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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Adaptive sensing for a gas leak detection

A method, a system and an apparatus for adaptively sensing a gas leak. The method includes: obtaining wind data from a wind sensor, identifying at least one wireless mote in a plurality of wireless motes that is most likely to detect a gas plume from the wind data, activating the identified at least one wireless mote to trigger measuring gas concentration of the gas plume, and identifying the location of the gas leak if the gas concentration is above a predetermined threshold. Also included is a system for adaptively sensing a gas leak having a wind sensor, a plurality of wireless motes and a server in communication therewith. An apparatus for adaptively sensing a gas leak in an industrial site is also provided.

03 NATURAL GAS↗
DOE OSTI2026

Precision measurement of positron decay modes of Xe-125 in the LUX-ZEPLIN experiment

The radioisotope $^{125}\text{Xe}$ is a short-lived ($T_{1/2}\sim16.9 h$) activation product of the neutron calibrations performed in the LUX-ZEPLIN experiment. Subsequently, $^{125}$Xe decays primarily ($>99\%$) via electron capture, but positron emission has been confirmed by direct measurement to at least the 243 keV level of $^{125}\text{I}$. An additional decay to the 188keV level is expected from triple-coincident measurements of the annihilation and relaxation $γ$ rays, but has not been directly confirmed. By utilizing multiple-scatter event analysis and the pre-activation data to constrain backgrounds, this work reports positron emission with a statistical significance of 5.5$σ$. This corresponds to a total branching ratio of $0.29\pm0.08_{\text{stat.}}\pm0.04_{\text{sys.}}$%, and is the first constraint to the individual branching levels of $^{125}\text{I}$.

Akerib, D. S. [SLAC; KIPAC, Menlo Park]↗
NASA NTRS1997

The Benchmark Active Controls Technology Model Aerodynamic Data

The Benchmark Active Controls Technology (BACT) model is a part of the Benchmark Models Program (BMP). The BMP is a NASA Langley Research Center program that includes a series of models which were used to study different aeroelastic phenomena and to validate computational fluid dynamics codes. The primary objective of BACT testing was to obtain steady and unsteady loads, accelerations, and aerodynamic pressures due to control surface activity in order to calibrate unsteady CFD codes and active control design tools. Three wind-tunnel tests in the Transonic Dynamics Tunnel (TDT) have been completed. The first and parts of the second and third tests focused on collecting open-loop data to define the model's aeroservoelastic characteristics, including the flutter boundary across the Mach range. It is this data that is being presented in this paper. An extensive database of over 3000 data sets was obtained. This database includes steady and unsteady control surface effectiveness data, including pressure distributions, control surface hinge moments, and overall model loads due to deflections of a trailing edge control surface and upper and lower surface

Scott, Robert C.↗
NASA NTRS1986

Implementation of Ada protocols on Mil-STD-1553 B data bus

Standardization activity of data communication in avionic systems started in 1968 for the purpose of total system integration and the elimination of heavy wire bundles carrying signals between various subassemblies. The growing complexity of avionic systems is straining the capabilities of MIL-STD-1553 B (first issued in 1973), but a much greater challenge to it is posed by Ada, the standard language adopted for real-time, computer embedded-systems. Hardware implementation of Ada communication protocols in a contention/token bus or token ring network is proposed. However, during the transition period when the current command/response multiplex data bus is still flourishing and the development environment for distributed multi-computer Ada systems is as yet lacking, a temporary accomodation of the standard language with the standard bus could be very useful and even highly desirable. By concentrating all status informtion and decisions at the bus controller, it was found to be possible to construct an elegant and efficient harware impelementation of the Ada protocols at the bus interface. This solution is discussed.

Ruhman, Smil↗
NASA NTRS1975

ASTP experiment support data processing

Activities associated with the generation of ASTP experiment support data in the areas of spacecraft ephemeris and orientation and instrument pointing and field-of-view are documented. It is intended that this document represent a cradle-to-grave chronicle of these activities. To satisfy this intent while facilitating the ready dissemination of information, the document is being published twice. The first publication, scheduled for release prior to ASTP liftoff, includes all preflight phases of the experiment support activity in addition to those appendixes that do not pertain to any mission-specific data. The second publication will provide any required updates to the original documentation and will add all mission-specific data, including documentation of all postflight data processing activities and data archiving information.

Osburn, R. K.↗
NASA NTRS2010

Onboard Processing of Multispectral and Hyperspectral Data of Volcanic Activity for Future Earth-Orbiting and Planetary Missions

Autonomous onboard processing of data allows rapid response to detections of dynamic, changing processes. Software that can detect volcanic eruptions from thermal emission has been used to retask the Earth Observing 1 spacecraft to obtain additional data of the eruption. Rapid transmission of these data to the ground, and the automatic processing of the data to generated images, estimates of eruption parameters and maps of thermal structure, has allowed these products to be delivered rapidly to volcanologists to aid them in assessing eruption risk and hazard. Such applications will enhance science return from future Earth-orbiting spacecraft and also from spacecraft exploring the Solar System, or beyond, which hope to image dynamic processes. Especially in the latter case, long communication times between the spacecraft and Earth exclude a rapid response to what may be a transient process - only using onboard autonomy can the spacecraft react quickly to such an event.

Jupiter↗
DOE OSTI2022

Applications of Autonomous Data Collection and Active Learning

Advances in sensors and robotics have dramatically improved the diversity of experimental approaches available to the materials community. Autonomous data collection platforms, either custom-made or commercially available, provide researchers with novel tools with which to probe materials behavior and perform advanced materials characterization. The application of novel control algorithms and active learning approaches can create much more robust experimental data, or can be used to improve the performance of existing characterization tools. Five papers within this special topic focus on experimental and computational methodologies for use in automatic data collection routines for materials characterization. From novel platforms for materials discovery to new statistical frameworks for assessing the autonomous experimentation process, these five papers highlight the diverse range of applications of automation for advancing materials science.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Measuring and Extracting Activity from Time Series Data

This report summarizes the results of an LDRD focused on developing and demonstrating statistically rigorous methods for analyzing and comparing complex activities from remote sensing data. Identifying activity from remote sensing data, particularly those that play out over time and span multiple locations, often requires extensive manual effort because of the variety of features that describe the activity and the required domain expertise. Our results suggest that there are some hidden challenges in extracting and representing activities in sensor data. In particular, we found that the variability in the underlying behaviors can be difficult to overcome statistically, and the report identifies several examples of the issue. We discuss key lessons learned in the context of the project, and finally conclude with recommendations on next steps and future work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Deep Learning for Full Waveform Inversion of Elastic Active-Source Seismic Data to Estimate P-Wave Velocity Models

Seismic imaging methods are critical for Global Security and Energy & Homeland Security missions and activities that rely on subsurface characterization, but traditional methods remain computationally expensive and require significant labor hours and expertise to execute. Within the past few years, machine learning (ML), namely deep learning (DL), has been used to develop data-driven end-to-end full waveform inversion (FWI) methods to estimate 2D P-wave velocity (Vp) models in a fraction of the time as conventional FWI. These methods, however, are trained on simplistic acoustic wave seismic data and Vp models that are not realistic nor representative of real-world observations, leaving a large gap between the state-of-the-art and deployable, feasible, and practical DL FWI methods. Here, we generate a synthetic active-source, 3D, elastic wave seismic data set and a variety of Vp models with realistic geologic structure for training DL FWI methods. We evaluate six different methods that have performed well for acoustic DL FWI or medical imaging tasks using our more realistic dataset. We find that these six trained models do not match the performance of published acoustic end-to-end DL FWI methods, indicating more training data may be needed, physics may need to be incorporated to achieve good accuracy at the sacrifice of the end-to-end advantage, and/or novel methods need to be developed to enable end-to-end DL FWI methods to perform well for real-world seismic data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1977

Consumables data base workbook: Formulation of consumables management models

Activity consumables data specifications and data applications are presented. The data are structured in a series of "Consumable Data Worksheets" for each activity that includes a profile of its operations and the rate of each consumable required to support the given activity. The data worksheets provide for the uniform specification of consumables data, allows for the ready identification of the consumables affected by a given activity, and facilitates the updating process. An activity is defined and the data that must be included in the data worksheets are specified. An example of its use and application is given, i.e. consumables data requirements for the performance of the EVA. The consumables data for the activities currently identified for the shuttle spacecraft are included. The consumables data sources are identified and information to facilitate the maintenance process is detailed.

Zamora, M. A.↗
DOE OSTI2020

Composite Analysis Solid Waste Release Data Reduction of Activity Flux from Waste Sites to the Vadose Zone for Baseline Assessment

This environmental calculation file (ECF) describes the data reduction methodology for the solid waste release datasets generated by the Composite Analysis Solid Waste Release (CASWR) model (CP-62766, Model Package Report: Composite Analysis Solid Waste Release Model [CASWR Model]) and documents the resulting reduced datasets for the updated Composite Analysis (CA) baseline assessment. This ECF is in support of the updated Hanford Site CA. The purpose of the updated Hanford Site CA is to provide an estimate of the cumulative radiological impacts from active and planned low-level radioactive waste disposals and other potentially interacting radioactive waste disposal sources that will remain following Hanford Site closure. The vadose zone modeling activities associated with the CA includes solid waste forms as contaminant sources. To support the modeling of solid waste transport from the vadose zone to the groundwater at the Hanford Site, the CASWR model was designed to generate deterministic radionuclide release rates for the Hanford Site Central Plateau solid waste disposal sites. The complete CASWR model-generated dataset for the CA Baseline Assessment consists of 2,378,831 sets of time and release rates (1,073,869 sets for the 200 East Area and 1,304,962 sets for the 200 West Area), representing a course of the simulation from year 1953 to year 12,069, 16 radiological contaminants of potential concern (COPCs), and 237 solid waste sources as documented in ECFHANFORD- 19-0112, Solid Waste Release Calculations for the Composite Analysis Baseline Assessment. For several of the STOMP vadose zone models, the number of release rate data pairs required for release at all waste sites would exceed the limitations imposed by the STOMP modelling software package used to simulate contaminant transport through the vadose zone. As a result, a data reduction of the CASWR dataset is required prior to its use as a source input for the CA vadose zone modeling activities.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Validation Study of the Spacecraft Background Activation using RHESSI Data

This document serves as a brief writeup of the work done to validate CINDER2008 and the Activation Analysis Tools in the Activation in Accelerator Radiation Environments (AARE) distribution that are used to calculate the activation of spacecraft material while in orbit [1{3]. The validation study involves replicating the decay gamma spectrum as observed onboard the RHESSI spacecraft in the high-purity germanium (HPGe) detectors after crossing the South Atlantic Anomaly (SAA) [4]. The tools involved are a suite of Python scripts, the transmutation code CINDER2008 accompanied with a suite of scripts distributed with AARE,MCNPX, and MCNP6.2 [2,5{7]. Figure 1 shows the gamma ray spectrum this study replicates as the spectrum designated \Difference".

42 ENGINEERING↗
DOE OSTI2023

Systems and methods for active learning from sparse training data

A method for active learning using sparse training data can include training a machine learning model using less than ten first training data points to generate a candidate machine learning model. The method can include performing a Monte Carlo process to sample one or more first outputs of the candidate machine learning model. The method can include testing the one or more first outputs to determine if each of the one or more first outputs satisfy a respective convergence condition. The method can include, responsive to at least one first output not satisfying the respective convergence condition, training the candidate machine learning model using at least one second training data point corresponding to the at least one first output. The method can include, responsive to the one or more first outputs each satisfying the respective convergence condition, outputting the candidate machine learning model.

Sankaranarayanan, Subramanian↗
DOE OSTI2024

233 U oxide Measurement Campaign Data: Passive and Active Neutron Multiplicity Measurements of Uranium Oxide Samples at Oak Ridge National Laboratory

During FY2023, three measurement campaigns were conducted at Oak Ridge National Laboratory. The goal was to quantify the neutron signatures of samples of uranium oxide containing uranium 233 and uranium-235. This report presents the neutron multiplicity data obtained using the large volume active well coincidence counter (LV-AWCC).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1998

Long-Term Global Morphology of Gravity Wave Activity Using UARS Data

This is the first quarter's report on research to extract global gravity-wave data from satellite data and to model those observations synoptically. Preliminary analysis of global maps of extracted middle atmospheric temperature variance from the CRISTA instrument is presented, which appear to contain gravity-wave information. Corresponding simulations of global gravity-wave and mountain-wave activity during this mission period are described using global ray-tracing and mountain-wave models, and interesting similarities among simulated data and CRISTA data are noted. Climatological simulations of mesospheric gravity-wave activity using the HWM-03 wind-temperature climatology are also reported, for comparison with UARS MLS data. Preparatory work on modeling of gravity wave observations from space-based platforms and subsequent interpretation of the MLS gravity-wave product are also described. Preliminary interpretation and relation to the research objectives are provided, and further action for the next quarter's research is recommended.

Eckermann, Stephen D.↗
DOE OSTI2021

Assessment of Modeling and Nuclear Data Needs for Active Neutron Interrogation

This document is the primary deliverable for a scoping study proposed to DOE National Laboratory Announcement Number LAB 19-2114 in the NNSA research area. The study supports user applications employing active neutron interrogation by providing a science plan to improve the modeling capability and the nuclear data that radiation transport codes use. Users rely on the accuracy of the elastic scattering and non-elastic cross-sections spanning thermal energies to 14 MeV (and higher in some cases) for modeling the neutron transport through complex geometries of materials potentially composed of many elements. While the elastic scattering cross-section data are accepted for all commonly occurring elements, the non-elastic cross-section data and the associated emission data include reaction channels that require attention. The study focused on the non-elastic reactions that emit secondary, also known as prompt, gammas with the premise that many users would benefit from improved modeling of these reactions. Many users develop material assay technologies based upon gamma signatures from radiative capture, inelastic scattering, and reactions on low-Z isotopes emitting multiple particles, so the nuclear data gaps, modeling deficiencies, and recommendations for addressing the shortfalls were assessed for these reactions. Fission gammas were excluded from this study because there are other efforts underway to address known shortfalls. Follow-on efforts that successfully execute the recommendations will tangibly improve to the ability to model gamma signatures and backgrounds for user applications, such as controlled substance detection, oil-well logging, and space exploration.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Integration of seismic-pressure-petrophysics inversion of continuous active-seismic monitoring data for monitoring and quantifying CO 2 plume (Final Report)

The overall objective of this project is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring dataset capable of providing real-time monitoring of CO 2 plume during geologic carbon sequestration (GCS). The three specific developments include: (a) the methodologies for fast seismic full waveform inversion of continuous active source seismic monitoring, (CASSM) datasets for simultaneously estimating velocity and attenuation, and with data assimilation; (b) joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO 2 saturation models; (c) the methods using multiple datasets including (Crainfield and Frio-II borehole) synthetic, laboratory, and field CASSM datasets. The outcomes of jSPPI include (a) a workflow for processing CASSM data, (b) Bayesian inversion algorithms using CASSM data and pressure response data, and (c) integration with data assimilation algorithms for continuously updating site-specific models used for prediction and reservoir management. The validation of joint FWI will be conducted using synthetic models based on the Cranfield and Frio experiments as well as field CASSM datasets collected as part of the Frio-II pilot injection. To quantify and map the mass and distribution of CO 2 (saturation), we will jointly invert velocity and attenuation measurements from the FWI with a Bayesian approach using a rock physics model for attenuation (e.g., White’s attenuation model with two selected patch sizes (White, 1976; Dutta and Seriff, 1979)). The Bayesian inversion will be applied to each time step in the CASSM survey in an updating scheme, which integrates with an ensemble of reservoir simulations at each step. A more complete experimental validation dataset will be collected as part of a mesoscale (2-3 m) gas-CO 2 injection experiment utilizing a higher frequency version of the CASSM system developed for laboratory studies; the integrated inversion will be demonstrated using this dataset which will provide both a dense geometry as well as more precise secondary confirmation measurements (e.g. saturation) typically not available in the field. The resulting real-time map of CO 2 saturation is able to provide a deeper scientific understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of CO 2 leakage hazards.

25 ENERGY STORAGE↗