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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Designing Physicochemically‐Ordered Interphases for High‐Performance Composites

To enhance the mechanical properties of carbon fiber‐reinforced polymer composites, a physicochemical scaffold is designed incorporating microscopically architected chemically reactive nanofibers that act as a multiscale bridge between the carbon fibers and the matrix. Thermally activated nanofibers leverage their morphologically driven mechanochemical properties to form covalent bonds with adjacent polymer molecules, creating a co‐continuous network that dramatically enhances fiber‐matrix load transfer. By meticulously controlling the nanofiber architecture through variable surface area, functional group availability, and polymer chain alignment effects, the extent of covalent bonding between nanofibers and the matrix is manipulated ultimately resulting in improved carbon fiber‐matrix adhesion. Further, the concept was validated using polyacrylonitrile nanofibers within an acrylonitrile butadiene styrene matrix in a discontinuous carbon fiber‐reinforced composite system. Nanomechanical studies using atomic force microscopy and low‐field nuclear magnetic resonance spectroscopy confirmed immobilized, chemically transferred, and ordered nanostructures at the interphase. The resulting composites demonstrated ≈56% and ≈175% improvements in tensile strength and toughness, respectively, compared to composites without nanofiber. Comprehensive thermal, rheological, and X‐ray scattering analyses, along side all‐atomic molecular dynamics simulations, revealed the fundamental mechanisms behind these improvements in mechanical behavior. The versatility and efficacy of the approach have the potential to address longstanding interphase challenges in the composite industry.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗
DOE OSTI2023

Unveiling the catalytic mechanism of GTP hydrolysis in microtubules

Microtubules (MTs) are large cytoskeletal polymers, composed of αβ-tubulin heterodimers, capable of stochastically converting from polymerizing to depolymerizing states and vice versa. Depolymerization is coupled with hydrolysis of guanosine triphosphate (GTP) within β-tubulin. Hydrolysis is favored in the MT lattice compared to a free heterodimer with an experimentally observed rate increase of 500- to 700-fold, corresponding to an energetic barrier lowering of 3.8 to 4.0 kcal/mol. Mutagenesis studies have implicated α-tubulin residues, α:E254 and α:D251, as catalytic residues completing the β-tubulin active site of the lower heterodimer in the MT lattice. The mechanism for GTP hydrolysis in the free heterodimer, however, is not understood. Additionally, there has been debate concerning whether the GTP-state lattice is expanded or compacted relative to the GDP state and whether a “compacted” GDP-state lattice is required for hydrolysis. In this work, extensive quantum mechanics/molecular mechanics simulations with transition-tempered metadynamics free-energy sampling of compacted and expanded interdimer complexes, as well as a free heterodimer, have been carried out to provide clear insight into the GTP hydrolysis mechanism. α:E254 was found to be the catalytic residue in a compacted lattice, while in the expanded lattice, disruption of a key salt bridge interaction renders α:E254 less effective. The simulations reveal a barrier decrease of 3.8 ± 0.5 kcal/mol for the compacted lattice compared to a free heterodimer, in good agreement with experimental kinetic measurements. Additionally, the expanded lattice barrier was found to be 6.3 ± 0.5 kcal/mol higher than compacted, demonstrating that GTP hydrolysis is variable with lattice state and slower at the MT tip.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Machine-learning modeling of magnetization dynamics in quasi-equilibrium and driven metallic spin systems

Here, we present a perspective on recent progress in machine-learning (ML) force-field approaches for large-scale Landau–Lifshitz–Gilbert (LLG) simulations of metallic spin systems. Building on a generalization of the Behler–Parrinello (BP) architecture originally developed for quantum molecular dynamics, we develop scalable and transferable ML models that faithfully capture the complex, environment-dependent electron-mediated exchange fields characteristic of itinerant magnets. A central ingredient of this framework is the implementation of symmetry-aware magnetic descriptors based on group-theoretical bispectrum formalisms. Leveraging these ML force fields, LLG simulations faithfully reproduce hallmark non-collinear magnetic orders—such as the 120° and tetrahedral states—on the triangular lattice, and successfully capture the complex spin textures emerging in the mixed-phase states of a square-lattice double-exchange model under thermal quench. We further discuss a generalized potential theory that extends the BP formalism to incorporate both conservative and nonconservative electronic torques, thereby enabling ML models to learn nonequilibrium exchange fields from computationally demanding microscopic approaches such as nonequilibrium Green’s-function techniques. This extension yields quantitatively accurate predictions of voltage-driven domain-wall motion and establishes a foundation for quantum-accurate, multiscale modeling of nonequilibrium spin dynamics and spintronic functionalities.

Descriptors↗
NASA NTRSDate not supplied

Hierarchical Multiscale Process Modeling of A Textile Composite Y-Joint for the Aurora D8 Aircraft

Woven polymer matrix composites (PMCs) are widely used in aerospace applications for their favorable specific properties. However, the behavior of the inter- and intra-tow matrix during manufacturing of woven PMCs is difficult to isolate experimentally due to geometric and processing complexities. Classical closed-form homogenization approaches allow for composite thermos-chemo-mechanical properties to be characterized at any fiber volume fraction. In this work, virtual curing is applied to the inter- and intra-tow matrix materials of a plain weave repeating unit cell (RUC). Thermo-chemo-mechanical property evolution within the tows is calculated using the Concentric Cylinder Model (CCM) and the Rule of Mixtures (ROM). Curing is implemented through user-written subroutines within the commercial finite element method software Abaqus. Virtual curing results are compared with those from a linear-elastic thermal cool down simulation in Abaqus. Results indicate that tow property evolution during curing has a non-negligible effect on the final stress state.

curing↗
DOE OSTI2025

Influences of shock imprinting on mix in a 3D-printed porous media

Mixing of materials in porous media can cause a significant impact on fusion yield as previously demonstrated by the National Ignition Facility (NIF) MARBLE Campaign. Initially, the reactants are separated, with deuterium in the lattice struts and a tritium gas fill in the voids. Lattice parameters such as the strut thickness and relative pitch, provide a control for the mix parameters in the experiment. Los Alamos National Laboratory’s (LANL) BOSQUE project looks to better understand how the mix of the reactants and shell materials impact the fusion burn and resultant yield on various laser platforms. xRAGE’s Eulerian hydrodynamics and adaptive mesh refinement (AMR) provide the unique ability to study the impacts of multiscale features of complex lattice structures. This modeling provides the ability to measure shock front variations as the wave progress’ through a given media. Initial conditions of the lattice are essential to accurately model mix and burn measured by experiment. By varying the initial orientation and densities of these lattice regions the early time dynamics of how the shock is launched into the system is changed and advocates for the study of resulting effects. In this work, we will study the sensitivities of shock effects in varying 3D printed geometric systems and how these shocks alter the structure and mix in the lattice. We will discuss both preliminary experimental results and simulations to help plan and constrain future experiments where we will study the impact of different lattice geometries and lattice bulk densities. This work concludes with the relative impacts of lattice geometries on shock speeds at different bulk densities and the resultant mix widths due to those shock interactions. We see agreement with theory at the higher end of our bulk density study, however, as we approach lower bulk density systems the dynamics of these interactions begin to change.

2 Photon Polymerization↗
DOE OSTI2024

Driving macro-scale transformations in three-dimensional-printed biopolymers through controlled induction of molecular anisotropy at the nanoscale

Motivated by the need to harness the properties of renewable and biodegradable polymers for the design and manufacturing of multi-scale structures with complex geometries, we have employed our additive manufacturing platform that leverages molecular self-assembly for the production of metre-scale structures characterized by complex geometries and heterogeneous material composition. As a precursor material, we used chitosan, a chemically modified form of chitin, an abundant and sustainable structural polysaccharide. We demonstrate the ability to control concentration-dependent crystallization as well as the induction of the preferred orientation of the polymer chains through the combination of extrusion-based robotic fabrication and directional toolpathing. Anisotropy is demonstrated and assessed through high-resolution micro-X-ray diffraction in conjunction with finite element simulations. Using this approach, we can leverage controlled and user-defined small-scale propagation of residual stresses to induce large-scale folding of the resulting structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Determining the Length Scale of Transport Impedances in Li-Ion Electrodes: Li(Ni 0.33 Mn 0.33 Co 0.33 )O 2

Battery cathodes are complex multiscale, multifunctional materials. The length scale at which the dominant impedance arises may be difficult to determine even with the most advanced experimental characterization efforts, and thus modeling can play an important role in analysis. Discharge and voltage relaxation curves, interrogated with theory, are used to distinguish between transport impedance that arise on the scale of the active crystal and on the scale of agglomerates (secondary particles) comprised of nanoscale crystals. Model-selection algorithms are applied to determine that the agglomerate scale is dominant in the Li Ni 0.33 Mn 0.33 Co 0.33 O 2 electrode studied here. Furthermore, conditions where the agglomerate and crystal-scale models yield distinct simulation results are demonstrated, providing approaches that can be applied to other systems.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Porosity Model Parameter Effects on Metal Additive Manufacturing Simulations

This work investigates the effects of model parameters on thermomechanical simulations of a metal additive manufacturing process. The first half of this work explores the sensitivity and effects of the two porosity parameters used in the evolving constitutive model of the simulation. Varying the two parameters of the model show that for the simulations conducted here, the linear coefficient drives the predicted residual stress results while the constant term has little impact. The second half of the work considers the size, order, and the number of element layers in the finite element mesh. The stress distribution plots show that second-order elements along with a dense mesh marginally improve mesh convergence at a significant cost.

Additive Manufacturing↗
NASA NTRSDate not supplied

NavCube3-mini Lunar GNSS Receiver

This paper describes development and testing of NASA Goddard Space Flight Center’s new NavCube3-mini (NC3m) spaceborne, weak-signal GNSS receiver, which targets all Earth orbit regimes with special focus on lunar applications. NC3m derives from the ground-breaking Magnetospheric Multiscale (MMS) mission Navigator GPS receiver. The MMS-Navigator (launched 2015) holds a Guinness World Record for highest altitude GPS fix and is currently in a highly elliptic orbit with a 29 Earth radii apogee, nearly half lunar distance. NC3m has reduced size, weight, and power compared to the MMS-Navigator, making it suitable for smallsat applications, and adds multi-frequency and multi-GNSS capabilities, among other improvements. A NC3m engineering test unit was subjected to and successfully completed a comprehensive Technology Readiness Level 6 (system/subsystem model or prototype demonstration in a relevant environment) testing campaign in the second half of 2022. This involved high-fidelity simulations in LEO, GEO, and lunar regimes and full environmental testing, including vibration, thermal vacuum, and electromagnetic compatibility. An overview of the NC3m receiver, the test setup, and a sample of results is presented. The results include predicted performance at high-altitude and in the lunar regime.

NavCube3↗
DOE OSTI2023

The Role of Topography in Controlling Evapotranspiration Age

Abstract Evapotranspiration (ET) age is a key metric of water sustainability but a major unknown partly due to the extreme difficulty in modeling it. Groundwater is found to be important in ET age variations in small‐scale studies, yet our understanding is insufficient because groundwater systems are nested across scales. Here, we conducted GPU‐accelerated particle tracking with integrated hydrologic modeling to quantify the variations in ET age at a regional scale of ∼0.4 M km 2 . Simulation results reveal topography‐driven flow paths shaping the spatial and temporal patterns of ET age variations. On ridges, where root zone decoupling with deep subsurface storage, ET age is generally young, with seasonal variations dominated by meteorological conditions. In the valley bottom, ET age is generally old, with significant subseasonal variations caused by the convergence of subsurface flow paths. On hillslopes with water table depths ranging from 1 to 10 m, ET age shows strong seasonal variations caused by the connections with lateral groundwater regulated by ET demand. Our modeling approach provides insights into the basic linkages between ET age and topography at large scale. Our work highlights the perspective of multiscale studies of ET age, suggesting new field experiments to test these process connections and to determine if such linkages warrant inclusion in Earth System Models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A novel conditional formulation of the Vlasov–Ampère equations: a conservative, positivity, asymptotic and Gauss law preserving scheme

We propose a novel reformulation of the Vlasov–Ampère equations for plasmas that reveals discrete symmetries that enables simultaneous conservation of mass, momentum and energy; preservation of Gauss’s law; positivity of the distribution function; and consistency with quasi-neutral asymptotics. The approach employs variable and coordinate transformations to yield a coupled system comprising a modified Vlasov equation and associated moment–field equations. The modified Vlasov equation advances a conditional distribution function that excludes mass, momentum and energy densities, which are instead evolved through moment equations enforcing the relevant symmetries, conservation laws and involution constraints. This reformulation aligns naturally with a recent slow-manifold reduction technique, which separates fast electron time scales and simplifies the treatment of the quasi-neutral limit within the reduced moment–field subsystem. Using this framework, we develop a numerical method for the reduced 1D1V subsystem that, for the first time in the literature, satisfies all key physical constraints while maintaining a quasi-neutral asymptotic behaviour. The advantages of the method are demonstrated on canonical electrostatic test problems, including the multiscale ion acoustic shock wave.

1D1V↗
NASA NTRS2010

Multiscale Modeling of Solar Coronal Magnetic Reconnection

Magnetic reconnection is widely believed to be the primary process by which the magnetic field releases energy to plasma in the Sun's corona. For example, in the breakout model for the initiation of coronal mass ejections/eruptive flares, reconnection is responsible for the catastrophic destabilizing of magnetic force balance in the corona, leading to explosive energy release. A critical requirement for the reconnection is that it have a "switch-on' nature in that the reconnection stays off until a large store of magnetic free energy has built up, and then it turn on abruptly and stay on until most of this free energy has been released. We discuss the implications of this requirement for reconnection in the context of the breakout model for CMEs/flares. We argue that it imposes stringent constraints on the properties of the flux breaking mechanism, which is expected to operate in the corona on kinetic scales. We present numerical simulations demonstrating how the reconnection and the eruption depend on the effective resistivity, i.e., the effective Lundquist number, and propose a model for incorporating kinetic flux-breaking mechanisms into MHO calculation of CMEs/flares.

Antiochos, Spiro K.↗
NASA NTRS2018

Effects of Multiscale Phase-Mixing and Interior Conductance in the Lunar-like Pickup Ion Plasma Wake. First Results from 3-D Hybrid Kinetic Modeling

The study of multiscale pickup ion phase-mixing in the lunar plasma wake with a hybrid model is the main subject of our investigation in this paper. Photoionization and charge exchange of protons with the lunar exosphere are the ionization processes included in our model. The computational model includes the self-consistent dynamics of the light (hydrogen ions or hydrogen molecule ion or helium ion), and heavy (sodium ion ) pickup ions. The electrons are considered as a fluid. The lunar interior is considered as a weakly conducting body. In this paper we considered for the first time the cumulative effect of heavy neutrals in the lunar exosphere (e.g., Aluminum, Argon), an effect which was simulated with one species of sodium ion but with a tenfold increase in total production rates. We find that various species produce various types of plasma tail in the lunar plasma wake. Specifically, sodium ion and helium ion pickup ions form a cycloid-like tail, whereas the hydrogen ion or hydrogen molecule ion pickup ions form a tail with a high density core and saw-like periodic structures in the flank region. The length of these structures varies from 1:5 R(sub M) to 3:3 R(sub M) depending on the value of gyro radius for hydrogen ion or hydrogen molecule ion pickup ions. The light pickup ions produce more symmetrical jump in the density and magnetic field at the Mach cone which is mainly controlled by the conductivity of the interior, an effect previously unappreciated. Although other pickup ion species had little effect on the nature of the interaction of the Moon with the solar wind, the global structure of the lunar tail in these simulations appeared quite different when the hydrogen molecule ion production rate was high.

Lipatov, A.S.↗
NASA NTRSDate not supplied

AI-Enhanced Computational Tools for Entry Systems Modeling

To advance the understanding of complex atmospheric entry phenomena, NASA’s Entry Systems Modeling (ESM) team [1] has developed high-fidelity computational tools addressing multiscale challenges, from material microstructures to full-scale heatshield response. This abstract highlights a subset of ESM tools, focusing on AI integration to enhance workflows and predictive modeling. - PuMA [2] computes effective material properties from high-resolution micro-CT scans, supporting TPS analysis for NASA missions. - TomoSAM [3] automates 3D tomography dataset segmentation for PuMA using the Segment Anything Model, reducing manual effort and improving accuracy. - PATO [4] models porous reactive materials under extreme conditions, with advancements such as unified solvers, mechanical erosion, and TPS coatings for NASA missions. - arcjetCV [5] employs deep learning to analyze arc jet test footage, measuring recession rates, shape changes, and shock standoff distances, bridging simulations, and experiments to reveal TPS ablation behavior. - ARCHeS [6] simulates arc heater plasma flows, modeling turbulence, radiation, and electromagnetic interactions to optimize arc heater performance, validate TPS under extreme conditions, and serve as a foundation for developing digital twins of arc heater facilities. - SPARTA [7] simulates rarefied hypersonic flows and gas-surface interactions for planetary entry missions, leveraging GPU architectures for scalable and efficient aerothermal and ablation analyses. AI-driven solutions, such as deep learning segmentation, have streamlined workflows in ESM tools and still hold significant potential to further accelerate processes and enhance automation in entry systems modeling. [1] Haskins, J.B. (2023), [2] Ferguson, J.C. (2018), [3] Meurisse, J.B.E. (2018), [4] Semeraro, F. (2023), [5] Quintart, A. (2024) [6] Meurisse, J.B.E. (2022), [7] Plimpton, S.J. (2019)

Predictive Modeling↗
DOE OSTI2023

Model America - Arizona extract from ORNL's AutoBEM v1.1

Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM).Two sets of sample data are provided for 2,555,152 buildings located within the boundary of Arizona in the United States:Data (846.3MB *.csv) - minimalist list of each building (rows) for the following fields (columns) • ID - unique building ID • Centroid - building center location in latitude/longitude (from Footprint2D) • Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) • State_abbr - state name • Area - estimate of total conditioned floor area (ft2) • Area2D - footprint area (ft2) • Height - building height (ft) • NumFloors - number of floors (above-grade) • WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) • CZ - ASHRAE Climate Zone designation • BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards • Standard - building vintage • Sample Models (114GB*.zip by county) - OpenStudio and EnergyPlus building energy models named according to IDThis data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗