Results for “Data gaps” — Page 58

DOE OSTI2025

Assessing electrification readiness in U.S. single-family homes based on a nationwide survey of electrical panel capacities

Electrification of residential buildings is a key strategy for increasing the use of renewable energy sources. Central to this transition is understanding the capacity of existing electrical infrastructure—specifically electrical panels—to safely and effectively manage increased electricity demands from electrification technologies. However, comprehensive nationwide data on electrical panel capacities in U.S. single-family homes is currently lacking. To address this gap, we conducted a nationwide survey of single-family homes, collecting detailed data on electrical panel capacities, breaker slot availability, major electric and gas appliances, electrical panel models, and home characteristics such as construction year and floor area. Photographic documentation was used to verify electrical panel data and appliance information. Results show that approximately 60% of surveyed homes have electrical panels rated at ≥200 amperes (A), indicating that a significant portion of the existing housing stock can accommodate additional electric loads. However, 31% of homes possess panels rated at ≤100 A, potentially restricting their ability to adopt new electric appliances without significant upgrades. Panel capacities positively correlate with both home size and construction year, with newer and larger homes generally better suited for electrification. Homes with higher-capacity panels tend to have fewer gas appliances, reflecting a gradual shift toward electric technologies. Conversely, homes with lower-capacity panels frequently rely on multiple gas appliances, highlighting substantial electrification challenges. Additionally, approximately 3% of surveyed homes had potentially hazardous electrical panel models, emphasizing important safety considerations in the residential electrification process. Our findings underscore the need for targeted policies, financial incentives, and infrastructure investments designed specifically to address infrastructural and safety barriers, particularly in older and smaller homes, to support equitable and efficient electrification across the U.S. residential sector.

Gul, Sadia↗

NASA NTRS2004

PARAGON: A Systematic, Integrated Approach to Aerosol Observation and Modeling

Aerosols are generated and transformed by myriad processes operating across many spatial and temporal scales. Evaluation of climate models and their sensitivity to changes, such as in greenhouse gas abundances, requires quantifying natural and anthropogenic aerosol forcings and accounting for other critical factors, such as cloud feedbacks. High accuracy is required to provide sufficient sensitivity to perturbations, separate anthropogenic from natural influences, and develop confidence in inputs used to support policy decisions. Although many relevant data sources exist, the aerosol research community does not currently have the means to combine these diverse inputs into an integrated data set for maximum scientific benefit. Bridging observational gaps, adapting to evolving measurements, and establishing rigorous protocols for evaluating models are necessary, while simultaneously maintaining consistent, well understood accuracies. The Progressive Aerosol Retrieval and Assimilation Global Observing Network (PARAGON) concept represents a systematic, integrated approach to global aerosol Characterization, bringing together modern measurement and modeling techniques, geospatial statistics methodologies, and high-performance information technologies to provide the machinery necessary for achieving a comprehensive understanding of how aerosol physical, chemical, and radiative processes impact the Earth system. We outline a framework for integrating and interpreting observations and models and establishing an accurate, consistent and cohesive long-term data record.

PARAGON↗

DOE OSTI2020

Experiences with a Flexible User Research Process to Build Data Change Tools

Scientific software development processes are understood to be distinct from commercial software development practices due to uncertain and evolving states of scientific knowledge. Sustaining these software products is a recognized challenge, but under-examined is the usability and usefulness of such tools to their scientific end users. User research is a well-established set of techniques (e.g., interviews, mockups, usability tests) applied in commercial software projects to develop foundational, generative, and evaluative insights about products and the people who use them. Currently these approaches are not commonly applied and discussed in scientific software development work. The use of user research techniques in scientific environments can be challenging due to the nascent, fluid problem spaces of scientific work, varying scope of projects and their user communities, and funding/economic constraints on projects.In this paper, we reflect on our experiences undertaking a multi-method user research process in the Deduce project. The Deduce project is investigating data change to develop metrics, methods, and tools that will help scientists make decisions around data change. There is a lack of common terminology since the concept of systematically measuring and managing data change is under explored in scientific environments. To bridge this gap we conducted user research that focuses on user practices, needs, and motivations to help us design and develop metrics and tools for data change. This paper contributes reflections and the lessons we have learned from our experiences. We offer key takeaways for scientific software project teams to effectively and flexibly incorporate similar processes into their projects.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

Block distributions on the lunar surface: A comparison between measurements obtained from surface and orbital photography

Among the hazards that must be negotiated by lunar-landing spacecraft are blocks on the surface of the Moon. Unfortunately, few data exist that can be used to evaluate the threat posed by such blocks to landing spacecraft. Perhaps the best information is that obtained from Surveyor photographs, but those data do not extend to the dimensions of the large blocks that would pose the greatest hazards. Block distributions in the vicinities of the Surveyor 1, 3, 6, and 7 sites have been determined from Lunar Orbiter photography and are presented here. Only large (i.e., greater than or equal to 2.5 m) blocks are measurable in these pictures, resulting in a size gap between the Surveyor and Lunar Orbiter distributions. Nevertheless, the orbital data are self-consistent, a claim supported by the similarity in behavior between the subsets of data from the Surveyor 1, 3, and 6 sites and by the good agreement in position (if not slopes) between the data obtained from the Surveyor 3 photography and those derived from the Lunar Orbiter photographs. Confidence in the results is also justified by the well-behaved distribution of large blocks at the surveyor site. Comparisons between the Surveyor distributions and those derived from the orbital photography permit these observations: (1) in all cases but that for Surveyor 3, the density of large blocks is overestimated by extrapolation of the Surveyor-derived trends; (2) the slopes of the Surveyor-derived distributions are consistently lower than those determined for the large blocks; and (3) these apparent disagreements could be mitigated if the overall shapes of the cumulative lunar block populations were nonlinear, allowing for different slopes over different size intervals. The relatively large gaps between the Surveyor-derived and Orbiter-derived data sets, however, do not permit a determination of those shapes.

Cintala, Mark J.↗

DOE OSTI2022

Principles of the Battery Data Genome

Batteries are central to modern society. They are no longer just a convenience but a critical enabler of the transition to a resilient, low-carbon economy. Battery development capabilities are provided by communities spanning materials discovery, battery chemistry and electrochemistry, cell and pack design, scale-up, manufacturing, and deployments. Despite their relative maturity, data-science practices among these diverse groups are far behind the state of the art in other fields, which have demonstrated an ability to significantly improve innovation and economic impact. The negative consequences of the present paradigm include incremental improvements but few breakthroughs, significant manufacturing uncertainties, and cascading investment risks that collectively slow deployments. The primary roadblock to a battery-data-science renaissance is the requirement for large amounts of high-quality data, which are not available in the current fragmented ecosystem. Here, in this study, we identify gaps and propose principles that enable the solution by building a robust community of data hubs with standardized practices and flexible sharing options that will seed advanced tools spanning innovation to deployment. Precedents are offered that demonstrate that both public good and immense economic gains will arise from sharing valuable battery data. The proposed Battery Data Genome looks to broadly transform innovations and revolutionize their translation from research to societal impact.

25 ENERGY STORAGE↗

NASA NTRS1998

Induction Bonding of Prepreg Tape and Titanium Foil

Hybrid structural laminates made of titanium foil and carbon fiber reinforced polymer composite offer a potential for improved performance in aircraft structural applications. To obtain information needed for the automated fabrication of hybrid laminates, a series of bench scale tests were conducted of the magnetic induction bonding of titanium foil and thermoplastic prepreg tape. Foil and prepreg specimens were placed in the gap of a toroid magnet mounted in a bench press. Several magnet power supplies were used to study power at levels from 0.5 to 1.75 kW and frequencies from 50 to 120 kHz. Sol-gel surface-treated titanium foil, 0.0125 cm thick, and PIXA/IM7 prepreg tape were used in several lay-up configurations. Data were obtained on wedge peel bond strength, heating rate, and temperature ramp over a range of magnet power levels and frequencies at different "power-on" times for several magnet gap dimensions. These data will be utilized in assessing the potential for automated processing. Peel strengths of foil-tape bonds depended on the maximum temperature reached during heating and on the applied pressure. Maximum peel strengths were achieved at 1.25kW and 8OkHz. Induction heating of the foil appears to be capable of good bonding up to 10 plies of tape. Heat transfer calculations indicate that a 20-40 C temperature difference exists across the tape thickness during heat-up.

Messier, Bernadette C.↗

NASA NTRS1981

Near perihelion observations of Comet Halley from Shuttle orbiter

Intercept missions and the space telescope will return unique data on Comet Halley, but will leave important gaps in the observational coverage of the comet's activity, especially around the time of perihelion passage. A small package of instruments, which could be scheduled to fly on several shuttle missions, would be an effective means of extending observational coverage of Comet Halley to include the critical part of the apparition near perihelion passage. This approach would certainly be "second best" to a dedicated orbital comet observatory. However, it would be feasible in the sense that payload space appears to be available for at least two flights during the apparition, and instruments exist, or could be modified, or are being developed, which could be integrated into a package of the required size, and which would return useful physical data on the comet.

Bergstralh, J. T.↗

DOE OSTI2021

First-Principles Study on the Electronic Properties of PDPP-Based Conjugated Polymer via Density Functional Theory

In this study, we focus on computational predictions of the electronic and optical properties of a one-dimensional periodic model of a single chain of a diketopyrrolopyrrole (DPP)-based conjugated polymer (PDPP3T) as a function of electronic configuration changes due to charge injection. Here, we employ density functional theory (DFT) to explore the ground-state and excited-state electronic properties as well as optical properties influenced by charge injection. We utilize both the Heyd–Scuseria–Ernzerhof (HSE06) and Perdew–Burke–Ernzerhof (PBE) functionals to predict the band gap and compute the absorption spectrum. Our DFT results point out that utilizing the HSE06 functional in conjunction with momentum sampling over the Brillouin zone can appropriately predict the band gap and absorption spectrum in good agreement with experimental data. Moreover, we explore the influence of charge-carrier injection on the electronic configuration of the PDPP3T polymer. Our results indicate that the injection of charge carriers into the PDPP3T semiconducting polymer model greatly affects the electrical properties and ends in a low band gap and high mobility of charge carriers in PDPP3T polymers, offering the potential to tailor the material electronic performance for organic photovoltaic and optoelectronic device applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Multiband superconductivity in V 3 Si determined from studying the response to controlled disorder

The London penetration depth, λ(T), was measured in a single crystal V 3 Si. The superfluid density obtained from this measurement shows a distinct signature of two almost decoupled superconducting gaps. This alone is insufficient to distinguish between s ± and s ++ pairing states, but it can be achieved by studying the effect of a controlled non-magnetic disorder on the superconducting transition temperature, T c . For this purpose, the same V 3 Si crystal was sequentially irradiated by 2.5 MeV electrons three times, repeating the measurement between the irradiation runs. A total dose of 10 C/cm 2 (6.24 × 10 19 electrons/cm 2 ) was accumulated, for which T c has changed from 16.4 K in a pristine state to 14.7 K (9.3 %). This substantial suppression is impossible for a single isotropic gap, but also it is not large enough for a sign-changing s± pairing state. Our electronic band-structure calculations show how five bands crossing the Fermi energy can be naturally grouped to support two effective gaps, not dissimilar from the iron pnictides physics. We analyze the results using two-gap models for both, λ(T) and T c , which describe the data very well. Finally, the experimental results and theoretical analysis provide strong support for an s ++ superconductivity with two unequal gaps, Δ 1 (0) ≈ 2.53 meV and Δ 2 (0) ≈ 1.42 meV, and a very weak inter-band coupling in V 3 Si superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Leveraging computational genomics to understand the molecular basis of metal homeostasis

Genome-based data is helping to reveal the diverse strategies plants and algae use to maintain metal homeostasis. In addition to acquisition, distribution and storage of metals, acclimating to feast or famine can involve a wealth of genes that we are just now starting to understand. The fast-paced acquisition of genome-based data, however, is far outpacing our ability to experimentally characterize protein function. Computational genomic approaches are needed to fill the gap between what is known and unknown. To avoid misconstruing bioinformatically derived data, which is the root cause of the inaccurate functional annotations that plague databases, functional inferences from diverse sources and contextualization of that evidence with a robust understanding of protein family evolution is needed. Phylogenomic- and comparative-genomic-based studies can aid in the interpretation of experimental data or provide a spark for the discovery of a new function. These analyses not only lead to novel insight into a target protein's function but can generate thought-provoking insights across protein families.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Developing a Vision for Heliophysics Infrastructure: The LIKED Resource and the DIARieS Ecosystem

Heliophysics data and computational infrastracture are not equipped for 21st science, suffering from holes in the know-how to build better systems. Without a clear vision, efforts to improve the infrastructure have been incremental and incoherent. This poster presents both the vision and the technology required: an online LIbrary KnowledgE and Discovery (LIKED) resource for discovering and implementing knowledge, data, and infrastructure resources; and an online analysis ecosystem to simplify Discovery, Implementation, Analysis, Reproducibility, and Sharing (DIARieS) of scientific results and environments. The LIKED and DIARieS solutions adopt FAIR data principles and the best practices from the budding field of open science. The proposed new infrastructure components will close many of the current gaps in heliophysics’ infrastructure, such as the ability to search for data and knowledge by phenomenon across domains, and to find software and examples relevant to the desired data set (including model data). Further, these components will enable community members to more efficiently use the resources already present and improve upon the content via a community-curated and trusted library. Combining these solutions lowers the barriers to heliophysics resources for all, increasing the return on our investments. Finally, the structure behind these ideas are topic-agnostic, so they are fully extensible to other fields, leading to invaluable connections to other disciplines. Just as with the development and construction of a long-term satellite mission, we must work together as a community to build a vision of the infrastructure that will most benefit the community, and then collaborate to construct, assemble, and test all the necessary pieces individually and as a unit. Our purpose in presenting this work is to not only describe the proposed vision, but also to gather feedback from the community on this topic.

infrastructure↗

DOE OSTI2025

House Advantage or House of Cards? Stacking the Deck for Data Videos Leads to Null Results: Preprint

Videos are becoming a ubiquitous means of sharing information on social media platforms. In response, data videos - short clips combining visualization with dynamic storytelling, audio descriptions, and spatial referencing - have gained popularity for communicating data. These affordances suggest that data videos might communicate data patterns, trends, and concepts more effectively than static visualizations, enhancing comprehension. However, existing research has not systematically tested this claim. To address this gap, we conducted three controlled studies to measure comprehension differences between data videos and static visualizations. Despite leveraging visual cues and audio explanations, no data video led to significantly better comprehension than an analogous static visualization. Our results suggest data videos are not categorically better and that future research should examine the tradeoffs between their engagement benefits and costs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

What can surface wind observations tell us about interannual variation in wind energy output?

The past decade of wind power growth was supported by capacity factor improvements and associated cost reductions. But are higher capacity factors a technology success story or, as suggested by recent research, has the influence of technology been overstated by ignoring positive surface wind speed trends? The answer could influence estimates of wind energy's cost and even future deployment rates. We find that US surface wind speed observations imply a 2.6% improvement in capacity factors from 2010 to 2019. Yet newer vintages of wind plants have recorded capacity factors that are ~25% larger than plants built close to 2010. It follows that technological factors and improved site quality, not higher wind speeds, drove most of the improvement in capacity factors. Additionally, we match hundreds of meteorological stations to nearby (< 25 km) wind plants and compare annual estimated generation, based on a function of surface wind speed observations, to annual recorded generation. Researchers rely on this publicly available surface data because measurements co-located with wind plants are generally considered proprietary. Our analysis addresses a research gap: interannual variation in observed surface wind speeds is rarely compared to observed data at wind plant locations and turbine heights. We find that despite its common use for this purpose, generation estimates based on publicly available surface observational data provide a poor proxy for interannual variability in recorded wind generation. These findings suggest that caution is generally needed when researchers use surface wind speed measurements to investigate long-term wind energy trends.

17 WIND ENERGY↗

NASA NTRS1986

Satellite 'wakes' and the orbit of the Encke Gap moonlet

A general model is developed for the quasi-periodic optical depth fluctuations observed in photopolarimeter and radio occultation profiles near the Encke Gap of Saturn's rings, which may be the gravitational 'wakes' of a moonlet orbiting within the same gap. The results obtained are used to estimate the moonlet's orbit and mass from the occultation data. In view of the present treatment's neglect of particle collisions and self-gravity, the longitude is consistent with other estimates based on a photopolarimeter scan exterior to the gap. The consistency of the orbit parameters inferred from photopolarimeter, radio, and wavy edge data strongly suggests that a single, dominant moonlet orbits within the gap.

Showalter, M. R.↗

NASA NTRS2018

Medical Data Architecture Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.

medical data architecture↗

NASA NTRS2018

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.

medical data architecture↗

NASA NTRS2019

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗

NASA NTRS2020

Medical Data Architecture Platform and Recommended Requirements for a Medical Data System for Exploration Missions

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically- relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions. In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗