Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Power Extraction”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

U.S. Efforts in Support of Examinations at Fukushima Daiichi - November 2022 Meeting Notes and Information Request Status

Information obtained from Fukushima Daiichi Nuclear Power Station (Daiichi) is required to inform future Decontamination and Decommissioning (D&D) activities, improving the ability of the Tokyo Electric Power Company Holdings, Incorporated (TEPCO Holdings) to characterize potential hazards and to ensure the safety of workers involved with cleanup activities. This information also has important implications for the safety and operation of U.S. commercial nuclear power plants. This document summarizes results from the Fiscal Year 2023 (FY2023) U.S. effort to review Daiichi information and extract insights to enhance the safety of existing and future nuclear power plant designs. This U.S. effort, which was initiated in 2014 by the Department of Energy Office of Nuclear Energy, is completed by a group of experts in reactor safety and plant operations that identify examination needs and evaluate recent Daiichi examination data to address these needs. Fukushima-related information and associated discussions during these meetings benefit operating, new, and advanced reactors. Significant safety insights have been and are continuing to be obtained in several areas: system and component performance, radionuclide surveys and sampling, debris end-state location, combustible gas effects, and plant operations and maintenance. In addition to reducing uncertainties related to severe accident modeling progression, these insights have and continue to be used to update guidance for severe accident prevention, mitigation, and emergency planning. Furthermore, Daiichi-related activities, such as code modeling improvements and analysis, testing, and new technology deployment efforts, have the potential to offer additional benefits to the operating fleet and new LWR and non-LWR designs. U.S. evaluations of obtained examination information and input regarding future Daiichi examinations are of interest to several organizations within Japan. Since its inception, the U.S. has provided consensus input for high priority time-sequenced examination tasks and supporting research activities. In their Mid-to-Long-term Examination Plan for 1F investigations, TEPCO included all remaining U.S. consensus information requests and additional information requests they identified. TEPCO periodically provides reports on the status of these requests (reflecting D&D priorities, new insights from investigations, and new technologies that become available). Hence, U.S. experts agreed that it was appropriate for TEPCO to track and prioritize these information requests as D&D progresses. U.S. experts will continue to review and comment on the information obtained from examinations and, as needed, provide additional details and relevant background material to support future examinations. As documented in this report, several other items, such as additional details on information requests pertaining to ex-vessel examinations, relevant references from prior research, additional documents to provide insights regarding recent investigation findings, and reviews of recently released documents, were agreed to during the FY2023 meeting.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2004

Ion Engine Grid Gap Measurements

A simple technique for measuring the grid gap of an ion engine s ion optics during startup and steady-state operation was demonstrated with beam extraction. The grid gap at the center of the ion optics assembly was measured with a long distance microscope that was focused onto an alumina pin that protruded through the center accelerator grid aperture and was mechanically attached to the screen grid. This measurement technique was successfully applied to a 30 cm titanium ion optics assembly mounted onto an NSTAR engineering model ion engine. The grid gap and each grid s movement during startup from room temperature to both full and low power were measured. The grid gaps with and without beam extraction were found to be significantly different. The grid gaps at the ion optics center were both significantly smaller than the cold grid gap and different at the two power levels examined. To avoid issues associated with a small grid gap during thruster startup with titanium ion optics, a simple method was to operate the thruster initially without beam extraction to heat the ion optics. Another possible method is to apply high voltage to the grids prior to igniting the discharge because power deposition to the grids from the plasma is lower with beam extraction than without. Further testing would be required to confirm this approach.

Soulas, Gerge C.↗
DOE OSTI2025

Large language model-driven database for thermoelectric materials

Thermoelectric materials have the ability to convert waste heat into electricity, offering a valuable solution for energy harvesting. However, their widespread use is hindered by low conversion efficiency, the reliance on expensive rare earth elements, and the environmental and regulatory concerns associated with lead-based materials. A fast and cost-effective way to identify highly efficient thermoelectric materials is through data-driven methods. These approaches rely on robust and comprehensive datasets to train models. Although there are several databases on thermoelectric materials, there is still a need to collect and integrate experimental data from peer-reviewed research articles to capture diverse compositions and properties of materials. Here, in this work, we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structural detail, seebeck coefficient, electrical and thermal conductivity, power factor, and figure of merit (ZT). We used the GPTArticleExtractor workflow, powered by large language models (LLM), to extract and curate data automatically from the scientific literature published in Elsevier journals. This process enabled the creation of a structured database that addresses the challenges of manual data collection. The open access database could stimulate data-driven research and advance thermoelectric material analysis and discovery.

Database↗
DOE OSTI2021

Direct Deposition of Nonaqueous SnO 2 Dispersion by Blade Coating on Perovskites for the Scalable Fabrication of p–i–n Perovskite Solar Cells

Tin(IV) oxide materials have been extensively used as electron transport materials in n–i–p perovskite solar cells (PSCs) due to their superior optoelectronic properties, low-temperature processability, and high chemical stability. However, solvent incompatibility and processing temperature have limited the direct deposition of fully solution-processed SnO 2 in p–i–n devices. In this study, we overcome this limitation by the functionalization of SnO 2 nanoparticles with acetate through ligand exchange, allowing their dispersion in anhydrous ethanol. The SnO 2 dispersion was deposited on the perovskite absorber by blade coating without damaging the underlying perovskite layer, as determined by X-ray diffraction and scanning electron microscopy. Photoluminescence spectroscopy confirmed effective electron extraction. The champion device shows 14.1% initial power conversion efficiency (PCE) which is unprecedented for a p–i–n device employing solution-phase SnO 2 . Finally, PSCs stored for 40 days in a nitrogen flow box retained an average of 95.8% of the initial PCE.

14 SOLAR ENERGY↗
DOE OSTI2024

Automated electrosynthesis reaction mining with multimodal large language models (MLLMs)

Leveraging the chemical data available in legacy formats such as publications and patents is a significant challenge for the community. Automated reaction mining offers a promising solution to unleash this knowledge into a learnable digital form and therefore help expedite materials and reaction discovery. However, existing reaction mining toolkits are limited to single input modalities (text or images) and cannot effectively integrate heterogeneous data that is scattered across text, tables, and figures. In this work, we go beyond single input modalities and explore multimodal large language models (MLLMs) for the analysis of diverse data inputs for automated electrosynthesis reaction mining. We compiled a test dataset of 65 articles (MERMES-T24 set) and employed it to benchmark five prominent MLLMs against two critical tasks: (i) reaction diagram parsing and (ii) resolving cross-modality data interdependencies. The frontrunner MLLM achieved ≥96% accuracy in both tasks, with the strategic integration of single-shot visual prompts and image pre-processing techniques. We integrate this capability into a toolkit named MERMES (multimodal reaction mining pipeline for electrosynthesis). Our toolkit functions as an end-to-end MLLM-powered pipeline that integrates article retrieval, information extraction and multimodal analysis for streamlining and automating knowledge extraction. This work lays the groundwork for the increased utilization of MLLMs to accelerate the digitization of chemistry knowledge for data-driven research.

Leong, Shi Xuan↗
DOE OSTI2024

Coherent mode and turbulence measurements with a fast camera

This study employs a fast camera with frame rates up to 900,000 fps to measure the transfer of energy across spatial scales in helicon source plasmas and during flux rope mergers and the measurement of azimuthal mode structures in helicon plasmas. By extracting pixel-scale dispersion relations and power spectral density (PSD) measurements, we measure the details of turbulent wave modes and energy distribution across a broad range of spatial scales within the plasma. We confirm the presence of drift waves in helicon plasmas, as well as the existence of strong dissipation regions in the PSD at electron skin depth scales for both helicon and flux rope merger experiments. This approach overcomes many limitations of conventional probes, providing high spatial and temporal resolution, without perturbing the plasma.

Instruments & Instrumentation↗
DOE OSTI2021

Synchrotron self-Compton radiation from magnetically dominated turbulent plasmas in relativistic jets

ABSTRACT Relativistic jets launched by rotating black holes are powerful emitters of non-thermal radiation. Extraction of the rotational energy via electromagnetic stresses produces magnetically dominated jets, which may become turbulent. Studies of magnetically dominated plasma turbulence from first principles show that most of the accelerated particles have small pitch angles, i.e. the particle velocity is nearly aligned with the local magnetic field. We examine synchrotron self-Compton radiation from anisotropic particles in the fast cooling regime. The small pitch angles reduce the synchrotron cooling rate and promote the role of inverse Compton (IC) cooling, which can occur in two different regimes. In the Thomson regime, both synchrotron and IC components have soft spectra, νFν ∝ ν1/2. In the Klein–Nishina regime, synchrotron radiation has a hard spectrum, typically νFν ∝ ν, over a broad range of frequencies. Our results have implications for the modelling of BL Lacertae objects (BL Lacs) and gamma-ray bursts (GRBs). BL Lacs produce soft synchrotron and IC spectra, as expected when Klein–Nishina effects are minor. The observed synchrotron and IC luminosities are typically comparable, which indicates a moderate anisotropy with pitch angles θ ≳ 0.1. Rare orphan gamma-ray flares may be produced when θ ≪ 0.1. The hard spectra of GRBs may be consistent with synchrotron radiation when the emitting particles are IC cooling in the Klein–Nishina regime, as expected for pitch angles θ ∼ 0.1. Blazar and GRB spectra can be explained by turbulent jets with a similar electron plasma magnetization parameter, σe ∼ 104, which for electron–proton plasmas corresponds to an overall magnetization σ = (me/mp)σe ∼ 10.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Model Validation and Uncertainty Quantification on the KRUSTY Microreactor Design Using GRIFFIN Neutron Transport Code [Poster]

Argonne National Laboratory (ANL) and INL have developed a GRIFFIN steady state neutronics model for the multiphysics simulations of the Kilopower Reactor Using Sterling TechnologY (KRUSTY) microreactor in the Multiphysics Object Oriented Simulation Environment (MOOSE). The reliability of such deterministic neutronics models can be validated by comparing with computations from Monte Carlo codes (e.g. MCNP, SERPENT, OpenMC, Shift, etc). Furthermore, potential modeling/design improvements can be identified by incorporating uncertainty quantification (UQ), which can be performed by MOOSE’s Stochastic Tools Module (STM). KRUSTY is a prototype for a 5-kW thermal nuclear-powered space reactor. Its primary components consist of nuclear fuel, heat pipes, a control rod, a reflector, and the shielding. The fuel consists of 3 stacked U-7.65Mo cylinders with a hole in the center for the control rod. 8 liquid sodium heat pipes transfer fission energy from the solid fuel block to the Sterling power conversion system where the energy is extracted, and the cooled sodium flows back to the core via capillary action . The movable Boron Carbide control rod regulates the neutron population during startup or when a reactor temperature boost is needed . The beryllium oxide reflector is in 3 places in the reactor; it surrounds the core axially, it lies beneath the core on a platen, and it is present in the shim. The axial and lower reflectors rest on an adjustable stainless-steel platen that moves upward to cover the fuel and help the reactor reach criticality. Lastly, radial stainless steel surrounds the core offering protection from radiation exposure .

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2027

Design and Integration of High Precision Superconducting Magnet Power Supply Systems

This paper reviews the design and integration approach being taken to power more than 400 superconducting magnets in Electron Ion Collider (EIC) by power supplies ranging from 20V to 400V and 100A to 18kA. A major challenge is to integrate existing legacy power supplies with new high current systems and maximize performance and reduce costs. Successful implementation requires coordinated integration of power convertors, current regulation, quench protection, energy extraction, machine protection, controls and existing accelerator infrastructure.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Contrastive Machine Learning with Gamma Spectroscopy Data Augmentations for Detecting Shielded Radiological Material Transfers

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting information that can be used in a latent space for categorizing observations between classes of data. Machine learning models that exploit learned data relationships can address a variety of nuclear nonproliferation challenges like the detection and tracking of shielded radiological material transfers. The high resource cost of manually labeling radiation spectra is a hindrance to the rapid analysis of data collected from persistent monitoring and to the adoption of supervised machine learning methods that require large volumes of curated training data. Instead, contrastive self-supervised learning on unlabeled spectra can enhance models that are built on limited labeled radiation datasets. This work demonstrates that contrastive machine learning is an effective technique for leveraging unlabeled data in detecting and characterizing nuclear material transfers demonstrated on radiation measurements collected at an Oak Ridge National Laboratory testbed, where sodium iodide detectors measure gamma radiation emitted by material transfers between the High Flux Isotope Reactor and the Radiochemical Engineering Development Center. Label-invariant data augmentations tailored for gamma radiation detection physics are used on unlabeled spectra to contrastively train an encoder, learning a complex, embedded state space with self-supervision. A linear classifier is then trained on a limited set of labeled data to distinguish transfer spectra between byproducts and tracked nuclear material using representations from the contrastively trained encoder. The optimized hyperparameter model achieves a balanced accuracy score of 80.30%. Any given model—that is, a trained encoder and classifier—shows preferential treatment for specific subclasses of transfer types. Regardless of the classifier complexity, a supervised classifier using contrastively trained representations achieves higher accuracy than using spectra when trained and tested on limited labeled data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1981

Recent work on an RF ion thruster

An experimental investigation of an rf ion thruster using an immersed coupler in an argon discharge is reported. The conical coil, used to couple rf power into the discharge, is placed inside the discharge vessel. The discharge was self-sustained by 100-150 MHz rf power at low environmental pressures. The ion extraction was accomplished by conventional accelerated grid optics from an unoptimized 8 cm diameter ion thruster.

Lee, R. Q.↗
NASA NTRS1979

Flight test evaluation of predicted light aircraft drag, performance, and stability

A technique was developed which permits simultaneous extraction of complete lift, drag, and thrust power curves from time histories of a single aircraft maneuver such as a pull up (from V max to V stall) and pushover (to V max for level flight). The technique, which is an extension of nonlinear equations of motion of the parameter identification methods of Iliff and Taylor and includes provisions for internal data compatibility improvement as well, was shown to be capable of correcting random errors in the most sensitive data channel and yielding highly accurate results. Flow charts, listings, sample inputs and outputs for the relevant routines are provided as appendices. This technique was applied to flight data taken on the ATLIT aircraft. Lack of adequate knowledge of the correct full throttle thrust horsepower true airspeed variation and considerable internal data inconsistency made it impossible to apply the trajectory matching features of the technique.

Smetana, F. O.↗
NASA NTRS1982

Incipient failure detection (IFD) of SSME ball bearings

Because of the immense noise background during the operation of a large engine such as the SSME, the relatively low level unique ball bearing signatures were often buried by the overall machine signal. As a result, the most commonly used bearing failure detection technique, pattern recognition using power spectral density (PSD) constructed from the extracted bearing signals, is rendered useless. Data enhancement techniques were carried out by using a HP5451C Fourier Analyzer. The signal was preprocessed by a Digital Audio Crop. DAC-1024I noise cancelling filter in order to estimate the desired signal corrupted by the backgound noise. Reference levels of good bearings were established. Any deviation of bearing signals from these reference levels indicate the incipient bearing failures.

Source record↗
NASA NTRS1990

Aurora and airglow on the night side of Neptune

The latitude-longitude distribution of emissions detected by the Voyager ultraviolet spectrometer on the dark hemisphere of Neptune have been examined. The emissions have two significant geographic features: (1) a broad peak near longitude 60 deg W that extends rather uniformly over the entire range of observed latitudes (55 deg S to 50 deg N); and (2) a brighter, narrower peak near the south pole and 240 deg W. The first peak is interpreted as due to excitation of the night side atmosphere by photoelectrons from the magnetically conjugate, sunlit atmosphere. The second peak can plausibly be attributed to a southern aurora; the field geometry would then seem to require a conjugate (and probably brighter) northern aurora that escaped detection poleward of the latitude range sampled by the UVS data. The power for such an aurora could be extracted from Neptune's rotation by the injection of plasma at Triton's orbit at a rate dm/dt of about 1 kg/s.

Sandel, B. R.↗
NASA NTRS1990

Determination of surface resistance and magnetic penetration depth of superconducting YBa2Cu3O(7-delta) thin films by microwave power transmission measurements

A novel waveguide power transmission measurement technique was developed to extract the complex conductivity of superconducting thin films at microwave frequencies. The microwave conductivity was taken of two laser ablated YBa2Cu3O(7-delta) thin films on LaAlO3 with transition temperatures of approx. 86.3 and 82 K, respectively, in the temperature range 25 to 300 K. From the conductivity values, the penetration depth was found to be approx. 0.54 and 0.43 micron, and the surface resistance (R sub s) to be approx. 24 and 36 micro-Ohms at 36 GHz and 76 K for the two films under consideration. The R sub s values were compared with those obtained from the change in the Q-factor of a 36 GHz Te sub 011-mode (OFHC) copper cavity by replacing one of its end walls with the superconducting sample. This technique allows noninvasive characterization of high transition temperature superconducting thin films at microwave frequencies.

Bhasin, K. B.↗
NASA NTRS1991

Determination of surface resistance and magnetic penetration depth of superconducting YBa2Cu3O(7-delta) thin films by microwave power transmission measurements

A novel waveguide power transmission measurement technique was developed to extract the complex conductivity of superconducting thin films at microwave frequencies. The microwave conductivity was taken of two laser ablated YBa2Cu3O(7-delta) thin films on LaAlO3 with transition temperatures of approximately 86.3 and 82 K, respectively, in the temperature range 25 to 300 K. From the conductivity values, the penetration depth was found to be approximately 0.54 and 0.43 micron, and the surface resistance (R sub s) to be approximately 24 and 36 micro-Ohms at 36 GHz and 76 K for the two films under consideration. The R sub s values were compared with those obtained from the change in the Q-factor of a 36 GHz Te sub 011-mode (OFHC) copper cavity by replacing one of its end walls with the superconducting sample. This technique allows noninvasive characterization of high transition superconducting thin films at microwave frequencies.

Bhasin, K. B.↗
NASA NTRS1998

Three-Dimensional Road Network by Fusion of Polarimetric and Interferometric SAR Data

In this paper a fuzzy classification procedure is applied to polarimetric radar measurements, and street pixels are detected. These data are successively grouped into consistent roads by means of a dynamic programming approach based on the fuzzy membership function values. Further fusion of the 2D road network extracted and 3D TOPSAR measurements provides a powerful way to analyze urban infrastructures.

Gamba, P.↗
NASA NTRS2001

Millimeter-Wave Radar Field Measurements and Inversion of Cloud Parameters for the 1999 Mt. Washington Icing Sensors Project

The Mount Washington Icing Sensors Project (MWISP) was a multi-investigator experiment with participants from Quadrant Engineering, NOAA Environmental Technology Laboratory (NOAA/ETL), the Microwave Remote Sensing Laboratory (MIRSL) of the University of Massachusetts (UMass), and others. Radar systems from UMass and NOAA/ETL were used to measure X-, Ka-, and W-band backscatter data from the base of Mt. Washington, while simultaneous in-situ particle measurements were made from aircraft and from the observatory at the summit. This report presents range and time profiles of liquid water content and particle size parameters derived from range profiles of radar reflectivity as measured at X-, Ka-, and W-band (9.3, 33.1, and 94.9 GHz) using an artificial neural network inversion algorithm. In this report, we provide a brief description of the experiment configuration, radar systems, and a review of the artificial neural network used to extract cloud parameters from the radar data. Time histories of liquid water content (LWC), mean volume diameter (MVD) and mean Z diameter (MZD) are plotted at 300 m range intervals for slant ranges between 1.1 and 4 km. Appendix A provides details on the extraction of radar reflectivity from measured radar power, and Appendix B provides summary logs of the weather conditions for each day in which we processed data.

Pazmany, Andrew L.↗