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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Figueroa, Fernando↗
NASA NTRS2001

Earth: Earth Science and Health

A major new NASA initiative on environmental change and health has been established to promote the application of Earth science remote sensing data, information, observations, and technologies to issues of human health. NASA's Earth Sciences suite of Earth observing instruments are now providing improved observations science, data, and advanced technologies about the Earth's land, atmosphere, and oceans. These new space-based resources are being combined with other agency and university resources, data integration and fusion technologies, geographic information systems (GIS), and the spectrum of tools available from the public health community, making it possible to better understand how the environment and climate are linked to specific diseases, to improve outbreak prediction, and to minimize disease risk. This presentation is an overview of NASA's tools, capabilities, and research advances in this initiative.

Maynard, Nancy G.↗
DOE OSTI2020

Data Federation Challenges in Remote Near-Real-Time Fusion Experiment Data Processing

Fusion energy experiments and simulations provide critical information needed to plan future fusion reactors. As next-generation devices like ITER move toward long-pulse experiments, analyses, including AI and ML, should be performed in a wide range of time and computing constraints, from near-real-time constraints, between-shot analysis, and to campaign-wide long-term analysis. However, the data volume, velocity, and variety make it extremely challenging for analyses using only local computational resources. Researchers need the ability to compose and execute workflows spanning edge resources to large-scale high-performance computing facilities.We present Delta, a system to address data analysis challenges, including AI/ML, in fusion science, by leveraging the ADIOS I/O library and middleware, to support executing science workflows over the wide area network for near-real-time streaming. We discuss the data federation challenges in performing remote workflows, focusing on on-going research work in (1) managing, reducing, and streaming data to minimize I/O and data movement overheads, (2) decompressing and reorganizing data for analysis, and (3) executing workflows for automated data analysis. We introduce examples for deep-learning based data analysis for the fusion domain and demonstrate how we use Delta to construct end-to-end workflows for a fusion device in Korea, connecting a remote DOE facility in the USA. The capability demonstrated by this project is the basis for improving the state of the art for near-real-time data federation amongst remote facilities.

Choi, Jong Youl↗
DOE OSTI2025

Digitizing and Enhancing Accessibility of the Fusion Safety Archives

This project focuses on the digitization and public accessibility to the Fusion Safety Archives at the Idaho National Laboratory. The first phase involves a thorough review of each document in the physical archives to determine its online availability. For documents that are available online, PDF copies and unique identifiers are collected for database integration. Documents not available online are delivered to Red Inc. for digitization. Additionally, defunct storage devices such as diskettes are sent to INL’s archival department for data retrieval where possible. The second phase of the project involves the creation of a comprehensive database to house the digital copies of the archives. The database will facilitate easy access and management of the digitized documents. Following the database creation, we plan to train a Retrieval-Augmented Generation (RAG) based AI on publicly available documents. The trained AI will be integrated into a front-facing application, allowing the public to easily access information from the Fusion Safety Archives. This project aims to preserve valuable historical data, improve accessibility, and promote transparency in fusion safety research.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Real-time cure monitoring of fiber-reinforced polymer composites using infrared thermography and recursive Bayesian filtering

Despite the desirable characteristics of fiber-reinforced polymer (FRP) composites, their utilization in high volume production industries is limited by a lack of efficient manufacturing techniques. Monitoring the curing process of these composites can help with improving the quality and efficiency of the manufacturing process. This article discusses a method that uses Kalman-filter-based fusion of the information obtained from infrared thermography (surface temperature measurements) and a heat conduction model to estimate degrees of cure and internal temperatures of curing FRP composite parts in real time. The effectiveness of the methodology is demonstrated by successfully monitoring the curing of an FRP composite part in a laboratory experiment. Finally, the proposed methodology is a crucial step towards identifying anomalies in the curing process that negatively impact the quality of FRP composite parts.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Technique for an improved and time-resolved carbon areal density measurement with a single channel diagnostic for inertial confinement fusion

Measurement of the areal density and velocity of the carbon ablator shell during peak burn in inertial confinement fusion give powerful information on the state of the ablator and where in the trajectory of implosion it reaches peak burn. Detailed comparison of the absolute densities and velocities of the carbon in implosions has been prevented by the limited ability to resolve shot-to-shot variation within a shot series or within a campaign. Here, a new approach using a single, ultra fast (~10 ps) gamma ray channel can massively reduce uncertainties and will provide insights on improvements to target and drive variables. Small improvements in these experimental design parameters may result in much greater yields.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

X-Ray Imaging And Assessment Of Non-Perturbing Magnetic Diagnostics For Intermediate-Density Fusion Experiments

This research adds to the understanding of when, why, where, and how fusion-grade plasmas generate X-rays. Normal fusion reactions create different spectra of X-rays from unwanted spurious situations so examination of the X-ray spectra provides information on whether a fusion device is operating properly or not. The characteristic time scale of the X-rays ranges from a few nanoseconds to a microseconds so a movie camera having a very high framing rate is required. The energy of the X-rays is not known and so the camera should provide information on what this energy is. The mechanism by which the X-rays are generated varies depend on whether the X-rays are from normal operation or from unwanted spurious effects. This project developed prototypes of a high-speed X-ray movie camera using two different technologies. These were tested on pulsed plasma experiments at Caltech. Despite having modest plasma parameters these experiments generated transient X-ray bursts suitable for developing and testing these cameras. One of the cameras was used on the MIFTI fusion-related experiment at UCSD and provided information on the energy, location, and timing of X-rays produced there. The camera could measure X-rays having energies from about 5 kilovolts to about 30 kilovolts with 40 nanosecond time resolution and space resolution of a few mm.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Distortions in charged-particle images of laser direct-drive inertial confinement fusion implosions

Energetic charged particles generated by inertial confinement fusion (ICF) implosions encode information about the spatial morphology of the hotspot and dense fuel during the time of peak fusion reactions. The knock-on deuteron imager (KoDI) was developed at the Omega Laser Facility to image these particles in order to diagnose low-mode asymmetries in the hotspot and dense fuel layer of cryogenic deuterium–tritium ICF implosions. However, the images collected are distorted in several ways that prevent reconstruction of the deuteron source. In this paper, we describe these distortions and a series of attempts to mitigate or compensate for them. We present several potential mechanisms for the distortions, including a new model for scattering of charged particles in filamentary electric or magnetic fields surrounding the implosion. Particle-tracing is used to create synthetic KoDI data based on the filamentary field model that reproduces the main experimentally observed image distortions. We conclude that the filamentary scattering model best matches the observed image distortions. Finally, we discuss potential impacts of filamentary fields on other charged-particle diagnostics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Fusion and Fission Energy and Science Directorate and Information Technology Services Directorate HPC Cluster Reduction, Consolidation, and Savings in Data Center Space, Power, and Cooling

This report evaluates the benefits of decommissioning six legacy FFESD purchased HPC clusters and consolidating services and workloads into a new HPC cluster named HELIOS. The findings demonstrate significant reductions in the data center power and cooling requirements, data center footprint, and operational overhead, while simultaneously increasing computational capacity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Data Fusion via Neural Network Entropy Minimization for Target Detection and Multi-Sensor Event Classification

Broadly applicable solutions to multimodal and multisensory fusion problems across domains remain a challenge because effective solutions often require substantive domain knowledge and engineering. The chief questions that arise for data fusion are in when to share information from different data sources, and how to accomplish the integration of information. The solutions explored in this work remain agnostic to input representation and terminal decision fusion approaches by sharing information through the learning objective as a compound objective function. The objective function this work uses assumes a one-to-one learning paradigm within a one-to-many domain which allows the assumption that consistency can be enforced across the one-to-many dimension. The domains and tasks we explore in this work include multi-sensor fusion for seismic event location and multimodal hyperspectral target discrimination. We find that our domain- informed consistency objectives are challenging to implement in stable and successful learning because of intersections between inherent data complexity and practical parameter optimization. While multimodal hyperspectral target discrimination was not enhanced across a range of different experiments by the fusion strategies put forward in this work, seismic event location benefited substantially, but only for label-limited scenarios.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Fusion Centers and State Energy Stakeholders: Pathways to Robust Threat Information Sharing

Threats to our nation’s critical infrastructure are escalating in frequency and sophistication. It is essential for public and private sectors to join forces to understand the threats, mitigate risks, and plan to respond and recover from disruption. Fusion centers — organizations purpose-built to facilitate communication and cooperation between federal, state, local, and territorial law enforcement entities — are well-positioned to play a pivotal role in this context. Although fusion centers historically focused on crime and terrorism, there is a need to engage more broadly and build stronger threat information sharing relationships among energy stakeholders within their states.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1988

Lunar Helium-3 and Fusion Power

The NASA Office of Exploration sponsored the NASA Lunar Helium-3 and Fusion Power Workshop. The meeting was held to understand the potential of using He-3 from the moon for terrestrial fusion power production. It provided an overview, two parallel working sessions, a review of sessions, and discussions. The lunar mining session concluded that mining, beneficiation, separation, and return of He-3 from the moon would be possible but that a large scale operation and improved technology is required. The fusion power session concluded that: (1) that He-3 offers significant, possibly compelling, advantages over fusion of tritium, principally increased reactor life, reduced radioactive wastes, and high efficiency conversion, (2) that detailed assessment of the potential of the D/He-3 fuel cycle requires more information, and (3) D/He-3 fusion may be best for commercial purposes, although D/T fusion is more near term.

Source record↗
DOE OSTI2021

Hydraulic fracture mapping using wavelet-based fusion of wave transmission and emission measurements

Fracture characterization is essential to hydrocarbon and geothermal exploration and production as well as carbon geo-sequestration. Active and passive measurements have been extensively applied to map fractures across various scales. Active and passive methods have inherent advantages and limitations that complement each other. Here, in this study, to improve the mapping of embedded fractures and the surrounding geomechanically altered regions, we integrate active shear-wave transmission measurement with passive acoustic-emission measurement collected during a lab-scale hydraulic-fracturing experiment. The proposed data fusion leverages the advantages of the two modalities of measurements, while minimizing their individual limitations. Polarized shear-wave transmission (active) measurement was collected before and after the hydraulic fracturing, and the acoustic emission (passive) measurement was collected during hydraulic fracturing. Two sets of two-dimensional maps of fracture and fracture-induced damage in axial, median and frontal planes were obtained by separately processing active and passive measurements. These 2D maps are then fed to wavelet-based image fusion technique to integrate the two sources of information for the reliable mapping/imaging of the embedded fractures and the surrounding geomechanically altered regions.

58 GEOSCIENCES↗
DOE OSTI2024

In-situ ETEM study of plasma-facing tungsten nanofuzz oxidation at atmospheric pressure: Microstructure evolution and substrate-free oxidation kinetics

To enable sustainable carbon-free fusion energy, managing reactor structural material degradation during normal operation as well as accident scenarios is vital. Tungsten (W) plasma-facing materials (PFMs) are susceptible to aggressive high-temperature oxidation during air-ingress fusion reactor accidents, yet there's a lack of oxidation kinetic data for irradiated tungsten. Here, in this study, we utilize atmospheric environmental transmission electron microscopy (ETEM) to present the first kinetic data for substrate-free W nanofuzz oxidation at 400 ºC and 500 ºC in 1 bar dry air. Comparison with pristine bulk W during the early parabolic stage suggests an irradiationdecelerated oxidation for W nanofuzz. Our time-resolved in-situ characterization reveals a durable amorphous surface oxide, likely promoted by high-flux He + irradiation-induced surface defects, serving as an effective passivating layer that impedes nanofuzz oxidation onset. This surface oxide layer also interfaces well with newly formed orthorhombic WO 3 , facilitated by stress relief through He bubble shrinkage, providing lasting passivating protection throughout the nanofuzz parabolic oxidation. This new finding challenges conventional notions of irradiation's negative impact on metal oxidation, and calls for advanced characterization to enhance our understanding of fusion energy materials degradation, informed by further accident modeling.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Simulating Operation of a Complex Sensor Network

Simulation Tool for ASCTA Microsensor Network Architecture (STAMiNA) ["ASCTA" denotes the Advanced Sensors Collaborative Technology Alliance.] is a computer program for evaluating conceptual sensor networks deployed over terrain to provide military situational awareness. This or a similar program is needed because of the complexity of interactions among such diverse phenomena as sensing and communication portions of a network, deployment of sensor nodes, effects of terrain, data-fusion algorithms, and threat characteristics. STAMiNA is built upon a commercial network-simulator engine, with extensions to include both sensing and communication models in a discrete-event simulation environment. Users can define (1) a mission environment, including terrain features; (2) objects to be sensed; (3) placements and modalities of sensors, abilities of sensors to sense objects of various types, and sensor false alarm rates; (4) trajectories of threatening objects; (5) means of dissemination and fusion of data; and (6) various network configurations. By use of STAMiNA, one can simulate detection of targets through sensing, dissemination of information by various wireless communication subsystems under various scenarios, and fusion of information, incorporating such metrics as target-detection probabilities, false-alarm rates, and communication loads, and capturing effects of terrain and threat.

Jennings, Esther↗
NASA NTRS2022

NASA System-Wide Safety Wildland Firefighting Operations Workshop Report

On March 9-11, 2022, NASA’s System-Wide Safety Wildland Firefighting Operations Workshop engaged the broader wildland firefighting management ecosystem in a safety-oriented discussion via a virtual platform. This enabled a better understanding of how NASA and community expertise can be leveraged in the safe development of current and future firefighting systems and operations. The goals of the workshop were to: (1) identify and prioritize the top safety-oriented risks, gaps in capabilities, and emerging technologies to enhance wildland firefighting for both near-term and far-term concepts, with a specific focus on aviation operations and (2) engage the stakeholder community in defining emergent safety-oriented scope, roles, responsibilities, and procedures for agents undergoing increasingly complex wildland firefighting operations in information-rich, but uncertain environments. Workshop participants were solicited from wildland firefighting stakeholders across government, industry, and academia. All levels of government were engaged, as NASA sought attendees from federal, state, local, and tribal government agencies. Industry participants from traditional wildland firefighting domains such as data visualization and equipment manufacturers were invited, and corporate attendees from novel application domains such as aerial robotics and autonomous systems were present as well. The top three findings were as follows: (1) Enhancing situation awareness is a safety priority, especially in the use of aerial assets; (2) Timely access to information along with data fusion and integrated displays will enhance safety-critical decision-making both inside and outside aviation contexts; and (3) Tailorable standards and common operating pictures in the field will enhance inter-agency cooperation in the wildland firefighting lifecycle and enable the optimal use of limited resources such as aerial assets. The workshop helped inform NASA of the relevant safety-related wildland firefighting concerns and aided the broader ecosystem in understanding the potential safety-oriented role NASA might play in this community. Increased engagement with crucial governmental stakeholders (e.g., U.S. Forest Service, CAL FIRE, etc.) along with industry partners in cutting- edge information -centric domains is a fundamental next step. Additionally, the workshop findings will help define the first of a series of operationally challenging demonstrations, held in concert with strategic ecosystem partners, known as the Safety Demonstrator Series for NASA’s System-Wide Safety project. The first demonstration is set in the wildland firefighting application domain and will: (1) examine high risk operational scenarios to reduce their overall risk via services, functions or capabilities that act as risk mitigators (or transfer that risk to automated systems better able to tolerate it) and (2) explore novel tools and technologies that will enhance safety margins by enabling non-traditional or neoteric operational paradigms.

wildland firefighting↗