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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

The Mapping X-Ray Fluorescence Spectrometer (MAPX)

MapX will provide elemental imaging at ≤100 micron spatial resolution over 2.5 X 2.5 centimeter areas, yielding elemental chemistry at or below the scale length where many relict physical, chemical, and biological features can be imaged and interpreted in ancient rocks. MapX is a full-frame spectroscopic imager positioned on soil or regolith with touch sensors. During an analysis, an X-ray source (tube or radioisotope) bombards the sample surface with X-rays or αlpha-particles / gamma rays, resulting in sample X-ray Fluorescence (XRF). Fluoresced X-rays pass through an X-ray lens (X-ray μ-Pore Optic, "MPO") that projects a spatially resolved image of the X-rays onto a CCD. The CCD is operated in single photon counting mode so that the positions and energies of individual photons are retained. In a single analysis, several thousand frames are stored and processed. A MapX experiment provides elemental maps having a spatial resolution of ≤100 micron and quantitative XRF spectra from Regions of Interest (ROI) 2 centimers ≤ x ≤ 100 micron. ROI are compared with known rock and mineral compositions to extrapolate the data to rock types and putative mineralogies. The MapX geometry is being refined with ray-tracing simulations and with synchrotron experiments at SLAC. Source requirements are being determined through Monte Carlo modeling and experiment using XMIMSIM [1], GEANT4 [2] and PyMca [3] and a dedicated XRF test fixture. A flow-down of requirements for both tube and radioisotope sources is being developed from these experiments. In addition to Mars lander and rover missions, MapX could be used for landed science on other airless bodies (Phobos/Deimos, Comet nucleus, asteroids, the Earth's moon, and the icy satellites of the outer planets, including Europa.

Blake, David↗
NASA NTRS2021

SMD Technology Highlights

Six technology highlights from the Science Mission Directorate (SMD) Heliophysics, Astrophysics, Earth, and Biological and Physical Sciences divisions. Technologies featured include 1. the 1653 m2 Solar Cruiser Solar Sail Propulsion system to enable missions to reach novel and otherwise difficult or impossible destinations for observing the Sun. 2. Technology sponsored by NASA and developed by MIT Space Nanotechnology Lab is developing high-performance space instrumentation for more powerful future X-ray telescopes that will study the dynamics of the high-energy universe. 3. Active thermal control technology that will help enable large ultra-stable telescopes needed to detect and characterize Earth-like planets around other stars. 4. SMD sponsored high-performance infrared sensors with reduced requirements for cooling onboard satellites and these sensors could potentially be flown on small satellite platforms like CubeSats. 5. A new technology that will utilize electron beams/ultraviolet light to remove dust that could help protect future space assets and astronauts from dangerous effects that arise from Moon/Mars dust exposure. 6. Studies using model organisms on ISS to understand the impact of the spaceflight environment on organisms in preparation for long-duration missions.

solar sail↗
NASA NTRS2021

SMD Technology Highlights

Two technology highlights from the Science Mission Directorate (SMD) Planetary Science Division and Biological and Physical Sciences division are featured: a) The Dynamic Radioisotope Power Systems Project (DRPS) may enable lunar science payloads to survive and thrive during the harsh lunar night. New robust DRPS have been built and delivered by industry and are in the process of being tested at NASA’s Glenn Research Center. b) NASA's Plant Water Management (PWM) project is demonstrating that even without the help of gravity, hydroponic plant watering methods can enable plant habitats aboard crewed or robotic space missions. On Earth, plants draw water upwards through the roots against gravity, via capillary action, which orients the plant and enables display of its canopy (foliage and branches) for optimal photosynthesis and transpiration. The plant grows above the nutrient-rich soil as the water U.S. Astronaut Kate Rubins poses with PWM after nearly doubling the science returns of the ISS experiment by drawing on her wealth of wet lab operations and handling experience—on Earth and in space.

RPS↗
NASA NTRS2020

Characterization of stellar activity using transits and its impact on habitability

Stellar magnetic field is the driver of activity in stars and can trigger spots, energetic flares, coronal plasma ejections and ionized winds. These phenomena play a crucial role in understanding the internal mechanisms of the star, but can also have potential effects in orbiting planets. During the transit of a planet, spots can be occulted producing features imprinted in the transit light curve. Here, we modelled these features to characterize the physical properties of the spots (radius, intensity, and location). In addition, we monitor spots signatures on multiple transits to estimate magnetic cycles length of Kepler stars. Flares have also been observed during transits in active stars. We derive the properties of the flares and analyse their UV impact on possible living organisms in planets orbiting in the habitable zone.

Estrela, Raissa↗
NASA NTRSDate not supplied

Indigenous Organic Matter Associated with Unusual Low Temperature Aqueous Secondary Phases in the Mars Meteorite Nakhla

The Martian meteorite Nakhla provides demonstrates evidence of mineral-water interactions that occurred in the Martian regolith within the last 1 Ga, as well as the presence of trace indigenous organic matter. The aim of our research is threefold: [1] provide a context in which to interpret alteration features; [2] determine the physical and chemical environment during alteration; and, [3] investigate the hypothesis that the formation of alteration phases was intimately involved in the accumulation and/or preservation of organic matter. In freshly fractured chips of the Mars meteorite Nakhla, we found carbonaceous matter intimately associated with secondary aqueous alteration phases interpreted to have formed through the low-temperature, mineral-water dissolution of the host Martian basalt. We have characterized the nature of carbonaceous matter and spatially associated secondary phases within Nakhla using a multidisciplinary suite of analytical instrumentation. The aim of our research is to provide a context to interpret the formation of secondary alteration assemblages within the Mars meteorite Nakhla and determine whether, and if so the extent to which, these phases participated in the accumulation and preservation of Martian organic matter.

Mars meteorite↗
DOE OSTI2020

Situation awareness and dynamic ensemble forecasting of abnormal behavior in cyber-physical system

A plurality of monitoring nodes may each generate a time-series of current monitoring node values representing current operation of a cyber-physical system. A feature-based forecasting framework may receive the time-series of and generate a set of current feature vectors using feature discovery techniques. The feature behavior for each monitoring node may be characterized in the form of decision boundaries that separate normal and abnormal space based on operating data of the system. A set of ensemble state-space models may be constructed to represent feature evolution in the time-domain, wherein the forecasted outputs from the set of ensemble state-space models comprise anticipated time evolution of features. The framework may then obtain an overall features forecast through dynamic ensemble averaging and compare the overall features forecast to a threshold to generate an estimate associated with at least one feature vector crossing an associated decision boundary.

Abbaszadeh, Masoud↗
DOE OSTI2025

PhotonIDs: ML-Powered Photon Identification System for Dark Count Elimination

Reliable single photon detection is the foundation for practical quantum communication and networking. However, today's superconducting nanowire single photon detector(SNSPD) inherently fails to distinguish between genuine photon events and dark counts, leading to degraded fidelity in long-distance quantum communication. In this work, we introduce PhotonIDs, a machine learning-powered photon identification system that is the first end-to-end solution for real-time discrimination between photons and dark count based on full SNSPD readout signal waveform analysis. PhotonIDs ~demonstrates: 1) an FPGA-based high-speed data acquisition platform that selectively captures the full waveform of signal only while filtering out the background data in real time; 2) an efficient signal preprocessing pipeline, and a novel pseudo-position metric that is derived from the physical temporal-spatial features of each detected event; 3) a hybrid machine learning model with near 98% accuracy achieved on photon/dark count classification. Additionally, proposed PhotonIDs ~ is evaluated on the dark count elimination performance with two real-world case studies: (1) 20 km quantum link, and (2) Erbium ion-based photon emission system. Our result demonstrates that PhotonIDs ~could improve more than 31.2 times of signal-noise-ratio~(SNR) on dark count elimination. PhotonIDs ~ marks a step forward in noise-resilient quantum communication infrastructure.

Linne, Karl C. [Chicago U.] (ORCID:000900091870358↗
DOE OSTI2026

Machine learning for slow-extraction uniformity at the Fermilab Delivery Ring

The Muon-to-Electron Conversion Experiment (Mu2e) requires uniform slow extraction from the Fermilab Delivery Ring during each 43 ms spill. This project analyzed 13,737 spills from seven parquet files collected during March and June 2026 commissioning. Each spill contained 430 samples at 0.1 ms resolution and was summarized by the Spill Duty Factor. Null Action and active proportional-integral-derivative conditions established operational baselines. Fixed-ramp sessions were segmented to evaluate reproducibility, drift, and spill-to-spill spread, while a deliberate quadrupole-ramp step identified the beam-response peak and trough. Median profiles were reproducible within fixed conditions but drifted over multi-hour periods. The resulting baselines and response features support future physics-based and machine-learning approaches to real-time spill regulation.

Prescott, Matthew J. [Purdue U., West Lafayette; F↗
DOE OSTI2021

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

Physics-informed neural networks (PINNs) are demonstrating remarkable promise in integrating physical models with gappy and noisy observational data, but they still struggle in cases where the target functions to be approximated exhibit high-frequency or multi-scale features. Here in this work we investigate this limitation through the lens of Neural Tangent Kernel (NTK) theory and elucidate how PINNs are biased towards learning functions along the dominant eigen-directions of their limiting NTK. Using this observation, we construct novel architectures that employ spatio-temporal and multi-scale random Fourier features, and justify how such coordinate embedding layers can lead to robust and accurate PINN models. Numerical examples are presented for several challenging cases where conventional PINN models fail, including wave propagation and reaction–diffusion dynamics, illustrating how the proposed methods can be used to effectively tackle both forward and inverse problems involving partial differential equations with multi-scale behavior.

42 ENGINEERING↗
NASA NTRS1990

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

Petty, Grant W.↗
NASA NTRS1991

A phenomenological approach to multisource data integration: Analysing infrared and visible data

A new method is described for combining multisensory data for remote sensing applications. The approach uses phenomenological models which allow the specification of discriminatory features that are based on intrinsic physical properties of imaged surfaces. Thermal and visual images of scenes are analyzed to estimate surface heat fluxes. Such analysis makes available a discriminatory feature that is closely related to the thermal capacitance of the imaged objects. This feature provides a method for labelling image regions based on physical properties of imaged objects. This approach is different from existing approaches which use the signal intensities in each channel (or an arbitrary linear or nonlinear combination of signal intensities) as features - which are then classified by a statistical or evident approach.

Nandhakumar, N.↗
NASA NTRSDate not supplied

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗
NASA NTRSDate not supplied

Utilization of Streamtubes to Analyze the Physical Interaction of a Dispersed Cloud with the CRM65 Hybrid Midspan Model

Recently there have been numerous efforts to identify the relevant icing physics related to the formation of complex three dimensional features, sometimes referred to as ’scallops’, on swept wings. However, much of the physics is still not well understood. This paper computationally investigates the interaction of the icing cloud with the 65 percent Common Research Model (CRM65). Both the interaction with an uniced model, and the interaction with a representative simulated three dimensional ice accretion are analyzed. Preliminary results suggest that the liquid water content increases near the aerodynamic body. For small droplets on the uniced geometry, the particle velocity vector becomes nearly parallel with the aerodynamic model resulting in a low value of collection efficiency. When a three dimensional feature with a length scale much smaller than the leading edge of the airfoil is introduced into the flow, the impingement of small particles can become significantly more perpendicular to the particle velocity vector in the region of these features. Since the liquid water content near the body has increased due to the interaction with the larger scale features of the aerodynamic model, i.e. the leading edge of the swept wing, extremely high collection efficiency is observed. These results suggest that three dimensional features are likely a significant physical driver that should be modeled in some capacity when simulating the impingement of a cloud on an aerodynamic model.

Icing↗
NASA NTRS1981

Observability of atomic line features in strong magnetic fields

The physical properties of atoms in superstrong magnetic fields, characteristic of neutron stars, and the possibility of detecting magnetically strongly shifted atomic lines in the spectra of magnetized X-ray pulsars are discussed. It is suggested that it is recommendable to look for magnetically strongly shifted Fe 26 Lyman lines in rotating neutron stars of not too high luminosity using spectrometers working in the energy range 10 - 20 keV, with sensitivities to minus 4 power photons per sq cm and second, and resolution E/delta E approx. 10-100.

Wunner, G.↗
DOE OSTI2021

Expanded Capabilities and Opportunities for Virtual Beamline Code

In the 25 years since LLNL broke ground on the National Ignition Facility (NIF) - a cornerstone of the National Nuclear Security Administration’s Stockpile Stewardship Program - the NIF and Photon Science (NIF&PS) Directorate has steadily pushed the boundaries of laser physics, nonlinear optics, and photonics in service of inertial confinement fusion experiments, and advanced photon sources development. Beyond the 192 beamlines of the primary laser facility with its world-record energy and fusion yields, NIF&PS capabilities have expanded to include chirped-pulse amplification, kilojoule petawatt-class short-pulse systems to generate hard x-ray radiographic probes, high-average power lasers as secondary sources for generation or wake field particle acceleration along directed energy applications, and other scientific pursuits. The Computing Directorate partners with NIF&PS on numerous projects and technologies from diagnostic measurements and high performance control systems to data analysis, information technology infrastructure, and scientific simulation code development. “This strong collaboration enables cutting-edge science, particularly with regard to physics-based modeling and simulation,” says physicist Jean-Michel Di Nicola. One crucial capability for NIF&PS is the Virtual Beamline (VBL) laser simulation code. It can model all the major laser physics and technology involved in the design optimization, commissioning, and operations of advanced laser architectures from tabletop to NIF-scale. VBL provides researchers with high-fidelity models and high-resolution calculations of laser performance predictions—including for the entire NIF laser system, the Advanced Radiographic Capability, parts of the High Repetition-Rate Advanced Petawatt Laser System laser delivered to the Czech Republic, and the Optical Science Laser. After more than two decades of experimentally verified physics and computing enhancements, this unique workhorse code is wrapping up another major milestone: migration from Java to C++ with a flurry of user interface and optimization features, as well as laser physics and high-resolution enhancements thanks to parallel execution on Livermore Computing platforms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Identifying critical features of iron phosphate particle for lithium preference

One-dimensional (1D) olivine iron phosphate (FePO 4 ) is widely proposed for electrochemical lithium (Li) extraction from dilute water sources, however, significant variations in Li selectivity were observed for particles with different physical attributes. Understanding how particle features influence Li and sodium (Na) co-intercalation is crucial for system design and enhancing Li selectivity. Here, we investigate a series of FePO 4 particles with various features and revealed the importance of harnessing kinetic and chemo-mechanical barrier difference between lithiation and sodiation to promote selectivity. The thermodynamic preference of FePO 4 provides baseline of selectivity while the particle features are critical to induce different kinetic pathways and barriers, resulting in different Li to Na selectivity from 6.2 × 10 2 to 2.3 × 10 4 . Importantly, we categorize the FePO 4 particles into two groups based on their distinctly paired phase evolutions upon lithiation and sodiation, and generate quantitative correlation maps among Li preference, morphological features, and electrochemical properties. By selecting FePO 4 particles with specific features, we demonstrate fast (636 mA/g) Li extraction from a high Li source (1: 100 Li to Na) with (96.6 ± 0.2)% purity, and high selectivity (2.3 × 10 4 ) from a low Li source (1: 1000 Li to Na) with (95.8 ± 0.3)% purity in a single step.

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

Collision Tracking in OpenMC: Methods and Applications in Neutron Noise, Neutron Imaging, Time-of-Flight, and Multiplicity Counting

We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.

Monte Carlo code↗
DOE OSTI2024

Griffin: A MOOSE-based reactor physics application for multiphysics simulation of advanced nuclear reactors

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE) based reactor physics application for multiphysics simulations of advanced reactor designs jointly developed by Idaho National Laboratory and Argonne National Laboratory. This paper summarizes the motivation, significance, architecture, design, and features of Griffin. Griffin offers flexible and extensible features to address the challenges associated with advanced reactor designs. These features range from fundamental particle transport to specific reactor physics tasks. The features cover a wide range including on-the-fly and traditional two-step cross-section generation methods, steady-state and transient transport solvers suitable for both heterogeneous and homogeneous models, high-fidelity depletion where thousands of isotopes can be tracked and low-fidelity depletion characterized by burnup, etc. The most fundamental aspect that sets Griffin apart from other reactor analysis codes is that it is developed based on the MOOSE framework. A modular development approach is strongly enforced, with multiphysics being an essential element considered since the beginning of Griffin’s development. Griffin links various MOOSE physics modules and couples to other MOOSE-based applications and non-MOOSE-based applications for multiphyiscs simulations. Griffin includes three modules: ISOXML for preparing and managing multigroup cross sections, radiation transport for solving the neutron transport equation, and reactor analysis for user-oriented reactor physics analysis functionalities. Griffin uses various finite element methods for spatial discretization, multigroup approximation for energy discretization and discrete ordinates method, spherical harmonics expansion method, and diffusion approximation for streaming direction discretization to solve the neutron transport equation. Griffin’s flexibility is evidenced through Griffin’s various applications to fast reactor, high-temperature reactor, pebble bed reactor, molten salt reactor, and microreactor designs. Griffin development follows the software quality assurance procedure for MOOSE-based applications and with software requirements consistent with the ASME NQA-1 standard. Griffin has been adopted into the reactor analysis system for the U.S. NRC and is in use at U.S. companies, universities and national laboratories.

97 MATHEMATICS AND COMPUTING↗