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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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DOE OSTI2026

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING↗

NASA NTRS1970

Aluminum chlorine battery

Rechargeable high energy density battery based on aluminum and chlorine carbon electrodes and molten aluminum chloride-alkali chloride eutectic as electrolyte

Giner, J.↗

NASA NTRS1992

The thermal engine of Venus: Implications from the impact crater distribution

Questions concerning the state of Venus' volcanological activity are currently under investigation. These questions were raised by the imaging radar and altimetric data obtained by the Magellan spacecraft, which began mapping Venus in Sept. 1990. Clues about the answers to these questions are provided by the nature and distribution of impact craters on the surface of Venus. Statistical tests show that the distribution of craters on Venus cannot be distinguished from a completely spatially random population. Further, the majority of craters look relatively pristine; only about 5 percent of the observed craters appear to be embayed or flooded by lavas. The simplest interpretation of these observations is a model in which the impact craters lie on a surface that has been undisturbed by volcanological and tectonic processes since the time the surface was formed. Counting up the number of craters and estimating the rate at which meteoroids strike the surface then gives an age for the venusian surface of 500 million years; in this model the volcanic activity since that time has been essentially nil. This scenario is described as a 'production' model, or perhaps more appropriately, a 'catastrophic' model.

Phillips, Roger J.↗

NASA NTRS2026

Integrated Computational Materials Engineering (ICME) Capability Maturity Levels for Ecosystems Enabling Digital Transformation

Digital engineering (DE) and integrated computational materials engineering (ICME) are widely recognized as critical enablers of faster, more affordable, and more reliable aerospace systems. However, many organizations have struggled to realize the promised return on investment (ROI) from digital initiatives. A primary reason is the absence of a shared, decision-focused framework that distinguishes simple digitization of existing workflows from true digital transformation that fundamentally changes how engineering decisions are made. This paper introduces an ICME capability maturity framework that fills this gap. The framework defines six cumulative ICME capability maturity levels (CMLs), explicitly tied to decision authority, engineering integration, optimization, and uncertainty management across material, process, structure, and performance scales. It is designed to complement established readiness metrics such as technology readiness levels (TRLs), manufacturing readiness levels (MRLs), and integration readiness levels (IRLs), by addressing a missing dimension: the conditions required for model-informed decision authority across scales. A unifying figure and capability table illustrate the six-level ICME Capability Maturity Framework, showing how organizations progress from digitization—with limited or negative ROI—to true digital transformation, where ICME-enabled workflows deliver measurable improvements in decision quality, cycle time, risk reduction, and reuse. The framework is intended for both technical practitioners and executive leadership, providing a common language to assess current state, guide roadmaps, align software ecosystem investments, and set realistic expectations for digital transformation outcomes. A regulatory-relevant statement clarifying the relationship between ICME capability and existing certification frameworks is provided.

ICME↗

DOE OSTI2026

A Python Tool for Aqueous Plutonium Nitrate Density Law Input Preprocessing in MCNP6

Here, this work develops a predictive density tool in Python, named Plutonium Nitrate Solutions (PuNS), to reduce bias and uncertainty in nuclear criticality safety calculations for plutonium nitrate systems. The Pitzer method and an empirical method were implemented into the PuNS tool to generate atom densities for use in MCNP6 material cards. These material cards are directly prepared into an MCNP6 input text file and are calculated based on customizable user inputs of plutonium content, nitric acid content, temperature, and plutonium isotope weight percentages. The PuNS tool is validated and verified against the International Criticality Safety Benchmark Evaluation Project Handbook experiments and is observed to predict densities within a root mean square error of 0.89% for the Pitzer method and 1.82% for the empirical method. These errors in density lead to up to 1569 pcm difference in MCNP6 calculated k eff for the Pitzer method and up to a 1751 pcm difference for the empirical method when compared to experimental benchmarks. Simultaneous work is also being performed at Los Alamos National Laboratory and the University of New Mexico to create a similar tool for plutonium chloride solutions, named Plutonium Chloride Solution, which aims to provide the accreditation of the chlorine absorption. These capabilities will not only provide more accurate models but also facilitate an improved understanding of solution systems and a potential relaxation in the conservatism of current aqueous plutonium processing criticality safety limits.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2026

Analysis and Overview of Hybrid Wired and Wireless Bi-Directional EV Charger Systems

Here, this paper analyzes and overviews hybrid wired and wireless bi-directional Electric Vehicle (EV) charging systems with a primary focus on resonant compensation methods that enable a unified power conversion architecture. Four compensation configurations based on series–series and LCC–LCC resonant networks are systematically evaluated for both wired transformer-based and wireless coupler-based operation. The analysis examines how coupling conditions, resonant component selection, and auxiliary compensation tuning influence voltage gain characteristics, resonant tank current magnitude and phase, and operating frequency requirements. Normalized frequency-domain results are presented to directly compare reactive current behavior and voltage regulation capability under wired and wireless operating conditions. A 60 kW bi-directional charger case study is used to demonstrate the feasibility of retaining a common hardware platform while accommodating distinct coupling scenarios through compensation tuning rather than structural modification. The presented results provide design-oriented insights into resonant network selection and compensation strategies for scalable and flexible hybrid EV charging systems.

Hybrid↗

NASA NTRS2026

Measure sea level air pressure from space to improve knowledge and forecasting of the atmospheric state

Modern numerical weather prediction (NWP) and analysis models require globally-observed meteorological data including sea-level pressure (SLP) for accurate operations. Up until now, SLP has only been measured by in situ instruments from ships, buoys, and ocean platforms. These measurements are sparse with large gaps, leaving models starved of this critical information to constrain the atmospheric state. Recent advancements in differential absorption radar (DAR) provide a path to close this critical observation gap through spaceborne observations in the coming decade, improving the analysis models relied upon for atmospheric research and the weather forecasts depended upon daily for public safety and commerce.

Matthew L Walker McLinden↗

NASA NTRSDate not supplied

A Machine Learning Framework for Error Compensation in Radiative Transfer Calculations

Radiative heat transfer influences the amount of heat flux transferred to the surface of the hypersonic vehicle, which is essential to evaluate the performance of thermal protection systems. The radiative heat flux is found to be computationally prohibitive while accounting for the variation in spatial, angular, and spectral domains. A new methodology has been recently developed to alleviate the cost of computation in the spectral domain by constructing flow-agnostic reduced-order models (ROMs). The developed spectral ROM databases provide grouping strategies that account for non-equilibrium absorption and emission as well as interaction between disparate species due to spectral overlap in associated radiative processes. However, the developed ROMs need to be optimized for a specific combination of interacting gas species and would need to re-calibrated in case individual species are added/omitted. In this work, we use various machine learning (ML) techniques to approximate the radiative intensities determined by a ROM optimized for a specific gas mixture. The ML model relies on the ROM databases developed for a single species which ignores any spectral overlap. Thus, radiation evaluation starts with a simple summation of radiative intensities predicted using these non-calibrated ROMs for the contributing species. The ML framework then provides a correction to account for the interplay in the frequency, i.e., emission of photons by one species and absorption by another, and yields mixture-specific radiation fields. Once trained on the individual ROM databases, the ML framework offers instantaneous corrections that serves as a time/cost effective alternative to the optimization of ROMs for a specific gas mixture. The ML framework is trained on both the high fidelity and ROM evaluated line of sight (LOS) data from Orion, Stardust, and FIRE II cases to obtain a general purpose correction model for earth re-entry scenarios when radiation contributions from both atomic nitrogen and atomic oxygen are considered. A geometric length scale parameter is used in the training process to account for errors introduced in the ROM databases as a consequence of high optical thickness. The efficacy of the ML framework is underscored through extensive analysis of train and test errors with respect to all the re-entry scenarios. The applicability of such an ML framework was further corroborated by embedding it in a state-of-the-art US3D - NERO system for determining the radiative heat flux transferred to the hypersonic vehicle surface.

Radiation↗

DOE OSTI2023

High Sulfur Loading and Capacity Retention in Bilayer Garnet Sulfurized‐Polyacrylonitrile/Lithium‐Metal Batteries with Gel Polymer Electrolytes

The cubic‐garnet (Li 7 La 3 Zr 2 O 12 , LLZO) lithium–sulfur battery shows great promise in the pursuit of achieving high energy densities. The sulfur used in the cathodes is abundant, inexpensive, and possesses high specific capacity. In addition, LLZO displays excellent chemical stability with Li metal; however, the instabilities in the sulfur cathode/LLZO interface can lead to performance degradation that limits the development of these batteries. Therefore, it is critical to resolve these interfacial challenges to achieve stable cycling. Here, an innovative gel polymer buffer layer to stabilize the sulfur cathode/LLZO interface is created. Employing a thin bilayer LLZO (dense/porous) architecture as a solid electrolyte and significantly high sulfur loading of 5.2 mg cm −2 , stable cycling is achieved with a high initial discharge capacity of 1542 mAh g −1 (discharge current density of 0.87 mA cm −2 ) and an average discharge capacity of 1218 mAh g −1 (discharge current density of 1.74 mA cm −2 ) with 80% capacity retention over 265 cycles, at room temperature (22 °C) and without applied pressure. Achieving such stability with high sulfur loading is a major step in the development of potentially commercial garnet lithium–sulfur batteries.

25 ENERGY STORAGE↗

DOE OSTI2024

Recognizing Blazars Using Radio Morphology from the VLA Sky Survey

Abstract Blazars are radio-loud active galactic nuclei whose jets have a very small angle to our line of sight. Observationally, the radio emissions are mostly compact or compact-core with a one-sided jet. With 2.″5 resolution at 3 GHz, the Very Large Array Sky Survey (VLASS) enables us to resolve the structure of some blazar candidates in the sky north of decl. −40°. We introduce an algorithm to classify radio sources as either blazar-like or non-blazar-like based on their morphology in the VLASS images. We apply our algorithm to three existing catalogs, including one of the known blazars (Roma-BzCAT) and two blazar candidates identified by Wide-field Infrared Survey Explorer colors and radio emission (WIBRaLS, KDEBLLACS). We show that in all three catalogs, there are objects with morphologies inconsistent with being blazars. Considering all the catalogs, more than 12% of the candidates are unlikely to be blazars, based on this analysis. Notably, we show that 3% of the Roma-BzCATconfirmedblazars could be a misclassification based on their VLASS morphology. The resulting table with all sources and their radio morphological classification is available online.

Astronomy & Astrophysics↗

DOE OSTI2026

Commercialization of the NLR Hydrogen Wide Area Monitor (HyWAM): Cooperative Research and Development (Final Report)

Hydrogen wide area monitoring refers to the temporal and quantitative 3-dimenasional spatial profiling of hydrogen plumes following either intentional or unintentional hydrogen releases. A hydrogen wide area monitor (HyWAM) would have applications as a research tool, for example to provide empirical data on the behavior of hydrogen dispersions following a release, which in turn can be used to validate modelling studies. Support of modeling studies and commercial applications are interrelated, since modeling can serve to guide HyWAM deployment for enhanced safety within medium to large scale hydrogen operations, such as those envisioned by H2@Scale.

08 HYDROGEN↗

NASA NTRS2013

A Panchromatic View of the Restless SN 2009ip Reveals the Explosive Ejection of a Massive Star Envelope

The double explosion of SN 2009ip in 2012 raises questions about our understanding of the late stages of massive star evolution. Here we present a comprehensive study of SN 2009ip during its remarkable rebrightenings. High-cadence photometric and spectroscopic observations from the GeV to the radio band obtained from a variety of ground-based and space facilities (including the Very Large Array, Swift, Fermi, Hubble Space Telescope, and XMM) constrain SN 2009ip to be a low energy (E (is) approximately 10(exp 50) erg for an ejecta mass approximately 0.5 solar mass) and asymmetric explosion in a complex medium shaped by multiple eruptions of the restless progenitor star. Most of the energy is radiated as a result of the shock breaking out through a dense shell of material located at approximately 5 × 10( exp 14) cm with M approximately 0.1 solar mass, ejected by the precursor outburst approximately 40 days before the major explosion. We interpret the NIR excess of emission as signature of material located further out, the origin of which has to be connected with documented mass-loss episodes in the previous years. Our modeling predicts bright neutrino emission associated with the shock break-out if the cosmic-ray energy is comparable to the radiated energy. We connect this phenomenology with the explosive ejection of the outer layers of the massive progenitor star, which later interacted with material deposited in the surroundings by previous eruptions. Future observations will reveal if the massive luminous progenitor star survived. Irrespective of whether the explosion was terminal, SN 2009ip brought to light the existence of new channels for sustained episodic mass loss, the physical origin of which has yet to be identified.

view↗

NASA NTRS2000

Mechanisms of Protonic Nonvolatile Memory Device

A nonvolatile memory device based on protonic transport in oxides has been proposed. The mobile H+ ions are introduced into the SiO2 layer by annealing Si/SiO2/Si structures in H2 at temperatures greater than 500 deg C. This effect has only been observed for confined oxides that have been annealed at greater than or equal to 1100 C prior to the hydrogenation anneal. This includes buried oxides such as Unibond and SIMOX as well as thermal oxides annealed with a polysilicon cap. An applied field moves the charge within the oxide and the charge stops moving when the field is removed. In a memory device, the hydrogen-annealed oxide is the gate oxide and the position of the mobile charge is sensed by the shift of the I-V curve. Much is still not understood about the motion of the charge across the buried oxide. Previous work has assumed that H+ transport and the time it takes to traverse the oxide is governed by interactions within the bulk of the oxide. Based on parameters that affect the transport time, we conclude that H+ trapping and detrapping at the Si/SiO2 interface are more important than H+ interactions within the oxide bulk. These parameters include the applied field, the H+ concentration and the oxide thickness. One consequence is that projections of device write-time based on the previous assumptions of H+ transport mechanisms may be overly optimistic.

P J Macfarlane↗

DOE OSTI2026

Achieving uniaxial magnetic anisotropy in Ce2⁢Fe17⁢N3 through Co- and Sm-substitution

Th2⁢Zn17−type structure-based permanent magnets, such as Sm2⁢Fe17⁢N3, offer strong potential as alternatives to neodymium magnets (NdFeB), but their practical use is limited by phase stability and the scarcity of Sm. Ce-based counterparts, particularly Ce2⁢Fe17⁢N3, are attractive low-cost candidates, yet their intrinsic planar magnetic anisotropy restricts permanent-magnet performance. Here, we induce uniaxial magnetic anisotropy in Ce2⁢Fe17⁢N3 through two approaches: (i) Co substitution on the Fe sublattice and (ii) partial substitution of Ce with Sm. Combined density functional theory and experimental results show that both strategies modify the 3⁢𝑑–4⁢𝑓 interactions and band filling, yielding magnetization values up to ∼1.2T and magnetocrystalline anisotropy energies exceeding 1MJ/m3 for Co-alloyed compositions, with significantly larger anisotropy achieved upon Sm substitution. In addition, the Sm-substituted Ce2⁢Fe17⁢N3 samples exhibit enhanced high-temperature stability compared to Sm2⁢Fe17⁢N3. These findings demonstrate that Ce2⁢Fe17⁢N3-based alloys can deliver magnetic performance suitable for permanent-magnet applications while reducing cost and reliance on critical rare-earth elements, and they provide practical design guidelines for rare-earth-lean magnets for energy and industrial applications.

Pokhrel, Nabaraj [ORNL] (ORCID:0000000328283076)↗

NASA NTRSDate not supplied

Simulations of Yarn Micro-Mechanics of Woven Heat Shield Materials

Carbon and phenolic fibers are commonly used in ablative thermal protection materials, such as 3-dimensional Mid-Density Carbon Phenolic (3MDCP), a 3D-woven composite comprised of mixed-fiber yarn bundles. Predicting the micro-mechanical response and fracture of twisted yarns composed of brittle and ductile fibers requires a modeling approach that captures per-fiber yielding, fiber fracture, and inter-fiber friction and contact. This work presents an extended bonded particle model (BPM) for discrete element method (DEM) simulation of fiber and yarn mechanics, implemented in LAMMPS. The model builds on the incremental bond formulation of Guo et al. and introduces a piecewise elasto-plastic constitutive law for axial extension, enabling representation of fibers that yield before failure. 3MDCP yarns were constructed using measured fiber radius distributions and helical twist geometry. Tensile simulations of single-ply 3MDCP yarns show good agreement with vender stress–strain results. Fiber breakage models also show details on yarn breakage propagration, centered radially in the yarn. Yarn breakage of multi-ply 3MDCP also matched experimental observations in per-ply breakage; however, predicted yarn breakage strength were found higher than experimental observations.

Discrete Element Method↗

NASA NTRSDate not supplied

Simulations of Yarn Micro-Mechanics of Woven Heat Shield Materials (3MDCP)

Woven↗

NASA NTRS1984

The Telecommunications and Data Acquisition Report

Tracking and ground-based navigation; communications, spacecraft-ground; station control and system technology; capabilities for new projects; networks consolidation program; and network sustaining are described.

E C Posner↗

DOE OSTI2026

SODAs: sparse optimization for the discovery of differential and algebraic equations

Differential-algebraic equations (DAEs) integrate ordinary differential equations (ODEs) with algebraic constraints, providing a fundamental framework for developing models of dynamical systems characterized by time-scale separation, conservation laws and physical constraints. While sparse optimization has revolutionized model development by allowing data-driven discovery of parsimonious models from a library of possible equations, existing approaches for dynamical systems assume DAEs can be reduced to ODEs by eliminating variables before model discovery. This assumption limits the applicability of such methods for DAE systems with unknown constraints and time scales. We introduce sparse optimization for differential-algebraic systems (SODAs), a data-driven method for the identification of DAEs in their explicit form. By discovering the algebraic and dynamic components sequentially without prior identification of the algebraic variables, this approach leads to a sequence of convex optimization problems. It has the advantage of discovering interpretable models that preserve the structure of the underlying physical system. To this end, SODAs improves since SODAs is singular numerical stability when handling high correlations between library terms, caused by near-perfect algebraic relationships, by iteratively refining the conditioning of the candidate library. We demonstrate the performance of our method on biological, mechanical and electrical systems, showcasing its robustness to noise in both simulated time series and real-time experimental data.

DAE↗