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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Experimental and data-driven characterization of window-induced air leakage in residential buildings

Windows contributes up to 40% of envelope heat losses and around 9% of total building energy consumption due to air leakage. In the U.S., 48 million homes still use single-pane windows. Although the U.S. has an estimated 1.4 billion windows in its building stock and about 24 million windows are installed annually, only around 29 million individual window replacements (∼2%) occur each year. To address this gap, this study generates empirical evidence by (1) evaluating the contribution of windows to whole-building air leakage in 20 residential buildings using blower door tests before and after window replacement and (2) assessing whether building and window characteristics influence the measured change. Most simulation studies assume that replacing windows not only lowers the U-factor but also reduces air leakage by 10–20%. However, this assumption lacks empirical validation, highlighting the need for experimental analysis of air leakage specifically associated with windows. Using blower door tests in accordance with ASTM E779–19, the results indicated an average reduction in air infiltration of 6.1% within the range of 0.5–19.30% across all buildings and no significant correlations were found between air leakage improvements and any building/window characteristics. This research aims to help homeowners, and energy modelers to provide empirical data on importance of upgrading to more energy-efficient windows, supporting energy-efficient building standards.

Air leakage↗
DOE OSTI2019

Roof-integrated radiative air-cooling system to achieve cooler attic for building energy saving

The building attic usually subjects to substantial solar heat gain and has much higher temperature compared to the conditioned living space during the day, especially in summer and in hot areas. Reducing attic temperature can reduce cooling energy consumption in buildings. However, conventional techniques such as cool roof or attic ventilation, suffer from either heating penalty in winter or limited attic temperature reduction. In this work, a new roof-integrated radiative air-cooling system is introduced, which couples radiative sky cooling with attic ventilation to reduce attic temperature. A radiative air cooler with 1.08 m 2 surface area is constructed using a recently developed daytime radiative sky cooling metamaterial [Zhai et al., Science 355, pp. 1062–1066, 2017]. Experimental tests show that sub-ambient air cooling is achieved throughout 24-h day-and-night cycle in a summer day with clear sky conditions. Depending on air flow rates, measured sub-ambient temperature reductions of air are 5–8°C at night and 3–5°C at noon under direct sunlight, respectively. An in-house model is first developed for the radiative air-cooling system, the model is then coupled with EnergyPlus to study annual energy saving of buildings. The performance of the radiative air-cooling system is compared with three reference systems: shingle roof, attic ventilation, and cool roof. Results show that for a single-family house, attic temperature can be substantially reduced by 15.5–21.0°C, varying with attic insulation level, compared to shingle roof on typical summer days. Compared to a shingle roof (solar reflectance 0.25, thermal emittance 0.9) residential building with attic insulations of R-30 (RSI-5.28), R-10 (RSI-1.76), and R-0.8 (RSI-0.14), the roof-integrated radiative air-cooling system can achieve annual cooling energy savings of 0.4–1.5 kWh/m 2 (4.6–18.8%), 1.2–3.6 kWh/m 2 (10.2–41.4%), and 3.7–11.8 kWh/m 2 (26.5–76.1%) respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Evaluation of Savings in Energy-Efficient Public Housing in the Pacific Northwest

This report presents the results of an energy performance and cost-effectiveness analysis. The Salishan phase 7 and demonstration homes were compared to Salishan phase 6 homes built to 2006 Washington State Energy Code specifications 2. Predicted annual energy savings (over Salishan phase 6) was 19% for Salishan phase 7, and between 19-24% for the demonstration homes (depending on ventilationstrategy). Approximately two-thirds of the savings are attributable to the DHP. Working with the electric utility provider, Tacoma Public Utilities, researchers conducted a billing analysis for Salishan phase 7. Median energy use for the development is 11,000 kWh; annual energy costs are $780, with a fair amount of variation dependent on size of home. Preliminary analysis of savings betweenSalishan 7 and previous phases (4 through 6) suggest savings of between 20 and 30 percent. A more comprehensive comparison between Salishan 7 and previous phases will take place in year two of this project.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Numerical Codes for the DESC-LSST Analysis Pipeline: Core Cosmology Library Standard Modules and Beyond wCDM Modules (Final Technical Report)

The overall objective of the project is to investigate and develop specific software modules and analysis components for the software pipeline of LSST Dark Energy Science Collaboration (DESC). Following the key projects of DESC Science Roadmap (SRM), we will write and test computer codes for the Core Cosmology Library (CCL) in order to complete its modules, functionalities, and interface to work with the analysis pipelines from the five science probes of DESC (parts of SRM deliverables CX4.2TJP, CX6.2CS). We will also code modules for CCL to test models beyond w-Cold-Dark-Matter (wCDM) and modification to gravity (MG). Interfaces for MG models will also be developed for the TJPCOSMO software which is the main pipeline of the Theory and Joint Probe (TJP) working group (deliverable TJP2.3). In order to use the full power of LSST data to constrain MG models, we will also work on constraints from nonlinear regime by running and analyzing MG N-Body simulations using a Parameterized-Post-Friedmann framework into the Gadget-2 simulation package (deliverable TJP2.2). Preliminary results for the simulations were obtained in the past. In collaboration with other DESC groups, we plan to make these simulations feedable to cosmic emulators that are practical for likelihood analyzes (deliverable TJP2.2, parts of CX6.2CS). We will also modify and integrate our current codes for consistency tests between data sets and probes into the pipeline (parts of deliverables CX8.2TJP, TJP2.3). We understand that other groups will contribute to some of these objectives but our team will focus and collaborate with others on the particular part of testing MG and models beyond wCDM and refine the DESC pipeline for this purpose. PI has been coordinating his work with the TJP and CS working groups and the DESC management team. PI is a full member of DESC since June 2013. He and his students have been contributing to LSST-DESC activities and work including TJP telecons, collaboration meetings, hack-weeks, and workshops. PI chaired or co-chaired sessions at collaboration meetings and hack-weeks about testing gravity and models beyond wCDM using LSST. He is coordinating the TJP2 projects for testing models beyond wCDM including the writing of DESC-research-note, development of code for pipeline, and N-Body simulations for MG and beyond wCDM models testable with LSST analyses. As stressed in the DESC white paper, SRM, and P5 report, one of the important questions in understanding cosmic acceleration and dark energy is to be able to distinguish whether the acceleration is due to a dark energy component in the universe or a modification to gravity. Answering these questions will have a significant impact on the question of cosmic acceleration and dark energy. The methods that we will use include analytical work, numerical code, and N-Body simulations. A first approach that that we will use consists of using growth rate parameters that enter the perturbed dynamics equations. These parameters take distinctive values for distinct gravity theories and have potential to distinguish between Dark Energy and Modified Gravity. The second method is to look for inconsistencies in Dark Energy parameter spaces using specific combinations of cosmological data sets. Our investigation addresses the Dark Energy problem that is relevant to the mission of the HEP program to understand how our universe works at its most fundamental level. It will allow us to make progress on the HEP mission to explore the nature of Dark Energy and the basic nature of space and time using future surveys such as LSST. The investigation supports the DOE HEP program Cosmic Frontier as it will contribute to the study and understanding of dark energy and fundamental properties of the universe. The investigation contributes directly to LSST-DESC key projects and their deliverables as described in the Science Road-map document to build analysis pipeline and to test dark energy and beyond wCDM models using LSST.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Modeling the direct sun component in buildings using matrix algebraic approaches: Methods and validation

Simulation tools that enable annual energy performance analysis of optically-complex fenestration systems have been widely adopted by the building industry for use in building design, code development, and the development of rating and certification programs for commercially-available shading and daylighting products. The tools rely on a three-phase matrix operation to compute solar heat gains, using as input low-resolution bidirectional scattering distribution function (BSDF) data (10–15° angular resolution; BSDF data define the angle-dependent behavior of light-scattering materials and systems). Measurement standards and product libraries for BSDF data are undergoing development to support solar heat gain calculations. Simulation of other metrics such as discomfort glare, annual solar exposure, and potentially thermal discomfort, however, require algorithms and BSDF input data that more accurately model the spatial distribution of transmitted and reflected irradiance or illuminance from the sun (0.5° resolution). This study describes such algorithms and input data, then validates the tools (i.e., an interpolation tool for measured BSDF data and the five-phase method) through comparisons with ray-tracing simulations and field monitored data from a full-scale testbed. Simulations of daylight-redirecting films, a micro-louvered screen, and venetian blinds using variable resolution, tensor tree BSDF input data derived from interpolated scanning goniophotometer measurements were shown to agree with field monitored data to within 20% for greater than 75% of the measurement period for illuminance-based performance parameters. The three-phase method delivered significantly less accurate results. We discuss the ramifications of these findings on industry and provide recommendations to increase end user awareness of the current limitations of existing software tools and BSDF product libraries.

14 SOLAR ENERGY↗
DOE OSTI2019

Data Sets for Evaluation of Building Fault Detection and Diagnostics Algorithms

This documentation and dataset can be used to test the performance of automated fault detection and diagnostics algorithms for buildings. The dataset was created by LBNL, PNNL, NREL, ORNL and ASHRAE RP-1312 (Drexel University). It includes data for air-handling units and rooftop units simulated with PNNL's large office building model.

AHU↗
DOE OSTI2019

Decision-support and Emissions Prediction Interactive Cities Tool

The Decision-support and Emissions Prediction Interactive Cities Tool (DEPICT) aims at predicting the cross-sectoral (building construction, operation and vehicles) energy consumption and greenhouse gases emissions at campus and urban scale. It leverages capabilities of multiple modeling tools: EnergyPlus for building operation, CalEEMod for building construction and gas vehicle, BEAM for electric vehicles and SAM for building–integrated photovoltaics. It distinguishes from other cross-sectoral model such as CalEEMod or BEST in that it uses physical models, rather than empirical models, for all sectors, which allows for a more accurate and customizable quantification. It is relevant for short-term multi-sectoral decision making by developers and city planners and long-term policy making by municipal and state officials. Information about all the developers

Ravache, Baptiste↗
DOE OSTI2013

Modelica buildings library

This paper describes the Buildings library, a free open-source library that is implemented in Modelica, an equation-based object-oriented modeling language. The library supports rapid prototyping, as well as design and operation of building energy and control systems. First, we describe the scope of the library, which covers HVAC systems, multi-zone heat transfer and multi-zone airflow and contaminant transport. Next, we describe differentiability requirements and address how we implemented them. We describe the class hierarchy that allows implementing component models by extending partial implementations of base models of heat and mass exchangers, and by instantiating basic models for conservation equations and flow resistances. We also describe associated tools for pre- and post-processing, regression tests, co-simulation and real-time data exchange with building automation systems. Furthermore, the paper closes with an example of a chilled water plant, with and without water-side economizer, in which we analyzed the system-level efficiency for different control setpoints.

42 ENGINEERING↗
DOE OSTI2023

Bishop Paiute Single Family Solar Home Project: Phase 4 (Final Technical Report)

The Bishop Paiute Tribe is committed to energy efficiency, renewable energy, and environmental protection and has a vision to install solar energy systems on all buildings on the Reservation where technically feasible. Through completion of the Bishop Paiute Tribe Residential Solar Program – Phase 4, Bishop Paiute Tribe continued its successful model partnering with non-profit solar installer GRID Alternatives to advance its vision and build energy self-sufficiency on the Bishop Paiute Reservation. The Bishop Paiute Tribe Residential Solar Program – Phase IV deployed 67 kW-AC of new clean, renewable energy through grid-tied, net-metered rooftop solar electric systems installed on a total of 20 (one more than the planned 19) existing owner-occupied, single-family homes for low-income families on the Reservation. This represents nearly 14% of the Reservation’s total “unsolarized” homes. These systems were provided at no cost to the homeowners, who will also receive energy efficiency education to further reduce energy consumption and lower electric bills. GRID led a solar installation for three (3) of the homes where Tribal/community members, were given an opportunity in participating in on-the-roof trainings to gain new skills while installing solar for their low-income community members. Subcontractors through GRID Sub Contractor Partnership Program (GRID SPP) led solar installations for seventeen (17) of the homes. Each installation provided paid employment for a solar trainee trainees hired by the SPP subcontractors as entry level solar installers. It is estimated that the installed 67 kW-AC of solar will produce at least 120,000 kWh/year, displacing at least 30-75% of the 20 homes’ total electricity use for a combined system lifetime electricity cost savings for the low-income homeowners of about $\$$500,000. It is further estimated that the installed renewable energy systems installed will prevent greenhouse gases by about 1,000 tons, equivalent to planting approximately 25,000 trees. Following the successful completed installations, it is expected that the Reservation and surrounding communities will benefit from improved air quality via reduced wood stove use for heating. Cumulatively with other initiatives, the project will result in nearly 40% of the Reservation’s solarizable homes being solarized. Overall, the triple impact of the phase 4 of the Bishop Paiute Tribe Residential Solar Program – Phase 4 is: 1) affordable energy for low-income families; 2) on-site clean energy production, 3) hands on training and paid solar installation work for local tribal/community workers. These impacts will support and grow the Tribe’s energy, economic, environmental, and social self-sufficiency and sovereignty amongst the neediest on the Reservation.

14 SOLAR ENERGY↗
DOE OSTI2023

Equitable Electrification Analysis for Existing Buildings in Richmond, CA

Over a 12-month period beginning in July 2022, NREL coordinated with a coalition of staff from the City of Richmond and local community organizations to develop and conduct a city-wide building energy use analysis and develop and assess the impacts of various approaches to electrifying and improving energy efficiency of all existing residential and commercial buildings within the city limits. Building on data available through NREL's ResStock™ and ComStock™ analysis tools, the authors looked at potential modeled impacts of building envelope and electrification upgrades on five indicators identified by the community coalition: building energy consumption, greenhouse gas (GHG) emissions, utility bill charges and cost-effectiveness, employment impacts, and health and safety impacts. This report summarizes the findings of that research and analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Energy saving potential of a two-pipe system for simultaneous heating and cooling of office buildings

This paper analyzes the performance of a novel two-pipe system that operates one water loop to simultaneously provide space heating and cooling with a water supply temperature of around 22 °C. To analyze the energy performance of the system, a simulation-based research was conducted. The two-pipe system was modelled using the equation-based Modelica modeling language in Dymola. A typical office building model was considered as the case study. Simulations were run for two construction sets of the building envelope and two conditions related to inter-zone air flows. To calculate energy savings, a conventional four-pipe system was modelled and used for comparison. The conventional system presented two separated water loops for heating and cooling with supply temperatures of 45 °C and 14 °C, respectively. Simulation results showed that the two-pipe system was able to use less energy than the four-pipe system thanks to three effects: useful heat transfer from warm to cold zones, higher free cooling potential and higher efficiency of the heat pump. In particular, the two-pipe system used approximately between 12% and 18% less total annual primary energy than the four-pipe system, depending on the simulation case considered.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

An analysis of the hybrid internal mass modeling approach in EnergyPlus

Accurate simulation of building system dynamics is particularly important for understanding building energy flexibility. Among all dynamics in a building, a zone temperature’s variation is especially important, as it significantly affects a building’s electricity load profile when its heating, ventilating, and air conditioning (HVAC) system is controlled with on/off cycles or setpoint reset strategies. To accurately simulate a zone temperature’s dynamics, internal mass needs to be modeled carefully. In this paper, we compare the two internal mass modeling approaches provided by EnergyPlus, i.e., internal mass object and zone air capacitance multiplier, to better understand their impacts on zone temperature simulation. Real building zone temperature dynamic data from small- and medium-sized office buildings are analyzed and compared with simulated data. In particular, we illustrate the effectiveness of a hybrid method of the two EnergyPlus modeling approaches, which yields more realistic zone temperature dynamics, especially when the zone is conditioned with heat pump systems with on/off cycling.

Chen, Zhelun↗
DOE OSTI2021

The energy saving potential of thermo-responsive desiccants for air dehumidification

The desiccant wheel is a promising technology for energy-efficient humidity control. However, its overall efficiency—hindered by the desiccant materials’ properties—remains low because traditional desiccants (e.g., silica gels) have a single isotherm regardless of their adsorption temperature. Thermo-responsive materials have been proposed to break this fixed affinity to water vapor, with drastically different adsorption isotherms depending on temperature. Its potential for improving dehumidification efficiency, however, has not been addressed. In this paper, we model the potential of a thermo-responsive interpenetrating polymer network (IPN) desiccant with temperature-dependent adsorption isotherms for energy-efficient dehumidification via a validated transient desiccant wheel model for humidity control of buildings. Thermo-responsive desiccants can improve the dehumidification performance due to their thermo-responsive switchable hydrophilicity below/above the lower critical solution temperature. Our analysis shows that thermo-responsive IPN desiccants can potentially reduce energy consumption by up to 30% compared to silica gels. Finally, the savings depend strongly on the critical temperature of the thermo-responsive desiccant and should be higher when the inlet temperatures are expected to be higher.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Landmark-Warped Emulators for Models with Misaligned Functional Response

Many computer models output functional data, and in some cases, these functional data have similar, but misaligned, shape characteristics. In this paper, we introduce a general approach for building emulators for computer models that output misaligned functional data when key values in the functional response (landmarks) can be easily identified. This approach has two main parts: modeling the aligned (using the landmarks) functional data, and modeling the functions that map the misaligned data to the aligned space (warping functions). As the warping functions are required to be monotonic, we give special attention to modeling monotonic functional response data. We discuss how our approach can be easily applied for a variety of typical emulators, such as Gaussian processes, Bayesian multivariate adaptive regression splines, and Bayesian additive regression trees, and how sensitivity analysis can be performed. We demonstrate our approach by building emulators for two applications: (1) a high-energy-density physics computer model used to simulate inertial confinement fusion ignition experiments, where model outputs are highly misaligned, and (2) a multiphysics continuum hydrocode used to simulate high-velocity impact experiments, where model outputs are only slightly misaligned. In case (1) traditional methods cannot be applied, while in (2) they can be applied, but the proposed method performs significantly better.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Engineering defect energy landscape of CoCrFeNi high-entropy alloys by the introduction of additional dopants

The concept of high-entropy alloys (HEAs) focusing on tuning the overall chemical complexity represents a novel alloy design strategy. In contrast, alloying of a metallic matrix with minor doping elements with limited and localized tunability has been a common practice to improve material performance. Combining the idea of globally engineering defect energy landscape in HEAs and the localized doping strategy in dilute alloys, in this work, we explore doping effects of minor elements in a HEA matrix to further enhance the overall and localized chemical tunability, aiming to improve its irradiation resistance. Specifically, we study the influence of minor Al, Cu, Ti, and Pd substitutional doping elements on defect energetics in a CoCrFeNi model HEA based on density-functional theory (DFT) calculations. The DFT results indicate that the formation and migration energies of vacancies can be strongly influenced when a dopant is introduced at the first nearest neighbor shells around a vacancy. On the other hand, interstitial energetics are only slightly affected. Among the four elements, Ti and Pd generally decrease vacancy formation energies and increase vacancy migration energies more significantly than Al and Cu. The doping effects become more pronounced when the concentration of the substitutional dopants increases. Based on the energy distributions obtained from DFT, we build a kinetic Monte Carlo (kMC) model to assess the impact of dopants on vacancy-mediated diffusivity in the doped HEAs. Our results suggest that Ti and Pd can lower the tracer diffusivity in the considered HEAs and act as trapping sites, whereas Cu may enhance the atomic transport. This work indicates that substitutional doping in HEAs is an effective strategy in metallurgy to further tune the defect and transport properties of complex alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Potential Adoption and Benefits of Co-Optimized Multimode Engines and Fuels for U.S. Light-Duty Vehicles

Exploring a diverse portfolio of technologies for decarbonization is crucial to understanding the potential impacts of different technological solutions and their associated environmental implications. Using high-octane, high-sensitivity biofuel blends in co-optimized multimode engines can increase engine efficiency and reduce vehicle emissions. Here, the multimode engine research focuses on the benefits of light-duty vehicle engines, which can operate in multiple modes depending on the vehicle's load. Low-temperature combustion can improve efficiency and reduce emissions (such as those from oxides of nitrogen and particulate matter) during low-load operation, while spark ignition performance is maintained in high-load operation. These advanced engines can be optimized to run on blends of biobased fuels. This analysis models scenarios for potential market adoption of co-optimized multimode vehicles fueled by three different bioblendstocks: ethanol, isopropanol, and isobutanol. An integrated modeling approach is used to forecast the energy and environmental impacts of the deployment of co-optimized multimode vehicles and fuels in the light-duty sector over the 2020-to-2050 time horizon. The multidisciplinary approach combines vehicle sales modeling, system dynamics modeling of the biorefining industry, and life cycle assessment to estimate the emissions and energy benefits. The models consider market forces such as consumer preferences for vehicle attributes, biofuel supply and demand dynamics subject to biorefinery capacity build-out and bioresource constraints, and forecasted changes to the U.S. bulk energy system over time. Market adoption of co-optimized vehicles is evaluated across a wide parameter space for incremental vehicle cost and engine efficiency improvement. This analysis reveals that the deployment of co-optimized multimode fuels and vehicles results in up to a 5% reduction in annual sector-wide life cycle greenhouse gas (GHG) emissions by 2050, relative to a business-as-usual scenario, but is also indicates environmental trade-offs, such as higher life cycle water-use. Emission benefits could potentially increase beyond 2050, as the new technologies penetrate the market and gain a foothold. Results also show that, under certain circumstances, vehicles with engines co-optimized for use with high-octane, high-sensitivity biofuel blends can be cost-competitive with conventional gasoline, while reducing GHG emissions. Our modeling results indicate that co-optimized multimode fuels and engines can be strategically leveraged in tandem with electrification to decarbonize the light-duty sector. Co-optimized vehicles could play a role in the early years of the time horizon, while electric vehicles (EVs) could become more competitive in the later years, highlighting the complementary benefits of these technologies for GHG reductions.

Oke, Doris↗
NASA NTRSDate not supplied

Estimating Future Changes of Energy Demand for Heating and Cooling Buildings at NASA Centers GC23J-1198

With its unique and trusted earth observations, NASA is a critical source in informing decisions that will help achieve the U.S. goal of Net-Zero Greenhouse Gas (GHG) Emissions by 2050. NASA’s Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data holdings within the energy, agricultural, and building heating/cooling design industries. POWER packages solar and meteorological data from several NASA projects in a user friendly GIS-enabled web services system (https://power.larc.nasa.gov). As part of the development of new data products to support the energy and building heating/cooling design communities, we estimate the changes in energy required to heat and cool buildings in the future climate at 14 different NASA site locations spread throughout the continental United States, as projected by CMIP6 climate models under different emissions scenarios. Bias-corrected downscaled time series of meteorological variables are taken from NASA Earth Exchange (NEX) Global Daily Downscaled Projections (GDDP-CMIP6) downscaled climate model data. The spread between the different model projections is accounted for by analyzing both the ensemble average of 22 CMIP6 models and 6 representative models with different climate sensitivities and different interannual variability. Changes in energy use are estimated in two ways. First, changes in the total annual heating and cooling degree days (HDD and CDD, respectively) are calculated relative to the current climate. This is done at all 14 sites. Second, the downscaled time series are used as inputs into RETScreen(R), a clean energy management decision tool, to give an estimate of heating/cooling energy use for a typical office building. We use this estimation method with model data at Langley Research Center. In the next 50 years, the annual total of HDD (CDD) is projected to decrease by 8-38% (increase by 5-28%) at all sites, with the increase in CDD typically a larger magnitude the decrease in HDD. For a typical small office building at Langley Research Center, the amount of energy needed to cool increases by 33-54% and the amount of energy to heat decreases by 29-40%. POWER is working to develop long term climate data services based on these results to include in future data products to provide to users.

Bradley M. Hegyi↗