutene polymer, and silicon nitride), we found that the surface termination significantly affects the NDR characteristics. We present an equivalent circuit model to explain the observed device behavior. These findings offer insights into surface-enabled NDR phenomena and present new knobs for engineering NDR devices.

Circuit theorems↗
DOE OSTI2023

Differential charge radii: Proton-neutron interaction effects

The analysis of self-consistency and proton-neutron interaction effects in the buildup of differential charge radii were carried out in covariant density functional theoretical calculations without pairing interaction on the example of selected configurations in the Pb isotopes. The proton-neutron interaction of neutron(s) added to the neutron 𝑁 = 126 core and the protons forming the 𝑍 = 82 proton core is responsible for a major contribution to the buildup of differential charge radii. It depends on the products of proton and neutron wave functions and thus on their nodal structure. This interaction leads to a redistribution of single-particle density of occupied proton states which in turn modifies the charge radii. Furthermore, the microscopic origin of this redistribution and its consequences for differential charge radii were investigated for the first time. Self-consistency effects affecting the shape of proton potential, total proton densities and the energies of the single-particle proton states provide only minor contribution to differential charge radii.

190 ≤ A ≤ 219↗