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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Impact of Connected Communities

Buildings account for 35% of CO 2 emissions and almost 40% of the United States’ energy use. High-performance homes and neighborhoods play an important role in supporting efforts to decarbonize the US power system by 2035. Significant reductions in CO 2 emissions within the residential sector can be realized through electrification of loads paired with the flexibility created by leveraging smart Internet of Things (IoT) capabilities to shift energy use based on grid signals, thus improving generation/distribution efficiency and maximizing the use of renewable generation capacity. All of this can be achieved while allowing smart home appliances and equipment to meet homeowner needs – including reducing power bills - while optimizing operation in conjunction with the grid using novel control techniques. The Grid-Interactive Efficient Buildings Roadmap by the US Department of Energy’s (DOE’s) Building Technologies Office (BTO) notes that implementing grid-interactive efficient building (GEB) technology has the potential to reduce CO 2 emissions by 80 million tons/year—roughly equivalent to 17 million cars. To achieve this vision, the US Department of Energy’s Oak Ridge National Laboratory (ORNL)—in collaboration with Southern Company Research & Development, Alabama Power, Georgia Power, BTO and the US DOE’s Office of Electricity (OE) —is developing and demonstrating novel connected communities at two locations. Southern Company in turn engaged with industry partners, including design firms, residential developers, and residential HVAC and appliance manufacturers because their participation would be critical to the success of the initial research project, as well as the future scaling to the Southern Company service territory and beyond. Impacts of the Connected Communities projects in Alabama and Georgia are outlined including: energy, grid services and data management learnings; homeowner feedback; vendor engagement; adoption by utilities; technical, policy and business model challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

Solar--heated and cooled office building--Dalton, Georgia

Modern energy efficient building is heated and cooled by five rows of flat plate solar collectors; its domestic hot water needs are also met. Final report includes detailed drawings and photographs, manufacturer's literature, performance specifications, acceptance test data, and performance verification statements. Operation and maintenance manual is also attached.

Source record↗
DOE OSTI2023

Sustainable Wood-Waste-Based Thermal Insulation Foam for Building Energy Efficiency

Wood is one of the most abundant biomaterials on Earth, which has been used for centuries in construction applications including furniture, roofing, flooring, and cabinetry. However, wood chips—which are a low-quality and plentiful waste byproduct of lumber milling, woodworking, and shipping operations—have low economic value and complicated disposal methods. In this paper, we propose a strategy for wood chip reuse through the fabrication of bio-based building insulation foam. Through a high-temperature chemical treatment delignification process, we introduced additional small pores within the wood chips, effectively lowering their thermal conductivity, and used them in combination with a binding agent to produce a porous insulation foam. The porous insulation foam achieved a low thermal conductivity of 0.038 W/(m·K) and a high compressive strength of 1.1 MPa (70% strain). These characteristics demonstrate that wood waste can be repurposed into an effective building material, addressing challenges in both waste management and sustainable construction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware Model Predictive Control for Residential Building Energy Efficiency and Occupant Comfort

The residential sector accounts for 25% of global primary energy consumption. Two methods have previously been proposed to reduce residential energy use associated with the provision of occupant thermal comfort: 1. Occupancy-based HVAC control, operating systems only during confirmed occupancy, and 2. model predictive control (MPC), harnessing a mathematical model and forecasts to find optimal operating strategies. Previous studies estimate the average energy savings of the two methods individually in the range of 21% and 16%, respectively. The research presented herein was carried out to evaluate the energy savings potential in residential buildings by combining both approaches across different climates, house vintages, and occupancy patterns. Occupancy and eight different physical modalities (e.g. CO2 and VOC) data were collected from five homes for time periods of 4–9 weeks. Collected data sets were used to train occupancy prediction models suggested by an extensive literature survey of occupancy model types. The trained prediction models were combined with MPC and detailed EnergyPlus building simulation models to evaluate residential building performance in terms of annual energy savings and thermal comfort, along with discomfort exceedance metrics. Multiple home types and regions were analyzed to understand regional and climate-dependent potential. Based on actual field data, the occupancy models had a prediction inaccuracy between 8% and 35% across the investigated homes. Average occupancy for the collected data ranged from 56% to 86%, a typical range reported in the literature. Building simulations were conducted for three control scenarios: conventional thermostatic control, occupancy-based, and occupancy-based MPC. The results indicate that all advanced strategies improve upon the conventional control, with some scenarios cutting energy use in half with only occasional incurrence of discomfort. The findings indicate that occupancy-aware model predictive residential building control has the potential to drastically reduce energy use and associated emissions while maintaining occupant comfort for both new and existing buildings.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2020

A macromolecular assembly directed ceramic aerogel monolith material

Ceramic aerogels exhibit remarkable thermal insulation for energy efficient building applications, while it is indispensable to understand their nanoporous structure evolution to control their thermal regulation performance. In this study, we design and synthesize a lightweight porous silica aerogel monolithic material, and demonstrate its thermal insulation performance regulated by the morphology of porous nanostructures controlled by surfactant induced self-assembly. The micelle networks and in situ gas bubble formation guide the formation of uniform pores in the as-synthesized monolith, which shows superior thermal and acoustic insulation and robust mechanical stability with a thermal conductivity of 0.032 W m –1 K –1 , a soundproof performance improvement by 17% at a frequency of 800 Hz, and a 1.3 MPa compressive strength with a Young's modulus of 15 MPa. Lastly, these findings provide a new route to manufacture low-cost aerogel monolithic insulation materials for energy efficient building applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Defining and applying an electricity demand flexibility benchmarking metrics framework for grid-interactive efficient commercial buildings

Building demand flexibility (DF) research has recently gained attention. To unlock building DF as a predictable grid resource, we must establish a quantitative understanding of the resource size, performance variability, and predictability based on large empirical datasets. Researchers have proposed various sets of theoretical metrics to measure this performance. Some metrics have been applied to simulation results, but most fall short of exploring the complexities in real building applications. There are practical metrics used in individual demand response field studies but they alone cannot fulfil the job of DF benchmarking across a diverse group of buildings. The electrical grid's geographically diverse and changing nature presents challenges to comparing building DF performance measured under different conditions (i.e., benchmarking DF). To address this challenge, a novel DF benchmarking framework focused on load shedding and shifting is presented; the foundation is a set of simple, proven single-event metrics with attributes describing event conditions. These enable benchmarking and visualization in different dimensions for identifying trends that represent how these attributes influence DF. To test its feasibility and scalability, the DF framework was applied to two case studies of 11 office buildings and 121 big-box retail buildings with demand response participation data. Furthermore, these examples provided a pathway for using both building level benchmarking and aggregation to extract insights into building DF about magnitude, consistency, and influential factors. Potential applications of the framework and real-world values have been identified for grid and building stakeholders.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

The Integration of Wi-Fi Location-Based Services to Optimize Energy Efficient Commercial Building Operations

This project investigated and demonstrated the use of Wi-Fi Location-Based Services (LBS) to perform occupancy sensing in commercial buildings. Wi-Fi LBS can be used to detect the presence of Wi-Fi enabled mobile devices and laptops that accompany occupants as they move through the building. These signals can be used to determine occupant presence, head count, and location. When integrated with the building automation system, this emerging technology approach can be used to manage other connected systems such as lighting and HVAC to reduce energy usage in the building and improve occupant comfort. An open source location detection algorithm was developed, which uses data collected from three or more Wi-Fi access points to determine the presence and estimate the location of mobile devices and laptops. Access points can detect Wi-Fi enabled devices even if they are not connected to the existing Wi-Fi network. Building occupancy is determined based on the presence, location, and movement of these devices through the space. From lab and small-scale in-situ testing, the Location Detection Algorithm (LDA) was found to be accurate to within 10 feet and could be further refined by tuning the algorithm for the specific space characteristics such as layout and obstructions (walls, furniture, etc.). An open source method to integrate the occupancy data with existing building automations systems was investigated. The Wi-Fi occupancy sensing approach was then demonstrated and validated at commercial buildings located in Saint Paul, MN; Madison, WI; New York City; and Fort Worth, TX.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Occupancy-aware heating, ventilation, and air conditioning (HVAC) control offers the opportunity to reduce energy use without sacrificing thermal comfort. Residential HVAC systems often use manually-adjusted or constant setpoint temperatures, which heat and cool the house regardless of whether it is needed. By incorporating occupancy-awareness into HVAC control, heating and cooling can be used for only those time periods it is needed. Yet, bringing this technology to fruition is dependent on accurately predicting occupancy. Non-probabilistic prediction models offer an opportunity to use collected occupancy data to predict future occupancy profiles. Smart devices, such as a connected thermostat, which already include occupancy sensors, can be used to provide a continually growing collection of data that can then be harnessed for short-term occupancy prediction by compiling and creating a binary occupancy prediction. Real occupancy data from six homes located in Colorado is analyzed and investigated using this occupancy prediction model. Results show that non-probabilistic occupancy models in combination with occupancy sensors can be combined to provide a hybrid HVAC control with savings on average of 5.0% and without degradation of thermal comfort. Model predictive control provides further opportunities, with the ability to adjust the relative importance between thermal comfort and energy savings to achieve savings between 1% and 13.3% depending on the relative weighting between thermal comfort and energy savings. In all cases, occupancy prediction allows the opportunity for a more intelligent and optimized strategy to residential HVAC control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2006

Building Operations Efficiencies into NASA's Crew Launch Vehicle Design

The U.S. Vision for Space Exploration guides NASA's challenging missions of technological innovation and scientific investigation. With the Agency's commitment to complete the International Space Station (ISS) and to retire the Space Shuttle by 2010, the NASA Administrator commissioned the Exploration Systems Architecture Study (ESAS) in mid 2005 to analyze options for a safer, simpler, more cost efficient launch system that could deliver timely human-rated space transportation capabilities. NASA's finite resources yield discoveries with infinite possibilities. As the Agency begins the process of replacing the Shuttle with new launch vehicles destined for missions beyond low-Earth orbit to the Moon and Mars, NASA is designing the follow-on crew and cargo systems for maximum operational efficiencies. This mandate is imperative to reduce the $4.5 billion NASA spends on space transportation each year. This paper gives top-level details of how the follow-on Crew Launch Vehicle (CLV) is being designed for reduced lifecycle costs as a primary catalyst for the expansion of future frontiers.

Dumbacher, Daniel L.↗
NASA NTRS2006

Building Operations Efficiencies into NASA's Ares I Crew Launch Vehicle Design

The U.S. Vision for Space Exploration guides the National Aeronautics and Space Administration s (NASA's) challenging missions that expand humanity s boundaries and open new routes to the space frontier. With the Agency's commitment to complete the International Space Station (ISS) and to retire the venerable Space Shuttle by 2010, the NASA Administrator commissioned the Exploration Systems Architecture Study (ESAS) in mid 2005 to analyze options for safe, simple, cost-efficient launch solutions that could deliver human-rated space transportation capabilities in a timely manner within fixed budget guidelines. The Exploration Launch Projects Office, chartered in October 2005, has been conducting systems engineering studies and business planning over the past few months to successively refine the design configurations and better align vehicle concepts with customer and stakeholder requirements, such as significantly reduced life-cycle costs. As the Agency begins the process of replacing the Shuttle with a new generation of spacecraft destined for missions beyond low-Earth orbit to the Moon and Mars, NASA is designing the follow-on crew and cargo launch systems for maximum operational efficiencies. To sustain the long-term exploration of space, it is imperative to reduce the $4.5 billion NASA typically spends on space transportation each year. This paper gives top-level information about how the follow-on Ares I Crew Launch Vehicle (CLV) is being designed for improved safety and reliability, coupled with reduced operations costs.

Dumbacher, Daniel↗
NASA NTRS2007

Building Operations Efficiencies into NASA's Ares I Crew Launch Vehicle Design

The U.S. Vision for Space Exploration guides the National Aeronautics and Space Administration's (NASA's) challenging missions that expand humanity's boundaries and open new routes to the space frontier. With the Agency's commitment to complete the International Space Station (ISS) and to retire the venerable Space Shuttle by 2010, the NASA Administrator commissioned the Exploration Systems Architecture Study (ESAS) in 2005 to analyze options for safe, simple, cost-efficient launch solutions that could deliver human-rated space transportation capabilities in a timely manner within fixed budget guidelines. The Exploration Launch Projects (ELP) Office, chartered by the Constellation Program in October 2005, has been conducting systems engineering studies and business planning to successively refine the design configurations and better align vehicle concepts with customer and stakeholder requirements, such as significantly reduced life-cycle costs. As the Agency begins the process of replacing the Shuttle with a new generation of spacecraft destined for missions beyond low-Earth orbit to the Moon and Mars, NASA is designing the follow-on crew and cargo launch systems for maximum operational efficiencies. To sustain the long-term exploration of space, it is imperative to reduce the $4 billion NASA typically spends on space transportation each year. This paper gives toplevel information about how the follow-on Ares I Crew Launch Vehicle (CLV) is being designed for improved safety and reliability, coupled with reduced operations costs. These methods include carefully developing operational requirements; conducting operability design and analysis; using the latest information technology tools to design and simulate the vehicle; and developing a learning culture across the workforce to ensure a smooth transition between Space Shuttle operations and Ares vehicle development.

Dumbacher, Daniel L.↗
DOE OSTI2023

Building an Efficient Cluster Cosmology Software Package for Modeling Cluster Counts and Lensing

We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and weak-lensing measurements need efficient software infrastructure to explore an increasingly large parameter space, and account for various cosmological and astrophysical effects. Our software package is designed to model the cluster observables in a wide-field optical survey, including galaxy cluster counts, their averaged weak-lensing masses, or the cluster's averaged weak-lensing radial signals. To ensure maximum efficiency, this software package is developed in C++ in the CosmoSIS software framework, making use of the CUBA integration library. We also implement a testing and validation scheme to ensure the quality of the package. We demonstrate the effectiveness of this development by applying the software to the Dark Energy Survey Year 1 galaxy cluster cosmological data sets, and acquired cosmological constraints that are consistent with the fiducial Dark Energy Survey analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Grid-Interactive Building Solutions: MelRok Energy IOT Touch Gateway

This fact sheet describes a grid-interactive efficient building technology that is undergoing field validation tests through DOE's National Labs. It summarizes the technology application (MelRok's Energy IOT Touch), the parameters of the demonstration, and the characteristics of the field validation site.

grid-interactive efficient buildings, GEB, technol↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗