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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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Learn about the recycling symbols that indicate whether products or packaging can be recycled. This fact sheet from Energy Saver describes the recycling codes for plastic, glass, and paper that indicate how materials should be recycled or disposed of.
Learn about different types of batteries and the proper ways to dispose of them. This fact sheet from Energy Saver includes information on single-use, rechargeable, and automotive batteries, as well as tips for disposal, recycling, and safe handling.
Learn how insulation material, when properly used, can make your home more comfortable and energy-efficient, greatly reducing heating and cooling bills throughout the year. This fact sheet from Energy Saver includes information on the benefits of insulation, types of insulation, and how to determine the right R-value for your home.
Learn about controlling moisture and ventilation in your attic, as well as the steps to create a durable attic. This fact sheet from Energy Saver includes information on why moisture control in attics is important and the strategies you can use to control moisture and ventilation in your attic.
Learn how good driving habits and maintaining your car can improve your fuel economy, as well as other ways to save fuel. This fact sheet from Energy Saver offers tips for how to save fuel and which driving habits and vehicle maintenance practices will have the greatest effect on your fuel economy.
Learn why straight vegetable oil and other waste cooking oils are not the same as biodiesel and why it is important to convert them to biodiesel for use in vehicles and heavy machinery. This fact sheet from Energy Saver includes information on straight vegetable oil performance, its effects on engines, and fuel blends approved for diesel vehicles and engines.
Learn what an electric vehicle (EV) could mean for you, including fuel economy, emission reductions, cost savings, and fueling flexibility. This fact sheet from Energy Saver includes information on types of electric vehicles, how an EV could save you on fuel and money, how to charge an EV, and EV safety standards.
Learn about types of heating and cooling systems, system maintenance, and best practices for saving energy with your heating and cooling. This fact sheet from Energy Saver also includes information on buying a new heating or cooling system; efficiency ratings; and selecting new systems including air conditioners, heat pumps, and furnaces.
Learn why it's important to reduce vehicle idling and some strategies to cut down on vehicle idling. This fact sheet from Energy Saver includes information on why modern cars do not need to idle, circumstances when you can turn off your engine, and some exceptions when you may need to idle.
Learn how air sealing can improve your home's energy efficiency, comfort, and durability. This fact sheet from Energy Saver includes information on proper ventilation, why to air seal, how to find and seal air leaks, working with contractors to seal your home, and materials to do-it-yourself.
Learn how ethanol is used in transportation fuels and about the different ethanol blends you may find at fueling stations. This fact sheet from Energy Saver includes information on the history of ethanol in the United States, what fuel ethanol is, the three categories of ethanol blends, and flex-fuel vehicles.
Complete residential solar-heating and hot-water system, when installed in highly-insulated energy-saver home, can supply large percentage of total energy demand for space heating and domestic hot water. System which uses water-heating energy storage can be scaled to meet requirements of building in which it is installed.
Design package for modular solar heating system includes performance specifications, design data, installation guidelines, and other information that should be valuable to those interested in system (or similar systems) for projected installation. When installed in insulated "energy saver" home, system can supply large percentage of total energy needs of building.
Climate change and anthropogenically-forced shift of weather in the future will impact energy use and resilience of both the built environment and the electric grid. The aim of this analysis is to understand how future climate scenarios will impact electricity and natural gas use of commercial buildings in the United States. Here, this study analyzes this impact for 2030, 2045, and 2100 using Representative Concentration Pathways (RCP) scenarios defined in Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5. The large, gridded simulation of meteorological variables for RCPs 2.6, 4.5, 6.0, and 8.5 are selected and downscaled to make available hourly Future Meteorological Year (FMY) weather files for use and improvement in subsequent studies. High performance computing resources use these FMYs to simulate commercial prototype buildings in every American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) climate zone of the United States (US), and results are scaled to nation-wide energy use using conditioned floor area multipliers. The analysis is conducted without speculating the physical and performance traits of future buildings or the grid characteristics. This analysis quantifies the impact of climate change on source electrical and natural gas usage for commercial buildings in the United States over the next 80 years. If US commercial floorspace remained constant, total energy use by 2100 is predicted between an 1.75% decrease under the greatest emission scenario (8.5) and a 1.76% increase under the lowest emission scenario (2.6). When adjusted for anticipated urban growth by 2100, the predicted range is 65% increase (8.5) and 71% increase (2.6). Under a global temperature rise climate scenario, the warmest US climate zones will see a large increases in electricity use derived from space cooling while the coldest US climate zones will see significant decreases in natural gas use caused by the decrease in heating necessary. While climate change may ultimately require adaptations of the built environment to withstand its effects and because the United States is a country that requires more heating than cooling, from a building energy perspective, climate change (average temperature rise) is a net energy saver for the United States.
Demand-response programs can help utilities manage rapidly evolving electric grids, but these programs are subject to the complexities of human behavior. This paper explores a novel method for uncovering heterogeneity in households. In this work, we use a machine-learning method known as a Conditional Inference Tree (c-tree) algorithm to categorize households based on their energy behavior characteristics collected via smart meters, and explore how this translates through into heterogeneity in their real-world response to a DR program. Using data from randomized controlled trial, we generate estimates of the changes in energy use caused by the program within each household group. Our results show that the c-tree approach differentiates households by their energy-use characteristics in a way that increases the spread in enrollment rates and critical peak reduction among household groups, compared with the spreads achieved via several conventional segmentation methods. Thus, the c-tree analysis enables the most tailored targeting of major potential energy savers and could provide the greatest increase in cost-effectiveness of household recruitment into DR programs. Our results also offer fresh insights into the relationships between household energy behavior characteristics – such as peak energy use and “structural winningness” (the ability to save money under a DR program without changing energy-use behaviors) – and household decisions about enrolling in DR programs and reducing energy use. Our research also demonstrates the potential of smart meter data, combined with machine learning and econometric methods, to provide significant value to utilities, program implementers, researchers, and other stakeholders.
The heating units shown in the accompanying photos are Panelbloc infrared heaters, energy savers which burn little fuel in relation to their effective heat output. Produced by Bettcher Manufacturing Corporation, Cleveland, Ohio, Panelblocs are applicable to industrial or other facilities which have ceilings more than 12 feet high, such as those pictured: at left the Bare Hills Tennis Club, Baltimore, Maryland and at right, CVA Lincoln- Mercury, Gaithersburg, Maryland. The heaters are mounted high above the floor and they radiate infrared energy downward. Panelblocs do not waste energy by warming the surrounding air. Instead, they beam invisible heat rays directly to objects which absorb the radiation- people, floors, machinery and other plant equipment. All these objects in turn re-radiate the energy to the air. A key element in the Panelbloc design is a coating applied to the aluminized steel outer surface of the heater. This coating must be corrosion resistant at high temperatures and it must have high "emissivity"-the ability of a surface to emit radiant energy. The Bettcher company formerly used a porcelain coating, but it caused a production problem. Bettcher did not have the capability to apply the material in its own plant, so the heaters had to be shipped out of state for porcelainizing, which entailed extra cost. Bettcher sought a coating which could meet the specifications yet be applied in its own facilities. The company asked The Knowledge Availability Systems Center, Pittsburgh, Pennsylvania, a NASA Industrial Applications Center (IAC), for a search of NASA's files
Learn about biodiesel fuel and how, when combined with vehicles with diesel engines, it can be a green transportation choice. This fact sheet from Energy Saver also includes information on biodiesel blends, biodiesel performance, and downsides of biodiesel.
The BRICR project applied large-scale building energy modeling concepts with the aim of reducing the cost of energy efficiency targeting, design, and project development, and measurement of energy savings for energy efficiency programs implemented by local governments that serve small and medium commercial buildings (SMB). The project leveraged the services and resources of existing local government energy programs serving disadvantaged and hard-to-reach SMB customers. In contrast to programs run by utilities, local government programs generally do not have direct access to energy billing records for an entire class of customers in a geographic area, which prior research demonstrated useful for large-scale building energy model baseline development and calibration. , However, local governments are rich in public records that offer important clues about physical attributes and uses that, along with behavior, determine energy use. Relying only on public records, BRICR demonstrated development of credible baseline energy models for 3,792 office, retail, and hotel buildings. Publicly disclosed annual energy use data from a local energy benchmarking program and anonymized data from the Building Performance Database, the nation’s largest dataset about energy-related characteristics of buildings, were utilized to validate and calibrate energy models via an innovative method comparing distributions of energy intensity by fuel type for portfolios of buildings of similar size, vintage, and use. Portfolio calibration does not provide certainty that an energy model fits an individual building; the method is useful when billing data is not accessible – a common situation for researchers, energy service providers and ESCOs, local governments, and any party other than a utility. A software component was developed, the BRICR gem, which automates simulation when relevant data is added or edited by the user to a file saved in the standardized BuildingSync XML schema for energy audit data. The component was demonstrated as a simplified means to generate a mass of energy models corresponding to public records containing basic attributes such as building scale, location, use, year built, and aspect ratio in combination with building energy code prototype data corresponding to use and vintage. The component was also demonstrated as a simplified means to automate energy simulation when attributes are revised; the intention was to enable iterative improvement of the baseline model and energy savings estimates for common energy conservation measures as users revise relevant attributes based on their observations. In the context of institutional change and uncertainty for the participating local government energy programs, 13 whole building retrofits were completed. Impacts were measured by applying the CalTRACK2.0 methods to standardize measurement of normalized metered energy consumption. The GRIDMeter methods of stratified sampling and individual load shape analysis were applied to adjust for impacts of the effect of COVID-19 on retrofitted buildings in the context of all local buildings of similar size and use. Excluding impacts of the pandemic, retrofitted buildings demonstrated between 1.6% and 25.1% reduction in energy use. The project contributed use cases and feedback that helped inform evolution of the software tools and data formats that were combined for the first time in the BRICR project.