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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Blending Behavioral Science and Physics-Based Models Inform Equitable Decarbonization Pathways in the US Housing Stock: Preprint

A just energy transition is an imperative of the Biden-Harris Administration, emphasizing the equitable distribution of benefits through energy-efficient and decarbonizing household technologies. Understanding the factors that increase a household's willingness to adopt these technologies helps policymakers implement more targeted and effective approaches. Our research addresses this by blending 550,000 housing stock types and energy simulation data with a nationally representative survey on residential technology adoption and decision-making (n=10,000). We identify energy equity gaps across tenure and income, highlighting disparities in energy burdens and insecurity. Findings show that households with prior modification experience are more willing to renovate, suggesting that small-scale retrofit programs could foster greater willingness. Energy secure but burdened homeowners are least willing to modify, highlighting the need to consider energy bill perceptions in policy design. Nearly half of US households that are energy burdened also face energy insecurity, with a significant gap in assistance for low-income households. We emphasize the need to understand household perceptions to improve policy. This research underscores the importance of understanding household behaviors to improve policy effectiveness, offering actionable insights for policymakers to promote equitable housing upgrades and advance a decarbonized future.

behavioral science↗
DOE OSTI2023

Influence of building heat distribution temperatures on the energy performance and sizing of 5th generation district heating and cooling networks

This paper investigates the energy performance and sizing criteria of 5th generation district heating and cooling (5GDHC) networks as a function of the heat distribution temperature in the building systems connected to the district network. An energy simulation model of a 5GDHC network was developed in Modelica for a case study located in Denmark. Calculations were carried out for four different building heating systems. Simulation results show that reducing the heat distribution temperatures from 70 °C to 23 °C leads to around 40% annual electric energy savings (from 10.4 kWh/m 2 to 6.2 kWh/m 2 ) for the operation of the heat pumps. Heat distribution temperatures of 23 °C cause higher water mass flow rates through the network, leading to annual electric energy consumption for the circulation pumps that are almost doubled (from 0.16 kWh/m 2 to 0.3 kWh/m 2 ) compared to the reference case at 70 °C. Furthermore, the paper discusses how the results obtained from the Danish case study can be generalized and applied to other cases using a simplified mathematical approach. In conclusion, it is found that about 1.5% of electric energy savings can be achieved for each temperature degree reduction in the heat distribution system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

Technical Subtopic 2.1: Modeling Variable Refrigerant Flow Heat Pump and Heat Recovery Equipment in EnergyPlus

The University of Central Florida/Florida Solar Energy Center, in cooperation with the Electric Power Research Institute and several variable-refrigerant-flow heat pump (VRF HP) manufacturers, provided a detailed computer model for a VRF HP system in the United States Department of Energy’s (U.S. DOE) EnergyPlus™ building energy simulation tool. Detailed laboratory testing and field demonstrations were performed to measure equipment performance and compare this performance to both the manufacturer’s data and that predicted by the use of this new model through computer simulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

A Pilot Demonstration of Electrochromic and Thermochromic Windows in the Denver Federal Center, Building 41, Denver, Colorado

Chromogenic glazing materials are emerging technologies that tint reversibly from a clear to dark tinted state either passively in response to environmental conditions or actively in response to a command from a switch or building automation system. Switchable coatings on glass manage solar radiation and visible light while enabling unobstructed views to the outdoors. Building energy simulations estimate that actively controlled, near-term chromogenic glazings can reduce perimeter zone heating, ventilation, and airconditioning (HVAC) and lighting energy use by 10-20% and reduce peak electricity demand by 20-30%, achieving energy use levels that are lower than an opaque, insulated wall. This project demonstrates the use of two types of chromogenic windows: thermochromic and electrochromic windows. By 2013, these windows will begin production in the U.S. by multiple vendors at high-volume manufacturing plants, enabling lower cost and larger area window products to be specified. Both technologies are in the late R&D stage of development, where cost reductions and performance improvements are underway. Electrochromic windows have been installed in numerous buildings over the past four years, but monitored energy-efficiency performance has been independently evaluated in very limited applications. Thermochromic windows have been installed in one other building with an independent evaluation, but results have not yet been made public.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Existing Whole-House Solutions Case Study: Greenbelt Homes, Inc. Pilot Retrofit Project

In the fall of 2010, a multiyear pilot energy efficiency retrofit project was undertaken by Greenbelt Homes, Inc., (GHI) a 1,566 home cooperative of circa 1930 and 1940 homes in Greenbelt, Maryland. GHI established this pilot project to serve as a basis for decision making for the rollout of a community-wide upgrade program that will incorporate energy efficiency improvements to the building envelope and mechanical equipment. With the community upgrade fully funded by the cooperative through their membership without outside subsidies, this project presents a unique opportunity to evaluate and prioritize the wide range of benefits of high-performance retrofits based on member experience with and acceptance of the retrofit measures implemented during the pilot project. Addressing the complex interactions between benefits, trade-offs, construction methods, project management implications, realistic upfront costs, financing, and other considerations, serves as a case study for energy retrofit projects that include high-performance technologies based on the long-term value to the homeowner. The pilot project focused on identifying the added costs and energy-savings benefits of improvements. Phase 1—baseline evaluation for a representative set of 28 homes sited in seven buildings; Phase 2—installation of the building envelope improvements and continued monitoring of the energy consumption for the heating season; Phase 3—energy simulations supporting recommendations for HVAC and water heating upgrades.

Attic↗
DOE OSTI2020

Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches

Regulations corroborate the importance of retrofitting existing building stocks or constructing new energy-efficient districts. There is, thus, a need for modeling tools to evaluate energy scenarios to better manage and design cities, and numerous methodologies and tools have been developed. Among them, Urban Building Energy Modelling (UBEM) tools allow the energy simulation of buildings at large scales. Choosing an appropriate UBEM tool, balancing the level of complexity, accuracy, usability, and computing needs, remains a challenge for users. The review focuses on the main bottom-up physics-based UBEM tools, comparing them from a user-oriented perspective. Five categories are used: (i) the required inputs, (ii) the reported outputs, (iii) the exploited workflow, (iv) the applicability of each tool, and (v) the potential users. Moreover, a critical discussion is proposed, focusing on interests and trends in research and development. The results highlighted major differences between UBEM tools that must be considered to choose the proper one for an application. Finally, barriers of adoption of UBEM tools include the needs of a standardized ontology, a common three-dimensional city model, a standard procedure to collect data, and a standard set of test cases. This feeds into future development of UBEM tools to support cities’ sustainability goals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Accuracy of HVAC Load Predictions: Validation of EnergyPlus and DOE-2 using FLEXLAB Measurements

The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

SU-E-T-90: Concrete Forward-Scatter Fractions for Radiotherapy Shielding Applications

Purpose: There is little instruction within the primary shielding guidance document NCRP 151 for vault designs where the primary beam intercepts the maze. We have conducted a Monte-Carlo study to characterize forward-scattered radiation from concrete barriers with the intent of quantifying what amount of additional shielding outside the primary beam is needed in this situation. Methods: We reproduced our vault in MCNP 5 and simulated spectra obtained from the literature and from our treatment planning system for 10 and 18 MV beams. Neutron and gamma-capture contributions were not simulated. Energy deposited was scored at isocenter in a water phantom, within various cells that comprised the maze, and within cells that comprised the vault door. Tracks were flagged that scattered from within the maze to the door and their contributions were tallied separately. Three different concrete mixtures found in the literature were simulated. An empirically derived analytic equation was used for comparison, utilizing patient scatter fractions to approximate the scatter from concrete. Results: Our simulated data confirms that maze-scattered radiation is a significant contribution to total photon dose at the door. It contributes between 20-35% of the photon shielding workload. Forward-scatter fractions for concrete were somewhat dependent on concrete composition and the relative abundance of higher-Z elements. Scatter fractions were relatively insensitive to changes in the primary photon spectrum. Analytic results were of the same magnitude as simulated results. Conclusions: Forward-scattered radiation from the maze barrier needs to be included in the photon workload for shielding calculations in non-standard vault designs. Scatter fractions will vary with concrete composition, but should be insensitive to spectral changes between machine manufacturers. Further plans for investigation include refined scatter fractions for various concrete compositions, scatter fraction measurement, and simulation of photo-nuclear interaction within the maze barrier for high-energy beams.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Fast and self-learning indoor airflow simulation based on in situ adaptive tabulation

Fast simulation for stratified indoor airflow distributions is desired for various applications, such as design of advanced indoor environments, emergency management, and coupled annual energy simulation for buildings with stratified air distributions. Reduced order models trained by pre-computed computational fluid dynamics results are fast, but their prediction may be inaccurate when applied for conditions outside the training domain. To overcome this limitation, we propose in this paper a fast and self-learning model based on an in situ adaptive tabulation (ISAT) algorithm, which is trained by a fast fluid dynamics (FFD) model as an example. The idea is that the ISAT will retrieve the solutions from an existing data set if the estimated prediction error is within a pre-defined tolerance. Otherwise, the ISAT will execute the FFD simulation, which is accelerated by running in parallel on a graphics processing unit, for a full-scale simulation. This paper systematically investigates the feasibility of the ISAT for indoor airflow simulations by presenting the ISAT-FFD implementation alongside results related to its overall performance. Using a stratified indoor airflow as an example, we evaluated how the training time of ISAT was impacted by four factors (training methods, error tolerances, number of inputs, and number of outputs). Then we demonstrated that a trained ISAT model can predict the key information for inputs both inside and outside the training domain. The ISAT was able to answer query points both inside and close to training domain using retrieve actions within a time less than 0.001 s for each query. In conclusion, we provided suggestions for using the ISAT for building applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Predicting Chemical Reaction Barriers with a Machine Learning Model

In the past few decades, tremendous advances have been made in the understanding of catalysis at solid surfaces. Despite this, most discoveries of materials for improved catalytic performance are made by a slow trial and error process in an experimental laboratory. Computational simulations have begun to provide a way to rationally design materials for optimizing catalytic performance, but due to the high computational expense of calculating transition state energies, simulations cannot adequately screen the phase space of materials. In this work, we attempt to mitigate this expense by using a machine learning approach to predict the most expensive and most important parameter in a catalyst’s affinity for a reaction: the reaction barrier. Previous methods which used the step reaction energy as the only parameter in a linear regression had a mean absolute error (MAE) on the order of 0.4 eV, too high to be used predictively. Here in our work, we achieve a MAE of about 0.22 eV, a marked improvement towards the goal of computational prediction of catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Simulation Models for Improved Water Heating Systems

This research improved the design of computer simulation models of water heaters and hot water distribution systems to increase their accuracy and flexibility, and to allow for future inclusion of new technologies. The models will be incorporated into the Buildings Library at Lawrence Berkeley National Laboratory to assist those performing whole-building energy simulations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Correlating and Simulating Socio-Demographically Driven Residential End-Use Activity Schedules

Incorporating socio-demographic and behavioral considerations into decision-support tools is crucial for identifying gaps and addressing consumer needs to ensure reliable and affordable energy solutions. In energy simulation models, the correlation between socio-demographics and time-use behavior is not well-captured. Thus, we developed a large-scale simulation workflow to generate schedules for 10 residential activities across 24 population segments defined by age, income, and employment status. Using pre-pandemic 2015-2019 American Time Use Survey (ATUS) data, we used ANOVA to confirm the correlation between demographic factors and time use. We explored three k-modes clustering methods-backward, forward, and a new hybrid approach-to delineate the occupancy patterns based on demographics. Using the probability of cluster membership for each population segment and a time inhomogeneous Markov chain to generate activity transition probabilities for each cluster, we simulated 50,000 schedules per segment and validated them against the ATUS data. The hybrid method produced the most socio-demographically differentiated clusters while demonstrating comparable performance to other approaches, with an overall root mean square error of 0.12 for both weekday and weekend schedules. Thus, the hybrid method, where each cluster is dominated by certain demographic segments and occupancy patterns, offers more modeling versatility in terms of scenario analysis. The new workflow improves the socio demographic differentiation of energy consumption by considering differences in time use. This approach enables future research on demographically segmented time of use (TOU) energy consumption, including impacts of TOU utility bills and rate analysis, long-run marginal emissions, and energy retrofits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Performance Assessment of the Overall Building Envelope Thermal Performance—Building Envelope Performance (BEP) Metric

Today, to describe the thermal performance of the building envelope and its components we use a variation of metrics; such as, R-value, ACH (air exchange rate per hour), SHGC (solar heat gain coefficient) of windows, U-factor etc. None of these performance indicators is meant to represent the overall thermal performance. In this paper, such a metric is introduced, the BEP (building envelope performance) value. Unlike the thermal resistance, typically expressed as an R-value, the BEP-value considers additional elements of heat transfer that affect the energy demand of the building because of exterior and interior (solar) thermal loads: conductive and radiant heat transfer, and air infiltration. To demonstrate BEP’s utility, validation studies were carried out by comparing the BEP-value to theoretical results using whole building energy simulation tools such as EnergyPlus and WUFI Plus. Results show that BEP calculations are comparable to calculations made using these simulation tools and that unlike other similar metrics, the BEP-value accounts for all heat transfer mechanisms that are relevant for the overall energy performance of the building envelope. The BEP-value thus allows comparing envelopes of buildings with different use types in a fair and realistic manner.

42 ENGINEERING↗
DOE OSTI2015

Whitepaper prepared for DOE Workshop on Integrated Simulations for Magnetic Fusion Energy Sciences: Topic E: Beyond interpretive simulations

Predictive simulations of magnetic confinement fusion and burning plasmas will require the quantification of all uncertainties and errors relating to the simulation capabilities. These include: discretization error (temporal and spatial); incomplete convergence error (nonlinear, linear, etc.); uncertainties in input data (initial conditions, boundary conditions, coefficients, thermo-physical properties, source terms, etc.); and uncertainties in the component models (the specific form and parameter values).13 Typically, there is a focus on model parameter uncertainties but uncertainties about which model to use and about the bias or discrepancy of a particular model (sometimes called model form error) often dominate parameter uncertainty. This whitepaper addresses the challenges of performing uncertainty quantification (UQ) for expensive computational models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

Evolutionary Tuning of Building Models to Monthly Electrical Consumption

Building energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Calibrating models is costly because it is currently an art which requires significant manual effort by an experienced and skilled professional. An automated methodology could significantly decrease this cost and facilitate greater adoption of energy simulation capabilities into the marketplace. The Autotune project is a novel methodology which leverages supercomputing, large databases of simulation data, and machine learning to allow automatic calibration of simulations to match measured experimental data on commodity hardware. This paper shares initial results from the automated methodology applied to the calibration of building energy models (BEM) for EnergyPlus (E+) to reproduce measured monthly electrical data.

Garrett, Aaron↗
DOE OSTI2015

Building America Case Study: Whole-House Solutions for Existing Homes: Greenbelt Homes, Inc. Pilot Retrofit Program; Whole-House Solutions for Existing Homes, Energy Efficiency & Renewable Energy (EERE)

In the fall of 2010, a multiyear pilot energy efficiency retrofit project was undertaken by Greenbelt Homes, Inc, (GHI) a 1,566 home cooperative of circa 1930 and 1940 homes in Greenbelt, Maryland. GHI established this pilot project to serve as a basis for decision making for the rollout of a decade-long community-wide upgrade program that will incorporate energy efficiency improvements to the building envelope and mechanical equipment. With the community upgrade fully funded by the cooperative through their membership without outside subsidies, this project presents a unique opportunity to evaluate and prioritize the wide-range of benefits of high-performance retrofits based on member experience with and acceptance of the retrofit measures implemented during the pilot project. Addressing the complex interactions between benefits, trade-offs, construction methods, project management implications, realistic upfront costs, financing, and other considerations, serves as a case study for energy retrofit projects to include high-performance technologies based on the long-term value to the homeowner. The pilot project focused on identifying the added costs and energy savings benefits of improvements. Phase 1: baseline evaluation for a representative set of 28 homes sited in seven buildings; Phase 2: installation of the building envelope improvements and continued monitoring of the energy consumption for the heating season and energy simulations supporting recommendations for HVAC and water heating upgrades to be implemented in Phase 3.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1979

The updated algorithm of the Energy Consumption Program (ECP): A computer model simulating heating and cooling energy loads in buildings

The energy Comsumption Computer Program was developed to simulate building heating and cooling loads and compute thermal and electric energy consumption and cost. This article reports on the new additional algorithms and modifications made in an effort to widen the areas of application. The program structure was rewritten accordingly to refine and advance the building model and to further reduce the processing time and cost. The program is noted for its very low cost and ease of use compared to other available codes. The accuracy of computations is not sacrificed however, since the results are expected to lie within + or - 10% of actual energy meter readings.

Lansing, F. L.↗
DOE OSTI2024

The role of air sealing while ground source heat pump system retrofits in the U.S. single-family houses

Widespread commercial adoption of ground source heat pumps (GSHP) is hindered by the relatively high initial cost associated with drilling boreholes in the ground to deploy ground heat exchangers. Reducing the energy demand of buildings has the potential to reduce the required borehole length and the associated drilling costs. In single-family residential buildings, air sealing can significantly lower heating energy usage, according to recent studies and reports. Thus, air sealing in conjunction with GSHP retrofits can lower the required GSHP system's capacity and borehole length to meet the thermal demands of the buildings. In order to understand the role of combining air sealing with GSHP retrofit quantitatively, the current study employs a whole building energy simulation tool integrated with an advanced design tool for the ground heat exchanger to determine changes in required GSHP capacity, total borehole length, and building energy consumption for with- and without-air sealing in single-family houses in 3 climate zones in the United States. The study considers one representative city for each climate zone, Phoenix, AZ for a hot climate, Seattle, WA for a moderate climate, and Minneapolis, MN for a cold climate. The results from this study show that reducing air infiltration from 0.8 ACH to the minimum ventilation requirement (0.35 ACH) can reduce borehole length requirement by up to 24% in Phoenix, 32% in Seattle, and 70% in Minneapolis. A similar magnitude of reduction can be seen for GSHP capacity and total building energy usage as well.

Prem Anand Jayaprabha, Jyothis Anand↗