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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Edge at the Pier: EPCAPE Software-Defined Sensing Field Campaign Report

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) was aimed to enhance the understanding of cloud and aerosol properties in the region surrounding La Jolla, California. To address challenges in data collection and processing from various instruments, an edge computing device known as Waggle Sage Node (WSN) was deployed at the Ellen Browning Scripps Memorial Pier. WSN is a distributed-sensing platform designed to collect and analyze environmental data at the edge. Sage is a multi-agency-supported project that designs and builds a new kind of national-scale reusable cyberinfrastructure to enable artificial intelligence (AI) at the edge based on the Waggle platform. Sponsors include the U.S. Department of Energy (DOE) Advanced Scientific Computing Research (ASCR), DOE National Nuclear Security Administration (NNSA), DOE Biological and Environmental Research (BER) through DOE Artificial Intelligence for Earth System Predictability (AI4ESP), Argonne Laboratory-Directed Research and Development (LDRD). Sage (https://sagecontinuum.org/) is funded as a National Science Foundation Mid-Scale Research Infrastructure (MSRI) project (https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935984). This robust, multi-architecture edge computing platform facilitated environmental monitoring during the campaign. This report details the scientific objectives, deployment process, and key results of integrating Waggle into the EPCAPE field campaign.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Early Inference of Nuclear Technology-Directed Research Activities of Authors from Scientific Publications

Nuclear research articles can provide information about early nuclear proliferation indicators such as influential research entities and technology capability levels of a country, but detection of nuclear activities typically occurs after they have started. We investigate the extent to which nuclear research articles can be used to infer whether a research entity will acquire or develop a nuclear technology before it happens. Early detection of nuclear proliferation or technology development indicators from data is challenging due to partial observability, sparse and unlabeled information, and confounding signals from multiple concurrent activities. This paper presents the early detection problem as a sequential decision-making, goal inference problem, where the objective is to characterize and predict an individual’s, organization’s, or a country’s intent (unobserved goal-directed behavior) towards developing a nuclear capability from partially observed sequences of their research publications, using inverse reinforcement learning and Bayesian goal inference methods. A computational framework is presented, and its application demonstrated using 29,196 Scopus records for a case study related to a civil nuclear capability. The case study results serve as a proof-of-concept demonstration for inference of technology-directed research activity of authors who publish in the nuclear domain. The inference method, combined with advanced computing, may be used to assess and monitor activities pertaining to early developmental stages of a nuclear technology or capability, which in turn can help to identify and prioritize activities with nuclear proliferation potential for further investigation.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

A workflow for segmenting soil and plant X-ray computed tomography images with deep learning in Google’s Colaboratory

X-ray micro-computed tomography (X-ray μCT) has enabled the characterization of the properties and processes that take place in plants and soils at the micron scale. Despite the widespread use of this advanced technique, major limitations in both hardware and software limit the speed and accuracy of image processing and data analysis. Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data. Yet, challenges remain in applying convolutional neural networks to the analysis of environmentally and agriculturally relevant images. Specifically, there is a disconnect between the computer scientists and engineers, who build these AI/ML tools, and the potential end users in agricultural research, who may be unsure of how to apply these tools in their work. Additionally, the computing resources required for training and applying deep learning models are unique, more common to computer gaming systems or graphics design work, than to traditional computational systems. To navigate these challenges, we developed a modular workflow for applying convolutional neural networks to X-ray μCT images, using low-cost resources in Google’s Colaboratory web application. Here we present the results of the workflow, illustrating how parameters can be optimized to achieve best results using example scans from walnut leaves, almond flower buds, and a soil aggregate. We expect that this framework will accelerate the adoption and use of emerging deep learning techniques within the plant and soil sciences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Beyond the List: Bioagent-Agnostic Signatures Could Enable a More Flexible and Resilient Biodefense Posture Than an Approach Based on Priority Agent Lists Alone

As of 2021, the biothreat policy and research communities organize their efforts around lists of priority agents, which elides consideration of novel pathogens and biotoxins. For example, the Select Agents and Toxins list is composed of agents that historic biological warfare programs had weaponized or that have previously caused great harm during natural outbreaks. Similarly, lists of priority agents promulgated by the World Health Organization and the National Institute of Allergy and Infectious Diseases are composed of previously known pathogens and biotoxins. To fill this gap, we argue that the research/scientific and biodefense/biosecurity communities should categorize agents based on how they impact their hosts to augment current list-based paradigms. Specifically, we propose integrating the results of multi-omics studies to identify bioagent-agnostic signatures (BASs) of disease—namely, patterns of biomarkers that accurately and reproducibly predict the impacts of infection or intoxication without prior knowledge of the causative agent. Here, we highlight three pathways that investigators might exploit as sources of signals to construct BASs and their applicability to this framework. The research community will need to forge robust interdisciplinary teams to surmount substantial experimental, technical, and data analytic challenges that stand in the way of our long-term vision. However, if successful, our functionality-based BAS model could present a means to more effectively surveil for and treat known and novel agents alike.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The Concept of a Quantum Edge Simulator: Edge Computing and Sensing in the Quantum Era

Sensors, enabling observations across vast spatial, spectral, and temporal scales, are major data generators for information technology (IT). Processing, storing, and communicating this ever-growing amount of data pose challenges for the current IT infrastructure. Edge computing—an emerging paradigm to overcome the shortcomings of cloud-based computing—could address these challenges. Furthermore, emerging technologies such as quantum computing, quantum sensing, and quantum communications have the potential to fill the performance gaps left by their classical counterparts. Here, we present the concept of an edge quantum computing (EQC) simulator—a platform for designing the next generation of edge computing applications. An EQC simulator is envisioned to integrate elements from both quantum technologies and edge computing to allow studies of quantum edge applications. The presented concept is motivated by the increasing demand for more sensitive and precise sensors that can operate faster at lower power consumption, generating both larger and denser datasets. These demands may be fulfilled with edge quantum sensor networks. Envisioning the EQC era, we present our view on how such a scenario may be amenable to quantification and design. Given the cost and complexity of quantum systems, constructing physical prototypes to explore design and optimization spaces is not sustainable, necessitating EQC infrastructure and component simulators to aid in co-design. We discuss what such a simulator may entail and possible use cases that invoke quantum computing at the edge integrated with new sensor infrastructures.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Building Stock Models for Embodied Carbon Emissions—A Review of a Nascent Field

Building stock modeling emerges as a critical tool in the strategic reduction of embodied carbon emissions, which is pivotal in reshaping the evolving construction sector. This review provides an overall view of modern methodologies in building stock modeling, homing in on the nuances of embodied carbon analysis in construction. Examining 23 seminal papers, our study delineates two primary modeling paradigms—top-down and bottom-up—each further compartmentalized into five innovative methods. This study points out the challenges of data scarcity and computational demands, advocating for methodological advancements that promise to refine the precision of building stock models. A groundbreaking trend in recent research is the incorporation of machine learning algorithms, which have demonstrated remarkable capacity, improving stock classification accuracy by 25% and urban material quantification by 40%. Furthermore, the application of remote sensing has revolutionized data acquisition, enhancing data richness by a factor of five. This review offers a critical examination of current practices and charts a course toward an environmentally prudent future. It underscores the transformative impact of building stock modeling in driving ecological stewardship in the construction industry, positioning it as a cornerstone in the quest for sustainability and its significant contribution toward the grand vision of an eco-efficient built environment.

Hu, Ming (ORCID:0000000325831161)↗
DOE OSTI2024

Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, https://doi.org/10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Córdoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Flight Testing

It is considered by the Flight Mechanics Panel of AGARD as vitally important that the NATO flight test community meet regularly so that new techniques for flight test, instrumentation and data analysis and lessons learned from past and on-going programs be disseminated to ensure that safe efficient cost-effective and timely testing is accomplished. There are many new systems being tested or planned for testing in the near future. These include programmable signal processor radars, integrated flight, fire and propulsion control systems, thrust vectoring, low observable technologies, multifunction pilot displays and multisensor integration. Acquisition and processing of large quantities of avionics multiplex data are challenges that must be met. There is a need for greater use of simulators and other hardware-in-the-loop ground test facilities.

Source record↗
NASA NTRS1993

Space Station Freedom ground data system: Design and operations

Over the previous year the Space Station Freedom (SSF) Program (SSFP) ground data distribution system has become independent of a number of data systems that were to have been provided by other National Aeronautics and Space Administration (NASA) programs. Consequently, the SSFP has outlined the basic architecture of a new data system dedicated to supporting SSF requirements. This has been accomplished through a complete redesign of the ground network and a reallocation of selected functions. There are a number of aspects of the new ground data distribution system that are unique among NASA programs. These considerations make SSF ground data distribution one of the most extensive and complex data management challenges encountered in the arena of Space Operations. A description of this system comprises the main focus of the paper.

Dunning, Richard A., Jr.↗
NASA NTRS1995

Finding the forest in the trees. The challenge of combining diverse environmental data

Development of analytical and functional guidelines to help researchers and technicians engaged in interdisciplinary research to better plan and implement their supporting data management activities is addressed. An emphasis is on the projects that involve both geophysical and ecological issues. Six case studies were used to identify and to understand problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a range of temporal scales. These case studies were also used to elaborate the common barriers to interfacing data of disparate sources and types. A number of lessons derived from the case studies are summarized and analyzed.

Source record↗
NASA NTRS1998

IMAGE Mission Science

Simultaneous, global measurement of major magnetospheric plasma systems will be performed for the first time with the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) Mission. The ring current, plasmasphere, and auroral systems will be imaged using energetic neutral and ultraviolet cameras. Quantitative remote measurement of the magnetosheath, plasmaspheric, and magnetospheric densities will be obtained through radio sounding by the Radio Plasma Imager. The IMAGE Mission will open a new era in global magnetospheric physics, while bringing with it new challenges in data analysis. An overview of the IMAGE Theory and Modeling team efforts will be presented, including the state of development of Internet tools that will be available to the science community for access and analysis of IMAGE observations.

Gallagher, D. L.↗
NASA NTRS1998

Rotating Pressure and Temperature Measurements on Scale Model Fans Using Luminescent Paints

Pressure and temperature sensitive paint (PSP, TSP) technology is a rapidly developing measurement technique that is widely accepted in external aerodynamic wind tunnel measurements. Almost all quantitative full field measurements have been on stationary surfaces. Rotating pressure and temperature measurements were successfully acquired during scale-model fan tests in the NASA Lewis Research Center 9 foot by 15 foot low speed wind tunnel at speeds as high as 9500 RPM. The use of PSP and TSP on rotating surfaces presents additional challenges to data acquisition. This paper describes in detail the techniques used to acquire global rotating pressure and temperature measurements and overcome the problems associated with this type of measurement. These include illumination and detection problems associated with moving surfaces, temperature dependence of PSP and limited emitted light available from short duration illumination sources. Solutions to these problems as well as pressure and temperature results will be discussed.

Bencic, Timothy J.↗
NASA NTRS2003

Finite Element Simulation of a Space Shuttle Solid Rocket Booster Aft Skirt Splashdown Using an Arbitrary Lagrangian-eulerian Approach

Explicit finite element techniques employing an Arbitrary Lagrangian-Eulerian (ALE) methodology, within the transient dynamic code LS-DYNA, are used to predict splashdown loads on a proposed replacement/upgrade of the hydrazine tanks on the thrust vector control system housed within the aft skirt of a Space Shuttle Solid Rocket Booster. Two preliminary studies are performed prior to the full aft skirt analysis: An analysis of the proposed tank impacting water without supporting aft skirt structure, and an analysis of space capsule water drop tests conducted at NASA's Langley Research Center. Results from the preliminary studies provide confidence that useful predictions can be made by applying the ALE methodology to a detailed analysis of a 26-degree section of the skirt with proposed tank attached. Results for all three studies are presented and compared to limited experimental data. The challenges of using the LS-DYNA ALE capability for this type of analysis are discussed.

Melis, Matthew E.↗
NASA NTRS2004

TIGER: Development of Thermal Gradient Compensation Algorithms and Techniques

In a wind tunnel facility, the direct measurement of forces and moments induced on the model are performed by a force measurement balance. The measurement balance is a precision-machined device that has strain gages at strategic locations to measure the strain (i.e., deformations) due to applied forces and moments. The strain gages convert the strain (and hence the applied force) to an electrical voltage that is measured by external instruments. To address the problem of thermal gradients on the force measurement balance NASA-LaRC has initiated a research program called TIGER - Thermally-Induced Gradients Effects Research. The ultimate goals of the TIGER program are to: (a) understand the physics of the thermally-induced strain and its subsequent impact on load measurements and (b) develop a robust thermal gradient compensation technique. This paper will discuss the impact of thermal gradients on force measurement balances, specific aspects of the TIGER program (the design of a special-purpose balance, data acquisition and data analysis challenges), and give an overall summary.

Hereford, James↗
NASA NTRS2005

Ground System for Solar Dynamics Observatory (SDO) Mission

NASA s Goddard Space Flight Center (GSFC) has recently completed its Critical Design Review (CDR) of a new dual Ka and S-band ground system for the Solar Dynamics Observatory (SDO) Mission. SDO, the flagship mission under the new Living with a Star Program Office, is one of GSFC s most recent large-scale in-house missions. The observatory is scheduled for launch in August 2008 from the Kennedy Space Center aboard an Atlas-5 expendable launch vehicle. Unique to this mission is an extremely challenging science data capture requirement. The mission is required to capture 99.99% of available science over 95% of all observation opportunities. Due to the continuous, high volume (150 Mbps) science data rate, no on-board storage of science data will be implemented on this mission. With the observatory placed in a geo-synchronous orbit at 36,000 kilometers within view of dedicated ground stations, the ground system will in effect implement a "real-time" science data pipeline with appropriate data accounting, data storage, data distribution, data recovery, and automated system failure detection and correction to keep the science data flowing continuously to three separate Science Operations Centers (SOCs). Data storage rates of approx. 45 Tera-bytes per month are expected. The Mission Operations Center (MOC) will be based at GSFC and is designed to be highly automated. Three SOCs will share in the observatory operations, each operating their own instrument. Remote operations of a multi-antenna ground station in White Sands, New Mexico from the MOC is part of the design baseline.

Tann, Hun K.↗
NASA NTRS2006

Recent Project Experience Mars Reconnaissance Orbiter (MRO)

This viewgraph presentation reviews the experiences of the Mars Reconnaissance Orbiter (MRO). It includes an overview of the MRO mission; the challenges of data Management and Transport; a representation of the end-to-end flow for the telemetry data; a review of the data issues, and Coherent File Distribution Protocol (CFDP) uses and issues.

Mars Exploration Rover (MER)↗
NASA NTRS2010

Air-Loads Prediction of a UH-60A Rotor inside the 40- by 80-Foot Wind Tunnel

The presented research extends the capability of a loose coupling computational fluid dynamics (CFD) and computational structure dynamics (CSD) code to calculate the flow-field around a rotor and test stand mounted inside a wind tunnel. Comparison of predicted air-load results for a full-scale UH-60A rotor recently tested inside the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel at Ames Research Center and in free-air flight are made for three challenging flight data points from the earlier conducted UH-60A Air-loads Program. Overall results show that the extension of the coupled CFD/CSD code to the wind-tunnel environment is generally successful.

Chang, I-Chung↗