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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Evaluation of Composite Airframe Dynamic Impact Modeling Using Hawker 4000 Fuselage Drop Test Data

Two drop tests of partial Hawker 4000 fuselage sections were conducted at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) to characterize the response of representative composite aerospace structure to dynamic impact loads. Test conditions were selected to induce damage into the composite structure in order to study material failure within a composite fuselage and evaluate the capability of finite element (FE) model analysis to predict that failure. The tests were simulated using FE models which were generated to isolate the effect of developmental data availability on predictive capability. FE Models of the tested fuselage sections were generated using two limited data sets. The first model configuration was reverse engineered from the test article with no information related to design or fabrication details which would be known only by the manufacturer. The second model was generated from data provided by the manufacturer but without additional material characterization test data. Models were developed using these methodologies for both fuselage sections tested. Correlation of each model to the tests conducted was evaluated in terms of damage, deformation, and cabin acceleration measurements. Correlation between the developed models and the tested fuselage sections showed that the reverse engineered model predicted the composite damage and cabin acceleration measured during test though it was limited due to lack of detail in the composite layup changes through the structure. The model developed using manufacturer specifications did not predict damage, due to limited material and component model characterization data, but it did predict acceleration on par with the reverse engineered model. Model capability and limitation sources identified were verified through correlation of a final model which was developed by combining the individual data sets. The combined model demonstrated that the addition of calibrated composite material models to accurate composite layup definitions and detailed geometry led to improved correlation of damage and acceleration response within the composite fuselage structures.

Crashworthiness↗
NASA NTRS1998

EGRET High Energy Capability and Multiwavelength Flare Studies and Solar Flare Proton Spectra

The accomplishments of the participation in the Compton Gamma Ray Observatory Guest investigator program is summarized in this report. The work involved the study of Energetic Gamma Ray Experiment Telescope (EGRET)/Total Absorption Shower Counter(TASC) flare data. The specific accomplishments were the use of the accelerator neutron measurements obtained at the University of New Hampshire to verify the TASC response function and to modify the TASC fitting program to include a high energy neutron contribution, and to determine a high energy neutron contribution to the emissions from the 1991 June 11, solar flare. The next step in the analysis of this event was doing fits to the TASC energy-loss spectra as a function of time. A significant hardening of the solar proton spectrum over time was found for the flare. Further data was obtained from the Yohkoh HXT time histories and images for the 1991 October 27 flare. The results to date demonstrate that the TASC spectral analysis contributes crucial information on the particle spectrum interacting at the Sun. The report includes a paper accepted for publication, a draft of a paper to be delivered at the 26th International Cosmic Ray Conference and an abstract of a paper to be presented at the Meeting of the American Physical Society.

Chupp, Edward L.↗
DOE OSTI2025

Analysis of Bis(trifluoromethylsulfonyl)imide Interactions with Metal Cations Through a Chemical Informatics Approach

Nominally weakly coordinating anions are useful for modulating the solubility and chemical properties of metal complexes, but identification and analysis of the systematics of the interactions of anions with cationic metal complexes has not received the attention it deserves. Here, a chemical informatics approach is demonstrated for identifying and quantitatively analyzing the ways that the bis(trifluoromethylsulfonyl)imide anion (TFSI) can interact with metal-containing species. An open access computer program (PyCIFTer) was developed to facilitate large-scale structural analysis of TFSI-containing species by utilization of experimental atomic coordinate data from single-crystal X-ray diffraction (XRD) studies obtained from the Cambridge Structural Database (CSD). PyCIFTer establishes a three-dimensional vector space from the raw atomic coordinates, generating acyclic, undirected graphs that are used to rapidly analyze the structural properties (bond lengths and angles) of TFSI in individual structures in sequential/batch fashion. The structures are sorted by PyCIFTer into groups based on pre-set and chemically sensible criteria, affording a comprehensive and systematic view of TFSI structural chemistry. This approach avoids tedious one-at-a-time interrogation of structures, a prospect unreasonable in this case, and many others of contemporary chemical relevance; there were over 1500 structures in the CSD containing TFSI as of November 2024. The results demonstrate that TFSI only rarely binds to cations in the solid state, favoring the formation of species in which TFSI is found in cations’ outer coordination spheres. The prospect of applying PyCIFTer to other moieties is also discussed. PyCIFTer is also schematically compared to the commercial CSD Python application programming interface (API). Taken together, this work demonstrates the usefulness of modular workflows for sequential/batch analysis of structural data from XRD, an approach that appears poised to accelerate the translation of legacy structural results into new chemical insights and hypotheses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1995

Automated Propulsion Data Screening demonstration system

A fully-instrumented firing of a propulsion system typically generates a very large quantity of data. In the case of the Space Shuttle Main Engine (SSME), data analysis from ground tests and flights is currently a labor-intensive process. Human experts spend a great deal of time examining the large volume of sensor data generated by each engine firing. These experts look for any anomalies in the data which might indicate engine conditions warranting further investigation. The contract effort was to develop a 'first-cut' screening system for application to SSME engine firings that would identify the relatively small volume of data which is unusual or anomalous in some way. With such a system, limited and expensive human resources could focus on this small volume of unusual data for thorough analysis. The overall project objective was to develop a fully operational Automated Propulsion Data Screening (APDS) system with the capability of detecting significant trends and anomalies in transient and steady-state data. However, the effort limited screening of transient data to ground test data for throttle-down cases typical of the 3-g acceleration, and for engine throttling required to reach the maximum dynamic pressure limits imposed on the Space Shuttle. This APDS is based on neural networks designed to detect anomalies in propulsion system data that are not part of the data used for neural network training. The delivered system allows engineers to build their own screening sets for application to completed or planned firings of the SSME. ERC developers also built some generic screening sets that NASA engineers could apply immediately to their data analysis efforts.

Hoyt, W. Andes↗
DOE OSTI2026

Battery Life Prediction Using Reduced-Order Physics Models and Machine Learning (CRADA Final Report)

Phase 1 (Original CRADA, plus no-cost extension modifications #1-3, 6/1/2017 to 3/13/2021): The Australian Department of Defence (AUDoD) is performing accelerated aging tests of Li-ion batteries to benchmark their reliability and degradation characteristics. Using its previously developed battery lifetime predictive model framework, the National Laboratory of the Rockies (NLR) will develop analytical models based the AUDoD data to predict lifetime of the multiple Li-ion battery chemistries under real-world use scenarios of interest to AUDoD. The NLR model is based on physical degradation mechanisms encountered by Li-ion batteries and has been previously validated. Phase 2 (CRADA modification #4, plus no-cost extension modification #5, 2/22/2021 to 3/30/2025): Train and support Australian Department of Defence personnel to use NLR software for model-based estimation of Li-ion battery lifetime using accelerated battery aging data collected by the Australian Department of Defence. Under separate DOE funding from 2019 to 2021, NLR enhanced its battery life-prediction software using machine learning algorithms to automate portions of the model-fitting process, requiring significantly less labor and expert judgment and also adding uncertainty quantification, increasing statistical rigor. Under Phase 2, NLR will customize NLR Software and provide it to AuDoD. NLR will enhance its NLR Model to capture aging modes of AuDoD's multi-cell modules, including cell-balancing effects. NLR will develop example single-cell and multi-cell models based on one AuDoD battery aging dataset. NLR will train AuDoD personnel on NLR Software. By the conclusion of the project, NLR will have provided AuDoD the training materials, a user manual and software needed to perform their own analysis of additional and/or future battery aging datasets.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2021

Center of Gravity Quasi-Static Load Estimate Using Random Vibration Responses

The quasi-static load (QSL) is often levied on flight hardware structural designers as a requirement. This requirement is verified either by test or analysis with engineers using different approaches to meet this requirement. A commonly used approach is to consider the rms acceleration Center of Gravity (CG) responses of test articles undergoing random vibration tests. The differences between structural engineers and/or test conductors within the space industry exist on how the data obtained from flight hardware random vibration tests are used to estimate QSLs. In this paper, a method to accurately estimate the CG grms from the acceleration power spectral densities with an appropriate sigma value to estimate peak CG accelerations is discussed. Recommendations are made to ensure that the community follows consistent QSL estimation from random vibration test data. The method of estimating the CG acceleration responses may also be used to response limit if the flight hardware responses exceed flight limit loads with margins.

Kolaini, Ali↗
DOE OSTI2020

Key Accomplishments & Results: Sustainable Wastewater Infrastructure of the Future

This fact sheet summarizes the key accomplishments and results from DOE's Better Buildings Sustainable Wastewater Infrastructure of the Future (SWIFt) Accelerator. The Accelerator was a 3-year effort between DOE and state and local jurisdictions to promote energy data management practices in wastewater operations in an effort to increase energy efficiency in wastewater facilities around the country. Accelerator participants shared implementation plans, and DOE combined the results into a final toolkit.

wastewater, water resource recovery facilities, en↗
DOE OSTI2023

The High Energy X-ray Probe (HEX-P): supernova remnants, pulsar wind nebulae, and nuclear astrophysics

HEX-P is a probe-class mission concept that will combine high spatial resolution X-ray imaging (< 10" full width at half maximum) and broad spectral coverage (0.2–80 keV) with an effective area far superior to current facilities (including XMM-Newton and NuSTAR) to enable revolutionary new insights into a variety of important astrophysical problems. HEX-P is ideally suited to address important problems in the physics and astrophysics of supernova remnants (SNRs) and pulsar wind nebulae (PWNe). For shell SNRs, HEX-P can greatly improve our understanding via more accurate spectral characterization and localization of non-thermal X-ray emission from both non-thermal-dominated SNRs and those containing both thermal and non-thermal components, and can discover previously unknown non-thermal components in SNRs. Multi-epoch HEX-P observations of several young SNRs (e.g., Cas A and Tycho) are expected to detect year-scale variabilities of X-ray filaments and knots, thus enabling us to determine fundamental parameters related to diffusive shock acceleration, such as local magnetic field strengths and maximum electron energies. For PWNe, HEX-P will provide spatially-resolved, broadband X-ray spectral data separately from their pulsar emission, allowing us to study how particle acceleration, cooling, and propagation operate in different evolution stages of PWNe. HEX-P is also poised to make unique and significant contributions to nuclear astrophysics of Galactic radioactive sources by improving detections of, or limits on, 44Ti in the youngest SNRs and by potentially discovering rare nuclear lines as evidence of double neutron star mergers. Throughout the paper, we present simulations of each class of objects, demonstrating the power of both the imaging and spectral capabilities of HEX-P to advance our knowledge of SNRs, PWNe, and nuclear astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2018

Preliminary Saturn Atmospheric Density Results From Cassini's Final Plunge

The Cassini spacecraft made its final descent into the planet Saturn on September 15, 2017, capping a twenty year mission full of scientific discoveries. The high gain antenna was held on Earth-point until torques from atmospheric drag caused the spacecraft to lose line-of-sight lock with Earth. The Doppler data collected during the final plunge contains information about the spacecraft’s acceleration due to atmospheric drag, and therefore, the density of Saturn’s atmosphere. In this work, we present preliminary analysis of the end of mission Doppler data and its implications regarding the density of Saturn’s upper atmosphere. Are construction of the spacecraft’s final trajectory is discussed and used to fit a model of Saturn’s atmosphere to the Doppler data taken during the final plunge. The Cassini navigation team’s experience flying the spacecraft through the final five low altitude Saturn periapses is also discussed in the context of atmospheric drag and density models.

Roth, Duane↗
NASA NTRS1999

A Parametric Study of Accelerations of an Airplane Due to a Wake Vortex System

A study was conducted using strip theory to systematically investigate the effects of progressively more complete descriptions of the interaction of an airplane with a wake vortex system. The emphasis was in roll-dominant, parallel, vortex encounters. That is, the simulated airplane's longitudinal axis was nearly parallel to the rotation axis of the vortex system for most of the results presented. The study began with a drag-less rectangular wing in the flow field of a single vortex and progressed to a complete airplane with aerodynamic surfaces possessing taper, sweep, dihedral, and stalling and immersed in the flow field of a vortex pair in ground effect. The effects of the pitch, roll, and yaw attitudes of the airplane on the calculated accelerations were also investigated. The airplane had the nominal characteristics of a Boeing 757, and the vortex flow field had the nominal characteristics of the wake of a Boeing 767. The Bumham-Hallock model of a vortex flow field was used throughout the study. The data are presented mainly in terms of contours of equal acceleration in a two-dimensional area centered on the vortex pair and having dimensions of 300 feet by 300 feet.

Stewart, Eric C.↗
DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗
DOE OSTI2025

Accelerating Control Systems with GitOps: A Path to Automation and Reliability

GitOps is a foundational approach for modernizing infrastructure by leveraging Git as the single source of truth for declarative configurations. The poster explores how GitOps transforms traditional control system infrastructure, services and applications by enabling fully automated, auditable, and version-controlled infrastructure management. Cloud-native and containerized environments are shifting the ecosystem not only in the IT industry but also within the computational science field, as is the case of CERN and Diamond Light Source among other Accelerator/Science facilities which are slowly shifting towards modern software and infrastructure paradigms. The ACORN project, which aims to modernize Fermilab’s control system infrastructure and software is implementing proven best-practices and cutting-edge technology standards including GitOps, containerization, infrastructure as code and modern data pipelines for control system data acquisition and the inclusion of AI/ML in our accelerator complex.

Gonzalez, M. [Fermilab]↗
DOE OSTI2024

Updated ASME design correlations and qualification plan for powder bed fusion 316H stainless steel

This report provides an update on the Advanced Materials and Manufacturing Technologies (AMMT) program effort to qualify Laser-Powder Bed Fusion (L-PBF) 316H stainless steel for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5 rules. The report summarizes progress in testing and characterizing L-PBF material at elevated temperatures by providing preliminary design data for L-PBF 316H and by comparing the elevated temperature performance of the L-PBF material to wrought and conventional fusion welded 316H. The report then updates the initial AMMT qualification plan for L-PBF 316H, originally developed in 2023, to update the accelerated qualification strategy adopted in that plan to account for the new high temperature test data. The report also explores a few methods for further accelerating the qualification process using machine learning techniques to supplement the more conventional, empirical analysis methods typically used by ASME to correlate and extrapolate time-dependent material test data.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Ulysses orbit determination at high declinations

The trajectory of the Ulysses spacecraft caused its geocentric declination to exceed 60 deg South for over two months during the Fall of 1994, permitting continuous tracking from a single site. During this time, spacecraft operations constraints allowed only Doppler tracking data to be collected, and imposed a high radial acceleration uncertainty on the orbit determination process. The unusual aspects of this situation have motivated a re-examination of the Hamilton-Melbourne results, which have been used before to estimate the information content of Doppler tracking for trajectories closer to the ecliptic. The addition of an acceleration term to this equation is found to significantly increase the declination uncertainty for symmetric passes. In addition, a simple means is described to transform the symmetric results when the tracking pass is non-symmetric. The analytical results are then compared against numerical studies of this tracking geometry and found to be in good agreement for the angular uncertainties. The results of this analysis are applicable to the Near Earth Asteroid Rendezvous (NEAR) mission and to any other missions with high declination trajectories, as well as to missions using short tracking passes and/or one-way Doppler data.

Mcelrath, Timothy P.↗
DOE OSTI2025

SITCOMTN-154: Initial studies of photometric redshifts with LSSTComCam from DP1

This technote holds reports based on the first analyses of the Data Preview 1 (DP1) data by the Science Unit for photometric redshifts. Although photometric redshifts are not an official DP1 data product, the "Photo-z Science Unit" generated photo-z estimates for every galaxy in DP1 using the available multi-band imaging on a best-effort basis. This work included developing training and test datasets by matching DP1 data to high-quality reference redshifts obtained with spectroscopy, Grism data, and multi-band photometry. The Science Unit used the RAIL software package to make photometric redshift estimates using eight different algorithms, developed simple scientific performance metrics, used those metrics to explore how the performance of the algorithms varied with configuration changes, derived more optimized configurations of the algorithms and tested the performance of those configurations. This work, the resulting data products and expected data distribution mechanism are all described there.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2023

Heavy Ion Acceleration in 3he-Rich Solar Energetic Particle Events: New Insights From Solar Orbiter

We present Solar Orbiter energetic particle observations of two 3 He-rich events with features more clearly observed than in prior studies. The event of 2022 November 9 observed from 0.59 au contained hundreds of ultra-heavy ions (UH, mass >78 amu) whereas previous observations at 1 au have shown only an occasional count or two. The event of 2023 April 8 observed from 0.29 au fortuitously had very low ambient activity, making it possible to observe spectra from the 3 He acceleration mechanism without contamination, revealing extremely low H and 4 He intensities arriving simultaneously with other ions observed in typical 3 He-rich events. Taken together with previous studies we believe these data show that 3 He-rich events have a single acceleration mechanism that is responsible for the unique abundance features of 3 He, heavy ions, and UH ions. Considering the acceleration model of Roth and Temerin (1997) that heats the ions over a broad range of gyrofrequencies away from those damped by H and 4 He, we calculate reasonable fits to the observed abundances O-Fe. A key result is that high values of, e.g., Fe/O typical of such events is not due to preferential Fe heating, but on the contrary is due mainly to the depletion of O which at elevated temperatures has a charge-to-mass ratio in the region of the waves damped by 4He. The model also naturally incorporates features of high ionization states and neutron-rich isotope enhancements that have been long-standing puzzles in observations of this type of flare.

Solar flares↗
DOE OSTI2025

Data-Driven Analysis of Multipactor Dynamics via Dynamic Mode Decomposition

Multipactor effect is a performance-limiting kinetic plasma effect that can occur in high-power microwave and radio frequency (RF) devices. Multipactor effect is of special concern in vacuum or near-vacuum conditions such as those in particle accelerators and spaceborne devices. In this work, we present a data-driven reduced-order model (ROM) based on dynamic mode decomposition (DMD) for modeling of multipactor effects. We study multipactor effects and the resulting nonlinear harmonic generation by processing high-fidelity data generated from electromagnetic particle-in-cell (EMPIC) simulations using the DMD algorithm. We also investigate time-delay embedding extensions of DMD with improved generalizability and accuracy for modeling the electron plasma current density behavior. Here, the results show that DMD provides valuable insights into multipactor phenomena by extracting relevant modal spatiotemporal patterns and frequencies. In addition, DMD offers the potential to time extrapolate EMPIC simulations at a minimal cost, thereby reducing overall simulation time.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities

Cities, the world over, are fuelling economic growth. At the same time, rapid urbanization is a root cause of serious environmental damage. Recent WHO global air pollution guidelines highlight air pollution as a critical environmental threat along with climate change. To address these threats, smart cities and clean air programs are on a rise. In smart cities, data and Information and Communication Technologies (ICT) are major drivers of city transformations. The 4th Industrial Revolution (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing have the potential to accelerate these transformations toward urban resilience. However, the success of smart cities and clean air programs depends on cohesive multi-sector stakeholder contributions. This study conducted interdisciplinary participative stakeholder analysis to understand the data, and sectorial challenges, to outline the technological opportunities to facilitate clean air programs in Indian smart cities. The research highlights gaps due to siloed stakeholder operations, lack of data calibration, non-alignment of smart city and air quality management services, non-availability of health exposure data, and difficulty in translating scientific data into implementable actions. Stakeholders expressed potential ‘fit for the purpose’ use of IoT devices, satellites, smartphones, and mobility data augmented by AI methods in bridging these gaps. In conclusion, the analysis points toward a need to develop an easily accessible and ubiquitous urban data governance ecosystem enabling seamless cross-sector data exchanges to build trusting relationships among the stakeholders across the air quality management value chain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗