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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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328 records · Page 5
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NASA NTRS2014

Influential Factors for Liquid Acquisition Device Screen Selection for Cryogenic Propulsion Systems

This paper presents the influential factors which govern screen selection for liquid acquisition devices (LADs) operating in microgravity conditions for future in-space cryogenic propulsion engines and cryogenic propellant depots. Space flight requirements, which include mass flow rate, acceleration level and direction, and thermal environment, dictate screen selection for a particular mission. The five influential factors include bubble point pressure, flow-through-screen pressure drop, wicking rate, screen compliance, and material compatibility. Governing equations and analytical models for these parameters are developed from first principles. A comprehensive survey of the historical data on coarser LAD meshes over four decades of work is conducted, and liquid hydrogen data for finer Dutch Twill meshes (325 x 2300, 450 x 2750, 510 x 3600) from recently concluded experiments is also presented to validate analytical models. Each of these parameters is measurable from ground based tests, making it facile to predict flight system performance. Therefore analytical models in this paper will be valuable for future LAD designs for both cryogenic and storable propulsion systems. Additionally, analysis will be given on the impact of the factors on liquid hydrogen systems.

Fuel Depot↗
DOE OSTI2026

Boron Coordination in Multicomponent Glasses: Analytical Models and Machine Learning With Uncertainty

Borosilicate glasses are extensively used in a variety of applications from kitchenware to nuclear waste immobilization due to the strong network formed by the Si-O-B bond that makes it resistant to chemical corrosion and gives it a low thermal expansion. Boron, however, exists in both trigonal BO3 and tetrahedral BO4 bonds in glass systems, which impacts the chemical durability and thermal resistance of the glass, amongst other properties. Boron coordination (N4), or the ratio of the amount of BO4 to BO3 within a glass, may aid in predicting these properties but is difficult to derive without experimental data due to the complexity of impacts from varied glass compositions and processing factors. For this reason, compositional models have been developed to predict boron coordination, but the models typically include a limited number of glass components. To help fill this gap in the models, in this work, a diverse multicomponent glass dataset of 809 glasses is compiled from a literature search, and then a number of analytical and machine learning (ML) models are trained on the dataset. Previously developed modified Bernstein and modified Du Stebbins analytical models were fitted to update parameters with the new dataset. Then, partially Bayesian neural networks, Gaussian process regressor, and heteroskedastic deterministic neural networks were evaluated. The ML models examined all have different strategies to overcome the potential for overfitting as a result of a limited training dataset, and return results that account for model uncertainty, which can be valuable for understanding model reliability. For the first time, cooling rate is introduced as an input parameter for ML models, showing consistent improvements in performance and solidifying the importance of including parameters outside of composition alone for N4 prediction. The machine learning models examined here show promise in accurate predictions of boron coordination in borosilicate glasses, all achieving R2 values of 0.91.

boron coordination↗
DOE OSTI2026

The 10 September 2025 M w 4.1 Earthquake in Northeastern Utah, United States: An Archetypal Continental Mantle Event

The 10 September 2025 M w 4.1 earthquake in northeastern Utah, United States, had a focal depth 68 km beneath sea level, which is ∼20–25 km greater than estimates of local crustal thickness, making it a rare example of a continental mantle earthquake (CME). The focal depth is well resolved from arrival-time inversion (nearest station ∼13 km away) and moment tensor inversion of regional waveforms. Similar to other CMEs in the Intermountain West, there were no obvious aftershocks or foreshocks, and the waveforms were enriched in high-frequency energy. Spectral modeling gives a stress drop of ∼80 MPa and a radiation efficiency of ∼0.08, albeit with large uncertainties. The high stress drop and low radiation efficiency are consistent with a dissipative source process such as thermal runaway. Also similar to previous Intermountain West CMEs, the event occurred along the boundary of the Archean Wyoming craton, where pressure–temperature conditions favor ductile deformation. We hypothesize that edge-driven or regional-scale mantle convection produces increased strain rates near the craton boundary that make either conventional brittle failure or thermal runaway feasible at relatively high pressure–temperature conditions. High conductivity inferred around the edge of the craton may suggest that fluids also contribute to CME occurrence.

Koper, Keith D. [Univ. of Utah, Salt Lake City, UT↗
DOE OSTI2023

A physics informed bayesian optimization approach for material design: application to NiTi shape memory alloys

Abstract The design of materials and identification of optimal processing parameters constitute a complex and challenging task, necessitating efficient utilization of available data. Bayesian Optimization (BO) has gained popularity in materials design due to its ability to work with minimal data. However, many BO-based frameworks predominantly rely on statistical information, in the form of input-output data, and assume black-box objective functions. In practice, designers often possess knowledge of the underlying physical laws governing a material system, rendering the objective function not entirely black-box, as some information is partially observable. In this study, we propose a physics-informed BO approach that integrates physics-infused kernels to effectively leverage both statistical and physical information in the decision-making process. We demonstrate that this method significantly improves decision-making efficiency and enables more data-efficient BO. The applicability of this approach is showcased through the design of NiTi shape memory alloys, where the optimal processing parameters are identified to maximize the transformation temperature.

Chemistry↗
NASA NTRS1999

System Identification for Integrated Aircraft Development and Flight Testing [l'Identification Des Systemes Pour le Developpement Integre des Aeronefs et les Essais en Vol]

Over the last decades flight vehicles such as aircraft and helicopters entering service and requiring increased operational effectiveness have with few exceptions experienced prolonged flight test development to achieve full certification. In many cases the original requirements had later to be reduced to enable release to service. The impact on the customer, and manufacturer has been considerable leading to increased costs and or reduced operational capabilities. These costly experiences are largely a result of the flight vehicle not behaving as modelled and designed. The evaluation of flight test data can be used as a tool for validating windtunnel results and mathematical models describing the flight dynamical behaviour. In this sense the uncertainty of important aerodynamic stability and control parameters can be reduced and the confidence of aircraft mathematical models improved. An additional important factor comes from the implementation of active control systems offering the promise of significantly increased flight vehicle performance and operational capability. This approach extends the traditional trade-offs between aerodynamics, structures and propulsion systems to include full- time, full-authority fly-by-wire/light systems. It is imperative that the aerodynamic stability and control parameters of such integrated flight and propulsion control systems have to turn out inflight as predicted, since inherent stability margins will be lower and the flight control system must correct these deficiencies to provide flight critical redundancy and safety. With the methodology of system identification from flight tests it is possible to sense the control inputs and the flight vehicle reactions Such as accelerations, rates and attitudes. The mathematical model, e.g. the model structure and parameters, has to be determined from the relationship of the measured control inputs and the system's responses. The aim of this symposium was to review the present state of the art of flight vehicle system and parameter identification techniques, and to provide a critical appraisal of current methods developed and applied to flight test data in a number of NATO nations. Particular emphasis was placed on practical aspects and lessons learned in order to generate information useful to the flight test community in industry and government agencies. The technical papers share invaluable experience and emphasize the advances of flight vehicle system identification over the last years to the point where confidence and robustness level is now reasonably high. The symposium covered overviews of identification methodologies, flight test techniques, recent aircraft and helicopter application programs, and a session of short papers covering up-to-the-minute flight test results. A final discussion included prepared comments from experts and concluded with key issues learned in the application of system identification and future research needs. The essential benefits to NATO nations can be condensed as follows: More accurate mathematical models for high bandwidth flight control systems, Improved assessment and evaluation of flying qualities, High fidelity mathematical models for flight vehicle development and mission training simulators, and generally, Reduced flight test time and costs.

Advisory Group for Aerospace Research and Developm↗
NASA NTRSDate not supplied

Introduction to the JPSS-2 Advanced Technology Microwave Sounder (ATMS) Government Calibration Data Book (GCDB)

The third Advanced Technology Microwave Sounder (ATMS) is an instrument onboard the Joint Polar Satellite System (JPSS), JPSS-2 (renamed NOAA-21 in orbit) mission. This report is to introduce the JPSS-2 Government Calibration Data Book (J2 GCDB) for ATMS, SN 304. This J2 GCDB document contains key information generated during the calibration testing campaign that is driving parameters for radiometric performance. This document also contains supporting data that augments the calibration results. The values in this document are utilized by ATMS’s calibration packet which is, in turn, an integral component in the interpretation of science data. The calibration data in this report was collected from tests such as shelf-level testing, antenna testing, instrument thermal vacuum (TVAC) testing; satellite TVAC testing; and JPSS-2 post-launch tests. JPSS-2 was launched on November 10, 2022. In the subsequent years, the Government will release an ATMS GCDB for each JPSS mission. We expect that all public users can download these ATMS GCDBs from the NOAA operational Integrated Calibration and Validation System (ICVS) website, see more discussions below. The goal of this GCDB is to demonstrate how to characterize ATMS measurements using JPSS-2 ATMS on-orbit operational data and to provide relevant explanations. This document serves as a primary public domain reference for calibrating operational ATMS Raw Data Records (RDR) science data, as used in the current operational Interface Data Processing Segment (IDPS) system. This same RDR science data is distributed through direct broadcast (DB) to DB users for use in their ground processing systems. This J2 GCDB provides the results of the ATMS system radiometric calibration, the antenna flat reflector emissivity [1], the antenna pattern measurements, the antenna pattern corrected brightness temperature [2], the brightness temperature of the lunar disk [3], Lunar Intrusion (LI) correction algorithm [4], receiver spectral parameters, and mechanical alignment on-orbit pointing results, and the striping effect appeared significantly in S-NPP on-orbit radiance data when the data are compared to the Radiative Transfer Model (RTM) simulation in numerical weather prediction (NWP) system [5]. It also provides the parameters required for conversion of telemetry counts to engineering units, for radiometric calibration, and for antenna beam geo-location. Moreover, it provides JPSS-2 ATMS Spectral Response Functions data, some additional information related to ATMS on-orbit performance, on-orbit lunar intrusion correction parameters and Earth contamination bias, and on how to derive ATMS RDR, antenna Temperature Data Records (TDR), and Sensor Data Records (SDR). Furthermore, an introduction of NOAA operational Integrated Calibration and Validation System (ICVS) website and services is added in this J2 GCDB. This ICVS hosts a long-term monitoring system which allows to visualization and comparison of data from JPSS missions, NOAA legacy Polar Operational Environmental Satellites (POES), and Geostationary Operational Environmental Satellites (GOES). From NOAA Comprehensive Large Array-data Stewardship System (CLASS), the public users can download all JPSS ATMS data products for all JPSS missions.

Microwave Sounder↗
NASA NTRSDate not supplied

Kalman Filtering and RTS Smoothing for Arc-Jet Sample Edge Tracking

Accurate and temporally consistent measurements of test-article recession are required to characterize material response during arc-jet ablation experiments. However, image-based boundary measurements are often affected by segmentation noise, brightness variations, and frame-to-frame variability. This work extends arcjetCV [1] with filtering methods for tracking the evolving boundaries of hemispherical and ISO-Q test articles. Two boundary-tracking approaches based on Kalman filtering [2] were implemented. The first applies a point-wise Kalman filter followed by a Rauch–Tung–Striebel smoother [3] to individual boundary-point locations. The second applies the same filtering and smoothing framework to a reduced set of geometry-dependent shape parameters. The point-wise method reduces local frame-to-frame fluctuations while preserving spatial details along the detected boundary. The shape-parameter method provides a compact and geometrically constrained estimate of the sample contour. Figure 1 illustrates the two approaches for a hemispherical test article. Both methods improve temporal consistency and support more robust estimation of surface recession from arc-jet imagery. The two filtering approaches provide complementary representations of boundary evolution and improve the reliability of image-based recession measurements during arc-jet experiments.

recession measurement↗
NASA NTRS1992

On the isotopic signature of recent solar-wind nitrogen

One of the most intriguing discoveries yielded by the Apollo samples was evidence pointing towards a significant long-term change in the composition of the sun. Such a change, of the size inferred from the lunar sample data, is inconsistent with present theories of solar evolution. Consequently, there is much interest in exploring this phenomenon as closely as possible, to determine exactly what compositional changes have taken place and whether those changes really did take place in the sun, or whether the cause lies elsewhere. The reason why we can use the moon to analyze the elements in the sun is that the sun emits a stream of ions, known as the solar wind, whose composition, on average, is believed to be the same as that in the surface regions of the sun. When the solar-wind ions hit the surface of the moon, many of them penetrate a short distance into the dust grains lying on the lunar surface. Thus, after a grain has sat on the lunar surface for a while, it has a rim of material that is partly lunar and partly solar in composition. For most chemical elements, the difference between lunar and solar composition is so sufficiently small that the solar elements cannot be detected, but for a handful of elements that are missing from the moon, their solar 'signature' can be observed in samples of lunar soil brought back by the astronauts. Among those elements is nitrogen, the most common element in the air we breathe, but very rare indeed on the moon. Our analytical techniques are not sophisticated enough yet to enable us to analyze individual lunar soil grains for nitrogen, much less to zero in on just the nitrogen in the surface of such a grain. Consequently we are forced to analyze samples consisting of many different grains, each of which could have experienced its own individual history. This makes it difficult to identify the nitrogen implanted in grain surfaces, and also to define the age of a sample.

Kim, Y.↗
NASA NTRS1974

Development of a battery status monitor

A prototype battery status monitor system has been developed. The functions of the system are: (1) to provide the energy status of the battery, (2) to measure and transmit basic battery parameters, (3) to process these measurements required to determine abnormal functioning of the battery, and (4) to transmit warning signals of the abnormal condition along with a go/no go signal. The system was developed for use with the space shuttle.

Zimmerman, R. I.↗
DOE OSTI2026

Temperature as a control knob on spin-orbit coupling

Spin-orbit coupling (SOC) governs many physical phenomena. Through ab initio molecular dynamics simulations, Lu and Sun demonstrated that structural disorder at elevated temperatures substantially reduces the effective SOC contribution that stabilizes band inversion, driving a topological-to-normal-insulator transition in Bi2Se3. Their work identifies temperature as a meaningful control parameter for SOC-mediated topology and other properties.

Liang, Liangbo [ORNL] (ORCID:0000000311990049)↗
DOE OSTI2026

H 0 without the sound horizon (or supernovae): A 2% measurement in DESI DR1

The sound horizon scale rs is a key source of information for measurements of H 0 from early-time data, and is therefore a common target of new physics proposed to solve the Hubble tension. We present a sub-2% measurement of the Hubble constant that is independent of this scale, using data from the first data release of the Dark Energy Spectroscopic Instrument (DESI DR1). Building on previous work, we remove dependency on the sound horizon size using a heuristic rescaling procedure at the power spectrum level. A key innovation is the inclusion of uncalibrated (agnostic to r s ) post-reconstruction BAO measurements from DESI DR1, as well as using the CMB acoustic scale θ* as a high-redshift anchor. Uncalibrated type-Ia supernovae are often included as an independent source of Ω m information; here we demonstrate the robustness of our results by additionally considering two supernova-independent alternative datasets. We find somewhat higher values of H 0 relative to our previous work: 69.2 +1.3 -1.4 , 70.3 +1.4 -1.2 , and 69.6 +1.3 -1.8 km s -1 Mpc -1 respectively when including measurements from i) Planck/ACT CMB lensing × unWISE galaxies, ii) the DES Year 3 6×2pt analysis, and iii) Planck/ACT CMB lensing + the DES Year 5 supernova analysis. These remarkably consistent constraints achieve better than 2% precision; they are among the most stringent sound horizon-independent measurements from LSS to date, and provide a powerful avenue for probing the origin of the Hubble tension.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

In this work, we propose a hybrid model for Li-ion battery discharge and aging prediction that leverages fleet-wide data to predict future capacity drops.The model is built upon an hybrid approach merging physics-based and empirical equations, as well as neural network models in a recurrent neural network cell. The hybrid physics-informed neural network can predict voltage discharge cycles given the loading profile, and estimate the used capacity of the battery under random-loading conditions by tracking aging parameters connected to the residual capacity of the battery. By merging information on the battery aging parameters with existing fleet-wide aging data, the model can predict the future residual capacity of the battery that is being monitored, and therefore enable predictions of voltage discharge curves far ahead in the battery life cycle. We validated the approach using the NASA Prognostics Data Repository Battery data-set, which contains experimental data on Li-ion batteries discharged at random loading conditions in a controlled environment. The approach also allows the identification of discrepancies between the battery aging trend and the trend observed at the fleet level, so that batteries behaving differently from the rest of the fleet can be subject to closer monitoring and further testing to refine predictions.

PINN↗
DOE OSTI2024

Cosmological probes of Dark Radiation from Neutrino Mixing

Abstract Models of stepped dark radiation have recently been found to have an important impact on the anisotropies of the cosmic microwave background, aiding in easing the Hubble tension. In this work, we study models with a sector of dark radiation with a step in its abundance, which thermalizes after big bang nucleosynthesis by mixing with the standard model neutrinos. For this, we extend an earlier work which has focused on the background evolution only until the dark sector thermalizes by deriving the full background and perturbation equations of the model and implementing them in an Einstein-Boltzmann solving code. We expound on the behavior of this model, discussing the wide range of parameters that result in interesting and viable cosmologies that dynamically generate dark radiation during a range of epochs. We find that for the strongly self-coupled regime, there is no large cosmological impact for a tight prior on the mass, whereas larger mass ranges allow a smooth interpolation between a behavior close to the ΛCDM cosmological standard model and close to an additional component of strongly self-interacting dark radiation. In the weakly self-coupled regime we find that we can accommodate a parameter space relevant for the neutrino anomalies as well as one relevant to easing the Hubble tension.

Astronomy & Astrophysics↗
DOE OSTI2024

Active Learning for Rapid Targeted Synthesis of Compositionally Complex Alloys

The next generation of advanced materials is tending toward increasingly complex compositions. Synthesizing precise composition is time-consuming and becomes exponentially demanding with increasing compositional complexity. An experienced human operator does significantly better than a novice but still struggles to consistently achieve precision when synthesis parameters are coupled. The time to optimize synthesis becomes a barrier to exploring scientifically and technologically exciting compositionally complex materials. This investigation demonstrates an active learning (AL) approach for optimizing physical vapor deposition synthesis of thin-film alloys with up to five principal elements. We compared AL-based on Gaussian process (GP) and random forest (RF) models. The best performing models were able to discover synthesis parameters for a target quinary alloy in 14 iterations. We also demonstrate the capability of these models to be used in transfer learning tasks. RF and GP models trained on lower dimensional systems (i.e., ternary, quarternary) show an immediate improvement in prediction accuracy compared to models trained only on quinary samples. Furthermore, samples that only share a few elements in common with the target composition can be used for model pre-training. We believe that such AL approaches can be widely adapted to significantly accelerate the exploration of compositionally complex materials.

Chemistry↗
NASA NTRS1991

Low Temperature Environment Operations of Turboengines (Design and User's Problems)

The author summarizes and links together a number of papers that were presented at the Propulsion and Energetics (PEP) symposium on low temperature environment operation of turbojet engines that was held October 8 to 12, 1990. Topics covered include operational experience of ice ingestion in the turboprop engine in the 2,000 hp class, icing on helicopter turbo engines, icing test facilities, ice relevant cloud physical parameters, and low temperature and fuel problems.

R Jacques↗
DOE OSTI2026

Structure of Self-Generated Magnetic Fields in Laser-Solid Interaction from Proton Tomography

Self-generated magnetic fields in laser-solid interactions are experimentally characterized to reveal the 3D location and local field strength, rather than path-integrated quantities, using multi-view proton radiography and tomographic inversion. We infer magnetic fields that extend several millimeters off the target into the hot, rarefied corona, sufficient to strongly magnetize the plasma (Ω e τ e ≫ 1). The data are compared to MHD simulations incorporating recent improvements in modeling magnetic field generation and transport; the volume-averaged coronal field strength and magnetic flux agree to within 25% using a model with magnetic re-localization of transport, although the near-target morphology is not reproduced. This work demonstrates tomographic proton radiography as a valuable tool for investigating magnetic fields in laser-produced plasmas.

High-energy-density plasmas↗
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 OSTI2024

Simulating hindered grain boundary diffusion using the smoothed boundary method

Abstract Grain boundaries can greatly affect the transport properties of polycrystalline materials, particularly when the grain size approaches the nanoscale. While grain boundaries often enhance diffusion by providing a fast pathway for chemical transport, some material systems, such as those of solid oxide fuel cells and battery cathode particles, exhibit the opposite behavior, where grain boundaries act to hinder diffusion. To facilitate the study of systems with hindered grain boundary diffusion, we propose a model that utilizes the smoothed boundary method to simulate the dynamic concentration evolution in polycrystalline systems. The model employs domain parameters with diffuse interfaces to describe the grains, thereby enabling solutions with explicit consideration of their complex geometries. The intrinsic error arising from the diffuse interface approach employed in our proposed model is explored by comparing the results against a sharp interface model for a variety of parameter sets. Finally, two case studies are considered to demonstrate potential applications of the model. First, a nanocrystalline yttria-stabilized zirconia solid oxide fuel cell system is investigated, and the effective diffusivities are extracted from the simulation results and are compared to the values obtained through mean-field approximations. Second, the concentration evolution during lithiation of a polycrystalline battery cathode particle is simulated to demonstrate the method’s capability.

Materials Science↗