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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Improving Gas Furnace Performance: A Field and Laboratory Study at End of Life

In 2010, natural gas provided 54% of total residential space heating energy the U.S. on a source basis, or 3.5 Quadrillion Btu. Natural gas burned in furnaces accounted for 92% of that total, and boilers and other equipment made up the remainder. A better understanding of installed furnace performance is a key to energy savings for this significant energy usage. Natural gas furnace performance can be measured in many ways. The annual fuel utilization efficiency (AFUE) rating provides a fixed value under specified conditions, akin to the EPA miles per gallon rating for new vehicles. The AFUE rating is provided by the manufacturer to the consumer and is a way to choose between models tested on the same basis. This value is commonly used in energy modeling calculations. ASHRAE 103 is a consensus furnace testing standard developed by the engineering community. The procedure provided in the standard covers heat-up, cool down, condensate heat loss, and steady-state conditions and an imposed oversize factor. The procedure can be used to evaluate furnace performance with specified conditions or with some variation chosen by the tester. In this report the ASHRAE 103 test result will be referred to as Annualized Efficiency (AE) to avoid confusion, and any non-standard test conditions will be noted. Aside from these two laboratory tests, steady state or flue loss efficiency can be measured in the field under many conditions; typically as found or tuned to the manufacturers recommended settings. In this report, AE and steady-state efficiency will be used as measures of furnace performance.

03 NATURAL GAS↗
DOE OSTI2015

OpenEIS: Users Guide

This document is a users guide for OpenEIS, a software code designed to provide standard methods for authoring, sharing, testing, using and improving algorithms for operational building energy efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

Summary of Needs and Opportunities from the 2011 Residential Energy Efficiency Meeting: Atlanta, Georgia, March 16-18, 2011

This meeting brought together more than 200 professionals representing organizations with vested interest in energy efficiency improvements in residential buildings. Participants identified or reinforced a wide variety of needs and issues associated with delivering high-performance homes in both new and existing home scenarios,

residential building energy efficiency↗
DOE OSTI2012

Results of Laboratory Testing of Advanced Power Strips

Presented at the ACEEE Summer Study on Energy Efficiency in Buildings on August 12-17, 2012, this presentation reports on laboratory tests of 20 currently available advanced power strip products, which reduce wasteful electricity use of miscellaneous electric loads in buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

University of Louisville Research and Energy Independence Program

The development of domestic, environmentally friendly and sustainable sources of energy and liquid fuel is a critical need for the United States (US). Kentucky (KY) is rich in natural energy and agricultural resources that could provide sustainable energy for the state and for the nation. New technology is needed to capture, store, and distribute this sustainable energy in KY. Development of KY’s sustainable energy resources will create economic benefit for the citizens of KY and can serve as a model for other states in the US. Existing technologies for solar energy collection and storage are practical for regions with high and consistent solar intensity, such as the southwest US. Solar energy is plentiful in KY, but is less intense and less regular. As such, novel innovative technology is needed to capture, store, and distribute this energy. KY also has plentiful biomass resources that can be converted to renewable fuels. In addition, the state offers low energy rates, which are conducive for any type of manufacturing industry. A manufacturing R&D center at the University of Louisville (UofL) can help attract high-tech manufacturing industries to the city of Louisville and the state of KY.

09 BIOMASS FUELS↗
DOE OSTI2017

Integrated Multi-Scale Data Analytics and Machine Learning for the Distribution Grid and Building-to-Grid Interface

This white paper introduces the application of advanced data analytics to the modernized grid. In particular, we consider the field of machine learning and where it is both useful, and not useful, for the particular field of the distribution grid and buildings interface. While analytics, in general, is a growing field of interest, and often seen as the golden goose in the burgeoning distribution grid industry, its application is often limited by communications infrastructure, or lack of a focused technical application. Overall, the linkage of analytics to purposeful application in the grid space has been limited. In this paper we consider the field of machine learning as a subset of analytical techniques, and discuss its ability and limitations to enable the future distribution grid and the building-to-grid interface. To that end, we also consider the potential for mixing distributed and centralized analytics and the pros and cons of these approaches. Machine learning is a subfield of computer science that studies and constructs algorithms that can learn from data and make predictions and improve forecasts. Incorporation of machine learning in grid monitoring and analysis tools may have the potential to solve data and operational challenges that result from increasing penetration of distributed and behind-the-meter energy resources. There is an exponentially expanding volume of measured data being generated on the distribution grid, which, with appropriate application of analytics, may be transformed into intelligible, actionable information that can be provided to the right actors – such as grid and building operators, at the appropriate time to enhance grid or building resilience, efficiency, and operations against various metrics or goals – such as total carbon reduction or other economic benefit to customers. While some basic analysis into these data streams can provide a wealth of information, computational and human boundaries on performing the analysis are becoming significant, with more data and multi-objective concerns. Efficient applications of analysis and the machine learning field are being considered in the loop.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Epidemiologic Study of One Million U.S. Radiation Workers and Veterans

The single most important question in radiation epidemiology is determining the level of health risks associated with radiation exposures that occur gradually over time. The study of one million early U.S. radiation workers and veterans has been designed to provide information on risk following chronic exposures by focusing on occupational groups with differing radiation exposure patterns, including intakes of radionuclides. The cost-efficient study builds on the investments made and foundations laid by investigators and government agencies over the past 30-40 years, which have established early worker cohorts that can now provide answers to questions on the lifetime human health risks associated with low-level radiation exposures. Within the overall goal of the epidemiologic study of one million U.S. radiation workers and veterans, this project had a total of nine specific aims which included studies of six populations for multiple endpoints including cancer overall mortality, leukemia and non-cancer mortality. The six populations included: Mound, Ohio, workers exposed to polonium, tritium and plutonium; nuclear power plant workers within the Landauer dosimetry and Nuclear Regulatory Commission data files; industrial radiographers; Mallinckrodt uranium workers; uranium workers who linked with the US Renal Data System; and nuclear weapons test participants. Over 400,000 workers and atomic veterans are included in these populations, with vital status being determined and analyses of all causes of death undertaken. A critical, integral component of the studies has been comprehensive evaluations of dosimetry involving, in many cases, complex dose reconstructions, and assessments of uncertainties. The work has also involved development of state-of-the art statistical approaches and modeling. All nine aims were accomplished successfully, resulting in publication of two NCRP documents, 13 literature papers, numerous Boice Reports in Health Physics News and many presentations of the work at scientific meetings. Furthermore, recommendations have been developed for an approach to integrate epidemiologic observations with radiation biology for risk assessment and biological models of radiation effect. The results of this project, as well as ongoing epidemiology studies of US radiation workers and veterans, are providing much-needed insights into complex issues regarding cancer and non-cancer health risks from low dose irradiation, how to apply a "dose and dose rate effectiveness factor" to scale the risks from the A-bomb survivor data to current occupational and environmental circumstances, and how to evaluate risk following intakes of radioactive substances. In addition to application to radiation workers, the results of the studies can provide guidance as society debates the role of nuclear energy and deals with nuclear waste, threats of terrorist attacks with nuclear/radiological devices, the remarkable increase in medical exposures to CT scans and nuclear imaging, and to NASA as radiation protection for astronauts on long-duration mission beyond low-Earth orbit is planned.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Field Validation of High-R Windows: Market Assessment and Program Plan

This report provides a market assessment for high-performance residential windows based on information gathered from key researchers and industry stakeholders including a series of interviews conducted with high-performance builders in 2019. The report also outlines the U.S. Department of Energy’s planned field validation activities in support of high-R windows and provides the basis for planned field validation approaches. Although the report may be of general interest to those who work in fields pertaining to building energy efficiency and/or market adoption of energy-efficiency measures, the primary intent of this report is to document market characteristics, barriers, and activities related to high-performance residential windows in order to assist with internal program planning.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

End-Use Load Profiles for the U.S. Building Stock: Market Needs, Use Cases, and Data Gaps

States and utilities are developing increasingly ambitious energy goals. Part of the solution to meeting these goals is improving electric grid flexibility. This includes shifting electric demand to align with grid needs. Thus, identifying and using building energy efficiency and other distributed energy resources to produce the highest grid value requires highly resolved, accurate and accessible electricity end-use load profiles (EULPs).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Design and Performance of Kokkos Staging Space toward Scalable Resilient Application Couplings

With the growing number of applications designed for heterogeneous HPC devices, application programmers and users are finding it challenging to compose scalable workflows as ensembles of these applications, that are portable, performant and resilient. The Kokkos C++ library has been designed to simplify this cumbersome procedure by providing an intra-application uniform programming model and portable performance. However, assembling multiple Kokkos-enabled applications into a complex workflow is still a challenge. Although Kokkos enables a uniform programming model, the inter-application data exchange still remains a challenge from both performance and software development cost perspectives. In order to address this issue, we propose Kokkos data staging memory space, an extension of Kokkos' data abstraction (memory space) for heterogeneous computing systems. This new abstraction allows to express data on a virtual shared-space for multiple Kokkos applications, thus extending Kokkos to support inter-application data exchange to build an efficient application workflow. Additionally, we study the effectiveness of asynchronous data layout conversions for applications requiring different memory access patterns for the shared data. Our preliminary evaluation with a synthetic benchmark indicate the effectiveness of this conversion adapted to three different scenarios representing access frequency and use patterns of the shared data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Seamless Hybrid-integrated Interconnect NEtwork (SHINE)

Large-scale date centers are becoming increasingly limited by the capacity of interconnects due to the rapid increasing power consumption and bandwidth demands driven by the rigorous down scaling of CMOS critical dimensions in according with the Moore’s Law. As a result of the continuing bandwidth scaling, optical interconnects based on parallel optics, where data are simultaneously transmitted along more than one lane, have becoming a preferred interconnected solution over copper cables. To building an efficient optical interconnect system, optical coupling between different elements, such as optical fibers, photonics chips, is a critical step, which is challenging due to the mode mismatch of varies optical ports. In this project, we proposed and demonstrated an optical interfacing scheme, which provided a light coupling approach with low energy loss, broadband operation, high alignment tolerance and compatible with scalable fabrication and testing. Here, the mode transformation is achieved by a total internal reflection from a chip integrated microscale freefrom surface. Due to the enormous light wavefront manipulating ability associated with the gigantic design space, the freeform couplers platform is universally applicable to a wide range of optical coupling scenarios, such as the interfacing between a waveguide to a fiber, another waveguide, surface normal device, or free space.

42 ENGINEERING↗
DOE OSTI2022

Using Open Data to Characterize Building Stock Trends for Energy and Equity Evaluation

This project provides a methodology for retrieving data from both existing public data and municipal open data sets to characterize changes in the building stock, socioeconomic, demographic, and climate indicators at a neighborhood scale. This methodology forms the basis for a geospatial dashboard to analyze and share the data. The developed methodology may be used to collect data for further energy equity analyses. Additional data sets, such as from other municipalities, may be incorporated in the future to expand the extents of the possible analysis.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

At the forefront of employee engagement

When it comes to paving the way for successful plutonium processing and manufacturing in the Lab's Plutonium Facility (PF-4), Fran Rocha has a lot on her plate. As a deputy division leader supporting programs in PF-4, Rocha works to ensure facility operations are safe and efficient while building on the foundations of science and engineering. In addition to addressing these technical challenges, Fran also focuses on attracting and retaining highquality staff in plutonium science and technology.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Evaluating Energy Savings Measures for Building Retrofits in an Interactive Workshop Environment

As part of the Better Buildings Summit 2025, a workshop was developed to simulate the decision process for implementing a set of energy savings measures on an existing building. As part of the workshop a "game" was created around energy savings strategies, and workshop participants selected renovation cards that provided data around the impacts of that renovation choice. Participants then were able to calculate overall savings and payback from the selected retrofit opportunities. This publication has been produced to package the resources used in the activity in an organized document so that the materials can be distributed and reused more broadly. It provides a comprehensive framework for replicating the workshop, including step-by-step instructions, retrofit "game cards" with data points, and facilitation guidance. By using these materials, readers can conduct their own version of this interactive workshop with stakeholders in their networks, such as building owners, energy managers, or policy makers. The goal is to empower users to simulate the decision-making processes for energy projects, foster collaboration, and drive meaningful discussions around cost-effective retrofit opportunities and goal-oriented outcomes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Transfer Learning for HVAC System Fault Detection

Faults in HVAC systems degrade thermal comfort and energy efficiency in buildings and have received significant attention from the research community, with data driven methods gaining in popularity. Yet the lack of labeled data, such as normal versus faulty operational status, has slowed the application of machine learning to HVAC systems. In addition, for any particular building, there may be an insufficient number of observed faults over a reasonable amount of time for training. To overcome these challenges, we present a transfer methodology for a novel Bayesian classifier designed to distinguish between normal operations and faulty operations. The key is to train this classifier on a building with a large amount of sensor and fault data (for example, via simulation or standard test data) then transfer the classifier to a new building using a small amount of normal operations data from the new building. We demonstrate a proof-of-concept for transferring a classifier between architecturally similar buildings in different climates and show few samples are required to maintain classification precision and recall.

transfer learning, Building HVAC, Bayesian framewo↗
DOE OSTI2018

Engineering Design with Digital Thread

Digital Thread is a data-driven architecture that links together information generated from across the product lifecycle. Though Digital Thread is gaining traction as a digital communication framework to streamline design, manufacturing, and operation processes in order to more efficiently design, build, and maintain engineering products, a principled mathematical formulation describing the manner in which Digital Thread can be used for critical design decisions remains absent. The contribution of this paper is to present such a formulation from the context of a data-driven design and decision problem under uncertainty. This formulation accounts for the fact that the design process is highly iterative and not all information is available at once. Output design decisions are made not only on what data to collect but also on the costs and benefits involved in experimentation and sensor instrumentation to collect that data. The mathematical formulation is illustrated through an example design of a structural fiber-steered composite component. In this example, the methodology highlights how different sequencing of small-scale experimentation with manufacturing and deployment lead to different designs and different associated costs.

42 ENGINEERING↗
DOE OSTI2023

Mechanical Ventilation and Indoor Air Quality in Recently Constructed U.S. Homes in Marine and Cold-Dry Climates Data from Building America Project

Data were collected to characterize whole-house mechanical ventilation (WHMV) and indoor air quality (IAQ) in 55 homes in the Marine climate of Oregon and Cold-Dry climate of Colorado in the U.S. Sixteen homes were monitored for two weeks, with and without WHMV operating. Ventilation airflows; airtightness; time-resolved CO2, PM2.5 and radon; and time-integrated NO2, NOX and formaldehyde were measured. Participants provided information about IAQ-impacting activities, perceptions and ventilation use. All homes had operational cooktop ventilation and bathroom exhaust. Thirty homes had equipment that could meet the ASHRAE 62.2-2010 standard with continuous or controlled runtime and 34 had some WHMV operating as found. Thirty-five of 46 participants with WHMV reported they did not know how to operate it, and only half of the systems were properly labeled. Two-week homes had lower formaldehyde, radon, CO2, and NO (NOX-NO2) when operated with WHMV; and also had faster PM2.5 decays following indoor emission events. Overall IAQ satisfaction was similar in Oregon and Colorado, but more Colorado participants (19 vs. 3%) felt their IAQ could be improved and more reported dryness as a problem (58 vs. 14%). The collected data indicate that there are benefits of operating WHMV, even when continuous use may not be needed because outdoor pollutant concentrations are low and indoor sources do not present substantial challenges.

air quality↗
DOE OSTI2023

ResStock: Annual Baseline Results with Component Loads

The ResStock Analysis Tool was developed by NREL with support from the U.S. Department of Energy to provide a new approach to large-scale residential analysis by combining large public and private data sources, statistical sampling, detailed sub hourly building simulations, and high-performance computing. This combination achieves unprecedented granularity and accuracy in modeling the diversity of the housing stock and the distributional impacts of building technologies in different communities. The annual baseline energy results from a national-scale ResStock run use typical meteorological year 3 (TMY3) files for energy simulations. Results include heating and cooling loads for individual components of each building. Component loads describe the heating/cooling load that can be attributed to specific elements of a home, such as heat transfer through walls or internal gains. Additionally, these results include the standard ResStock outputs for housing characteristics and numerous energy outputs by end-use and fuel. A snapshot of the ResStock version used to produce this data, including a configuration file for the run can be found using the Source Code resource link.

Array↗