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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The Nevada Play Fairway Project — Phase II: Initial Search for New Viable Geothermal Systems in the Great Basin Region, Western USA

Estimates suggest that the Great Basin region is capable of producing much greater amounts of geothermal energy than the current ~600 MW from ~24 power plants. Because most of the geothermal resources in this region are blind, it is imperative that the favorable characteristics for geothermal activity be synthesized and methodologies developed to discover new robust systems. Nine geologic, geochemical, and geophysical parameters were synthesized to produce a new detailed geothermal play fairway map of a large transect across the Great Basin region (96,000 km2) from west-central to eastern Nevada. These parameters were grouped into subsets to delineate rankings for local permeability, regional permeability, and heat, which collectively defined geothermal play fairways (i.e., most likely locations for significant geothermal fluid flow). The primary objective of this work was to reduce the risks in geothermal exploration and thus facilitate discovery of commercial-grade, blind geothermal fields. Two dozen highly prospective areas, including both known systems and previously undiscovered potential blind systems, have been identified across the region for further analysis, of which several will be selected for detailed studies. Multiple techniques, including detailed geologic mapping, shallow temperature surveys, detailed gravity surveys, LiDAR, geochemical studies, seismic reflection analysis, and 3D modeling, are being employed in the detailed studies. Initial work on the detailed studies has begun and will proceed over the next year.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

A Lyapunov Function Based Remedial Action Screening Tool Using Real-Time Data

This report summarizes the outcome of a research project that comprised the development of a Lyapunov function based remedial action screening tool using real-time data (L-RAS). The L-RAS is an advanced computational tool that is intended to assist system operators in making real-time redispatch decisions to preserve power grid stability. The tool relies on screening contingencies using a homotopy method based on Lyapunov functions to avoid, to the extent possible, the use of time domain simulations. This enables transient stability evaluation at real-time speed without the use of massively parallel computational resources. The project combined the following components. 1. Development of a methodology for contingency screening using a homotopy method based on Lyapunov functions and real-time data. 2. Development of a methodology for recommending remedial actions based on the screening results. 3. Development of a visualization and operator interaction interface. 4. Testing of screening tool, validation of control actions, and demonstration of project outcomes on a representative real system simulated on a Real-Time Digital Simulator (RTDS) cluster. The project was led by Michigan State University (MSU), where the theoretical models including homotopy-based screening, trajectory correction using real-time data, and remedial action were developed and implemented in the form of research-grade software. Los Alamos National Laboratory (LANL) contributed to the development of energy margin sensitivity dynamics, which constituted a part of the remedial action portfolio. Florida State University (FSU) and Southern California Edison (SCE) developed a model of the SCE system that was implemented on FSU's RTDS cluster to simulate real-time data that was streamed over the internet to MSU where the L-RAS tool was executed and remedial actions were communicated back to FSU to execute stabilizing controls on the simulated system. LCG Consulting developed the visualization and operator interaction interface, based on specifications provided by MSU. The project was performed from October 2012 to December 2016, at the end of which the L-RAS tool, as described above, was completed and demonstrated. The project resulted in the following innovations and contributions: (a) the L-RAS software prototype, tested on a simulated system, vetted by utility personnel, and potentially ready for wider testing and commercialization; (b) an RTDS-based test bed that can be used for future research in the field; (c) a suite of breakthrough theoretical contributions to the field of power system stability and control; and (d) a new tool for visualization of power system stability margins. While detailed descriptions of the development and implementation of the various project components have been provided in the quarterly reports, this final report provides an overview of the complete project, and is demonstrated using public domain test systems commonly used in the literature. The SCE system, and demonstrations thereon, are not included in this report due to Critical Energy Infrastructure Information (CEII) restrictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Investigation of Stress Field and Fracture Development During Shale Maturation Using Analog Rock Systems

The emergence of hydrocarbons within shale as a major recoverable resource has sparked interest in fluid transport through these tight mudstones. Recent studies suggest the importance to recovery of microfracture networks that connect localized zones with large organic content to the inorganic matrix. This paper presents a joint modeling and experimental study to examine the onset, formation, and evolution of microfracture networks as shale matures. Both the stress field and fractures are simulated and imaged. A novel laboratory-scale, phase-field fracture propagation model was developed to characterize the material failure mechanisms that play a significant role during the shale maturation process. The numerical model developed consists of coupled solid deformation, pore pressure, and fracture propagation mechanisms. Benchmark tests were conducted to validate model accuracy. Laboratory-grade gelatins with varying Young’s modulus were used as scaled-rock analogs in two dimensional Hele-Shaw cell apparatus. Yeast within the gelatin generates gas in a fashion analogous to hydrocarbon formation as shale matures. These setups allow study and visualization of host rock elastic-brittle fracture and fracture network propagation mechanisms. The experimental setup was fitted to utilize photoelasticity principles coupled with birefringence properties of gelatin to explore visually the stress field of the gelatin as the fracture network developed. Stress optics image analysis and Linear Elastic Fracture Mechanics (LEFM) principles for crack propagation were used to monitor fracture growth for each gelatin type. Observed and simulated responses suggest gas diffusion within and deformation of the gelatin matrix as predominant mechanisms for energy dissipation depending on gelatin strength. LEFM, an experimental estimation of principal stress development with fracture growth, at different stages was determined for each gelatin rheology. Here, the interplay of gas diffusion and material deformation determines the resulting frequency and pattern of fractures. Results correlate with Young’s modulus. Experimental and computed stress fields reveal that fractures resulting from internal gas generation are similar to, but not identical to, type 1 opening mode.

58 GEOSCIENCES↗
DOE OSTI2019

Managing genomic variant calling workflows with Swift/T

Bioinformatics research is frequently performed using complex workflows with multiple steps, fans, merges, and conditionals. This complexity makes management of the workflow difficult on a computer cluster, especially when running in parallel on large batches of data: hundreds or thousands of samples at a time. Scientific workflow management systems could help with that. Many are now being proposed, but is there yet the “best” workflow management system for bioinformatics? Such a system would need to satisfy numerous, sometimes conflicting requirements: from ease of use, to seamless deployment at peta- and exa-scale, and portability to the cloud. We evaluated Swift/T as a candidate for such role by implementing a primary genomic variant calling workflow in the Swift/T language, focusing on workflow management, performance and scalability issues that arise from production-grade big data genomic analyses. In the process we introduced novel features into the language, which are now part of its open repository. Additionally, we formalized a set of design criteria for quality, robust, maintainable workflows that must function at-scale in a production setting, such as a large genomic sequencing facility or a major hospital system. The use of Swift/T conveys two key advantages. (1) It operates transparently in multiple cluster scheduling environments (PBS Torque, SLURM, Cray aprun environment, etc.), thus a single workflow is trivially portable across numerous clusters. (2) The leaf functions of Swift/T permit developers to easily swap executables in and out of the workflow, which makes it easy to maintain and to request resources optimal for each stage of the pipeline. While Swift/T’s data-level parallelism eliminates the need to code parallel analysis of multiple samples, it does make debugging more difficult, as is common for implicitly parallel code. Nonetheless, the language gives users a powerful and portable way to scale up analyses in many computing architectures.

Science & Technology - Other Topics↗
DOE OSTI2023

High-throughput printing of combinatorial materials from aerosols

The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces 1 . Whereas traditional combinatorial deposition methods can generate material libraries 2,3 , these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases 4–6 . We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.

36 MATERIALS SCIENCE↗
NASA NTRS2022

In Situ Measurements of Surface Texture with Virtual Environments Support Science-Driven Human Surface Operations on the Moon and Beyond

Visualization tools enabling real-time scientific analysis are important for supporting future astronaut operations on the lunar surface. Such tools can be built into virtual environments to support scientific investigations, as well as situational awareness, real-time decision making, and efficient communication between astronauts and ground and support systems. Understanding how these tools can be optimized for science is essential for upcoming Artemis missions. In this contribution, we discuss how measurements of surface texture at multiple length scales can greatly enhance in situ science on/of the Moon, and eventually Mars, asteroids, and beyond. Roughness measurements at various wavelengths directly support objectives defined in the Artemis Science Plan, including (O1) “understanding planetary processes,” (O2) “understanding volatile cycles,” and (O3) “interpreting the impact history of the Earth-Moon system” . Key scientific analyses enabled by texture measurements at different length scales include: ● Sub-centimeter scales: Texture measurements can help constrain lava flow crystallinity, lava rheology, emplacement flow dynamics, and cooling histories (O1). Measurements of lacunarity (voids in fractal fill space) can shed light on eruptive volatile content, residence time of migrating volatiles, and near-surface volume available for micro-cold trapping of volatiles (O1, O2). ● Centimeter–meter scales: Texture measurements can be used for the differentiation of individual lava flows, the reconstruction of local stratigraphies and emplacement sequences, characterization of post-emplacement surface modification processes (O1, O3). Derived roughness (polarization) metrics can be used in the detection of water ice and characterization of ice properties (e.g., purity, grade, depth, abundance). ● Hectometer–Kilometer scales: Texture measurements can be used to differentiate major geologic surface units and surface structures (O1), constrain the presence of abundant ground ices (O2), and analyze surface modification and estimate surface age (O3). Real-time measurements of surface texture across these multiple length scales will enable efficient sample identification and scientific investigations by future astronauts. To support these investigations and the objective classification of surface texture, virtual environments employed by astronauts should be able to instantaneously convert raw data into processed data (e.g., digital terrain and elevation models) and derived metrics (e.g., RMS, std, Hurst, CPR) and perform statistical analyses (e.g., PCA, outliers, correlation matrices). Such tools are being developed and tested by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team, a node of NASA’s Solar System Exploration Research Virtual Institute (SSERVI), and are an excellent example of the powerful synergies of human and robotic ground assets critical in the return of humans to the Moon.

Ariel N. Deutsch↗
NASA NTRS2000

Marshall Space Flight Center's Education Department

Marshall Space Flight Center's Education Department is a resource for Educator, Students and Lifelong Learners. This paper will highlight the Marshall Space Flight Center's Education Department with references to other NASA Education Departments nationwide. The principal focus will be on the responsibilities of the Pre-college Education Team which is responsible for supporting K- 12 teachers highlighting how many of the NASA Pre-college Offices engage teachers and their students in better understanding NASA's inspiring missions, unique facilities, and specialized workforce to carryout these many agency-wide tasks, goals and objectives. Attendee's will learn about the Marshall Educational Alliance Teams, as well, which is responsible for using NASA's unique assets to support all types of learning. All experience and knowledge levels, all grades K-12, and teachers in these specified groupings will gain a true appreciation of what is available for them, through Marshall Space Flight Center's Education Department. An agency-wide blue directory booklet will be distributed to all attendees, for future references and related points of contact.

Henderson, Arthur J., Jr.↗
DOE OSTI2018

Continuous Silicon Consolidation and Reduction

The goal of the Department of Energy’s (DOE’s) Sunshot program is to increase the adaptability of photovoltaic (PV) solar power generation by reducing the cost of power generation. The cost of polysilicon is one of several factors affecting the costs of a solar power module. The National Renewable Energy Laboratory (NREL) assumes module manufacturing costs (all-in vertically integrated module production) of 0.63 (cents)/Wdc (2015 NREL data). If the NREL polysilicon costs are replaced by the SRI International (SRI) polysilicon costs, the module manufacturing costs are reduced to 0.58 (cents)/Wdc (2015 basis) i.e., reduction of 0.05 (cents)/Wdc. The NREL cost model (System Advisor Module, SAM) is based on $20/kg of blended polysilicon silicon cost. The Continuous Silicon Consolidation and Reduction (CoSiRC) process is estimated to produce polysilicon at 8.06 (dollars)/kg. In addition, SRI’s CoSiRC process introduces a commercially viable path to recycle and reclaim kerf loss silicon fines that would otherwise go to a landfill, thereby reducing a precious resource from going to waste. The results of this project demonstrate that SRI’s silicon production process that uses a reduction reaction can be successfully integrated with a kerf loss reclaiming process. The combined process was first demonstrated at lab scale and then fit to a bench-scale process. Leveraging the industrial expertise of the commercial partners, it is feasible to adapt industrial-scale equipment for SRI’s CoSiRC process.

14 SOLAR ENERGY↗
DOE OSTI2026

Mauka Energy FEVER Tool Dataset

Mauka Energy’s dataset, developed under the Forestry Electric Vehicle Energy Routing (FEVER) project and funded by the U.S. Department of Energy’s Small Business Innovation Research program, is a high-resolution geospatial resource designed to support energy modeling for electric log trucks in complex forestry environments. The dataset integrates detailed spatial and road network data to enable accurate simulation of vehicle performance across varied terrain. At its core, the dataset incorporates lidar-derived elevation models, road alignments, and surface classifications from Oregon State University’s McDonald-Dunn Research Forest. These data capture fine-scale variations in slope, curvature, and surface conditions across forest road systems, allowing for vehicle-level analysis of energy consumption and recovery. The dataset also includes data collected on the surrounding public and private road networks in Benton County, Oregon, used in real-world haul routes. These connecting segments provide critical context for modeling transitions between forest operations and regional transportation infrastructure, incorporating attributes such as grade profiles, elevation change, and speed constraints. This combined dataset underpins the development of Mauka Energy’s rolldown tool, which quantifies energy use and regenerative braking potential on downhill and variable-grade segments. By leveraging high-resolution terrain and road data, the FEVER project enables more accurate assessment of electric vehicle feasibility and performance in forestry applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

An FPGA-Based Neuromorphic Processor with All-to-All Connectivity

Neuromorphic computing is a promising paradigm for future energy-efficient computing. At present, however, it is in its nascent stages—most hardware implementations are research-grade, commercial products are not available, and the software tools are not production-ready. The lack of hardware and software tools makes neuromorphic computing inaccessible to researchers around the globe. To this extent, we intend to build a low-cost, open-source, FPGA-based digital neuromorphic processor that can be used by researchers worldwide. In this paper, we present a preliminary implementation of the processor on a Xilinx Artix-7 FPGA using SystemVerilog. Our implementation supports the integrate-and-fire neuron with two parameters each for neurons and synapses. It also features all-to-all connectivity among neurons on the hardware. We test our implementation on four cases: bars and stripes datasets, shortest path algorithm, logic gates, and 8-3 encoder. We also perform a scalability study to understand the resource utilization of the FPGA as the number of all-to-all connected neurons increases. With our implementation, the Artix- 7 supports 65 neurons with all-to-all connectivity. Moreover, all the test cases mentioned above achieve 100% accuracy.

Maheshwari, Disha↗
NASA NTRS2012

Portable Intravenous Fluid Production Device for Ground Use

There are several medical conditions that require intravenous (IV) fluids. Limitations of mass, volume, storage space, shelf-life, transportation, and local resources can restrict the availability of such important fluids. These limitations are expected in long-duration space exploration missions and in remote or austere environments on Earth. Current IV fluid production requires large factory-based processes. Easy, portable, on-site production of IV fluids can eliminate these limitations. Based on experience gained in developing a device for spaceflight, a ground-use device was developed. This design uses regular drinking water that is pumped through two filters to produce, in minutes, sterile, ultrapure water that meets the stringent quality standards of the United States Pharmacopeia for Water for Injection (Total Bacteria, Conductivity, Endotoxins, Total Organic Carbon). The device weighs 2.2 lb (1 kg) and is 10 in. long, 5 in. wide, and 3 in. high (.25, 13, and 7.5 cm, respectively) in its storage configuration. This handheld device produces one liter of medical-grade water in 21 minutes. Total production capacity for this innovation is expected to be in the hundreds of liters.

Scarpa, Philip J.↗
DOE OSTI2023

Field surveying data of low-cost networked flood sensors in southeast Texas

Floods are common natural disasters worldwide and pose substantial risks to life, property, food production, and natural resources. Effective measures for flood mitigation and warning are essential. Southeast Texas is still at significant risk of flooding, and Lamar University is assisting the region with asset management of a flood sensor network for flooding events. This network provides real-time water stage information. Lamar University developed a survey program to measure elevation and coordinates at each sensor site location to make this data more useful for flood monitoring and mapping. This paper overviews the measurement of the elevation and coordinates of 74 networked flood sensors and various flood stage thresholds at critical points that flood decision-makers can use for reference at each site. In the first phase of this program, these sensors were deployed throughout a 7-county region spanning nearly 6,000 square miles in Southeast Texas. The latitude and longitude of the sensors and their elevations were determined using survey-grade Global Navigation Satellite System (GNSS) technology. Various Continually Operating Reference Stations (CORS) were utilized for post-processing to achieve sub-inch resolution. The flood stage thresholds, water level sensors elevation, and the elevations and positions of other critical surrounding points are viewable to the public through two online repositories and a web-based sensor management dashboard. The data is used to aid with decisions related to road closures or modeling efforts by mitigation decision-makers, emergency managers, and the public, including the Texas Department of Transportation, Houston Transtar, the National Weather Service, and the Sabine River Authority of Texas (SRA).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Science Communication versus Science Education: The Graduate Student Scientist as a K-12 Classroom Resource

Science literacy is a major goal of science educational reform (NRC, 1996; AAAS, 1998; NCLB Act, 2001). Some believe that teaching science only requires pedagogical content knowledge (PCK). Others believe doing science requires knowledge of the methodologies of scientific inquiry (NRC, 1996). With these two mindsets, the challenge for science educators is to create models that bring the two together. The common ground between those who teach science and those who do science is science communication, an interactive process that galvanizes dialogue among scientists, teachers, and learners in a rich ambience of mutual respect and a common, inclusive language of discourse . The dialogue between science and non-science is reflected in the polarization that separates those who do science and those who teach science, especially as it plays out everyday in the science classroom. You may be thinking, why is this important? It is vital because, although not all science learners become scientists, all K-12 students are expected to acquire science literacy, especially with the implementation of the No Child Left Behind Act of 2001 (NCLB). Students are expected to acquire the ability to follow the discourse of science as well as connect the world of science to the context of their everyday life if they plan on moving to the next grade level, and in some states, to graduate from high school. This paper posits that science communication is highly effective in providing the missing link for K-12 students cognition in science and their attainment of science literacy. This paper will focus on the "Science For Our Schools" (SFOS) model implemented at California State Univetsity, Los Angeles (CSULA) as a project of the National Science Foundation s GK-12 program, (NSF 2001) which has been a huge success in bridging the gap between those who "know" science and those who "teach" science. The SFOS model makes clear the distinctions that identify science, science communication, science education, and science literacy in the midst of science learning by bringing together graduate student scientists and science teachers to engage students in the two world s dialogue in the midst of the school science classroom. The graduate student scientists and the science teachers worked as a team throughout the school year and became effective science Communicators as they narrowed the gulf between the two worlds. 1

communications↗
DOE OSTI2018

Compositionally Graded Alloy Quantum Dot Phosphors for Solid State Lighting. Final Report

To push the boundaries of efficiency and cost in solid state lighting (SSL), narrow band red emitting down conversion phosphors must be improved. These materials are critical to both the color rendering ability and optical output of phosphor converted light emitting diodes (LEDs). Improvements in these performance parameters will have a significant impact on the adoption of SSL in retail, office, and home lighting applications. Quantum Dots (QDs) are widely acknowledged as a cost-effective front-runner among developing downconverting technologies because they emit narrow band luminescence that is tunable across the visible spectrum. Current syntheses of quantum dots, however, utilize expensive and toxic reagents and often involve several time-intensive purification steps. To address this, we have introduced a novel, cost-effective synthetic scheme, whereby the final quantum dot structures can be accessed with fewer synthetic steps using a library of inexpensive, easily-synthesized precursors. With the help of automated high throughput synthesis robotics, Columbia, LBNL, and OSRAM have optimized red and amber CdS/CdSe/CdS QD architectures for SSL. QDs with improved shelling layers have been identified that meet the industry state of the art performance on chip under high humidity accelerated aging tests. This is remarkable considering the time frame of this project compared to the time and resources allocated for the development of the industrial standard. Furthermore, although particle stability to optical charging is often stressed in improving QLED performance, we have identified effective ZnS particle over-coating as the most important factor determining particle survivability and device performance in down-converting LEDs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-purity electrolytic lithium obtained from low-purity sources using solid electrolyte

Lithium (Li) is an important resource for the sustainability of socioeconomic systems given its wide use in various industrial applications. The industrial production of Li metals relies on the electrolysis of a mixture consisting of high-purity lithium chloride (LiCl) and potassium chloride. However, the purification of LiCl is expensive and unsustainable, requiring a substantial amount of energy and the use of noxious chemical reagents, so that producing high-purity Li efficiently and sustainably is a challenge. In this paper we report a new method of producing high-purity electrolytic Li from low-purity LiCl using solid-state electrolyte. Taking advantage of the high Li-ion selectivity of the solid electrolyte, we directly obtained high-purity metallic Li through the electrolysis of low-purity LiCl. Our new method provides two important advantages over conventional methods: (1) the cost of producing high-purity Li is reduced by using low-purity LiCl from low-grade brine, and the simpler purification process reduces the use of energy and chemical reagents; and (2) the operating temperature of the electrolytic process decreases from 400 °C to 240 °C, leading to an additional reduction in energy use.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor

Neuromorphic processors have garnered considerable interest in recent years for their potential in enabling energy-efficient and high-speed computing. The Locally Competative Algorithm (LCA) has been utilized for power efficient sparse coding on neuromophic processors, including the first Loihi processor \cite{appletospikes, loihi1}. With the Loihi 2 processor enabling custom neuron models and graded spike communication, more complex implementations of LCA are possible \cite{loihi2}. We present a new implementation of LCA designed for the Loihi 2 processor and perform an initial set of benchmarks comparing it to LCA on CPU and GPU devices. In these experiments LCA on Loihi 2 is faster and orders of magnitude more efficient, while maintaining similar reconstruction quality. We find this performance improvement increases as the LCA parameters are tuned towards greater representation sparsity. Our study highlights the potential of neuromorphic processors, particularly Loihi 2, in enabling intelligent,autonomous, real-time processing on small robots, satellite where there are strict SWaP (small, lightweighr, and low-power) requirement. By demonstrating the superior performance of LCA on Loihi 2 compared to conventional computing device, our study suggests that Loihi 2 could be a valuable tool in advancing these types of applications. Overall, our study highlights the potential of neuromorphic processors for efficient and accurate data processing on resource-constrained devices.

Parpart, Gavin G.↗
DOE OSTI2021

Model America: Data and Models for every U.S. Building

The 5-year goal of the “Model America” concept was to generate a model of every building in the United States. This data repository delivers on that goal with "Model America v1". Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM). There were 125,715,609 buildings detected in the United States. Of this number, 122,146,671 (97.2%) buildings resulted in a successful generation and simulation of a building energy model. This dataset includes the full 125 million buildings. Future updates may include additional buildings, data improvements, or other algorithmic model enhancements in "Model America v2". This dataset contains OSM and IDF zip files for every U.S. county. Each zip file contains the generated buildings from that county. The .csv input data contains the following data fields: 1. ID - the Unique Building Identifier (UBID), generated using the Pacific Northwest National Laboratory (PNNL) BuildingID framework 2. Centroid - building center location in latitude/longitude (from Footprint2D) 3. Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) 4. State_abbr - state name 5. Area - estimate of total conditioned floor area (ft2) 6. Area2D - footprint area (ft2) 7. Height - building height (ft) 8. NumFloors - number of floors (above-grade) 9. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) 10. CZ - ASHRAE Climate Zone designation 11. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards 12. Standard - building vintage This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA). Update (September 23, 2025): We corrected the ID field in all state-level.csv input files to ensure one-to-one consistency with the corresponding .osm and .idf output files. The schema and file structure are unchanged; only the values in the ID column were modified. No files were added or removed, and the .zip bundles (containing .osm / .idf) are unchanged. The corrected .csv inputs were re-extracted in March 2025 from the original data generated ~ 2021 (Theta supercomputer runs), and published here to align input IDs with model outputs. Update (September 6, 2026): The Model America dataset was updated to replace the previous building ID field with the Unique Building Identifier (UBID), using the Pacific Northwest National Laboratory (PNNL) BuildingID framework. UBIDs provide standardized, location-based identifiers for individual building footprints and improve interoperability with other building and geospatial datasets. The data files containing the previous building identifiers were updated to include UBIDs. This update standardizes building identification; the underlying Model America building characteristics and energy simulation results were not recomputed as part of this update.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Towards a Circular Economy for PET Bottles in the US

The United States generates the most plastic waste of any country. Along with that GHG emissions from the global plastic economy are expected to increase to 15% of the global carbon budget by 2050. It is imperative that plastic recycling is made a reality to reduce both plastic pollution in the environment and GHG emissions. A portfolio of end-of-life strategies must be implemented to minimize environmental impacts and retain valuable plastic material, but it is challenging to compare options that generate products with different utility and lifetime. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. The novel analysis framework, Plastic Parallel Pathways Platform (4P) has been equipped with consequential life cycle assessment, techno-economic analysis, and a plastic circularity indicator to estimate the greenhouse gas (GHG) emissions, circularity, and cost of polyethylene terephthalate (PET) down-cycling to lower-quality resin, closed-loop recycling to food-grade PET bottles, up-cycling to fiber-reinforced plastic (FRP), and conversion to non-plastic products (electricity, oil) on a United States economy-wide basis. Integrating system dynamics into this robust plastics model that already incorporates techno-economics, circularity, and environmental impacts will enable identification of key bottlenecks between manufacturers, waste sorters, and reclaimers that currently prevent rapid decarbonization of the plastics economy. System dynamics (SD) explore the evolution of activities and technologies based on changed macro parameters such as plastic demand and supply, market shifts, and cross-sectoral interactions. This project particularly aims to explore the interplay between, waste collection, plastic waste sorting, recycling, and manufacturing, as well as the effect of plastic bale quality and plastic reuse initiatives on the surrounding process stages. This functionality will facilitate combinatory analysis in which a portfolio of end-of-life pathways are assessed simultaneously, with the exact makeup of that portfolio affected by parameters such as technology scales, resource constraints, and waste mitigation efforts. Integrating SD with the 4P framework enables analyzing the effect of increased revenue and reinvestment into improving process efficiencies, sorting and collection quantities. Through that, market effects of increased recycled resin availability can be studied for the plastics systems model for the US. The results will help identify technical or economic bottlenecks that currently limit efforts to decarbonize the U.S. plastics economy.

circular economy↗