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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Effective Kitchen Ventilation for Healthy Zero Net Energy Homes with Natural Gas

Past studies indicate that kitchen ventilation that minimally complies with California’s Residential Building Code is inadequate at controlling combustion pollutants from natural gas burners and particulate matter produced during cooking. Effectiveness is further limited by misperceptions that kitchen ventilation is infrequently needed. This project developed the technical basis for updating kitchen ventilation requirements to protect health in new California homes, especially in smaller homes common among low-income renters. Tasks included (1) a field study of ventilation equipment performance and indoor air quality in 23 low-income apartments at four sites; (2) analysis of range hood use related to cooking time and household parameters using data from 54 houses and 17 low-income apartments; (3)a measurement-based study to quantify performance of over-the-range microwave ovens with integrated exhaust fans;and (4) pollutant exposure simulations to inform capture efficiency standards.The field study found operational deficiencies with mechanical ventilation systems in a substantial fraction of low-income apartments that affected performance, resulting in higher exposures to pollutants generated indoors. Using gas cooking burners produced high short-term and weekly time-averaged nitrogen dioxide in apartments.Range hoods were used more frequently with cooking in houses (36percent) than apartments (28percent); use increased with overall cooking frequency in a home and with duration of cooktop but not oven events; actual use was correlated to, but lower than,self-reported use;and use was more frequent in houses when cooking generated any fine particulate matter (PM2.5)or when high PM2.5resulted from cooking in apartments. Performance of over-the-range microwaves with integrated exhaust fans was similar to that of range hoods of comparable price. Simulation analysis found that performance standards need to be updated to ensure that kitchen exhaust ventilation adequately protects for substantial cooking in new California residences.

03 NATURAL GAS↗
DOE OSTI2025

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Cost-Optimized Cold Climate Heat Pump Development and Field Test

Cold climate heat pumps (CCHPs) expand the heat pump market to climates where heating demand is dominant. They can achieve more than 70% energy savings compared with electric resistance heating and operate at lower cost than using tank-stored propane to fuel a furnace. A high-efficiency heat pump with a heating seasonal performance factor (HSPF)—as defined by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI 2008)—greater than 10.0 would be more efficient than gas heating in terms of source energy. However, developing a cost-effective CCHP involves some challenges. A typical single-speed, air-source heat pump (ASHP) with an HSPF of 7.7 Btu/Wh does not work well under cold outdoor temperature conditions typical of cold climate locations for four major reasons: 1. Discharge temperature is too high—The low suction pressure and high compression pressure ratio at low ambient temperatures causes high compressor discharge temperatures in excess of the maximum limit for many of the compressors on the market. Furthermore, system charge of a heat pump is usually optimized in the cooling mode, which leads to overcharge conditions in the heating mode, further increasing the discharge temperature. 2. Heating capacity is insufficient if sized to meet the building design cooling load— Heating capacity of a single-speed heat pump decreases with ambient temperature. The heating capacity at -13°F (-25°C) typically decreases to 20%–40% of the rated heating capacity at 47°F (8.3°C) (~equivalent to the rated cooling capacity at 95°F [35°C]). Therefore, a single-speed heat pump, typically sized to match the building design cooling load, cannot provide adequate heating capacity to match the building heating load at low ambient temperatures. The capacity deficit is filled by inefficient resistance heat, thus lowering the system efficiency and significantly increasing power demand. 3. Cyclic loss is significant if sized to meet the building design heating load—If a single-speed heat pump is sized to meet the heating load, it will be significantly oversized relative to the cooling load in many cold climates. This will cause excessive on/off cyclic loss during the cooling and heating operations at moderately low ambient temperatures. Thus, capacity modulation capability (e.g., using a variable-speed or multi-stage compressor) is necessary for a CCHP, which uses its full capacity to meet the peak heating load and partial capacity to meet the cooling and part-load heating loads. 4. Coefficient of performance (COP) is low—Heating COP degrades significantly at low ambient temperatures owing to the large temperature difference between the heat source and sink. A target CCHP should be sized to meet the building design heating load while minimizing the cyclic loss for the cooling and heating operations at moderate ambient temperatures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Synthesis and functionalization of electron-deficient perfluoroalkyl porphyrin building blocks for supermolecular systems

Synthetic strategies for electron-deficient meso-perfluoroalkylporphyrins bearing diverse functional groups are described. Scalable and efficient syntheses for 5-triisopropylsilylethynyl-10,15,20-tris(heptafluoropropyl)porphyrin and 5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphyrin that equip meso-ethynyl functional groups via the bilane route have been established, along with a refined route to [5,15-bis(heptafluoropropyl)porphinato]zinc(II). meso-Position halogenation of [5,15-bis(heptafluoropropyl)porphinato]zinc(II) was achieved by selective meso-nitration and subsequent reduction, diazonium salt formation, and iodination reactions. Computational data describe the low energy excited states of these chromophores and the electronic structural factors that control reactivity of these meso-perfluoroalkyl substituted porphyrin complexes. meso-Functionalized [5-triisopropylsilylethynyl-10,20-bis(heptafluoropropyl)porphinato]zinc(II) and [5-iodo-10,20-bis(heptafluoropropyl)porphinato]zinc(II) building blocks lay the foundation for the construction of highly conjugated multiporphyrin arrays that feature electronic structural properties important for the development of n-type materials and high potential photooxidants.

Chemistry↗
DOE OSTI2023

Advanced Fuel Cycle Cost Basis Report: Supporting Document 5 Considerations on Learning

Learning refers here to the increased experience associated to each new build of a given type of fuel cycle facility, which results generally in design improvements, increased construction and operational efficiencies and reduced mistakes, and therefore in reduced costs. These are important considerations, for example, when modeling transitions from first-of-a-kind (FOAK) to nth-of-a-kind (NOAK) nuclear facilities and deciding the magnitude of the cost reduction (if any) to be applied to each successive build. Different assumptions on learning can significantly affect the results of the economic analyses during transitions. Other competing electricity-generation technologies, such as wind and solar power for example, have demonstrated substantial cost reductions through learning during the last few decades.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Decarbonizing or illusion? How carbon emissions of commercial building operations change worldwide

To lead the low-carbon transition in global buildings, this study is the first to use the generalized Divisia index method (GDIM) to identify the factors driving carbon emissions and assess the decarbonization performance in commercial building operations (CBOs) of sixteen countries during 2000–2019. Results show that (1) while the global carbon emissions from CBOs have increased at a modest rate of 0.9%/yr, this trend runs counter to the declining emissions in the U.S. (-1.1%/yr) and the significant growth in China (14.4%/yr), which can be attributed to the impact of economy-related factors. (2) The U.S. and China, as the largest emitters, contributed 66.8% of the samples’ decarbonization of CBOs (919.1 million tons of carbon dioxide). (3) Most countries’ CBOs had a decarbonization efficiency level of less than 10%, except for Spain (27.8%). Spain excelled in both areas of per capita and per floor area with an average efficiency of nearly 30%. Moreover, ridge regression successfully confirms the stability of GDIM results and it should be noted GDIM has limitations in characterizing the end-use activity. Overall, this study tracks the historical decarbonization of global CBOs and offers benchmarks for different emitters to forecast the dynamic of building emissions along with economic booms.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Transforming New Multifamily Construction to Zero: Strategies for Implementing Energy Targets and Design Pathways: Preprint

Creating zero energy (ZE) mid- to high-rise multifamily buildings represent significant challenges in the design world. Tenants often take responsibility for some of the utilities and are responsible for consumption of some of the largest end uses: hot water and plug loads. Furthermore, designers can experience risk in creating new sets of details and recommending new strategies to reach aggressive EUI targets. To assist in a more streamlined and successful design approach to ZE multifamily buildings, five major professional societies and experts from the multifamily space created a Zero Energy Advanced Energy Design Guide (AEDG) for multifamily buildings based on data driven results coupled with actual design experiences and case studies. Pathways to achieve ZE design were established including whole building energy use intensity targets coupled with details on how to achieve success in implementing individual efficiency measures. The guidance strives to overcome design barriers and this paper provides an overview of the recommended process to achieve ZE or ZE-ready status, along with details on selecting energy targets, and strategy pathways to achieve the targets.

advanced energy design guide↗
DOE OSTI2025

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗
DOE OSTI2021

Addressing energy storage needs at lower cost via on-site thermal energy storage in buildings

Cost-effective energy storage is a critical enabler for the large-scale deployment of renewable electricity. Significant resources have been directed toward developing cost-effective energy storage, with research and development efforts dominated by work on lithium ion (Li-ion) battery technology. Though Li-ion batteries have many attractive qualities, it is not clear whether they can provide an affordable levelized cost of storage (LCOS) for certain applications, such as buildings. Buildings consume most of the world's electricity, and as much as 50% of their consumption goes toward meeting thermal loads. Thermal energy storage (TES) can provide a cost-effective alternative to Li-ion batteries for buildings; however, two questions remain to be answered. First, how much of total building energy storage requirements can be met via thermal storage for building loads? Second, can the LCOS for TES be favorable compared with Li-ion batteries? In this perspective, using the United States as a case study, we show that the total requirement for TES in buildings is in the range of ~1200–4500 electrical GW h, depending on the fraction of solar versus wind in the generation mix. Furthermore, we show that with at least 25% wind generation, all of the storage needed by buildings to support the grid can be met by TES. We also introduce a framework to calculate LCOS for on-site TES in buildings to enable a direct comparison with electrical storage technologies such as Li-ion batteries. This is not trivial, because the input energy type for TES (electricity) differs from the output energy type (thermal energy), and the efficiency can depend on ambient conditions. Our LCOS analysis shows that in many situations, TES can be more cost-effective for buildings than Li-ion batteries. We conclude our perspective by discussing future research and development opportunities that can significantly advance the deployment of TES for buildings to help enable a renewable electricity-dependent grid.

25 ENERGY STORAGE↗
NASA NTRS1999

A New High Efficiency Segmented Thermoelectric Unicouple

To achieve high thermal-to-electric energy conversion efficiency, it is desirable to operate thermoelectric geneteor devices over large temperature gradients and also to maximize the thermoelectric performance of the materials used to build the devices.

Energy↗
DOE OSTI2025

A dataset for understanding self-reported patterns influencing residential energy decisions

Household occupant behavior and decision-making dynamics substantially impact technology uptake and residential building energy performance. Although significant research underscores the importance of social science in energy studies, few public data with representative samples on household energy decision-making patterns are available. The dataset (UPGRADE-E: Understanding Patterns Guiding Residential Adoption and Decisions about Energy Efficiency) presents 9,919 responses from U.S. residents of single-family and small multifamily homes. Derived from a national-scale internet survey, the dataset contains 391 variables: demographics, building characteristics, home modifications, willingness to adopt new technologies, motivations for making changes, barriers, program participation, trusted information sources, and energy scenarios. Responses were validated via internal consistency checks and comparison with other U.S. national scale datasets. UPGRADE-E advances knowledge of household energy related decision-making, tying demographics, home modifications, and self-reported cognitive drivers together at a scale and breadth that has not been previously achieved. Policymakers and researchers at local, regional, and national levels may leverage this dataset to understand drivers influencing the adoption of key technologies in U.S. homes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Astrophysics & cosmology from line intensity mapping vs galaxy surveys

Line intensity mapping (LIM) proposes to efficiently observe distant faint galaxies and map the matter density field at high redshift. Building upon the formalism in a companion paper, we first highlight the degeneracies between cosmology and astrophysics in LIM. We discuss what can be constrained from measurements of the mean intensity and redshift-space power spectra. With a sufficient spectral resolution, the large-scale redshift-space distortions of the 2-halo term can be measured, helping to break the degeneracy between bias and mean intensity. With a higher spectral resolution, measuring the small-scale redshift-space distortions disentangles the 1-halo and shot noise terms. Additionally, cross-correlations with external galaxy catalogs or lensing surveys further break degeneracies. We derive requirements for experiments similar to SPHEREx, HETDEX, CDIM, COMAP and CONCERTO. We then revisit the question of the optimality of the LIM observables, compared to galaxy detection, for astrophysics and cosmology. We use a matched filter to compute the luminosity detection threshold for individual sources. We show that LIM contains information about galaxies too faint to detect, in the high-noise or high-confusion regimes. We quantify the sparsity and clustering bias of the detected sources and compare them to LIM, showing in which cases LIM is a better tracer of the matter density. We extend previous work by answering these questions as a function of Fourier scale, including for the first time the effect of cosmic variance, pixel-to-pixel correlations, luminosity-dependent clustering bias and redshift-space distortions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Comparative evaluation of analogue front-end designs for the CMS Inner Tracker at the High Luminosity LHC

The CMS Inner Tracker, made of silicon pixel modules, will be entirely replaced prior to the start of the High Luminosity LHC period. One of the crucial components of the new Inner Tracker system is the readout chip, being developed by the RD53 Collaboration, and in particular its analogue front-end, which receives the signal from the sensor and digitizes it. Three different analogue front-ends (Synchronous, Linear, and Differential) were designed and implemented in the RD53A demonstrator chip. A dedicated evaluation program was carried out to select the most suitable design to build a radiation tolerant pixel detector able to sustain high particle rates with high efficiency and a small fraction of spurious pixel hits. The test results showed that all three analogue front-ends presented strong points, but also limitations. The Differential front-end demonstrated very low noise, but the threshold tuning became problematic after irradiation. Moreover, a saturation in the preamplifier feedback loop affected the return of the signal to baseline and thus increased the dead time. The Synchronous front-end showed very good timing performance, but also higher noise. For the Linear front-end all of the parameters were within specification, although this design had the largest time walk. This limitation was addressed and mitigated in an improved design. The analysis of the advantages and disadvantages of the three front-ends in the context of the CMS Inner Tracker operation requirements led to the selection of the improved design Linear front-end for integration in the final CMS readout chip.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Optimizing Multi-Robot Placements for Wire Arc Additive Manufacturing

Wire arc additive manufacturing is a metal additive manufacturing process in which the material is deposited using arc welding technology. It is gaining popularity due to high material deposition rates and faster build time. It is en-abled using robotic manipulators and can build relatively large-scale parts faster when compared with other metal additive manufacturing processes. However, the size of the large-scale parts is limited by the size of the industrial manipulator being used for the process. This limitation is overcome by using a fixed configuration multi-robot cell in which manipulators work cooperatively to build large-scale parts quickly. A fixed multi-robot cell with closely spaced industrial manipulators has high flexibility, but it restricts the part size that can be built. If the manipulators are spread out, the cell loses its flexibility but can build relatively larger parts. This issue can be avoided by using larger size manipulators, which are expensive, or by moving the modest size manipulators based on the part geometries. This paper presents a novel algorithm to generate multi-robot placements for different part geometries to be built using wire arc additive manufacturing. Furthermore, the algorithm hierarchically optimizes the build time and the inverse kinematics consistency in robot paths to improve the process efficiency and part quality. We compare the results with fixed multi-robot cells and provide insights to users to make an informed decision on whether to use a fixed or a flexible multi-robot cell for wire arc additive manufacturing.

Bhatt, Prahar↗
DOE OSTI2023

Build Optimization Software Tools (BOOST) v2.0.0

Build Optimization Software Tools (BOOST) accelerate the design of DNA, RNA and protein sequences for their synthesis and assembly in an automated and scalable fashion. The BOOST Juggler automates the following two design tasks: - Reverse-Translation of protein sequences into DNA sequences - Codon Juggling of DNA sequences The BOOST Polisher provides the following design tasks: - The Verification of DNA sequences against DNA synthesis constraints - The Modification of DNA sequences in case they violate any DNA synthesis constraint In addition, the BOOST Polisher can be instructed to verify and modify DNA sequences against sequence patterns, such as restriction sites. The BOOST Partitioner supports both Gibson/chewback and Yeast assembly (also known as Transformation-Associated Recombination, or TAR) methods when performing the decomposition of large sequences that exceed the maximum length of DNA synthesis into synthesizable building blocks. The Partitioner can be instructed to find building blocks with appropriate overlap sequences, making their assembly into the complete construct more efficient. BOOST Workflows enable, in a customized fashion, the execution of the Juggler, Polisher, and Partitioner tools on a batch of sequences.

Sharkey, Michael↗
DOE OSTI2022

MULTISTEP AND CONTINUOUS PHYSICS-INFORMED NEURAL NETWORK METHODS FOR LEARNING GOVERNING EQUATIONS AND CONSTITUTIVE RELATIONS

In this work, we investigate the applicability and relative merit of discrete and continuous versions of physics-informed neural network (PINN) methods for learning unknown governing equations or constitutive relations in a nonlinear dynamical system. In the case of unknown dynamics, entire right-hand-side (RHS) equations of the ordinary differential equations are unknown. In the case of unknown constitutive relations, however, the RHS equations are known up to the specification of constitutive relations (that may depend on the state of the system). We use a deep neural network to model unknown governing equations or constitutive relations. The discrete PINN approach combines classical multistep discretization methods for dynamical systems with neural-network-based machine learning methods. On the other hand, the continuous versions utilize deep neural networks to minimize the residual function for the continuous governing equations. We use the case of a fedbatch bioreactor system to study the effectiveness of these approaches and discuss conditions for their applicability. Our results indicate that the accuracy of the trained neural network models is much higher for the cases where we only have to learn a constitutive relation instead of all dynamics. This finding corroborates the well-known fact from scientific computing that building as much structural information as is available into an algorithm can enhance its efficiency and/or accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Review: Sensor Impact on Building Controls and Automatic Fault Detection and Diagnosis (AFDD)

This report summarizes a literature review as a Q1 deliverable of the “Sensor Impact Evaluation and Verification” project. This project’s overarching goal is to develop a framework for investigating the impact of sensor deployment and configuration for building energy optimization, fault detection and diagnosis (FDD), occupants’ thermal comfort, and potential grid efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗