Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Building America”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Empirical Validation of UBEM: An Assessment of Bias in Urban Building Energy Modeling for Chicago

Residential and commercial buildings currently account for 30% of total global final energy consumption. Urban-scale building energy modeling (UBEM) can enable scalable investments and unlock building improvements by quantifying energy, demand, emissions, and cost reductions of specific measures or packages for building-specific technologies in large geographic regions. While the sophistication of UBEM data sources and technologies have increased dramatically in the past decade, there remains a knowledge gap for empirical validation and sources of bias between building-specific energy models and measured data at varying geographic scales.As UBEM continues to develop, systemic analysis of accuracy, bias, and limitations of the resulting models is necessary to inform best practices and move toward standardization. These are characterized for the Automatic Building Energy Modeling (AutoBEM) software suite with an initial case study involving metered electricity consumption data from 247,188 buildings in Chicago, Illinois, USA - averaged across years 2019-2021 - compared to the following datasets: (1) the AutoBEM-generated nation-scale Model America version 2 (MAv2) data for 596,064 buildings, (2) tax assessor data for 579,829 buildings, (3) tax assessor data filled with MAv2, and (4) 102 representative dynamic archetypes. The accuracy is reported for every building type and vintage combination, along with multiple sources of bias for unique building descriptors. The AutoBEM simulation workflow produced energy consumption estimates that closely match aggregated metered electricity consumption data for different types of buildings constructed during various time periods at the city scale - with initial normalized mean bias error of 10.9%, and 1.1% after removing outliers. Contribution of statistically significant factors including building type, land use, age, and size to variance in UBEM bias is quantified.

Garg, Ankur↗
DOE OSTI2025

UrbanScaping: Community Spatial Data Visualization & Analytics

Evaluating the electrification potential of buildings through retrofitting is crucial for reducing carbon emissions and the carbon footprint of built environments. This study leverages the Automatic Building Energy Modeling (AutoBEM) software, integrating the Model America database to create an urban context-based spatial analysis platform for community engagement and development. We selected Camp Hill Borough, PA, as a case study to analyze building-specific energy performance and evaluate the electrification potential of each building by switching to different Heating, Ventilation, and Air Conditioning (HVAC) systems and measurement components. The simulation results generated by the workflow provide retrofitting suggestions to help mitigate the carbon footprint as well as energy saving statistics of buildings. Additionally, the developed web-based interface serves as a community engagement platform, allowing residents to provide feedback and further develop interactive communication protocols. The outcomes of this project offer a baseline for community electrification planning and contribute to the design of low-carbon communities.

Chowdhury, Shovan [ORNL]↗
DOE OSTI2025

Investigating Building Energy Consumption and CO2 Emission in Phoenix Using AutoBEM and Future Typical Meteorological Year (fTMY) Weather Data

This research investigates the energy performance and CO2 emissions of each building stock across the Phoenix metropolitan area using the Automatic Building Energy Modeling (AutoBEM) framework and Model America v2 (MAv2) dataset from Oak Ridge National Laboratory (ORNL). Typical Meteorological Year (TMY) and Future Typical Meteorological Year (fTMY) files were used for AutoBEM simulation. The simulation results from TMY and fTMY were compared. It was found that a projected 10.28% increase in total CO2 emissions and a 9.30% rise in total energy consumption by 2080–2099 relative to current typical conditions. The results highlight the disparities in emissions among different building stocks and the influence of climate change on future energy demand. The findings underscore the necessity of targeted policy interventions and retrofitting strategies (eg. advanced HVAC systems, improved insulation, reflective roofing) to mitigate emissions in high-energy-use and emission-intensed buildings, particularly as climate conditions evolve. This study contributes to the growing understanding of building-sector emissions and their long-term implications under future climate scenarios.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2026

AutoBEM: A scalable framework for nationwide building energy simulation and retrofit evaluation in the United States

This paper presents AutoBEM, an integrated, automated framework for nationwide building energy modeling and retrofit evaluation in the United States. Unlike prior UBEM platforms that either rely primarily on representative stock sampling or operate at city scale, AutoBEM automates the generation of building-resolved, physics-based EnergyPlus/OpenStudio simulation models at national scale using GIS-derived geometry, prototype-based assumptions, and standardized scalable workflows. Leveraging the Model America dataset and high-performance computing, AutoBEM generates and simulates energy models for 122.9 million buildings, representing 97.8% of the U.S. building stock. These models are being made publicly and freely available as the Model America v1.0 (MAv1) dataset. AutoBEM supports detailed, building-level assessments of energy consumption, CO2 emissions, and post-processed anthropogenic heat emissions (AHE), and evaluates 151 energy conservation measures (ECMs) using localized utility pricing and building characteristics. In addition, AutoBEM incorporates both typical and future climate conditions through integration with Typical Meteorological Year (TMY) and Future TMY (fTMY) weather data derived from IPCC scenarios. In a case study of Phoenix, Arizona, AutoBEM identified several high-efficiency HVAC upgrades and selected envelope measures with short modeled payback periods (1.5 years) for certain building types and standards. Simulations under future climate scenarios (SSP5–RCP8.5) project an 11.3% increase in electricity use and a 32% reduction in natural gas demand by 2100, underscoring the need for climate-adaptive retrofit planning. By enabling reproducible, bottom-up, and location-specific analysis at scale, AutoBEM provides a step toward a national digital twin of the built environment and supports data-driven screening and planning for decarbonization, resilience, and energy equity.

Li, Hang [ORNL] (ORCID:0000000306001920)↗
DOE OSTI2023

Model America - Arizona extract from ORNL's AutoBEM v1.1

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).Two sets of sample data are provided for 2,555,152 buildings located within the boundary of Arizona in the United States:Data (846.3MB *.csv) - minimalist list of each building (rows) for the following fields (columns) • ID - unique building ID • Centroid - building center location in latitude/longitude (from Footprint2D) • Footprint2D - building polygon of 2D footprint (lat1/lon1_lat2/lon2_...) • State_abbr - state name • Area - estimate of total conditioned floor area (ft2) • Area2D - footprint area (ft2) • Height - building height (ft) • NumFloors - number of floors (above-grade) • WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings) • CZ - ASHRAE Climate Zone designation • BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards • Standard - building vintage • Sample Models (114GB*.zip by county) - OpenStudio and EnergyPlus building energy models named according to IDThis 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), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Extending the Air and Moisture Leakage Calculator to add Residential Buildings and Additional Commercial Buildings

The DOE Windows and Building Envelope Research and Development Roadmap for Emerging Technologies shows that in 2010, infiltration was responsible for 4 quads of space conditioning primary energy use in the residential and commercial sectors. The relative contribution of air leakage in building heating and cooling load is increasing with improvement in the thermal resistance of building envelopes. Advanced air barrier technologies and construction practices have been developed to reduce air leakage in buildings. However, limited information on the impact of air barrier technologies on energy consumption and the durability of buildings has hindered their adoption. In the past Oak Ridge National Laboratory (ORNL), the National Institute of Standards and Technology (NIST), Air Barrier Association of America (ABBA), and U.S.-China Clean Energy Research Center for Building Energy Efficiency (CERC-BEE) collaborated to develop an online calculator that estimates the potential energy and cost savings in major U.S., Canadian and Chinese cities from improvement in air tightness in commercial buildings. In 2018–2019, the calculator was expanded to add moisture transfer calculations given that air leakage through the building envelope can have a significant impact on moisture transfer and associated impacts. In this study, the calculator is expanded further by adding data for two additional commercial buildings (strip mall and primary school) and a residential building. The team investigated the impact of airtightness on energy consumption and moisture transfer of the added buildings. The study includes the analysis of air tightness in 52 major cities in the U.S. and 5 cities in Canada.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Model America

Data set including 17 fields of information for 141,506,665 U.S. buildings. Advantages of this dataset include: Resolution - actionable data and models for individual U.S. buildings; Flexibility - ability to modify data, models, and analysis for any simulation-informed use case; Scalability - dynamic archetypes can be used as representative models for any geography of interest; Accuracy - error rates for total energy use at city-scale of 1-5%

New, JoshuaR↗
DOE OSTI2024

Equitable Energy Metrics for Integration into Building Performance Standard Tracking Platforms: Preprint

Building Performance Standards (BPS) are being adopted globally and in the United States of America, where 14 different states and jurisdictions have a policy in place and many others are under development (Department of Energy (DOE) 2023). Accurate and equitable data sources are essential to make informed decisions about focusing investment on upgrading buildings to meet jurisdictional goals. There have been multiple new tools developed related to Energy Equity and Environmental Justice (EEEJ) and the resulting datasets need to be integrated into large building port-folios for quick access and better scalability. Integrating EEEJ data in a user-friendly format can help decision makers more quickly assess impacts and analyze the multitude of potentially significant metrics for which there is not yet consensus. In the U.S. and Canada, many BPS ordinances rely primarily on ENERGY STAR Portfolio Manager (ESPM) to capture building characteristics and energy and water consumption data. These datasets can then be imported into city-specific building tracking tools like the Standard Energy Efficiency Data Platform (SEED). Crucially, BPS decision makers require an efficient means of identifying buildings in priority communities to effectively allocate resources and funding. This process must integrate seamlessly with existing jurisdictional toolsets for optimal utility. This paper will demonstrate, for the case of Washington D.C.'s (the District) data, a workflow that provides actionable data for building upgrade investment prioritization in disadvantaged communities.

BPS↗
DOE OSTI2025

Recycling Wind Energy Systems in the United States Part 1: Providing a Baseline for America's Wind Energy Recycling Infrastructure for Wind Turbines and Systems

The U.S. investments in building this new wind energy capacity will not only mobilize millions of tons of raw and processed materials in existing supply chains, some of which are critical materials, but also create new types and large volumes of end-of-life (EOL) waste streams. Building efficient, cost-effective, and environmentally responsible EOL management infrastructure of wind energy system components is pivotal in diverting upcoming volumes of waste stream from landfills, recovery of critical materials and reducing life cycle emissions from production of primary commodity materials . The primary goal of this report is to organize and communicate findings from this assessment on how alternate materials, designs and manufacturing processes could enable more efficient, cost-effective, and environmentally responsible disassembly and resource recovery from wind energy technologies. The findings of this assessment could inform prioritization of RD&D investment spending to meet Energy Act of 2020 directions. This assessment focused on key RD&D recommendations for three main temporal phases: Short-term (2023-2026), medium-term (2026 through 2035) and long-term (beyond 2035).

17 WIND ENERGY↗
DOE OSTI2022

High-Accuracy Angle Generator for Angular Calibrations to Support Optical Metrology Laboratories and Light Source Facilities

The overarching vision for this project was to build the most accurate full-rotation angular positioning system in the Americas, and that goal remains. In labs performing similar work, the environment is typically closer to a clean room than an office space, like we had before the upgrades. We are now positioned to achieve our intended result with our upgraded infrastructure, system hardware, calibration techniques, and software. As detailed below, the combination of the pandemic schedule and technical challenges have set us back, but we will continue on the path toward our vision beyond the end of this Phase 2. It’s too important for us, for industry, and for the nation not to do so.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗
DOE OSTI2022

2021 Component Innovation Awardee: Siva Powers America

Siva Powers America earned a Competitiveness Improvement Project (CIP) Component Innovation award that will enable the company to evolve its 250/50 wind turbine design, discontinue its existing 13.4-meter wind turbine blades, and develop new 14.4-meter blades. These longer blades, which have additional extenders at the hub, will increase the rotor diameter to 35 meters, allowing for improved energy production at sites with lower wind resources. A collaboration with the National Renewable Energy Laboratory (NREL) includes a redesign, build, and on-site structural test for the new prototype blades. This will ultimately allow Siva Powers America to pursue recertification of the SIVA 250/50 to meet international standards.

CIP↗
DOE OSTI2022

Prototype Integrated Hydrogen Fuel Cell Powered Data Center (Cooperative Research and Development Final Report)

Data centers are the backbone of the modern economy-from the server rooms that power small- to medium-sized organizations, to the enterprise-class data centers that support American corporations, and the server farms that run cloud computing services. Rather than a traditional grid-centric data center approach, work under the CRADA will be directed towards implementing a proof-of-concept "hydrogen-based" data center utilizing hydrogen fuel cells, electrolyzers, and solar photovoltaics as key building blocks. This integrated proof-of-concept builds on preliminary work done by HPE and its partners Mercedes-Benz Research & Development North America, Inc. (MBRDNA) and Power Innovations, to dramatically simplify the electrical infrastructure in the data center, leverage the latest automotive-scale hydrogen fuel cell technologies, and tightly couple renewably generated DC power directly to the Information Technology (IT). While some limited aspects of this concept have been demonstrated previously the entire integrated proof of concept proposed here has not yet been realized.

08 HYDROGEN↗
DOE OSTI2022

Cross-Laminated Timber Workshop: Pathways and Priorities for Cross-Laminated Timber Building Systems

A virtual workshop titled "BTO Cross-Laminated Timber Workshop: Pathways and Priorities for CLT Building Systems," was held on April 19, 2021, to identify research and development pathways, including the embodied energy content, operational energy efficiency, wall moisture profiles, structural connector durability, and health monitoring systems for CLT wall systems. In the workshop, perspectives were gathered from a wide range of stakeholders across North America from academia, the mass timber industry, trade groups, and federal government departments. The participants had knowledge in one or more areas of CLT building performance, production and construction, supply and demand dynamics of CLT panels, building codes, and recycling of CLT panels. To capture potential research opportunities from the participants in the mass timber field, the workshop was structured with the following objectives: 1. Identify the research and development opportunities to overcome technology gaps, integration issues, and market adoption challenges that are currently preventing the greater deployment of CLT, and 2. Understand what priorities and pathways are needed to advance energy efficient, high- rise CLT building systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Cloud-Control of Legacy Building Automation System: A case study

As Internet of Things devices and cloud-based platforms become more mature, Energy Management and Information Systems (EMIS) are increasingly gaining momentum in the building industry. In large commercial buildings, Fault-Detection and Diagnostic (FDD) and energy information systems (EIS) are now established technologies with tens of providers and thousands of deployment sites across North America. The new frontier for the EMIS technology is now represented by control systems that use advanced system optimization (ASO) methods to improve the operations of the HVAC system. Given the complexity of the integration of such systems with the existing building automation systems (BAS) and the higher risk involved with direct control of the HVAC, these systems are still emerging in the market. This paper presents the results of a project in which a start-up company partnered with a research institution to develop a cloud-based software EMIS solution and deployed it in a university campus in California. The software system included advanced sensing, data acquisition, storage and advanced control and analytics applications developed on top of the native BAS. The new platform controls ten buildings on the campus and the FDD and the ASO applications deployed on this platform were able to generate energy savings of up to 35% and 25% in certain buildings for each functionality respectively. Where the platform did not save energy, it improved building service (air quality). Lessons learned include the importance of collaborating with and training the building operators and evaluating whether the legacy system can work reliably with the new technology.

Prakash, Anand Krishnan↗
DOE OSTI2022

Water Electrolyzers and Fuel Cells Supply Chain: Supply Chain Deep Dive Assessment

The report “America’s Strategy to Secure the Supply Chain for a Robust Clean Energy Transition” lays out the challenges and opportunities faced by the United States in the energy supply chain as well as the federal government plans to address these challenges and opportunities. It is accompanied by several issue-specific deep dive assessments, including this one, in response to Executive Order 14017 “America’s Supply Chains,” which directs the Secretary of Energy to submit a report on supply chains for the energy sector industrial base. The Executive Order is helping the federal government to build more secure and diverse U.S. supply chains, including energy supply chains. This report is one of a series that supports the analysis of the energy industrial base called for in Executive Order 14017 on America’s supply chains (Exec. Order No. 14017, 2021). Specifically, it provides a review of the supply chain for water electrolyzers and fuel cells with a focus on polymer electrolyte membrane electrolyzer cells (PEMEC), polymer electrolyte membrane fuel cells (PEMFC), solid oxide electrolyzer cells (SOEC), and solid oxide fuel cells (SOFC). Water electrolysis and fuel cells are a nascent industry with little prior information related to supply chain needs and constraints. This report provides a preliminary assessment; further industry peer review and revisions are expected.

08 HYDROGEN↗
DOE OSTI2022

A High-Throughput Computing Infrastructure to Generate Custom, Open Community Geothermal Datasets

The most significant challenge facing geothermal research, development, and deployment is a lack of comprehensive datasets describing the geological and economical properties of North America. Automated knowledge base construction, the process of designing algorithms to analyze text and images to programmatically build new datasets, is one possible solution to this problem. The xDD library of full-text scientific articles (https://xdd.wisc.edu) is one of the largest collections of open and controlled-access scientific documents available for knowledge base construction in the world, but it has been underutilized by experts in geothermal research. The xDD development team attributed the lack of engagement by software developers and geothermal researchers to two perceived shortcomings of the system. First, the workflow for obtaining data from xDD for local development and testing of data mining applications was unnecessarily abstruse and required significant manual intervention by xDD systems administrators. Second, although xDD already held articles from a broad cross-section of scientific literature with an emphasis on the geosciences, it did not have an explicit set of geothermal research documents that could serve as the nucleus of a geothermal data mining application. To address these issues, the Automated Data Extraction PlaTform (ADEPT) was proposed to extend the data distribution capabilities of the xDD system. The ADEPT extension added the following four key features to xDD: 1) integration of National Geothermal Data System (NGDS) documents into the xDD library to provide an explicitly geothermally-themed collection; 2) improved RESTful (i.e., https-protocol driven) web services for external partners to access xDD data for machine learning application development; 3) a web platform for end-users and xDD administrators to coordinate the development of data mining applications from the initial step of browsing available documents to the final stage of deploying a production-quality machine learning application on high-throughput computing infrastructure; and 4) the development of demonstration data mining applications to illustrate the new workflow to potential collaborators. A total of 21,674 geothermal documents from NGDS were fully ingested into the xDD library and the associated metadata is publicly available through the xDD web services; furthermore, the ADEPT web platform is now publicly accessible and fully live at https://xdd.wisc.edu/adept/.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

A plan to revitalize the domestic superconducting radio-frequency industry

Superconducting radio-frequency (SRF) cavities are essential building blocks of modern particle accelerators for scientific research, and they offer unique capabilities that could be transformative for commercial applications. Growth of the domestic SRF industry in North America has faced several challenges over the past decades, as most of the international demand for cavities was supplied by European vendors. This contribution provides a brief review of the domestic industrial vendor space, an outlook of the global demand for SRF cavities and an outline of the challenges leading to this supply chain deficiency. One of the main challenges towards establishing a robust domestic SRF industry has been the large uncertainty in the demand. Meanwhile, research and development activities to raise technical readiness of SRF accelerators for industrial use have continued and several potential markets are emerging that may offer a consistent and growing demand for SRF cavities. Finally, reasons and means of establishing and sustaining competitive domestic suppliers are described.

Accelerator Physics↗