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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Emerging Pathways to Upgrade the US Housing Stock: A Review of the Home Energy Upgrade Literature

The residential buildings sector is responsible for about 20% of total US energy use. In order to achieve climate goals, we need ways to reduce carbon emissions and energy use in this sector. In addition, resiliency, electric grid stability, emergency survivability and other energy and building-related issues are becoming increasingly important challenges. New homes in most of the US meet various energy codes and are reasonably energy efficient. However, the vast majority of energy use is from existing homes that were not required to conform to energy performance requirements. It is becoming imperative to reach as many of these existing homes as possible and find ways to improve their energy-related performance. This must be done in such a way that it meets the needs and desires of homeowners and building occupants, as well as those of the contractors and design professionals engaged in doing the upgrades themselves. Energy retrofits of homes started in the 1970’s in response to the energy crisis, however, these retrofits were very limited in scope and relatively few homes were upgraded. Those homes that have been upgraded generally still have much scope for improvement. A huge effort is needed to get to scale to address the energy use in housing. The target population is effectively every home in the country, whether a large suburban single-family home, or a small downtown apartment. In order to provide a framework for analysis and the basis for plans to get to large-scale retrofits of homes, this literature review summarizes the state-of-the art in the US buildings industry. It identifies where more research, engineering, or technology is needed, as well as relevant industry trends, such as electrification, one-stop shop program design and others. It also examines other key topics, such as availability of financing, minimizing household disruption, and engaging home owners and occupants. This literature review builds on a similar review from several years ago (Less and Walker, 2014). The current review focuses on efforts in the intervening years. This literature review is part of a larger DOE study of deep energy upgrades that includes industry surveys and development of cost-stack analyses. For this review, we gathered data not just from the published literature, but also from practitioners in conjunction with other aspects of the larger DOE study. In some cases, we refer to comments from specific individuals or companies, or refer to specific products by name. This is not intended as an endorsement, but rather to provide clarity on sources of information and examples of relevant technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Data, Photographs, Videos, and Information for the Niwot Ridge Subalpine Forest (US-NR1) AmeriFlux site

This data package contains data and information about the operation of the Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1) between Nov 1998 to the present (2020). This data archive supplements the primary 30-min data storage for the US-NR1 data (i.e., https://doi.org/10.17190/AMF/1246088) by providing the following: (i) five-minute statistics (means, variances, covariances) of all data measured by the data system between Nov 1998 and September 2020 in netCDF format, (ii) CSV data files saved within the memory of the CR23X data loggers (as well as an archive of the data logger programs), (iii) an archive of previous 30-min ASCII data versions of the US-NR1 AmeriFlux data and information related to each data release (a replica of what can be found at http://urquell.colorado.edu/data_ameriflux/), (iv) a web calendar (in HTML format) documenting activity at the site (a replica of http://urquell.colorado.edu/calendar/), (v) photos (over 15,000) and video taken at the site between years 2001 and present day (2020), and (vi) several auxiliary datasets, primary related to trees near the site, soil moisture and soil temperature, and subcanopy radiation data. The data package is setup so that the web calendar, photos, and electronic logbook can be easily accessed on a local computer using a web browser. The provided data files are in either netCDF, CSV, ASCII, or MATLAB format. To obtain a better understanding about the archive, please start by reading the PDF: README_ESS_DIVE_USNR1_readme_first.pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

American Made Challenges Battery Voucher Program Cooperative Research and Development Agreement (Cooperative Research and Development Final Report, CRADA Number CRD-21-17533)

Renewance is a Phase II winner of the U.S. Department of Energy Lithium-ion Battery Recycling Prize. The Prize is designed to incentivize American entrepreneurs to develop and demonstrate processes that, when scaled, have the potential to profitably capture 90% of all discarded or spent lithium-based batteries (LIB) in the Unites States for eventual recovery of key materials for re-introductions into the U.S. supply chain. The objective of this work is to enable a more efficient evaluation of battery sources for second life applications prior to ultimately being recycled, through evaluation of chemistry characteristics, projected battery lifetime, and application history. This work will develop the capability to identify groups of batteries that may be useful for second life and reduce the cost of end-of-life (EOL) LIB evaluation and repurposing. To meet the objective, NREL will use existing and new data to create a refined algorithm that could be used to evaluate batches of batteries for potential reuse based on manufacturing date and historical use characteristics. Based on current battery market prices and compiled literature data, a starting-point estimate of the market value of the batteries for reuse based on expected lifetime will be included in the algorithm. With the projected surge in LIB demand, battery second life is a new area ripe for development and investment from companies like Renewance. With so few large format batteries reaching EOL to date, this is a new market with a variety of areas for optimization and adding value. This work with Renewance is an example of how existing expertise in battery degradation at NREL can be used to reduce the cost of shifting a battery into a second life application. With these cost reductions, this work is also facilitating the development of a battery circular economy in the United States. A robust circular economy can maximize the utilization of critical metals demanded by battery technology such as nickel and cobalt while also reducing the costs of batteries in the marketplace for the many end-uses needed for the green energy transition. The supply of these metals is limited, and we face a supply chain shortage both domestically and globally unless we can ensure they are being used to their maximum potential. This research can improve the economics of a battery circular economy to make it a more likely path for EOL batteries with critical metals. CRADA benefit to DOE, Participant, and US Taxpayer: assists laboratory in achieving programmatic scope competencies, uses the laboratory's core competencies.

25 ENERGY STORAGE↗
DOE OSTI2022

Sampling-based Sublinear Low-rank Matrix Arithmetic Framework for Dequantizing Quantum Machine Learning

We present an algorithmic framework for quantum-inspired classical algorithms on close-to-low-rank matrices, generalizing the series of results started by Tang’s breakthrough quantum-inspired algorithm for recommendation systems [STOC’19]. Motivated by quantum linear algebra algorithms and the quantum singular value transformation (SVT) framework of Gilyén et al. [STOC’19], we develop classical algorithms for SVT that run in time independent of input dimension, under suitable quantum-inspired sampling assumptions. Our results give compelling evidence that in the corresponding QRAM data structure input model, quantum SVT does not yield exponential quantum speedups. Since the quantum SVT framework generalizes essentially all known techniques for quantum linear algebra, our results, combined with sampling lemmas from previous work, suffice to generalize all prior results about dequantizing quantum machine learning algorithms. In particular, our classical SVT framework recovers and often improves the dequantization results on recommendation systems, principal component analysis, supervised clustering, support vector machines, low-rank regression, and semidefinite program solving. We also give additional dequantization results on low-rank Hamiltonian simulation and discriminant analysis. Our improvements come from identifying the key feature of the quantum-inspired input model that is at the core of all prior quantum-inspired results: ℓ 2 -norm sampling can approximate matrix products in time independent of their dimension. We reduce all our main results to this fact, making our exposition concise, self-contained, and intuitive.

Computer Science↗
DOE OSTI2026

Seeing values for LSST strategy simulations

The opsim4 operations simulation program for the LSST astronomical survey uses a database of seeing values covering the range of times to besimulated. Idescribethe creation of such a database using Dual Image Motion Monitor(DIMM)datacollected at Cerro Pachon from 2004-03-17 to 2019-10-07. In times during which the data overlap, I compare the distribution of DIMM seeing values to the seeing measured in DECamimages,takenatasite 10kmaway. Becauseinstrumentalproblemsinthe DIMMmay indicate unreliablemeasurements,cutsonimagequality(asindicatedby the measured Strehlratio)wereexplored. TheDIMMhassignificantgaps,soImodel thedata(withandwithoutcutsonStrehlratio)andgenerateartificialdatainthegaps according to the model. The model consists of a sinusoidal variation with a period of one year, an autoregressive (AR1) model for variations in mean seeing from one night to the next, and another AR1 model for variations on a 5 minute timescale. I create four databases according to thisprocedure, twobasedonDIMMdatastarting 2006-01-01 (with and without a Strehl ratio cut), and two starting 2009-01-01. I then run opsim simulations using each, and an otherwise identical simulation using the default seeing database, and explore the differences

Neilsen, Eric H. [Fermilab]↗
DOE OSTI2022

Enhancing HEP research in predominantly undergraduate institutions and community colleges

The long-term success of HEP lies in expanding inclusiveness beyond national labs and academic research institutions to a vast community of predominantly undergraduate institutions (PUI) and community colleges (CC). Institutions such as PUIs and CCs offer an early starting point in the pipeline that can mitigate issues of lack of diversity and underrepresented participation of different groups in HEP. However, there are many underlying systemic, structural, and cultural challenges that need to be addressed collectively. Experimental collaborations are largely populated by national labs and research-focused academic institutions (non-PUIs). The faculty at PUIs and CCs have a high teaching load that is detrimental to their research participation. In addition, there is a lack of guidance, access, and tough competition for securing research funding. The students also suffer from a lack of research infrastructure and technical equipment that can only be found at national labs and larger universities. There are existing successful efforts to enhance the HEP research experience of students and faculty members. This paper discusses ways to leverage these to provide more research opportunities and establish a sustainable national program targeting specifically the issues faced by communities at PUIs and CCs. The need for research mentoring and skill building for faculty members is also laid out. The changes discussed in this paper would make a direct impact on the current spectrum of challenges.

Bellis, Matt↗
DOE OSTI2022

Neutron Capture and Transmission Measurements of 54 Fe at the RPI LINAC [Slides]

Transmission and capture measurements provide a wholistic set of experimental data to start resonance evaluation on 54 Fe. Analysis thus far supports that changes are needed in 54 Fe evaluation. Major accomplishments include the completion of radiative capture measurements of 54 Fe and the completion of total cross section measurements of 54 Fe. Future work includes the completion of data analysis relevant to capture and transmission measurements (May 2022), complete fitting of new resonance parameters to 54 Fe data (early 2023), and completion of all required deliverables for graduation (May 2023).

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Novel Harsh Environment Materials and Fabrication Techniques for Wireless Sensor Applications (Final Report)

The overarching goal of this project is to establish a center of excellence program at the University of Maine that is focused on Harsh Environmental Materials and Fabrication Techniques for Wireless Sensor Applications. UMaine is well-positioned to build on previous successes in the areas of materials science research and sensor engineering. Since 1980, the Laboratory for Surface Science & Technology (LASST) has been a very successful interdisciplinary UMaine research center with a well-established infrastructure to investigate surfaces, interfaces, thin films, and micro/nano-fabrication. This infrastructure established through NSF, DOE, DOD, NASA, the State of Maine, and industry includes (i) a 3,500 ft2 clean room with nano/microfabrication and photolithography instrumentation, (ii) thin film synthesis, processing and characterization, (iii) surface and thin film analytical chemistry tools, and (iv) device packaging, electronic testing, wireless devices, system fabrication, and sensor test facilities. This strong foundation is the basis for a planned significant growth in R&D capacity currently underway. To that end, since the start of this project in the Fall of 2019, LASST has undergone a transition to become a new interdisciplinary center at UMaine, named the Frontier Institute for Research in Sensor Technologies (FIRST). This new focus represents a commitment and investment by UMaine that aligns with the proposed DOE-EPSCoR theme, capitalizing on the state-of-the-art instrumentation to form an energized group of faculty and students pursuing advances in sensor materials, devices, and applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

AMMT Round Robin 316H HFIR Irradiation Test Matrix and Readiness for Insertion

The Round Robin 316H HFIR-2 irradiation campaign, conducted under the Advanced Materials and Manufacturing Technologies (AMMT) Program, is designed to evaluate the variability in irradiation response of laser powder bed fusion (LPBF) stainless steel (SS)-316H across multiple national laboratories, powder heats, and processing conditions, with comparison to wrought counterparts. A total of 11 materials are intended for irradiation in the High Flux Isotope Reactor (HFIR), targeting two irradiation temperatures (400°C and 600°C) and one level of irradiation damage (2 dpa). This irradiation campaign utilizes the standardized general tensile (GENTEN) capsule design to accommodate subsized tensile specimens of these materials. Thermal analyses were performed to ensure appropriate temperature control by design and uniformity within the capsules. All the capsules for this irradiation except one have been successfully assembled, welded, and tested and are ready for HFIR insertion. The last capsule requires re-build following a failed weld. All eight capsules are intended to be inserted in HFIR cycle 517, which is scheduled to start September 8, 2026. This report summarizes the design, material selection, and readiness for insertion of the capsules.

36 MATERIALS SCIENCE↗
DOE OSTI2025

AI-Assisted Conceptual Development of a Pre-Geometric Cosmological Model - An Exercise in AI-Assisted Conceptual Framework Generation, Paper II: Local Geometry and Metric Structure

This paper develops the geometric sector of the replication-driven cosmogenesis framework introduced in Paper I. Starting from a pre-geometric spectral substrate and a minimal set of replication axioms, we show how coherent self-replicating units generate a spatial adjacency graph whose continuum limit acquires an effective Riemannian structure. The replication dynamics determines a characteristic correlation length that seeds the local metric, while overlap relations among coherent units produce an isotropic neighborhood geometry with an emergent dimensionality $d_{\rm eff}\simeq 3$ across a broad range of replication factors. As replication slows and causal order stabilizes, a limiting signal speed $c_\ast$ appears, providing the basis for the Lorentzian structure of spacetime without assuming a pre-existing light cone. We derive conditions under which the adjacency graph converges to a smooth three-dimensional manifold, describe the transition from Euclidean to Lorentzian propagation, and identify geometric invariants controlled by the replication parameters. This work establishes the geometric and causal layer of the replication cosmogenesis program, bridging the spectral axioms of Paper I to the cosmological dynamics explored in Paper III.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Unlocking Metamaterials At The Macro Scale (CRADA Final Report)

This project was part of the Cyclotron Road program, which supports scientific entrepreneurs in their efforts to commercialize novel technologies with potential to address energy, manufacturing and climate related issues. The participants' technology is a lightweight cellular material system which could be applied to a range of products and markets and offer benefits of reduced weight, cost, waste, and carbon footprint. The objective of the project was to investigate potential opportunities and de-risk technical and market barriers in pursuit of successful commercialization. This project’s purpose was to find market pathways and technical roadmaps for commercializing the lightweight cellular material technology. The main problems to overcome are the risks in both tech and market. On the technical side, performance, weight, cost and speed of manufacturing, and other scaleup problems needed to be addressed. On the market side, the challenges included finding product/market fit, developing business models and go to market strategies, and developing commercial relationships within various industries. Our approach typically started with market analysis, in order to identify potential applications where our technology could solve problems and address pain points. To do this, we performed customer discovery, interviewing hundreds of industry stakeholders along all parts of the value chain for a given product or industry. From here, we would develop technoeconomic models which combined aspects of numerical modeling for structural and mechanical performance based on criteria from customers or industry guidelines such as stiffness, strength, weight, and other physical properties. Then, this would be combined with detailed cost models to translate the engineering solution into a manufacturable, scalable product. The challenge here was to have equal or better performance at lower cost and higher speed than existing solutions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Automation of Vulnerability and Patch Management: Information Extraction, Association, and Optimization

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout the vulnerability management cycle. Security advisories provide key information about mitigation strategies, or actions that can be taken when a patch is unavailable or cannot be installed. Details of these strategies are not shared in public vulnerability databases and must be found manually. We approach this problem by designing a solution to automatically identify that information within vendor security advisories and retrieve it for operator use. We start with an approach that requires domain-specific knowledge of certain frequently-seen reference websites. Next, an approach that can work on an arbitrary website but relies on certain keywords. Finally, an approach that uses Natural Language Processing (NLP) methods and does not require specific knowledge or keywords. Each of these approaches is more general than its predecessor; we demonstrate high accuracy for all approaches Advisories also often contain details of affected products in non-standard or natural language formats. While this information can be easily understood when read by an operator, the non-standard format acts as a barrier to effective automation. We provide an approach for the first step in this process: identifying vendors in security advisories and mapping them to a standard framework for representing digital assets and software products. We evaluate five established string similarity algorithms, plus one of our own design that combines string similarity and information theory, on the task of mapping vendors to their corresponding entries in the Common Platform Enumeration (CPE) repository. Our results show that our proposed metric outperforms all others. Due to the constraints on time, finances, and personnel for organizations, Large Language Models (LLMs) may seem like attractive opportunities for security operators to speed up information gathering; however, it is still not clear whether LLMs can handle vulnerability management tasks well. To answer this question, we perform an empirical study of LLMs’ ability to provide consistent, accurate information about vulnerabilities in order to guide organizations in their adoption of LLMs. We observe poor performance for all models tested, suggesting that these models are not well-suited to the consistent retrieval of accurate vulnerability information. Finally, once vulnerabilities have been identified and any additional information has been obtained, operators must decide which remediation actions to implement based on their available resources. This already-complex problem becomes even more so when we consider that a vulnerability may have multiple avenues for remediation. We formulate this scenario as two knapsack problems and provide solutions, which we then compare against several existing strategies for vulnerability prioritization seen in real operational environments.

McClanahan, Kylie↗
DOE OSTI2023

FrESCO: Framework for Exploring Scalable Computational Oncology

The National Cancer Institute (NCI) monitors population level cancer trends as part of its Surveillance, Epidemiology, and End Results (SEER) program. This program consists of state or regional level cancer registries which collect, analyze, and annotate cancer pathology reports. From these annotated pathology reports, each individual registry aggregates cancer phenotype information from electronic health records. This data is then used to create summary statistics about cancer incidence and mortality to facilitate population health monitoring. Extracting phenotypic information from these reports is a labor intensive task, requiring specialized knowledge about the reports and cancer. Automating the information extraction process from cancer pathology reports has the potential to improve data quality by extracting information in a consistent manner across registries. It can also improve patient outcomes by reducing the time from diagnosis, enabling rapid case ascertainment for clinical trials. Here we present FrESCO, a modular deep-learning natural language processing (NLP) library initially designed for extracting pathology information from clinical text documents. This repository is not solely limited to clinical medical text, but may also be used by researchers just getting started with NLP methods and those looking for a robust solution for their classification problems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Thermal-hydraulic and Fuel Performance Scoping Studies of a Flowing Water Capsule in TREAT

The restart of the Transient Reactor Test (TREAT) facility has provided a much needed capability for integral transient testing of nuclear fuel. This testing is necessary to qualify new fuel concepts such as those developed under the Accident Tolerant Fuel (ATF) program, increasing the burnup limit of light water reactor (LWR) fuels, or a variety of other programs under the Advanced Fuels Campaign (AFC). The ATF campaign has been the main driver behind the development and implementation of a variety of capsules for TREAT experiments. The Separate-Effect Test Holder (SETH) was a dry capsule that enabled testing of ATF concepts under reactivity-initiated accident (RIA) heating conditions. Following SETH, the Static Environment Rodlet Transient Test Apparatus (SERTTA) was developed to enable RIA testing in a static water environment. In efforts to support the need for future Loss-of-Coolant Accident (LOCA) tests, the Transient Water Irradiation System for TREAT (TWIST) capsule has been developed that allows for water to drain from around the fuel rod and lower the pressure to simulate LOCA conditions. All these capsules that have been developed for LWR fuel testing all lack the capability for forced convective cooling which in some applications may limit their ability to test under prototypic conditions. A design and modeling effort has been started to modify the TWIST capsule by adding a flow tube and impeller that can create flowing coolant conditions for the fuel rod. RELAP5-3D and BISON models are being used to study the differences between RIA, LOCA, Anticipated Operational Occurrences (AOO), LWR power cycling, and other transient scenarios under flowing conditions capable in the flowing capsule and the current stagnant water capsules (SERTTA and TWIST). The scoping study will provide guidance on the needed capabilities for the flowing capsule and the limitations of the currently developed capsule for LWR testing in TREAT.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A comparative study of silver- and palladium-exchanged zeolites in propylene and nitrogen oxide adsorption and desorption for cold-start applications

Here, silver and palladium ion-exchanged BEA zeolites (Si/Al = 12.5) and silver ion-exchanged ZSM-5 zeolites (Si/Al = 15) were studied for their ability to adsorb and desorb propylene and NO under simulated diesel exhaust conditions. The adsorption experiment results demonstrated the excellent ability of bare BEA zeolites to adsorb propylene, but only a small amount of NO. The presence of H 2 O inhibited the adsorption of both C 3 H 6 and NO. Ion-exchanging BEA zeolites with Ag (1.2 and 5.1 wt.% Ag/BEA) attenuated the inhibiting effect of H 2 O on C 3 H 6 adsorption, while NO storage remained inhibited. Adsorption experiments indicated that C 3 H 6 and NO competed with each other for Pd sites with C 3 H 6 showing stronger adsorption compared to NO, whereas Ag sites preferentially adsorbed C 3 H 6 . DRIFTS data indicated the formation of nitrate, formate and acetate species on Ag and Pd, while C 3 H 6 and NO adsorption was also observed on the zeolite hydroxyl groups in the absence of H 2 O. However, the C 3 H 6 and NO adsorption on the zeolite hydroxyl groups was significantly inhibited in the presence of H 2 O. Additionally, nitrosyl, acrolein and carbonate species were formed over 1.0 wt.% Pd/BEA. The effluent analysis during the temperature-programmed desorption in the DRIFTS reactor revealed that adsorbed C 3 H 6 and NO reacted during the release to form oxidation reaction byproducts. The 1.0 wt.% Pd/BEA zeolite showed the greatest oxidation ability during desorption with the majority of stored C 3 H 6 converted to CO 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Net-Zero Carbon Microgrids

The microgrid concept has been effective in creating aggregations of distributed energy resources—generation, storage and loads—for resiliency, in the form of energy security. The success of microgrids in bringing energy security to a wide range of customers—from individual residences to commercial and industrial installations to military bases—has been exemplified during power disruptions and extended outages due to extreme weather events, cybersecurity attacks, and equipment failures. Now microgrids have an opportunity to meet the challenges of climate change and contribute to a carbon-free power delivery system. The transition to net-zero starts within microgrids themselves. In fact, today’s microgrids are largely dominated by generators using fossil fuels, natural gas and diesel, with high greenhouse gas emissions. In short, the transition to net-zero means replacing fossil fueled generators with renewable generation in microgrids. This transition is extended by including new dispatchable generation technologies that are 100% carbon-free and that offer additional advantage of a more-dependable and sustainable source of energy and power. Basically, the decarbonization of microgrids requires three elements: 1) maximizing generation from renewable energy resources, 2) management of storage and flexible loads to balance the variability and intermittency of renewable energy resources, and 3) introducing new clean power sources, including hydrogen-based generation and small modular reactors. This report affirms a need for specific focus by governmental agencies at national, regional, and local levels to establish technology, policy, and investment in this area. The intention of the Net-Zero Microgrid (NZM) Program is to inform these constituencies with cross-cutting research and tools for the reduction of GHG in microgrids – to net-zero in the near term eventually to zero in the longer term. The NZM Program is committed to achieving decarbonization for resiliency and for providing clean energy at the local or distribution level, from remote communities to underserved communities, and large industrial and military facilities. The NZM Planning and Design Platform is a core tool to be developed as an early deliverable of the NZM Program because only a fully integrated microgrid-design approach will ensure maximum carbon reduction in energy production.

13 HYDRO ENERGY↗
DOE OSTI2025

National Energy Education Development Project (NEED Project) (CRADA Final Report)

The U.S. Department of Energy Building Technologies Office (BTO) funds student competitions that introduce students to careers in the building sciences and increase public awareness around high-performance buildings to support the goal of developing, demonstrating, and accelerating the adoption of cost-effective technologies, techniques, tools, and services that enable high-performing, energy-efficient and demand-flexible residential and commercial buildings in both the new and existing buildings markets. The U.S. Department of Energy Solar Decathlon® (DOE/SD) is a flagship, high-visibility international competition started in 2002 that advances the goals of BTO by introducing students to building science careers; educating students and the public about the latest technologies and materials in high-performance buildings; encouraging student-led projects and research centered around building science; and demonstrating to the public the comfort and savings of homes that combine energy-efficient construction, home systems, appliances and innovative design with onsite renewable energy production. SD is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. Solar Decathlon is comprised of two Challenges – Design Challenge (annual) and Build Challenge (biennial). The National Renewable Energy Laboratory (NREL) provides competition management for Solar Decathlon. NREL and Participant establish this CRADA to enable the success of the overall Solar Decathlon program by managing sponsorship funds and creating a K12 education program. Participant is to act as an Education Partner to Solar Decathlon, which includes: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing K12 education program to support Solar Decathlon Competition Events in April each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Dataset Repository for Investigating Suicide Risk Using Social and Environmental Determinants of Health

Suicide is frequently modeled as a function of genetics and environment, where the latter refers to factors other than direct biological consequences, such as air quality, financial level, social connectivity, transportation and food access, and homelessness status. According to the World Health Organization, clean air, a stable climate, adequate water, sanitation and hygiene, safe chemical use, radiation protection, healthy and safe workplaces, sound agricultural practices, health-supportive cities and built environments, and a preserved natural environment are all prerequisites for good health. Understanding the relationships between these determinants and mental health outcomes requires standardized data that can be included in healthcare programs and health outcome models. There is a wealth of publicly available data on social and environmental factors provided by various US organizations that can benefit the design of health care systems and public health interventions, as well as improve our comprehension of factors that impact health. Such information would not only help improve the understanding of individual and community risk but also identify new risk factors that have not previously been therapeutically targeted, especially in terms of their impact on mental health. However, curating and standardizing such datasets is challenging because they are often recorded at numerous geographical and temporal resolutions and with varying spatial and temporal granularities. To address this challenge, we launched an endeavor in conjunction with the Veterans Health Administration to collect publicly available socioeconomic and environmental determinants of health statistics in the US. In this manuscript, we describe a social and environmental determinants of health (SEDH) datasets repository, data curation documentation, and a pipeline framework for data generation; This effort started in 2020, when we began constructing a scalable pipeline to automate the download, extraction, preparation, analysis, and production of datasets. These datasets have been made available to the VHA and may be shared upon agreement with collaborating organizations.

60 APPLIED LIFE SCIENCES↗