Chloride-based Wireline Tool for Measuring Feed Zone Inflow in Enhanced Geothermal Systems (EGS) Wells: Experimental, Numerical, and Data-driven Updates
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Sausan, Sarah↗
SEARCH · Engineering Papers
Results for “data enhancement”
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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(abstract) Science-Project Interaction in the Low-Cost Mission
Large, complex, and highly optimized missions have performed most of the preliminary reconnaisance of the solar system. As a result we have now mapped significant fractions of its total surface (or surface-equivalent) area. Now, however, scientific exploration of the solar system is undergoing a major change in scale, and existing missions find it necessary to limit costs while fulfilling existing goals. In the future, NASA's Discovery program will continue the reconnaisance, exploration, and diagnostic phases of planetary research using lower cost missions, which will include lower cost mission operations systems (MOS). Historically, one of the more expensive functions of MOS has been its interaction with the science community. Traditional MOS elements that this interaction have embraced include mission planning, science (and engineering) event conflict resolution, sequence optimization and integration, data production (e.g., assembly, enhancement, quality assurance, documentation, archive), and other science support services. In the past, the payoff from these efforts has been that use of mission resources has been highly optimized, constraining resources have been generally completely consumed, and data products have been accurate and well documented. But because these functions are expensive we are now challenged to reduce their cost while preserving the benefits. In this paper, we will consider ways of revising the traditional MOS approach that might save project resources while retaining a high degree of service to the Projects' customers. Pre-launch, science interaction can be made simplier by limiting numbers of instruments and by providing greater redundancy in mission plans. Post launch, possibilities include prioritizing data collection into a few categories, easing requirements on real-time of quick-look data delivery, and closer integration of scientists into the mission operation.
mission operation science community interaction co↗
A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems
We report faults in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings result in significant energy waste in building operation. With fast-growing sensing data availability and advancement in computing, computational modeling has demonstrated strong capability to detect and diagnose HVAC system faults, hence, ensuring efficient building operation. This paper comprehensively reviews the state-of-the-art computing-based fault detection and diagnosis (FDD) for HVAC systems. Overall, the reviewed computing-based FDD methods are classified as two major approaches: knowledge-based and data-driven approaches. We then identify multiple important topics, including data availability, training data size, data quality, approach generality, capability, interpretability, and required modeling efforts, along with corresponding metrics to summarize the most updated FDD development. Generally, the knowledge-based approaches are further divided as physics-based modeling, Diagnostic Bayesian Network, and performance indicator-based methods while data-driven approaches include supervised learning, unsupervised learning, and regression and statistics-based methods. State-of-the-art FDD development, remaining challenges, and future research directions are further discussed to push forward FDD in practice. Availability of fault data, capability of existing methods to deal with complex fault situations (such as simultaneous faults), modeling interpretability for data-driven methods, and required engineering efforts for physics-based methods are identified as remaining challenges in FDD development. Improving modeling fidelity and reducing modeling efforts are essential for applying physics-based methods in real buildings. Meanwhile, addressing fault data availability, increasing algorithm adaptability, and handling multiple faults are essential to further enhance the applicability of data-driven FDD approaches.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Application of LANDSAT-2 data to the implementation and enforcement of the Pennsylvania Surface Mining Conservation and Reclamation Act
The author has identified the following significant results. Evaluation of LANDSAT imagery indicates severe limitations in its utility for surface mine land studies. Image stripping resulting from unequal detector response on satellite degrades the image quality to the extent that images of scales larger than 1:125,000 are of limited value for manual interpretation. Computer processing of LANDSAT data to improve image quality is essential; the removal of scanline stripping and enhancement of mine land reflectance data combined with color composite printing permits useful photographic enlargements to approximately 1:60,000.
Russell, O. R.↗
Application of digital terrain data to quantify and reduce the topographic effect on Landsat data
Landsat multispectral scanner (MSS) data are integrated with 30 m US Geological Survey digital terrain data to quantify and reduce topographic effects on imagery of a forested mountain ridge in central Pennsylvania. Spectral band ratioing slightly decreased variation of Landsat data for 50% of the transects and could not eliminate direct-light topographic effects. A Lambertian model increased topographic effect, and a modified Lambertian model decreased variation produced by the original model, but gave higher variances than found in the raw Landsat data. A non-Lambertian model, however, decreased variation by 86%, reducing topographic effects. The study demonstrated that high quality digital terrain data can be used to develop and test improved radiative transfer models, and enhance the utility of MSS data.
Justice, C. O.↗
Effective use of remote sensing products in litigation
A boiled-down version of major legal principles affecting the admissibility of data and products from remote sensing devices is presented. It is suggested that enhancements or classifications of digital data (from scanning devices or from digitized aerial photography) be proffered as evidence in a fashion similar to the manner in which maps from photogrammetric techniques are introduced as evidence. Every effort should be made to illucidate the processes by which digital data are analytically treated or manipulated. Remote sensing expert witnesses should be practiced in providing concise and clear explanations of both data and methods. Special emphasis should be placed on being prepared to provide a detailed accounting of steps taken to calibrate and verify spectral characteristics with ground truth.
Jaynes, R. A.↗
Voyager-Uranus at our doorstep
Following the encounter of Voyager 2 with Saturn and the subsequent approach, in January 1986, to the planet Uranus, the NASA Deep Space Network (DSN) undertook a reshaping of Voyager's end-to-end data system to provide communication to earth with a sufficient number of images for Uranus characterization. In-flight evolution of the spacecraft and ground system is described, with particular attention given to the aspects of target motion compensation, line enhancement, arraying, and encoding data streams. Solutions to the on-board problems encountered during the flight are presented. Voyager and its principal elements, an actuator for the scan platform, and the coding diagram are among the illustrations included.
Laeser, R. P.↗
Transformation of the NASA Life Sciences Portal to a FAIR Data Point
The FAIR principles emphasize optimizing metadata, the vast majority of which are textual in nature, and often organized into attribute name-value pairs. This uniformity has led to the development of guidelines and best practices for providing programmatic access to scientific data through their metadata, yielding the first iteration of the FAIR Data Point Specifications (FDPS). A key feature of the FDPS is its support for automated agents seeking and fetching data without first needing to learn a plethora of different application programming interfaces. These software agents can interrogate metadata catalogs that adhere to FDPS in a uniform manner because each catalog describes itself and its metadata schema consistently. This approach enhances the sustainability of data retrieval support, allowing systems to refine and update their metadata schemas as needed and without requiring data-seeking software agents to change how they interrogate FDPS catalogs. An essential aspect of the FDPS is the standardization of data catalog semantics, which formalizes concepts such as “metadata” and “metadata service” and links them to other concepts specifications including the Data Catalog Vocabulary (DCAT), a W3C standard that is also the basis of NASA-STD-2831 “Metadata Standard for Data Discoverability,” authored by NASA’s Office of the Chief Information Officer. The FDPS references DCAT (version 2) elements which focus on the distribution of datasets and support the goal of stream-lined catalog integration across repositories for improved data discovery. Additionally, the FDPS also prescribe the use of Linked Data Platform elements for data catalog-metadata record containment descriptions, allowing users to ascertain which data and metadata belong to which catalogs. NASA’s Life Sciences Portal is implementing the FDPS while formalizing its metadata schema to support the accelerated synthesis of knowledge from space life sciences investigations.
platform↗
Quantum Time Dynamics Mediated by the Yang–Baxter Equation and Artificial Neural Networks
Quantum computing shows great potential, but errors pose a significant challenge. This study explores new strategies for mitigating quantum errors using artificial neural networks (ANNs) and the Yang–Baxter equation (YBE). Unlike traditional error mitigation methods, which are computationally intensive, we investigate artificial error mitigation. We developed a novel method that combines ANNs for noise mitigation combined with the YBE to generate noisy data. This approach effectively reduces noise in quantum simulations, enhancing the accuracy of the results. The YBE rigorously preserves quantum correlations and symmetries in spin chain simulations in certain classes of integrable lattice models, enabling effective compression of quantum circuits while retaining linear scalability with the number of qubits. This compression facilitates both full and partial implementations, allowing the generation of noisy quantum data on hardware alongside noiseless simulations using classical platforms. By introducing controlled noise through the YBE, we enhance the data set for error mitigation. We train an ANN model on partial data from quantum simulations, demonstrating its effectiveness in mitigating errors in time-evolving quantum states, providing a scalable framework to enhance quantum computation fidelity, particularly in noisy intermediate-scale quantum (NISQ) systems. We demonstrate the efficacy of this approach by performing quantum time dynamics simulations using the Heisenberg XY Hamiltonian on real quantum devices.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Central America Disasters: Using Earth Observations to Map Flooding for Disaster Monitoring, Inform Potential Risk, and Prepare for Possible Response
In November 2020, Hurricanes Eta and Iota hit Central America within weeks of each other, causing severe flooding, landslides, and widespread damage. NASA DEVELOP partnered with Comité Regional de Recursos Hidráulicos (CRRH), Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPREDENAC), and Sistema de la Integración Centroamericana (SICA) to better understand how flooding throughout Central America has impacted and will continue to affect communities, focusing on sites in Guatemala, Honduras, El Salvador, Belize, Nicaragua, western Panama, and eastern Costa Rica from January 2015 to October 2021. The team utilized surface reflectance data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). This project also utilized backscatter data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and elevation data from the Shuttle Radar Topography Mission (SRTM). Incorporating these Earth observations in NASA SERVIR’s Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) tool run on Google Earth Engine (GEE), the team produced historical surface water maps, a case study analysis of the two hurricanes, and a code tutorial. These results indicated that surface water increased in priority sites from 2015 to 2021, optical and SAR imagery detected similar flood patterns and extent after the hurricanes, and rainfall was concentrated on the east coast of the region. These products allow partners to make informed decisions around flooding preparation and disaster mitigation.
Caroline Williams↗
Coastal On-line Assessment and Synthesis Tool 2.0
COAST (Coastal On-line Assessment and Synthesis Tool) is a 3D, open-source Earth data browser developed by leveraging and enhancing previous NASA open-source tools. These tools use satellite imagery and elevation data in a way that allows any user to zoom from orbit view down into any place on Earth, and enables the user to experience Earth terrain in a visually rich 3D view. The benefits associated with taking advantage of an open-source geo-browser are that it is free, extensible, and offers a worldwide developer community that is available to provide additional development and improvement potential. What makes COAST unique is that it simplifies the process of locating and accessing data sources, and allows a user to combine them into a multi-layered and/or multi-temporal visual analytical look into possible data interrelationships and coeffectors for coastal environment phenomenology. COAST provides users with new data visual analytic capabilities. COAST has been upgraded to maximize use of open-source data access, viewing, and data manipulation software tools. The COAST 2.0 toolset has been developed to increase access to a larger realm of the most commonly implemented data formats used by the coastal science community. New and enhanced functionalities that upgrade COAST to COAST 2.0 include the development of the Temporal Visualization Tool (TVT) plug-in, the Recursive Online Remote Data-Data Mapper (RECORD-DM) utility, the Import Data Tool (IDT), and the Add Points Tool (APT). With these improvements, users can integrate their own data with other data sources, and visualize the resulting layers of different data types (such as spatial and spectral, for simultaneous visual analysis), and visualize temporal changes in areas of interest.
Brown, Richard↗
Measurements of middle-atmosphere electric fields and associated electrical conductivities
A simple antenna for measuring the vertical electric field in the 'middle atmosphere' has been flown on a number of rocket-launched parachute-borne payloads. The data from the first nine such flights, launched under a variety of geophysical conditions, are presented, along with electrical conductivities measured simultaneously. The data include indications of layered peaks of several volts per meter in the mesospheric field at high and low latitudes in situations of relatively low conductivity. During an auroral 'REP' event the electric field reversed direction in the lower stratosphere, accompanied by a substantial enhancement in conductivity. The data generally do not confirm speculations based only on the extension of the thunderstorm circuit from below or the mapping of ionospheric and magnetospheric fields from above, but seem to require, in addition, internal generation processes in the middle atmosphere.
Hale, L. C.↗
The National Aeronautics and Space Administration's Earth Science Applications Program: Exploring Partnerships to Enhance Decision Making in Public Health Practice
The National Aeronautics and Space Administration (NASA), Earth Science Enterprise is engaged in applications of NASA Earth science and remote sensing technologies for public health. Efforts are focused on establishing partnerships with those agencies and organizations that have responsibility for protecting the Nation's Health. The program's goal is the integration of NASA's advanced data and technology for enhanced decision support in the areas of disease surveillance and environmental health. A focused applications program, based on understanding partner issues and requirements, has the potential to significantly contribute to more informed decision making in public health practice. This paper intends to provide background information on NASA's investment in public health and is a call for partnership with the larger practice community.
Vann, Timi S.↗
Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing
Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.
AI/ML↗
Next generation experimental data access at NSLS-II
The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.
36 MATERIALS SCIENCE↗
A user's guide to the Mariner 9 television reduced data record
The Mariner 9 television experiment used two cameras to photograph Mars from an orbiting spacecraft. For quantitative analysis of the image data transmitted to earth, the pictures were processed by digital computer to remove camera-induced distortions. The removal process was performed by the JPL Image Processing Laboratory (IPL) using calibration data measured during prelaunch testing of the cameras. The Reduced Data Record (RDR) is the set of data which results from the distortion-removal, or decalibration, process. The principal elements of the RDR are numerical data on magnetic tape and photographic data. Numerical data are the result of correcting for geometric and photometric distortions and residual-image effects. Photographic data are reproduced on negative and positive transparency films, strip contact and enlargement prints, and microfiche positive transparency film. The photographic data consist of two versions of each TV frame created by applying two special enhancement processes to the numerical data.
Seidman, J. B.↗
Sounding rocket observation of a hot atomic oxygen geocorona
A sounding rocket measurement of the ultraviolet, atomic oxygen dayglow reveals an excess of emission compared to standard thermospheric model calculations at exospheric altitudes. We explore two explanations for this discrepancy: a breakdown of the radiative transfer model due to nonlocal thermal equilibrium (non-LTE) conditions above the exobase and a hot atomic oxygen geocorona. In particular, the effects of non-LTE on the 3P2, 1, 0 sublevel populations are modeled, and a hot O component in the upper thermosphere and lower exosphere is added to investigate the effects on the modeled emissions. For both cases, the data are reanalyzed and compared with the results using a standard LTE model. A hot O geocorona having a peak density of 10(exp 6)/cc at 550 km and a temperature of 4000 K is consistent with the data and appears to be the most reasonable explanation of the high-altitude enhanced emissions observed in the data.
Cotton, Daniel M.↗
Packaging and distributing ecological data from multisite studies
Studies of global change and other regional issues depend on ecological data collected at multiple study areas or sites. An information system model is proposed for compiling diverse data from dispersed sources so that the data are consistent, complete, and readily available. The model includes investigators who collect and analyze field measurements, science teams that synthesize data, a project information system that collates data, a data archive center that distributes data to secondary users, and a master data directory that provides broader searching opportunities. Special attention to format consistency is required, such as units of measure, spatial coordinates, dates, and notation for missing values. Often data may need to be enhanced by estimating missing values, aggregating to common temporal units, or adding other related data such as climatic and soils data. Full documentation, an efficient data distribution mechanism, and an equitable way to acknowledge the original source of data are also required.
Information Systems↗