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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Search for doubly and singly charged Higgs bosons decaying into vector bosons in multi-lepton final states with the ATLAS detector using proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for charged Higgs bosons decaying into W ± W ± or W ± Z bosons is performed, involving experimental signatures with two leptons of the same charge, or three or four leptons with a variety of charge combinations, missing transverse momentum and jets. A data sample of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded with the ATLAS detector at the Large Hadron Collider between 2015 and 2018 is used. The data correspond to a total integrated luminosity of 139 fb -1 . The search is guided by a type-II seesaw model that extends the scalar sector of the Standard Model with a scalar triplet, leading to a phenomenology that includes doubly and singly charged Higgs bosons. Two scenarios are explored, corresponding to the pair production of doubly charged H ±± bosons, or the associated production of a doubly charged H ±± boson and a singly charged H ± boson. No significant deviations from the Standard Model predictions are observed. H ±± bosons are excluded at 95% confidence level up to 350 GeV and 230 GeV for the pair and associated production modes, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Search for long-lived particles using out-of-time trackless jets in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for long-lived particles decaying in the outer regions of the CMS silicon tracker or in the calorimeters is presented. The search is based on a data sample of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded with the CMS detector at the LHC in 2016–2018, corresponding to an integrated luminosity of 138 fb −1 . A novel technique, using nearly trackless and out-of-time jet information combined in a deep neural network discriminator, is employed to identify decays of long-lived particles. The results are interpreted in a simplified model of chargino-neutralino production, where the neutralino is the next-to-lightest supersymmetric particle, is long-lived, and decays to a gravitino and either a Higgs or Z boson. This search is most sensitive to neutralino proper decay lengths of approximately 0.5 m, for which masses up to 1.18 TeV are excluded at 95% confidence level. The current search is the best result to date in the mass range from the kinematic limit imposed by the Higgs boson mass up to 1.8 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Accelerating Structure–Property Relationship Discovery with Multimodal Machine Learning and Self-Driving Microscopy

Microscopy combined with local spectroscopy is widely used to correlate nanoscale structure with functional properties in materials, but conventional measurements rely heavily on human-selected sampling locations and predefined targets, limiting data set diversity and the potential for discovery. Here, we present a framework that integrates autonomous microscopy with dual-novelty deep kernel learning (DN-DKL) for adaptive data acquisition and a dual variational autoencoder (VAE) for representation learning. DN-DKL actively guides the microscopy toward structurally and spectroscopically novel regions, enabling efficient collection of large spectral data sets. Dual-VAE embeds local structures and spectroscopic responses into a shared latent manifold that serves as a structure–property relationship map. We applied this framework for the investigation of halide perovskite films by using conductive atomic force microscopy. The results reveal distinct hysteresis behaviors that are linked to specific nanoscale structural motifs, including grain boundary junction points that show hysteresis under different bias conditions and asymmetric grain boundaries that suppress the charge transport. This framework establishes a general strategy that leverages the complementary strengths of self-driving microscopy, machine learning, and human expertise to accelerate scientific discovery in functional materials.

atomic force microscopy↗
DOE OSTI2021

Impact of Surface Recombination on Single-Event Charge Collection in an SOI Technology

Semiconductor–insulator interfaces play an important role in the reliability of integrated devices; however, the impact of these interfaces on the physical mechanisms related to single-event effects has not been previously reported. We present experimental data that demonstrate that single-event charge collection can be impacted by changes in interface quality. The experimental data, combined with simulations, show that single-event response may depend on surface recombination at interface defects. The effect depends on strike location and increases with increasing linear energy transfer (LET). Surface recombination can affect single-event charge collection for interfaces with a surface recombination velocity (SRV) of 1000 cm/s and is a dominant charge collection mechanism with SRV >10 5 cm/s.

42 ENGINEERING↗
DOE OSTI2026

Learning genetic perturbation effects with variational causal inference

Advances in sequencing technologies have enhanced the understanding of gene regulation in cells. In particular, Perturb-seq has enabled high-resolution profiling of the transcriptomic response to genetic perturbations at the single-cell level. This understanding has implications in functional genomics and potentially for identifying therapeutic targets. Various computational models have been developed to predict perturbational effects. While deep learning models excel at interpolating observed perturbational data, they tend to overfit in the lack of enough data and may not generalize well to unseen perturbations. In contrast, mechanistic models, such as linear causal models based on gene regulatory networks, hold greater potential for extrapolation, as they encapsulate regulatory information that can predict responses to unseen perturbations. However, their application has been limited to small studies due to overly simplistic assumptions, making them less effective in handling noisy, large-scale single-cell data. We propose a hybrid approach that combines a mechanistic causal model with variational deep learning, termed Single Cell Causal Variational Autoencoder (SCCVAE). The mechanistic model employs a learned regulatory network to represent perturbational changes as shift interventions that propagate through the learned network. SCCVAE integrates this mechanistic causal model into a variational autoencoder, generating rich, comprehensive transcriptomic responses. Our results indicate that SCCVAE exhibits superior performance over current state-of-the-art baselines for extrapolating to predict unseen perturbational responses. Additionally, for the observed perturbations, the latent space learned by SCCVAE allows for the identification of functional perturbation modules and simulation of single-gene knockdown experiments of varying penetrance, presenting a robust tool for interpreting and interpolating perturbational responses at the single-cell level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Predicting Dynamic-to-Static Correction Factor from Petrophysical Data and Chemostratigraphy using Unsupervised Machine Learning

Estimating static mechanical properties of stratigraphic layers is critical for optimizing subsurface engineering applications. To estimate dynamic-to-static correction factor F ds (static-to-dynamic Young’s modulus ratio) across the Caney shale interval in Oklahoma, USA, we integrated triaxial test measurements and petrophysical data, including well logs and X-ray fluorescence (XRF) using unsupervised machine learning (ML). We used a novel workflow that includes principal component analysis (PCA) to reduce data set dimensionality of well logs and XRF data sets—both separately and combined—creating three scenarios, and later applied inverse distance weighting (IDW) to derive F ds profiles for these scenarios. Furthermore, we applied K-means clustering on each scenario to predict depositional facies, and built a stiffness zonation profile through chemostratigraphic analysis of the terrigenous elements to validate the predicted F ds . The predicted F ds profile from each scenario using the PCA-IDW method was compared with the constant F ds approach from our previous study by calculating the root mean square error (RMSE). The combined data sets scenario yielded the lowest RMSE value of 0.113, while the RMSE values for the well logs and XRF scenarios were 0.131 and 0.129, respectively. In addition, the predicted F ds from the XRF scenario well-matched the stiffness zonation from the chemostratigraphic analysis that was built using the optimized K-means clustering of nine clusters for that scenario. These methods and findings offer a valuable tool for refining lithological classification and improving the F ds profile, potentially enhancing drilling and stimulation strategies for subsurface energy engineering applications.

clastic rock↗
DOE OSTI2021

A Method to Extract Spatially Resolved Polycyclic Aromatic Hydrocarbon Emission from Spitzer Spectra: Application to M51

The mid-infrared spectrum contains rich diagnostics to probe the physical properties of galaxies, among which the pervasive emission features from polycyclic aromatic hydrocarbons (PAHs) offer promising means of estimating the star formation rate (SFR) relatively immune from dust extinction. This paper investigates the effectiveness of PAH emission as a SFR indicator on subkiloparsec scales by studying the Spitzer/IRS mapping-mode observations of the nearby grand-design spiral galaxy M51. We present a new approach of analyzing the spatial elements of the spectral data cube that simultaneously maximizes spatial resolution and spatial coverage, while yielding reliable measurements of the total, integrated 5–20 μm PAH emission. We devise a strategy of extracting robust PAH emission using spectra with only partial spectral coverage, complementing missing spectral regions with properly combined mid-infrared photometry. We find that in M51 the PAH emission correlates tightly with the extinction-corrected far-ultraviolet, near-ultraviolet, and Hα emission, from scales of ∼0.4 kpc close to the nucleus to 6 kpc out in the disk of the galaxy, indicating that PAH serves as an excellent tracer of SFR over a wide range of galactic environments. But regional differences exist. Close to the active nucleus of M51 the 6.2 μm feature is weaker, and the overall level of PAH emission is suppressed. The spiral arms and the central star-forming region of the galaxy emit stronger 7.7 and 8.6 μm PAH features than the inter-arm regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

SCExAO/MEC and CHARIS Discovery of a Low-mass, 6 au Separation Companion to HIP 109427 Using Stochastic Speckle Discrimination and High-contrast Spectroscopy

We report the direct imaging discovery of a low-mass companion to the nearby accelerating A star, HIP 109427, with the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument coupled with the Microwave Kinetic Inductance Detector Exoplanet Camera (MEC) and CHARIS integral field spectrograph. CHARIS data reduced with reference star point spread function (PSF) subtraction yield 1.1–2.4 μm spectra. MEC reveals the companion in Y and J band at a comparable signal-to-noise ratio using stochastic speckle discrimination, with no PSF subtraction techniques. Combined with complementary follow-up L {sub p} photometry from Keck/NIRC2, the SCExAO data favors a spectral type, effective temperature, and luminosity of M4–M5.5, 3000–3200 K, and log{sub 10}(L/L{sub ⊙})=−2.28{sub −0.04}{sup +0.04}, respectively. Relative astrometry of HIP 109427 B from SCExAO/CHARIS and Keck/NIRC2, and complementary Gaia–Hipparcos absolute astrometry of the primary favor a semimajor axis of 6.55{sup +3.0} {sub −0.48} au, an eccentricity of 0.54{sub −0.15}{sup +0.28}, an inclination of 66.7{sub −14}{sup +8.5} degrees, and a dynamical mass of 0.280{sub −0.059}{sup +0.18} M {sub ⊙}. This work shows the potential for extreme AO systems to utilize speckle statistics in addition to widely used postprocessing methods to directly image faint companions to nearby stars near the telescope diffraction limit.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1979

Multiclass Bayes error estimation by a feature space sampling technique

A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Mobasseri, B. G.↗
NASA NTRS1982

Effects of higher order control systems on aircraft approach and landing longitudinal handling qualities

An investigation of approach and landing longitudinal flying qualities, based on data generated using a variable stability NT-33 aircraft combined with significant control system dynamics is described. An optimum pilot lead time for pitch tracking, flight path angle tracking, and combined pitch and flight path angle tracking tasks is determined from a closed loop simulation using integral squared error (ISE) as a performance measure. Pilot gain and lead time were varied in the closed loop simulation of the pilot and aircraft to obtain the best performance for different control system configurations. The results lead to the selection of an optimum lead time using ISE as a performance criterion. Using this value of optimum lead time, a correlation is then found between pilot rating and performance with changes in the control system and in the aircraft dynamics. It is also shown that pilot rating is closely related to pilot workload which, in turn, is related to the amount of lead which the pilot must generate to obtain satisfactory response. The results also indicate that the pilot may use pitch angle tracking for the approach task and then add flight path angle tracking for the flare and touchdown.

Pasha, M. A.↗
NASA NTRS1990

Satellite image analysis using neural networks

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

Sheldon, Roger A.↗
NASA NTRS1993

An Integrated XRF/XRD Instrument for Mars Exobiology and Geology Experiments

By employing an integrated x-ray instrument on a future Mars mission, data obtained will greatly augment those returned by Viking; details characterizing the past and present environment on Mars and those relevant to the possibility of the origin and evolution of life will be acquired. A combined x-ray fluorescence/x-ray diffraction (XRF/XRD) instrument was breadboarded and demonstrated to accommodate important exobiology and geology experiment objectives outlined for MESUR and future Mars missions. Among others, primary objectives for the exploration of Mars include the intense study of local areas on Mars to establish the chemical, mineralogical, and petrological character of different components of the surface material; to determine the distribution, abundance, and sources and sinks of volatile materials, including an assessment of the biologic potential, now and during past epoches; and to establish the global chemical and physical characteristics of the Martian surface. The XRF/XRD breadboard instrument identifies and quantifies soil surface elemental, mineralogical, and petrological characteristics and acquires data necessary to address questions on volatile abundance and distribution. Additionally, the breadboard is able to characterize the biogenic element constituents of soil samples providing information on the biologic potential of the Mars environment. Preliminary breadboard experiments confirmed the fundamental instrument design approach and measurement performance.

Koppel, L. N.↗
NASA NTRS2005

FY04 IRAD-funded GSFC Lambda Network (L-Net) Web Pages and Related Presentations

This presentation discusses the advances in Networking Technology combining the Global Lambda Integrated Facility (GLIF) cooperation with the National Lambda Rail (NLR) implementation. It also focuses on New NASA science needing Gigbit per second networks (Gbps) with coordinated Earth Observing Program, hurricane predictions, global aerosols, remote viewing and manipulation of large Earth Science Data Sets, integration of laser and radar topographic data with land cover data.

Gary, J. Patrick↗
NASA NTRS2010

Radiation-Hardened Solid-State Drive

A method is provided for a radiationhardened (rad-hard) solid-state drive for space mission memory applications by combining rad-hard and commercial off-the-shelf (COTS) non-volatile memories (NVMs) into a hybrid architecture. The architecture is controlled by a rad-hard ASIC (application specific integrated circuit) or a FPGA (field programmable gate array). Specific error handling and data management protocols are developed for use in a rad-hard environment. The rad-hard memories are smaller in overall memory density, but are used to control and manage radiation-induced errors in the main, and much larger density, non-rad-hard COTS memory devices. Small amounts of rad-hard memory are used as error buffers and temporary caches for radiation-induced errors in the large COTS memories. The rad-hard ASIC/FPGA implements a variety of error-handling protocols to manage these radiation-induced errors. The large COTS memory is triplicated for protection, and CRC-based counters are calculated for sub-areas in each COTS NVM array. These counters are stored in the rad-hard non-volatile memory. Through monitoring, rewriting, regeneration, triplication, and long-term storage, radiation-induced errors in the large NV memory are managed. The rad-hard ASIC/FPGA also interfaces with the external computer buses.

Sheldon, Douglas J.↗
NASA NTRS2011

Interpretation of the Arcade 2 Absolute Sky Brightness Measurement

We use absolutely calibrated data between 3 and 90 GHz from the 2006 balloon flight of the ARCADE 2 instrument, along with previous measurements at other frequencies to constrain models of extragalactic emission. Such emission is a combination of the cosmic microwave background (CMB) monopole, Galactic foreground emission, the integrated contribution of radio emission from external galaxies, any spectral distortions present in the CMB, and any other extragalactic source. After removal of estimates of foreground emission from our own Galaxy, and an estimated contribution of external galaxies, we present fits to a combination of the flat-spectrum CMB and potential spectral distortions in the CMB. We find 217 upper limits to CMB spectral distortions of u < 6x10(exp -4) and [Y(sub ff)] < 1x10(exp -4). We also find a significant detection of a residual signal beyond that, which can be explained by the CMB plus the integrated radio emission from galaxies estimated from existing surveys. This residual signal may be due to an underestimated galactic foreground contribution, an unaccounted for contribution of a background of radio sources, or some combination of both. The residual signal is consistent with emission in the form of a power law with amplitUde 18.4 +/- 2.1 K at 0.31 GHz and a spectral index of -2.57 +/- 0.05.

Seiffert, M.↗
NASA NTRS2014

Venus High Temperature Atmospheric Dropsonde and Extreme-Environment Seismometer (HADES)

The atmospheric composition and geologic structure of Venus have been identified by the US National Research Council's Decadal Survey for Planetary Science as priority targets for scientific exploration, however the high temperature and pressure at the surface, along with the highly corrosive chemistry of the Venus atmosphere, present significant obstacles to spacecraft design that have severely limited past and proposed landed missions. Following the methodology of the NASA Innovative Advanced Concepts (NIAC) proposal regime and the Collaborative Modeling and Parametric Assessment of Space Systems (COMPASS) design protocol, this paper presents a conceptual study and initial feasibility analysis for a Discovery-class Venus lander capable of an extended-duration mission at ambient temperature and pressure, incorporating emerging technologies within the field of high temperature electronics in combination with novel configurations of proven, high Technology Readiness Level (TRL) systems. Radioisotope Thermal Power (RTG) systems and silicon carbide (SiC) communications and data handling are examined in detail, and various high-temperature instruments are proposed, including a seismometer and an advanced photodiode imager. The study combines this technological analysis with proposals for a descent instrument package and a relay orbiter to demonstrate the viability of an integrated atmospheric and in-situ geologic exploratory mission that differs from previous proposals by greatly reducing the mass, power requirements, and cost, while achieving important scientific goals.

HADES↗
NASA NTRSDate not supplied

LS-DYNA User-Defined Internal Ballistic Modeling

- LS-DYNA Explicit Finite Element Analysis software and CADPROG Internal Ballistic Analysis code are integrated as a single modeling tool to analyze pyro-mechanical devices. - Combining these two codes allows the ballistic calculations to be performed without modeling the propellant in an FEA mesh. At each LS-DYNA time step, CADPROG is analytically run using the kinematic data (stroke, velocity, chamber volume) fed back from the LS-DYNA simulation. Calculated pressure is then applied to a piston or any applicable surface mesh in LS-DYNA model interactively. -All external loads such as friction, damping loads, assisting/resisting loads, locking/unlocking loads are modeled in LS-DYNA and coupled with pressure loads from CADPROG to create a fully defined equation of motion -Both codes are written in Fortran 77. CADPROG is inserted in LS-DYNA source code as a user-defined subroutine and re-compiled to generate a custom executable.

pyrotechnics↗
NASA NTRSDate not supplied

Integration of CFD and Wind-Tunnel Testing at NASA

The debate over when wind-tunnel testing will be replaced by Computational Fluid Dynamics (CFD) comes and goes. More recently, however, the debate has subsided with a more collaborative spirit between practitioners of these two disciplines. Combining these complementary disciplines has led to significant improvements in both as well as better understanding of aero- and fluid dynamics. Also, as CFD codes become more accurate, the need for comparisons with experimental data has increased. New measurement techniques, pressure-sensitive paint and off-body velocity measurements for example, have provided detailed, high-quality data for the comparisons. In-tunnel CFD simulations are also providing more direct comparisons between predicted and measured flows. Given this newenvironment, a concerted effort is now underway to facilitate in-tunnel CFD for the 12 major wind tunnels operated by NASA.The Aerosciences Evaluation and Test Capabilities Portfolio (AETC) manages the major aerodynamic ground-testing facilities within NASA. This group is responsible for the operation, maintenance, and improvement of the wind-tunnel facilities and their capabilities. AETC has recently added a project to integrate CFD and wind-tunnel testing to better support customers of the NASA wind tunnels and to better understand the flow in the wind tunnels themselves. Being able to perform CFD simulations of wind-tunnel models in the wind tunnel environment providesthe cleanest way to assess the accuracy of the simulations relative to test data. AETC plans to provide accurate geometry and guidance to wind-tunnel customers who request it, to facilitate in-tunnel simulations. How this effort got started will be presented along with the status and plans for the project.

CFD↗