Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “building energy”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Understanding Commercial Building Energy Use in the Greater Seattle Area: Building Stock Segmentation for Retrofit Planning

This report is part of the second phase of a publication series focusing on approximately 100 different local geographies, or "clusters." Each report provides characteristic features and energy data for commercial buildings in a specific area to help policy makers at the city, county, and state level better understand building energy use and emissions. This report breaks down the energy consumption and emissions of the building stock in the counties shown in Figure 2 by building type, building size, end use, energy consumption, emissions, and segment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

A systematic review of building energy sufficiency towards energy and climate targets

Among the sufficiency, efficiency, and renewable frameworks for reducing energy use and energy-related carbon emissions, Building Energy Sufficiency (BES) is gaining attention from policy makers and engineers. Despite the significant role of the building sector in the success of national energy and climate plans, there is a lack of research on the drivers, technologies, and effective policy instruments required to achieve BES in the building operational phase. To fill this gap, this study presents a systematic review of the definition and paradigm of BES and concludes that BES should address both occupant demand and energy or emissions requirements simultaneously. The characteristics of occupant demand in building services are divided into four dimensions: time and space, quality and quantity, control and adjustment, and flexibility. Technical options regarding the building architecture, the envelope system, and the building energy system are reviewed. Finally, policy implications and recommendations are discussed. As a result, the multiple benefits and multidisciplinary nature of BES justify further research and accelerated policy implementation in developed and developing countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Automatic Building Energy Modeling (AutoBEM)

AutoBEM provides automated building energy modeling for quantifying energy, demand, emissions, and cost reductions for over 1 million buildings per hour. It creates a digital twin energy model of a building from a set of descriptors. Benefits include: Scale - has been used to simulate every building in the U.S. Speed - fastest creation and simulation of energy models for buildings. Accuracy - validated against 15-minute data for 178,000 buildings as well as multiple cities.

New, JoshuaR↗
DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗
DOE OSTI2023

Understanding Building Energy Use in the Greater Memphis Area: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

building stock↗
DOE OSTI2025

A machine learning method of modern urban building energy modeling: A case study of Chicago

Urban-scale building energy modeling is vital for urban planning. However, it can be challenging to assimilate reliable non-geometry building data for urban-scale modeling without extensive investment. Here, this study introduces a novel approach to developing modern urban-scale building energy stock data using geographic information systems and machine learning algorithms without necessarily requiring pre-supplied non-geometric metadata. The proposed framework integrates building footprint and height data to estimate gross floor areas, and matches each building to a pool of candidate records from ComStock or ResStock—filtered to the same county and ranked by geometric similarity—demonstrate a proof-of-concept case study in Chicago for predicting energy use intensity (EUI) using scalable datasets. The model achieved a mean bias error (MBE) of 0.08 kWh/m² and root mean square error (RMSE) of 14.84 kWh/m² under full metadata input for EUI prediction. With only location inputs, the model captured 69.2 % of EUI within predicted ranges. These results demonstrate the model’s potential to support early-stage urban planning, identify candidates for energy-efficient retrofits. By removing the dependency on detailed pre-surveys or extensive building metadata, the approach overcomes a key barrier in traditional urban-scale building energy modeling, illustrating a pathway toward broader and more cost-effective application, though further multi-city validation and improved treatment of pre-1925 buildings are needed.

Energy Use Intensity↗
DOE OSTI2023

Understanding Building Energy Use in Boise-Twin Falls: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in the Rural Mountain West: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in the Northern Pacific Coast: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in the Greater Louisville Area: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in the Greater Seattle Area: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in San Antonio to Waco: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in Rural Climate Zone 3A: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in California Climate Zone 3: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in California Climate Zone 4: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in California Climate Zone 7: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in California Climate Zone 8: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Understanding Building Energy Use in California Climate Zone 9: Basic Building Stock Characterization

This report is part of a publication series that focuses on approximately 100 different local geographies, or "clusters." Each report provides commercial and multifamily building characteristic and energy data for a local geography, with the intention of helping policymakers at the city, county and state levels better understand building energy use. Specifically, this report breaks down the building stock in the counties shown in Figure 1 by building type, size, energy consumption, and emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗