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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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This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 1 Charging" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging" measure upgrade methodology and briefly discusses key results.
Groundbreaking efforts are necessary to mitigate contributors increasing impacts of climate change. In parallel to inventing pioneering clean energy technologies it is even more fundamental to rethink designing energy systems within a singular facility and collectively to function as a district. Facilities should not be continuously passive by just consuming; there is a need to shift to perform more dynamically. Designing for zero energy and zero carbon on a multi-building scale can uncover opportunities for building energy efficiency, decarbonization, demand flexibility, and resiliency that are not accessible at an individual building scale. This approach can be challenging without innovative tools to evaluate the multitude of possibilities. As an investigated result, we highlight the use of a campus-scale energy modeling platform - URBANopt™ - for the expansion of the National Renewable Energy Laboratory's (NREL's) South Table Mountain campus in Golden, Colorado. Programmatic growth included the design of three new all-electric, zero-energy, and zero-carbon, mixed used buildings (a combination of research laboratories and office space). This investigation is critical to NREL reaching net-zero emissions for its operational footprint, which will occur in phases over the next decade. Leveraging URBANopt's capabilities, we evaluate 1) high-performance building energy efficiency and decarbonization measures, 2) 4th generation district heating and cooling (4th GDHC) systems, 3) optimized onsite generation and energy storage assets that meet zero-energy and zero-carbon targets at minimum life-cycle costs, and 4) cost-optimal distributed energy technology mixes, dispatch strategies, and associated capacities that increase resiliency to grid outages. This work demonstrates the use and capabilities of URBANopt through a real-world case study on a multi-building scale.
Energy expenditure can be regarded as the sum of two components; the basal metabolic rate and the energy costs of activity. Weight loss is usually associated with an energy deficit. A negative energy balance exists when energy intake is less that energy utilization. The deficit is made up by tissue catabolism (principally fat, but also some protein). By analyzing food and water intake, urine and fecal output, and changes in body weight, the Skylab investigators reached the unexpected conclusion that energy expenditure during spaceflight was about 5% greater than at 1 G (Leonard, 1983; Rambaut et al., 1977). Possible explanations for the human metabolic responses are an increased workload during spaceflight (Leonard, 1983), or as Rambaut and co-workers (1977) suggested, a progressive decrease in metabolic efficiency. It is likely to be very difficult to distinguish between these two possibilities in man because the activity component may be different during spaceflight than it is the ground. The problem is to measure energy expenditure with efficient precision during spaceflight in a non-invasive manner which will not interfere with other investigations or take an time. The doubly labeled water (DLW) method meets these criteria. The DLW method is the only method available for continuously measuring energy expenditure during spaceflight given the severely restricted conditions in the spaceflight environment. Therefore, this study focuses on the development and use of this procedure on nonhuman primates during spaceflight. Energy expenditure and total body water was determined in two Rhesus monkeys by the doubly labeled water (2H2'80) method. Three determinations were made. Monkey B (#2483) was studied twice, during the flight of COSMOS 2044 and during a follow-up ground control study a month later. A second monkey was studied on the ground only (Monkey D, #782).
This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Electric Vehicle Adoption With Level 2 Charging and Demand Flexibility" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Reference Space Heating and Air Conditioning Upgrade Circa 2025" measure upgrade methodology and briefly discusses key results.
Building on the 3-year End-Use Load Profiles project to calibrate and validate the U.S. Department of Energy's ResStock and ComStock models, this work produces national data sets that enable cities, states, utilities, and other stakeholders to answer a broad range of questions regarding their commercial building stock. ComStock is a highly granular, bottom-up model that uses various data sources, statistical sampling methods, and advanced building energy simulations to estimate the annual subhourly energy consumption of the commercial building stock across the United States. The "baseline" model intends to represent the U.S. commercial building stock as it existed in 2018. The methodology of the baseline model is discussed in the ComStock Reference Documentation. The goal of this work is to develop energy efficiency and demand flexibility measures that cover market-ready technologies and study their mass adoption impact on the baseline building stock. "Measures" refers to various "what-if" scenarios that can be applied to buildings. The results for the baseline and measure scenario simulations are published in public data sets that provide insights into building stock characteristics, operational behaviors, utility bill impacts, and annual and sub-hourly energy usage by fuel type and end use. This report describes the modeling methodology for a single ComStock measure scenario - high-efficiency rooftop unit (RTU) - and briefly introduces key results. The full public data set can be accessed on the Comstock data lake or via the Data Viewer at comstock.nlr.gov. The public data set enables users to create custom aggregations of results for their use case (e.g., filter to a specific county or building type).
This report is part of a series describing different ResStock (TM) measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Propane Fuel 95% AFUE and Fuel Oil Furnace 88% AFUE" measure upgrade methodology and briefly discusses key results.
This report is part of a series describing different ResStock measures. "Measures" refers to energy efficiency retrofits that can be applied to buildings during modeling. This documentation covers the "Advanced Air Sealing, Attic Floor Insulation, Duct Sealing and Insulation, and Drill-and-Fill Wall Insulation" measure upgrade methodology and briefly discusses key results.
The efficiency of energy transfer in chlorosome antennas in the green sulfur bacteria Chlorobium vibrioforme and Chlorobium limicola was found to be highly sensitive to the redox potential of the suspension. Energy transfer efficiencies were measured by comparing the absorption spectrum of the bacteriochlorophyll c or d pigments in the chlorosome to the excitation spectrum for fluorescence arising from the chlorosome baseplate and membrane-bound antenna complexes. The efficiency of energy transfer approaches 100% at low redox potentials induced by addition of sodium dithionite or other strong reductants, and is lowered to 10-20% under aerobic conditions or after addition of a variety of membrane-permeable oxidizing agents. The redox effect on energy transfer is observed in whole cells, isolated membranes and purified chlorosomes, indicating that the modulation of energy transfer efficiency arises within the antenna complexes and is not directly mediated by the redox state of the reaction center. It is proposed that chlorosomes contain a component that acts as a highly quenching center in its oxidized state, but is an inefficient quencher when reduced by endogenous or exogenous reductants. This effect may be a control mechanism that prevents cellular damage resulting from reaction of oxygen with reduced low-potential electron acceptors found in the green sulfur bacteria. The redox modulation effect is not observed in the green gliding bacterium Chloroflexus aurantiacus, which contains chlorosomes but does not contain low-potential electron acceptors.
An efficient neutron detection system with good energy resolution is required to correctly characterize decays of neutron-rich nuclei where β-delayed neutron emission is a dominant decay mode. The Neutron dEtector with Xn Tracking (NEXT) has been designed to measure β-delayed neutron emitters. By segmenting the detector along the neutron flight path, NEXT reduces the associated uncertainties in neutron time-of-flight measurements, improving energy resolution while maintaining detection efficiency. Detector prototypes are comprised of optically separated segments of a neutron-gamma discriminating plastic scintillator coupled to position-sensitive photomultiplier tubes. In this work we discuss how the first performance studies of this detector showed that high intrinsic neutron detection efficiency could be achieved while retaining good energy resolution. The results from the efficiency measurements using neutrons from direct reactions are presented
Freight travel accounts for a major share of the energy consumed in the transportation sector in any country, and the United States is no exception. Understanding and modeling freight movement is critical, particularly in the context of capturing the impact of emerging technologies on freight travel and its externalities. The domain of freight modeling and forecasting is gaining pace in the recent years, but advancement in comprehensive freight performance metrics is still lagging. Conventional freight performance metrics such as truck-miles, ton-miles, or value-miles are unidimensional and aggregated in nature, making them unsuitable to accurately capture the impact of emerging transportation trends on the performance of freight systems. Addressing this research need, this paper presents the 'Freight Mobility Energy Productivity' metric to quantify freight performance of current as well as future freight systems, accounting for various costs associated with freight transport. The proposed metric was implemented using data from the Freight Analysis Framework along with other published sources, which shows intuitive results in quantifying freight performance. Further, a scenario analysis exercise was conducted to test the capability of the metric in tracking improvements in system-level freight efficiency as a result of vehicle powertrain technology improvement. Results of the scenario analysis reinforce confidence that the proposed metric can be used as a decision support tool in assessing the efficiency of existing as well as future freight trends and technologies.
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Lighting significantly contributes to electricity consumption in buildings. The most widely used measure of lighting energy efficiency, luminous efficacy, quantifies only the intensity of light generated by light sources, weighted by the spectral sensitivity of the human visual system (i.e., the energy efficiency of individual lighting devices). However, luminous efficacy does not fully address the use of lighting in architectural spaces. To address these limitations, we developed a framework to framework to calculate lighting application efficacy (LAE), the relationship between the electrical power consumed by lighting hardware, and the amount of light that contributes to the visual perception of building occupants. The proposed LAE framework is based on the primary pathway of light in architectural settings: the generation and emission of light from a luminaire, the travel of the light throughout the space and into the eyes of occupants, and the process of visual perception. The project’s primary outputs are a method for measuring lighting application efficacy and a framework for facilitating future research to improve the metric.
This dataset is meant to accompany the Methods page for A Targeted Approach to Energy Burden Reduction Measures: Comparing the Effects of Energy Storage, Rooftop Solar, Weatherization, and Energy Efficiency Upgrades.
Nano-electrospray (nES) produces a plume of charged liquid droplets which have drag interactions with the surrounding gas after they are emitted from a source capillary. The resulting induced gas flow has often been considered unimportant, but we have demonstrated that a gas microjet of significant velocity up to 10s of m/s can be produced. In this work we present a thermodynamic framework that enables analysis of gas jet generation from electrosprays and introduce the important metrics for such analysis, effectiveness (a measure of momentum transfer from the electrosprayed aerosol to gas) and efficiency (a measure of energy conversion from electrical energy generating the electrospray to gas kinetic energy). This analytical framework is applicable to any two-phase flows consisting of discrete conservative-force-driven particles which exchange momentum with an inert, otherwise quiescent fluid medium to yield a co-flowing two-phase jet. Here, we apply this framework to sprays of water from nano-electrospray emitters to demonstrate that increasing the applied electrical potential difference, increasing liquid mass flowrate, and decreasing droplet size all can increase electrospray induced gas jet strength, but only the latter two do so while also increasing the momentum transfer effectiveness and energy conversion efficiency.
A report on calibrating energy-measuring equipment to maximize energy efficiency of lighting and other systems. The report describes best practices for accrediting calibration laboratories and for calibrating measuring equipment, compares and contrasts service providers accredited for energy-measuring equipment calibration, presents a tailorable specification template for requesting such calibration, and offers recommendations to a range of stakeholders.
This multi-year project delivered a comprehensive, human-factors-driven framework to understand, model, and improve pooled rideshare (PR) adoption in the United States. Through three large-scale national survey studies involving more than 16,000 participants across multiple cities and demographic groups, the research established one of the most extensive datasets to date on user perceptions, behavioral barriers, and service expectations related to pooled rideshare. These data revealed key human factors barriers of user acceptance of PR and suggested potential actionable experience optimizations that could lead to increased PR usage. This foundational knowledge guided the development of novel human-factors models and behavioral choice models that quantify how psychological, demographic, and trip-level factors influence willingness to pool. Building on these empirical insights, the project developed advanced behavioral modeling tools, including mixed logit and integrated choice and latent variable models, to capture both observable and latent influences on PR adoption. These models significantly improved the ability to predict riders’ acceptance of pooled trips, explaining choice heterogeneity through latent constructs such as safety, service experience, privacy concerns, time sensitivity, and environmental attitudes. Together, these models provide a robust analytical foundation for designing PR systems that more effectively meet user needs. The project translated human-factors insights and behavioral models into actionable technology innovations by extending POLARIS—an agent-based, activity-based travel simulation platform—into a fully functional pooled rideshare simulation environment. New PR modules, acceptance models, and regional scenarios were implemented for Greenville, SC and Austin, TX, enabling high-fidelity validation of algorithmic strategies under realistic demand and traffic conditions. The simulation platform supported the development and evaluation of adaptive discount-based assignment algorithms, enhanced willingness-to-pay formulations, demographic-aware incentive mechanisms, and a proactive joint assignment and repositioning strategy. Simulation results demonstrated substantial gains in pooling uptake, average vehicle occupancy, energy efficiency, and fleet profitability. In Greenville, pooling adoption more than doubled, while reductions in vehicle-miles traveled and energy consumption were significant. In Austin, pooling improvements were achieved with minimal service-quality trade-offs, and profitability increased across all fleet sizes. Through this research, we developed a comprehensive understanding of the human factors barriers that limit user acceptance of pooled rideshare services. These insights enabled the design of human-factors-aware pooled rideshare technologies that more effectively address user concerns and improve adoption rates. By integrating these models into an advanced agent-based simulation framework, we demonstrated that higher adoption of pooled rideshare can lead to measurable improvements in energy efficiency and system performance. Together, these contributions establish a validated pathway from human-centered analysis to technology development and energy-saving outcomes, supporting national goals for more sustainable and efficient mobility systems.