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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Applications of reduced-basis methods to the nuclear single-particle spectrum

Reduced-basis methods provide a powerful framework for building efficient and accurate emulators. Although widely applied in many fields to simplify complex models, reduced-basis methods have only been recently introduced into nuclear physics. In this Letter we build an emulator to study the single-particle structure of atomic nuclei. By scaling a suitable mean-field Hamiltonian, a “universal” reduced basis is constructed capable of accurately and efficiently reproduce the entire single-particle spectrum of a variety of nuclei. Indeed, the reduced-basis model reproduces both ground- and excited-state energies as well as the associated wave functions with remarkable accuracy. Here our results bode well for more demanding applications that use Bayesian optimization to calibrate nuclear energy density functionals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Importance of Window Installation in Residential Building Envelopes Having Continuous External Insulation in Order to Realize Energy Efficiency

Residential buildings are one of the prime candidates in the United States for reducing energy consumption. Continuous exterior insulation (CEI) is being used increasingly often in residential buildings to improve energy efficiency. Windows constitute 15–40% of a building envelope and are the weakest component in energy performance. The installation of windows in walls with CEI has not been well evaluated. We identified four cases of installing windows in walls with CEI of 25–76 mm (1–3 in.) thickness and analyzed the energy loss between the window and wall interface (flanking loss), structural issues, air leakage, and moisture penetration. Thermal analysis showed that the insulation value (RSI) of the 305 mm (12 in.) perimeter wall surrounding a window decreased by 7.6–34.5% in the four cases when compared with the RSI of the wall without the window. A window installation method is proposed to address the issues likely to occur with installation methods currently being used in the field. An out-of-the-box installation system was also designed to achieve a better thermal performance, cost effectiveness, and structural performance in high-performance residential buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

A cross-sectional study of the temporal evolution of electricity consumption of six commercial buildings

Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged- Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15- minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Pilgrim Hot Springs Building Dimensions and Energy Modeling

This dataset was created to model the anticipated heating load of a geothermal project in development for the historical site of Pilgrim Hot Springs, and adds to the history of geothermal studies at the site. Models include an historical building (Nun's Quarters), existing modern buildings (Caretaker's Cabin, Igloo, Visitor's Cabin, Staff Shower Hut), and planned building projects (Changing Room, Greenhouse). Modeling results were used to determine feasible geothermal system typologies. The previous study linked below ("Village of Solomon Development of Energy Efficiency Building Standards for New Construction") feeds in to this project. The dataset includes DWG drawings and AKwarm energy models (.hm2) of a subset of existing buildings at the site of Pilgrim Hot Springs. All buildings were modeled in their current state, and some were additionally modeled with improvements to the building envelope. Energy modeling results exported from AKwarm include .htm and .png images.

AKwarm↗
DOE OSTI2020

Assessing and Reducing Plug and Process Loads in Office Buildings

Plug and process loads (PPLs) account for 33% of U.S. commercial building electricity consumption (McKenney et al. 2010). (See Figure 1.) Minimizing these loads is a significant challenge in the design and operation of an energy-efficient building. Lobato et al. (2011) and Lobato et al. (2012) define PPLs as energy loads that are not related to general lighting, heating, ventilation, cooling, and water heating, and that typically do not provide comfort to the occupants. The percentage of total building energy use from PPLs is increasing. According to the U.S. Department of Energy (DOE), by 2030, commercial building energy consumption is expected to increase by 24%; PPL energy consumption is anticipated to increase by 49% in the same time frame (DOE 2010). These trends illustrate the importance of PPL energy reduction to achieve an overall goal of reducing whole-building energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Assessing and Reducing Plug and Process Loads in Retail Buildings

Plug and process loads (PPLs) account for 33% of U.S. commercial building electricity consumption (McKenney et al. 2010). (See Figure 1.) Minimizing these loads is a significant challenge in the design and operation of an energy-efficient building. Lobato et al. (2011) and Lobato et al. (2012) define PPLs as energy loads that are not related to general lighting, heating, ventilation, cooling, and water heating, and that typically do not provide comfort to the occupants. The percentage of total building energy use from PPLs is increasing. According to the U.S. Department of Energy (DOE), by 2030, commercial building energy consumption is expected to increase by 24%; PPL energy consumption is anticipated to increase by 49% in the same time frame (DOE 2010). These trends illustrate the importance of PPL energy reduction to achieve an overall goal of reducing whole-building energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

Enhancing Building Resilience: Maintaining Energy Efficiency and Thermal Comfort During Power Outages in Cold Climates

The increasing frequency and intensity of extreme weather events, such as heatwaves and cold snaps, present significant challenges to building energy performance and occupant comfort. Highly correlated with climate events are widespread long duration power interruptions that may affect thousands of buildings and millions of customers. This study evaluates the impact of building energy performance and occupant thermal comfort in medium-sized office buildings in a cold climate region. Using energy models representing pre-1980 and 2019 vintages, simulations were conducted to assess energy performance under typical weather conditions and occupant thermal comfort during power interrupted extreme cold snap and heatwave climate events under both current 2020s and future 2050s weather conditions. The results show a projected 33% increase in cooling energy demand and a 19% reduction in heating energy by 2050. Findings reveal that older buildings are more susceptible to cold discomfort during cold snaps, while modern airtight buildings are more vulnerable to overheating during heatwaves. Various passive energy efficiency measures, such as improved infiltration control, thermal windows, solar-controlled windows, and cool envelopes, were evaluated for their ability to mitigate thermal discomforts. Solar controlled windows and weatherstripping contribute to reducing cold thermal discomfort by 21% during a power-interrupted cold snap. Solar-controlled windows were found to reduce hot thermal discomfort by 34% during a future power-interrupted heatwave. The study highlights the importance of targeted retrofitting strategies to enhance thermal resilience, especially during power outages, to ensure occupant safety and comfort during extreme climate events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

2021 Thermal Energy Storage Systems for Buildings Workshop: Priorities and Pathways to Widespread Deployment of Thermal Energy Storage in Buildings

The 2021 U.S. Department of Energy's (DOE) "Thermal Energy Storage Systems for Buildings Workshop: Priorities and Pathways to Widespread Deployment of Thermal Energy Storage in Buildings" was hosted virtually on May 11 and 12, 2021. This report provides an overview of the workshop proceedings. Organized by DOE's Building Technologies Office (BTO), the National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, and Oak Ridge National Laboratory, the workshop convened more than 600 stakeholders from around the world to discuss the need for advancing the deployment of thermal energy storage (TES) in buildings. This workshop was designed to build on BTO's webinar series and 2019 workshop. The goals of this workshop were to promote discussion on TES related to: 1. Market adoption and deployment barriers, 2. Key applications and value drivers, 3. System cost, performance, and market requirements, and 4. End-use specific needs. The workshop took place over two days and consisted of keynote presentations, moderated panels, breakout sessions, and open discussion forums. The keynote presentations introduced opportunities for building TES, barriers to widespread deployment, and future visions. Moderated panel discussions presented diverse perspectives, breakout sessions provided opportunities for more intimate conversations, and open discussions captured feedback from the entire workshop group. Over the course of the two days, attendees exchanged experiences and ideas surrounding multiple aspects of TES in buildings. The first section of this report provides background on the motivations behind advancing TES for residential and commercial buildings and elaborates on the workshop objectives. The second section details the workshop structure and participant demographics. The third section provides key findings of the discussions that took place during the breakout sessions. Finally, this report details recommendations and actions to increase the TES deployment. Several recommendations from workshop attendees are presented in Table ES-1. TES holds significant potential to help increase building efficiency, grid-interactivity, and energy resilience, as well as reduce associated carbon emissions. The outputs generated from this workshop will aid stakeholders in advancing TES in buildings through a deeper understanding of the opportunities and barriers surrounding widespread deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems

We report faults in Heating, Ventilation, and Air Conditioning (HVAC) systems of buildings result in significant energy waste in building operation. With fast-growing sensing data availability and advancement in computing, computational modeling has demonstrated strong capability to detect and diagnose HVAC system faults, hence, ensuring efficient building operation. This paper comprehensively reviews the state-of-the-art computing-based fault detection and diagnosis (FDD) for HVAC systems. Overall, the reviewed computing-based FDD methods are classified as two major approaches: knowledge-based and data-driven approaches. We then identify multiple important topics, including data availability, training data size, data quality, approach generality, capability, interpretability, and required modeling efforts, along with corresponding metrics to summarize the most updated FDD development. Generally, the knowledge-based approaches are further divided as physics-based modeling, Diagnostic Bayesian Network, and performance indicator-based methods while data-driven approaches include supervised learning, unsupervised learning, and regression and statistics-based methods. State-of-the-art FDD development, remaining challenges, and future research directions are further discussed to push forward FDD in practice. Availability of fault data, capability of existing methods to deal with complex fault situations (such as simultaneous faults), modeling interpretability for data-driven methods, and required engineering efforts for physics-based methods are identified as remaining challenges in FDD development. Improving modeling fidelity and reducing modeling efforts are essential for applying physics-based methods in real buildings. Meanwhile, addressing fault data availability, increasing algorithm adaptability, and handling multiple faults are essential to further enhance the applicability of data-driven FDD approaches.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Brick Schema Standardized Plug Load Control Strategies for Load Reduction: Preprint

Plug loads comprise a significant percentage of commercial building energy consumption. Applying intelligent controls to turn off plug loads when unused can provide dynamic load reduction and flexibility, which are key traits of grid-interactive efficient buildings. This capability is important for equitable decarbonization as it can enable disadvantaged communities to electrify buildings without costly upgrades to electrical infrastructure. In this work, we present the effectiveness of various control strategies along with the operational lessons that informed their design. During a three-year period, we operated over 600 smart outlets in 12 university office buildings. The attached plug loads consisted primarily of printers, TVs, water dispensers, and copiers. After recording baseline power measurements for one year, we designed plug load control (PLC) strategies for each plug load type, use, and for different risk tolerance levels because PLC can potentially be disruptive to daily work. We used the Brick Schema to facilitate the management of plug load locations and other metadata. For advanced controls, we integrated the smart plugs with heating, ventilation, and air conditioning (HVAC) systems through the campus building automation system. We found static schedules to be the least disruptive and most predictable for occupants, resulting in 38% and 66% energy savings in two studies. For printers, print server-triggered PLC produced 86% savings, the highest of all strategies with minimal occupant impact. Scheduling of water dispensers and digital signage TVs produced 49% and 70% savings respectively with opportunities to improve performance with the use of HVAC occupancy data.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2017

Energy savings potential from improved building controls for the US commercial building sector

The U.S. Department of Energy’s (DOE’s) Building Technologies Office (BTO) sponsored a study to determine the potential national savings achievable in the commercial building sector through widespread deployment of best practice controls, elimination of system and component faults, and use of better sensing. Detailed characterization of potential savings was one source of input to set research, development, and deployment (RD&D) goals in the field of building sensors and controls. DOE’s building energy simulation software, EnergyPlus, was employed to estimate the potential savings from 34 measures in 9 building types and across 16 climates representing almost 57% of commercial building sector energy consumption. In addition to estimating savings from individual measures, three packages of measures were created to estimate savings from the packages. These packages represented an 1) efficient building, 2) typical building, and 3) inefficient building. To scale the results from individual measures or a package to the national scale, building weights by building type and climate locations from the Energy Information Administration’s 2012 Commercial Building Energy Consumption Survey (CBECS) were used. The results showed significant potential for energy savings across all building types and climates. The total site potential savings from individual measures by building type and climate location ranged between 0% and 25%. The total site potential savings by building type aggregated across all climates (using the CBECS building weights) for each measure varied between 0% and 16%. The total site potential savings aggregated across all building types and climates for each measure varied between 0% and 11%. Some individual measures had negative savings because correcting underlying operational problems (e.g., inadequate ventilation) resulted in increased energy consumption. When combined into packages, the overall national savings potential is estimated to be 29%; seven of the nine building types were in the range of 23 to 29% and two exceeded 40%. The total potential national site savings in for each building type ranged between 95x106 GJ (0.09 Quadrillion British thermal units [Quads]; Large Hotels) to 222x106 GJ (0.21 Quads; Large Office, Hospital Administrative areas, and College/University), resulting in total site savings of 1,393x106 GJ (1.32 Quads) when the three packages are applied to the U.S. commercial buildings stock. Using the source (or primary) energy conversion factors of 1.05 for natural gas and 3.14 for electricity resulted in an approximate potential primary energy savings of 2,912x106 GJ (2.76 Quads), which would be 15% of the sector’s 2015 use of approximately 18,991x106 GJ (18 Quads). Extrapolating the results for other building types not analyzed as part of this study, the primary energy savings could be in the range of 4,220x106 GJ to 5,275x106 GJ (4 to 5 Quads). If this savings potential is realized, it would be equivalent to not combusting 180 to 230 million tons of coal or reducing the energy impacts, at today’s energy intensities, of the per capita consumption of 12 to 15 million people in the U.S. To realize most of this potential savings, many gaps can be addressed through RD&D, as recommended in this paper.

Fernandez, Nick↗
DOE OSTI2017

Automated Measurement and Verification and Innovative Occupancy Detection Technologies

In support of DOE’s sensors and controls research, the goal of this project is to move toward integrated building to grid systems by building on previous work to develop and demonstrate a set of load characterization measurement and evaluation tools that are envisioned to be part of a suite of applications for transactive efficient buildings, built upon data-driven load characterization and prediction models. This will include the ability to include occupancy data in the models, plus data collection and archival methods to include different types of occupancy data with existing networks and a taxonomy for naming these data within a Volttron agent platform.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Is the BPD Nationally Representative? A Comparison of the Building Performance Database to the Commercial Buildings Energy Consumption Survey

The Building Performance Database (BPD) contains building characteristics and energy use data that can be used to benchmark buildings against their peers. However, the BPD contains data from any source that was willing to contribute data, regardless of whether that dataset is representative of the national building stock. This report explores the representativeness of the BPD. Namely, we compared the BPD to the Commercial Buildings Energy Consumption Survey (CBECS), which was designed to be a nationally representative sample of buildings. We divided the datasets into subgroups based on building type and location, we focused on three key variables (floor area, site energy use intensity, and source energy use intensity), and we compared their statistical properties in the BPD to the CBECS. We found that while the BPD contains significantly more buildings with larger floor areas, the BPD is reasonably representative in terms of site and source energy use intensity and does not appear to have a systemic bias towards energy efficient buildings.

42 ENGINEERING↗
DOE OSTI2019

Representing Small Commercial Building Faults in EnergyPlus, Part I: Model Development

Small commercial buildings (those with less than approximately 1000 m2 of total floor area) often do not have access to cost-effective automated fault detection and diagnosis (AFDD) tools for maintaining efficient building operations. AFDD tools based on machine-learning algorithms hold promise for lowering cost barriers for AFDD in small commercial buildings; however, such algorithms require access to high-quality training data that is often difficult to obtain. To fill the gap in this research area, this study covers the development (Part I) and validation (Part II) of fault models that can be used with the building energy modeling software EnergyPlus® and OpenStudio® to generate a cost-effective training data set for developing AFDD algorithms. Part I (this paper) presents a library of fault models, including detailed descriptions of each fault model structure and their implementation with EnergyPlus. This paper also discusses a case study of training data set generation, representing an actual building.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1992

High-resolution terrain map from multiple sensor data

The authors present 3-D vision techniques for incrementally building an accurate 3-D representation of rugged terrain using multiple sensors. They have developed the locus method to model the rugged terrain. The locus method exploits sensor geometry to efficiently build a terrain representation from multiple sensor data. The locus method is used to estimate the vehicle position in the digital elevation map (DEM) by matching a sequence of range images with the DEM. Experimental results from large-scale real and synthetic terrains demonstrate the feasibility and power of the 3-D mapping techniques for rugged terrain. In real world experiments, a composite terrain map was built by merging 125 real range images. Using synthetic range images, a composite map of 150 m was produced from 159 images. With the proposed system, mobile robots operating in rugged environments can build accurate terrain models from multiple sensor data.

Kweon, In S.↗
DOE OSTI2022

End-Use Load Profiles for the U.S. Building Stock: Practical Guidance on Accessing and Using the Data

End-use load profiles (EULP), which quantify how and when energy is used, are critically important to utilities, public utility commissions, state energy offices, and other stakeholders. Applications of EULPs focus on understanding how efficiency, demand response, and other distributed energy resources are valued and used in R&D prioritization, utility resource and distribution system planning, and state and local energy planning and regulations. Consequently, high-quality EULPs are critical for widespread adoption of electrification, demand flexibility, and grid-interactive efficient buildings. For example, EULPs can be used to forecast energy savings in buildings or to identify energy using activities that can be shifted to different times of the day.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Developing and Evaluating Metrics for Demand Flexibility in Buildings: Comparing Simulations and Field Data

Building demand flexibility (DF) has attracted significant attention in recent years among researchers, technology developers and control companies, aggregators, utilities, and many others. There are numerous challenges with today’s electricity systems such as managing peak demand capacity and integrating variable renewables into the grid. Flexible building loads can provide various grid services to help reduce electricity costs, smooth out renewables intermittency and balance supply and demand. Recognizing this, the US DOE is leading the Grid-interactive Efficient Buildings (GEB) initiative which includes research to evaluate the potential, availability and timing of flexible loads. In this paper we present load shed metrics for three building types – medium office, large office and retail store – and compare prototype simulation results with measured data from 12 actual buildings that participated in hot summertime utility demand response (DR) events. The DR strategies included varying zone temperature and reducing light levels. The magnitude of a key DF metric, “demand decrease intensity” (or “shed intensity”) (W/ft2), between the simulation results and field data are similar (14-32% differences) for both mean and median values, though the field data show much larger variation among DR events. The coefficient p-values from linear regression model tests showed that outside air temperature is a significant variable for the whole building shed intensity when the resetting zone temperature strategy is deployed. These findings support the concept of using prototype building simulation to estimate building DF and expanding future simulation research to additional building types and climate zones.

Liu, Jingjing↗