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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Thermal protection system gap heating rates of the Rockwell International flat plate heat transfer model (OH2A/OH2B)

Heat transfer data for the Rockwell International Flat Plate Thermocouple Model are presented. The model simulated the Space Shuttle Vehicle Thermal Protection System. Data were recorded for locations in and around various size gaps for various gap orientation configurations. The test was conducted at Mach 5.1 for free-stream Reynolds number per foot values from 500,000 to 1,500,000.

Foster, T. F.↗
DOE OSTI2026

Machine-Protection System for the PIP-II Linear Accelerator: Architecture and Data Processing Schemes

PIP-II at Fermilab features a brand-new, 800 MeV leading-edge Linear Accelerator (Linac) that will enable the Fermilab complex to deliver more than a megawatt of beam power to the Long Base-line Neutrino Facility (LBNF), requiring a robust Machine Protection System (MPS) to prevent beam-induced damage to delicate cryomodules and vacuum components. Signals in various accelerator components, in both analog and digital format, are collected and processed to assest the operating conditions of the accelerator. In the situation a potential damage is foreseen, the beam permit signal will be drop. A critical element of this system is the fast Analog Machine Protection System, a high-bandwidth platform designed for real-time beam loss monitoring. The system utilizes a modular, FPGA-based architecture to digitize signals from beam-sensing devices, such as AC Current Transformers (ACCTs), non-invasive Ring Pickups (RPUs) and beam scrapers. To eliminate both high frequency as well as 60 Hz noise that might be picked up in the industrial environment, data processing schemes beyond regular digital filtering are planned and implemented.

Wu, Jinyuan [Fermilab] (ORCID:0000000344329521)↗
NASA NTRS1997

Overview of HZETRN and BRNTRN Space Radiation Shielding Codes

The NASA Radiation Health Program has supported basic research over the last decade in radiation physics to develop ionizing radiation transport codes and corresponding data bases for the protection of astronauts from galactic and solar cosmic rays on future deep space missions. The codes describe the interactions of the incident radiations with shield materials where their content is modified by the atomic and nuclear reactions through which high energy heavy ions are fragmented into less massive reaction products and reaction products are produced as radiations as direct knockout of shield constituents or produced as de-excitation products in the reactions. This defines the radiation fields to which specific devices are subjected onboard a spacecraft. Similar reactions occur in the device itself which is the initiating event for the device response. An overview of the computational procedures and data base with some applications to photonic and data processing devices will be given.

Wilson, John W.↗
NASA NTRSDate not supplied

Carbon Nanotube – Polysiloxane Nanocomposites for Ablative Thermal Protection Systems

Ultra-high temperature resins (UHTR) such as polysiloxane possess excellent characteristics for ablation including low thermal conductivity, lightweight composition, high thermal resistance, and the ability to form a durable char layer. To enhance its mechanical strength, the aerospace industry utilizes fiber reinforcement, such as carbon fiber reinforced polysiloxane (CF-polysiloxane), due to its high strength-to-weight ratio. Carbon nanotubes (CNTs) have advantages over microfibers including higher specific strength, lower density, and customizable thermal conductivity. Their nano-scale dimensions allow for a more homogenous material compared to traditional microfibers. Conventional methods of incorporating CNTs into resins often have structural defects such as voids, CNT agglomerations, and randomly dispersed CNTs, resulting in marginal improvements in properties. A novel approach known as bulk nanocomposite laminating (BNL) has been introduced involving CNT densification, resin polymer infiltration, and pressurized curing to achieve a high packing density exceeding 35% by volume. Characterization and testing to simulate re-entry conditions is performed with a sample of CNT-polysiloxane nanocomposite cured onto a CF-polysiloxane backing. These samples are subjected to ablation by an oxyacetylene flame while collecting temperature data to evaluate thermal protection properties.

Palak B Patel↗
NASA NTRS2016

Novel Radiomitigator for Radiation-Induced Bone Loss

Radiation-induced bone loss can occur with radiotherapy patients, accidental radiation exposure and during long-term spaceflight. Bone loss due to radiation is due to an early increase in oxidative stress, inflammation and bone resorption, resulting in an imbalance in bone remodeling. Furthermore, exposure to high-Linear Energy Transfer (LET) radiation will impair the bone forming progenitors and reduce bone formation. Radiation can be classified as high-LET or low-LET based on the amount of energy released. Dried Plum (DP) diet prevents bone loss in mice exposed to total body irradiation with both low-LET and high-LET radiation. DP prevents the early radiation-induced bone resorption, but furthermore, we show that DP protects the bone forming osteoblast progenitors from high-LET radiation. These results provide insight that DP re-balances the bone remodeling by preventing resorption and protecting the bone formation capacity. This data is important considering that most of the current osteoporosis treatments only block the bone resorption but do not protect bone formation. In addition, DP seems to act on both the oxidative stress and inflammation pathways. Finally, we have preliminary data showing the potential of DP to be radio-protective at a systemic effect and could possible protect other tissues at risk of total body-irradiation such as skin, brain and heart.

countermeasure↗
DOE OSTI2020

Combined Force-Frequency Sampling for Simulation of Systems Having Rugged Free Energy Landscapes.

An adaptive, machine learning-based sampling method is presented for simulation of systems having rugged, multidimensional free energy landscapes. The method's main strength resides in its ability to learn both from the frequency of visits to distinct states and the generalized force estimates that arise in a system as it evolves in phase space. This is accomplished by introducing a self-integrating artificial neural network, which generates an estimate of the free energy directly from its derivatives. The usefulness of the proposed combined approach is examined in the context of two concrete examples, namely, an alanine dipeptide molecule in water and a polymer diffusing through a narrow pore. This new method is found to be robust, faster, and more accurate than approaches that rely only on frequency-based or generalized force-based estimations. After combining the proposed approach with overfill protection and support for sparse data storage and training, the method is shown to be more effective than comparable, previously available techniques and capable of scaling efficiently to larger numbers of collective variables.

Sevgen, Emre↗
DOE OSTI2022

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Abstract Projection of land use and land‐cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land‐use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well‐defined conservation goals while minimizing impacts to agriculture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Explosion Detection Using Smartphones: Ensemble Learning with the Smartphone High-Explosive Audio Recordings Dataset and the ESC-50 Dataset

Explosion monitoring is performed by infrasound and seismoacoustic sensor networks that are distributed globally, regionally, and locally. However, these networks are unevenly and sparsely distributed, especially at the local scale, as maintaining and deploying networks is costly. With increasing interest in smaller-yield explosions, the need for more dense networks has increased. To address this issue, we propose using smartphone sensors for explosion detection as they are cost-effective and easy to deploy. Although there are studies using smartphone sensors for explosion detection, the field is still in its infancy and new technologies need to be developed. We applied a machine learning model for explosion detection using smartphone microphones. The data used were from the Smartphone High-explosive Audio Recordings Dataset (SHAReD), a collection of 326 waveforms from 70 high-explosive (HE) events recorded on smartphones, and the ESC-50 dataset, a benchmarking dataset commonly used for environmental sound classification. Two machine learning models were trained and combined into an ensemble model for explosion detection. The resulting ensemble model classified audio signals as either “explosion”, “ambient”, or “other” with true positive rates (recall) greater than 96% for all three categories.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1984

Managing geometric information with a data base management system

The strategies for managing computer based geometry are described. The computer model of geometry is the basis for communication, manipulation, and analysis of shape information. The research on integrated programs for aerospace-vehicle design (IPAD) focuses on the use of data base management system (DBMS) technology to manage engineering/manufacturing data. The objectives of IPAD is to develop a computer based engineering complex which automates the storage, management, protection, and retrieval of engineering data. In particular, this facility must manage geometry information as well as associated data. The approach taken on the IPAD project to achieve this objective is discussed. Geometry management in current systems and the approach taken in the early IPAD prototypes are examined.

Dube, R. P.↗
NASA NTRS1979

System for monitoring lightning strikes

System for monitoring lightning strikes utilizes optical data link between lightning sensor and recording instruments thus making data link immune to electrical interference induced in wires by huge burst of energy in lightning strikes. It also protects people and equipment at data receiving end from electrical shock.

Fucas, J. C.↗
DOE OSTI2020

Facility Cybersecurity Framework Best Practices

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought. The U.S. Department of Energy’s (DOE) Federal Energy Management Program (FEMP) funded the Pacific Northwest National Laboratory (PNNL) to develop various cybersecurity tools, trainings, and reports to aid federal facility managers – and other building owners and operators – in better applying frameworks and lessons learned from the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF), risk management framework (RMF), DOE’s cybersecurity capability maturity model (C2M2), and a wide variety of industry best practices and guidance documents (i.e., NIST 800 series, Department of Defense United Facilities Criteria). This set of tools, collectively known as the FEMP Facility-Related Control System Cyber Toolkit (FRCS Cyber Toolkit)2, is focused on cybersecurity concerns from facility-related control systems and other operational technology (OT), such as industrial control systems (ICS). The FRCS Cyber Toolkit can be applied across six of the sixteen critical infrastructure sectors designated by the Department of Homeland Security, including government facilities, healthcare and public health, commercial facilities (e.g., public assembly, offices, lodging), financial services (e.g., banking and insurance), emergency services (e.g., fire and police stations), and information technology. With increasingly converged IT and OT systems, it is crucial to address OT cybersecurity considerations and assess how the seam of these two systems could impact the overall cybersecurity posture of a facility. The objective of this report is to provide an overview of the best possible method to use FRCS Cyber Toolkit (section 2.0) and distilled cybersecurity best practices for the federal facilities to address growing non-linear cyber threats (section 3.0). Recommendations in this document are aggregated from several NIST and other documents (see Appendix A for additional details).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The ab initio non-crystalline structure database: empowering machine learning to decode diffusivity

Non-crystalline materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven exploration and design of non-crystalline materials is hampered by the absence of a comprehensive database covering a broad chemical space. In this work, we present the largest computed non-crystalline structure database to date, generated from systematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductivity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching non-crystalline structures provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in universal machine learning potentials, impacting design beyond that of non-crystalline materials. In addition, combining diffusion trajectories from our dataset with models that predict liquidus viscosity and melting temperature could be utilized to develop models for predicting glass-forming ability.

36 MATERIALS SCIENCE↗
DOE OSTI2023

ROSE LCOM Tools

This project provides a tool to compute LCOM metrics for important Ada abstraction mechanisms (e.g., packages, protected objects). It analyzes data accesses and routine calls to compute an abstract representation of an Ada package (or some other abstraction). Different LCOM metrics (1-5) are computed from the abstract representation. The project also provides support for representing the abstraction graphically (via graphviz). The LCOM tool requires an existing ROSE installation configured with the GNAT 2019 compiler.

Lamar, KennethM↗
DOE OSTI2023

Effect of surface oxides on tritium entrance and permeation in FeCrAl alloys for nuclear fuel cladding: a review

Abstract Iron-chromium-aluminum (FeCrAl) alloys are being considered for the cladding of uranium dioxide fuel in light water reactors (LWRs). FeCrAl alloys have good mechanical properties at temperatures of 300 °C and higher, and have superlative resistance to attack by steam at temperatures of up to 1000 °C and higher. A concern has been raised that the use of FeCrAl for cladding would result in a higher content of tritium in the reactor coolant as compared with the current system where the cladding is a zirconium based alloy. This review shows that the flux of tritium from the fuel rod cavities to the coolant across the fuel cladding wall will be greatly reduced by the presence of oxides on the surface of the cladding. The review of current literature and permeation data show that (a) protective oxides are expected to be present on both sides of the FeCrAl cladding, and (b) depending on the characteristics of these oxide layers it is reasonable to expect about two–three orders of magnitude reduction in tritium permeation, relative to the permeation response in clean, unoxidized condition for FeCrAl steels of interest, around 277 °C–377 °C temperatures.

Electrochemistry↗
DOE OSTI2024

The ab initio amorphous materials database: Empowering machine learning to decode diffusivity

Amorphous materials exhibit unique properties that make them suitable for various applications in science and technology, ranging from optical and electronic devices and solid-state batteries to protective coatings. However, data-driven ex- ploration and design of amorphous materials is hampered by the absence of a com- prehensive database covering a broad chemical space. In this work, we present the largest computed amorphous materials database to date, generated from sys- tematic and accurate ab initio molecular dynamics (AIMD) calculations. We also show how the database can be used in simple machine-learning models to connect properties to composition and structure, here specifically targeting ionic conductiv- ity. These models predict the Li-ion diffusivity with speed and accuracy, offering a cost-effective alternative to expensive density functional theory (DFT) calculations. Furthermore, the process of computational quenching amorphous materials provides a unique sampling of out-of-equilibrium structures, energies, and force landscape, and we anticipate that the corresponding trajectories will inform future work in uni- versal machine learning potentials, impacting design beyond that of non-crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Nevada National Security Site Environmental Report 2019

This report presents the National Nuclear Security Administration Nevada Field Office environmental protection and monitoring programs data and the compliance status for calendar year 2019 at the Nevada National Security Site and at its two support facilities, the North Las Vegas Facility and the Remote Sensing Laboratory-Nellis. This report also addresses environmental restoration projects conducted by the Environmental Management Nevada Program Office at the Tonopah Test Range.

54 ENVIRONMENTAL SCIENCES↗