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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Working Fluid Trade Study for a Two-Phase Mechanically Pumped Loop Thermal Control System

NASA Jet Propulsion Laboratory is investigating a two-phase mechanically pumped fluid loop (MPFL) technology for spacecraft thermal control for future planetary space science mission concepts. The two-phase technology combines the potential of single-phase MPFL and the passive two-phase heat pipe systems. Previous two-phase MPFL studies at JPL have identified an evaporator system with a separated flow architecture as providing a robust light mass thermal control system with very high spatial and temporal thermal stability required by the science instruments on these missions. These studies have further identified the thermophysical properties of the working fluid to be key to the performance of a two-phase fluid loop. This paper describes the methodology used in the selection of the working fluids for optimizing the performance of the two-phase MPFL. A high level model was developed that includes the constraints and boundaries driven by the system components. The performance of fluids from the REFPROP database are investigated and rated for this system. The working fluid attributes such as cost, hazardous properties, and heritage were taken into account in this selection. A typical spacecraft dissipating 1000 W and a fluid loop consisting of an evaporator, accumulator, radiator, and associated tubing components is used as an example in this study.

Daimaru, Takuro↗
NASA NTRS2018

Working Fluid Trade Study for a Two-Phase Mechanically Pumped Loop Thermal Control System

NASA Jet Propulsion Laboratory is investigating a two-phase mechanically pumped fluid loop (MPFL) technology for spacecraft thermal control for future planetary space science mission concepts. The two-phase technology combines the potential of single-phase MPFL and the passive two-phase heat pipe systems. Previous two-phase MPFL studies4,5 at JPL have identified an evaporator system with a separated flow architecture as providing a robust light mass thermal control system with very high spatial and temporal thermal stability required by the science instruments on these missions. These studies have further identified the thermophysical properties of the working fluid to be key to the performance of a two-phase fluid loop. This paper describes the methodology used in the selection of the working fluids for optimizing the performance of the two-phase MPFL. A high level model was developed that includes the constraints and boundaries driven by the system components. The performance of fluids from the REFPROP database were investigated and rated for this system. The working fluid attributes such as cost, hazardous properties, and heritage were taken into account in this selection. A typical spacecraft dissipating 1000 W and a fluid loop consisting of an evaporator, accumulator, radiator, and associated tubing components was used as an example in this study.

Daimaru, Takuro↗
DOE OSTI2022

Development of a Data Platform for High-Temperature Gas-cooled Reactor (HTGR) Nuclear Energy University Program (NEUP) Thermal-Fluid Experiments

Since the U.S. Department of Energy (DOE)’s Office of Nuclear Energy (NE) initiated the Nuclear Energy University Program (NEUP) in 2009, a total of 30 NEUP projects focused on High-Temperature Gas-cooled Reactor (HTGR) thermal-fluid experiments were funded up to fiscal year (FY) 2021. This represents a total DOE investment of approximately $23M over the 12-year period, covering thermal fluid phenomena important to both pebble bed and prismatic HTGR designs. The NEUP projects have produced a large amount of high-quality experimental and computational data that were published in final project reports, journal articles, dissertations, and conference proceedings, but in most cases the actual data sets and supporting information such as facility and instrumentation descriptions were not publicly disseminated to the HTGR community. To the authors’ best knowledge, a data platform that organizes and summarizes these NEUP-funded projects for HTGR research does not currently exist. To improve access to this HTGR validation data and optimize the return on the significant investment made by DOE, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects with the aim of developing a public-access data platform that can be used to retrieve computational fluid dynamics (CFD) and system code validation data and guide future NEUP investments. This paper summarizes the status of the current ART-GCR database, provides an overview of the NEUP-funded HTGR-related research projects from FY2009 to FY2021 and identify validation knowledge gaps still existing in HTGR thermal-fluid research.

42 ENGINEERING↗
DOE OSTI2021

Analysis and Optimization of Seismo-Acoustic Monitoring Networks with Bayesian Optimal Experimental Design

The Bayesian optimal experimental design (OED) problem seeks to identify data, sensor configurations, or experiments which can optimally reduce uncertainty. The goal of OED is to find an experiment that maximizes the expected information gain (EIG) about quantities of interest given prior knowledge about expected data. Therefore, within the context of seismic monitoring, we can use Bayesian OED to configure sensor networks by choosing sensor locations, types, and fidelity in order to improve our ability to identify and locate seismic sources. In this work, we develop the framework necessary to use Bayesian OED to optimize the ability to locate seismic events from arrival time data of detected seismic phases. In order to do utilize Bayesian OED we must develop four elements:1. A likelihood function that describes the uncertainty of detection and travel times; 2. A Bayesian solver that takes a prior and likelihood to identify the posterior; 3. An algorithm to compute EIG; and, 4. An optimizer that finds a sensor network which maximizes EIG. Once we have developed this framework, we can explore many relevant questions to monitoring such as: how and what multiphenomenology data can be used to optimally reduce uncertainty, how to trade off sensor fidelity and earth model uncertainty, and how sensor types, number, and locations influence uncertainty

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

FY2021 Report on Magnetic Microcalorimeter Development for the IAEA NML

The goal of this project is to develop high-resolution decay energy spectroscopy (DES) of actinides using magnetic microcalorimeters (MMCs). This requires testing different techniques to fully enclose a source inside an absorber and coupling it to an MMC with optimized energy resolution and speed. The goal is to develop DES with MMCs to allow its transfer to the IAEA Nuclear Materials Laboratory (NML).

42 ENGINEERING↗
DOE OSTI2023

Multi-Probe Campaign FY24 Omega EP Shot Request [Slides]

The ultimate goal of the Multi-Probe experimental campaign is to assess the feasibility of using multiple probe species (x-ray, proton, neutron, and electron) in future LANL radiographic facilities. To use Omega EP most efficiently, two different experiments are proposed for each of the two requested days in FY24. In this way, shots may be interleaved on the two short pulse beams and the shot rate doubled. In FY24, we propose to continue to develop the neutron source by first optimizing the “pitcher” source of deuterons/protons and then adding the “catcher” neutron converter on day 2. The second series of experiments continues examining the origin and nature of the x-ray background found in our last two experiments. This background is not well understood or characterized by the community. The first day will measure the electrons emanating from the proton and x-ray targets while also optimizing the background shielding first used in FY23. The second day will test a geometry that enables simultaneous radiographs using both short-pulse beams.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Robust Heat-Flux Sensors for Coal-Fired Boiler Extreme Environments

In this project, robust heat-flux measurement systems were developed. The heat-flux sensors utilize thermoelectric effects to directly transduce the heat-flux inputs to analog electrical voltage signals. They were constructed from dedicated materials that can withstand temperatures of at least 1000°C and maintain adequate performance at these conditions for prolonged periods of time. The proposed approaches took into account numerous considerations, including system cost, sensor head resilience, sensor footprint, data accuracy, response time, and maintenance requirements. Through modern thermoelectric materials design, methodical materials selection and rigorous testing in materials characterization labs and medium-scale fire research facilities, we have demonstrated functioning laboratory prototypes, upon which one could base industrial heat-flux sensing platforms capable of operating in the challenging high-temperature, corrosive environments of the boilers of coal-fired power plants. A distributed sensor array for heat-flux measurements throughout the furnace water-wall, the superheater area and the economizer coils can provide critical data for the power plant control systems to increase efficiency, improve safety and reduce down times. For example, the combined heat-flux sensor/control systems can contribute to the optimization of burner and boiler operations under flexible loads, the optimization of heat-exchange conditions and overall reduction of heat rate and emissions, the prediction of imminent overheating conditions, and the optimization of the soot-blowing protocols.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2006

Preface to Special Section: Validation of Atmospheric Infrared Sounder Observations

The papers described below demonstrate that the AIRS calibrated radiances and retrieved geophysical products generally meet or exceed the prelaunch specifications. The retrieved quantities show little variation in uncertainty as a function of cloud amount. However, AIRS retrieval yield is a rapidly decreasing function of cloud amount; at about 80% cloudiness essentially no infrared radiances are used in the retrieval processes. Also, AIRS performance has not been demonstrated for all conditions and products. Calibrated and forward calculated radiances meet performance specifications for conditions varying from the cold poles to warm tropics. The retrieval system performs well over extrapolar land in the free troposphere (~2-15 km above the surface) and over extrapolar oceans at all tropospheric altitudes. The AIRS retrieval algorithms have not been optimized for polar winter conditions, so no such results are presented in these papers.

temperature↗
DOE OSTI2024

The future of self-driving laboratories: from human in the loop interactive AI to gamification

Recent developments in artificial intelligence (AI) and machine learning (ML), implemented through self-driving laboratories (SDLs), are rapidly creating unprecedented opportunities for the accelerated discovery and optimization of materials. This paper provides a joint analysis of SDLs from both academic and industry perspectives, highlighting the importance of integrating human intelligence in these systems. It discusses the necessity of careful planning in SDL design across physical, data, and workflow dimensions, including instrumental setup, experimental workflow, data management, and human–SDL interaction. The significance of integrating human input within SDLs, especially as the focus shifts from individual tools and tasks to the creation and management of complex workflows, is emphasized. The paper stresses on the crucial role of reward function design in developing forward-looking workflows and examines the interplay between hardware evolution, ML application across chemical processes, and the influence of reward systems in research. Ultimately, the article advocates for a future where SDLs blend human intuition in hypothesis formulation with AI's precision, speed, and data-handling capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Robust Medium-Voltage Distribution System State Estimation using Multi-Source Data

Due to the lack of sufficient online measurements for distribution system observability, pseudo-measurements from short-term load or distributed renewable energy resources (DERs) forecasting are used. However, the accuracy of them is low and thus significantly limits the performance of distribution system state estimation (DSSE). In this paper, a robust DSSE that integrates multi-source measurement data is proposed. Specifically, the historical low-voltage (LV) side smart meters are used to forecast load and DERs injections via the support vector machine (SVM) with optimally tuned parameters. By contrast, the online smart meters at LV side are utilized to derive equivalent power injections at the MV/LV transformers, yielding more accurate pseudo-measurements compared to the forecasted injections. Furthermore, to deal with bad data caused by communication loss, instrumental errors and cyber attacks, robust DSSE that relies on generalized maximum-likelihood (GM)-estimation criterion is developed. The projection statistics are developed to adjust the weights of each measurement, leading to better balance between pseudo- and real-time measurements. Numerical results conducted on modified IEEE 33-bus system with DG integration demonstrate the effectiveness and robustness of the proposed method.

distribution system state estimation↗
DOE OSTI2021

High-Current Light-Ion Cyclotron for Applications in Nuclear Security and Radioisotope Production

In this article, we propose the conceptual design, with supporting beam dynamics results, of a normal conducting, separated-sector cyclotron with a strong-focusing field gradient designed to accelerate light ions with a charge-to-mass ratio of 1/2 up to 15–20 MeV/u. The design can support a host of applications for therapy, radiobiology, material science, and instrumentation development. The light-ion species, which can include a mixed ion beam, can be dynamically chosen to provide a range of characteristic signals appropriate for specific material identification such as special nuclear materials. A conservative baseline concept is presented which has been optimized for radioisotope production of alpha emitters and theranostic radiopharmaceuticals. The modular design is also demonstrated to be scalable in gross physical parameters by a factor of 2–3, thereby reducing the size, weight, and power requirements (SWaP) and enabling near-term security applications.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1981

Coronal observations from the SMM satellite

The scientific purpose, coronal observations, and the instrument design and control of the Coronagraph/Polarimeter aboard the Solar Maximum Mission (SMM) satellite are discussed. The instruments were made with an optical design using an achromatic objective lens providing a 10 arcsec resolution in imaging and an SEC vidicon detector allowing integration on the low light levels of the corona. The computer control assures flexibility in the observing program to optimize observations of changing solar phenomena and allows rapid response to SMM or ground-commanded solar flare alerts.

Csoeke-Poeckh, A.↗
NASA NTRS1988

Some test/analysis issues for the space station structural characterization experiment

The Space Station Structural Characterization Experiment (SSSCE) 1,2 is an early space flight experiment that uses the space station as a generic structure to study the dynamic characteristics of Large Space Structures (LSS). On-orbit modal testing will be conducted to determine natural frequencies, mode shapes and damping of dominant structural modes of the space structure assembly. This experiment will utimately support the development of system identification and analytical modeling techniques for Large Space Structures. In order to ensure the success of SSSCE (in-space validation of modeling techniques for LSS), adequate measurement and instrumentation requirements have to be established during the experiment-definition study. Among the issues affecting these requirements, spatial and modal coverages of the modal test data are of particular interest. Topics such as total number of sensors, type of measurements (translation and rotation), optimal sensor locations (measurement degrees-of-freedom), selection of target modes, effects of modal superposition and truncation, separation of global and local modes, etc., are all a fundamental importance and must be investigated.

Chou, Chaur-Ming↗
NASA NTRS2005

Experience With Bayesian Image Based Surface Modeling

Bayesian surface modeling from images requires modeling both the surface and the image generation process, in order to optimize the models by comparing actual and generated images. Thus it differs greatly, both conceptually and in computational difficulty, from conventional stereo surface recovery techniques. But it offers the possibility of using any number of images, taken under quite different conditions, and by different instruments that provide independent and often complementary information, to generate a single surface model that fuses all available information. I describe an implemented system, with a brief introduction to the underlying mathematical models and the compromises made for computational efficiency. I describe successes and failures achieved on actual imagery, where we went wrong and what we did right, and how our approach could be improved. Lastly I discuss how the same approach can be extended to distinct types of instruments, to achieve true sensor fusion.

Stutz, John C.↗
NASA NTRS2008

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Sowers, T. Shane↗
NASA NTRS2008

Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics

The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance, there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. The Systematic Sensor Selection Strategy is a methodology that optimally selects a sensor suite from a pool of sensors based on the system fault diagnostic approach, with the ability of taking cost, weight, and reliability into consideration. This procedure was applied to a large commercial turbofan engine simulation. In this initial study, sensor suites tailored for improved diagnostic performance are constructed from a prescribed collection of candidate sensors. The diagnostic performance of the best performing sensor suites in terms of fault detection and identification are demonstrated, with a discussion of the results and implications for future research.

Sowers, T. Shane↗
NASA NTRS2009

The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII): Spatially Resolved Spectroscopy in the Far-Infrared

Astronomical studies at infrared wavelengths have dramatically improved our understanding of the universe, and observations with Spitzer, the upcoming Herschel mission, and SOFIA will continue to provide exciting new discoveries. The relatively low angular resolution of these missions, however, is insufficient to resolve the physical scale on which mid-to far-infrared emission arises, resulting in source and structure ambiguities that limit our ability to answer key science questions. Interferometry enables high angular resolution at these wavelengths - a powerful tool for scientific discovery. We will build the Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII), an eight-meter baseline Michelson stellar interferometer to fly on a high-altitude balloon. BETTII's spectral-spatial capability, provided by an instrument using double-Fourier techniques, will address key questions about the nature of disks in young star clusters and active galactic nuclei and the envelopes of evolved stars. BETTII will also lay the technological groundwork for future space interferometers and for suborbital programs optimized for studying extrasolar planets.

Rinehart, Stephen↗