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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Who is participating in residential energy efficiency programs? Exploring demographic and other household characteristics of participants in utility customer-funded energy efficiency programs

In addition to benefiting all customers by reducing the total electric system cost, utility customer-funded energy efficiency programs provide direct benefits to the participants. Understanding the current demographic and household characteristics of participants will help assess the extent of inequities in program participation and figure out what characteristics need to be targeted to achieve equitable outcomes. This report describes how 11 demographic and household characteristics including income, race and ethnicity, and education affect participation in residential utility customer-funded energy efficiency programs. It compiles previous work on this topic and adds new primary analysis of four datasets with different levels of detail from the Residential Energy Consumption Survey (RECS), two New England states, and a Midwestern state.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Getting Beyond Widgets: Performance of Efficient Indoor Air Quality System Retrofit Packages for Schools A report on the modeled energy, greenhouse gas, and cost savings of several multi-measure retrofit packages for energy efficiency and indoor air quality in primary schools

School facilities are often underfunded with aging and poorly maintained HVAC and lighting systems. Most existing school buildings stand to benefit significantly from retrofits in terms of energy, cost, and emissions savings. Ventilation and indoor air quality (IAQ), which are important aspects of a healthy and productive learning environment, can also be enhanced by some energy efficiency measures (EEMs). Packaging energy efficiency and IAQ systems retrofits may represent a golden opportunity to improve performance in this critical building sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1992

Operationally efficient propulsion system study (OEPSS) data book: Space Transfer Propulsion Operational Efficiency Study Task of OEPSS - Volume 6

This document is the final report for the Space Transfer Propulsion Operational Efficiency Study Task of the Operationally Efficient Propulsion System Study (OEPSS) conducted by the Rocketdyne Division of Rockwell International. This Study task studied, evaluated and identified design concepts and technologies which minimized launch and in-space operations and optimized in-space vehicle propulsion system operability.

Harmon, Timothy J.↗
DOE OSTI2022

Route Optimization for Energy Efficient Airport Shuttle Operations - A Case Study from Dallas Fort Worth International Airport

Air travel and requisite surface traffic supporting passenger arrival/departure constitutes a significant portion of travel and emissions in cities with large airports. An airport trip can segment into three parts namely: i) travel from a location in the city to the airport; ii) travel from a parking lot or rental car center to the terminal (i.e., within the airport premises), and iii) travel inside the terminal. Depending on the airport access mode all or a part of these legs comprise a traveler’s journey to the airport. The priority of airport ground transport management teams is to provide passengers with a seamless travel experience within the airport, so it is understandable that within airport shuttle routes might not be optimized for minimizing energy consumption. Solutions that meet the dual objective of reducing energy consumption from airport shuttle operations without compromising on passenger travel experience are key to improving system efficiency. There is currently a dearth of research and tools that can inform airports in making such decisions. Addressing this need, this research effort puts forth an optimization model that generates optimal shuttle routes for a given set of constraints, and a discrete-event simulator that evaluates the optimal solutions in a stochastic environment to understand the tradeoffs between passenger wait times, and within airport shuttle energy consumption. The proposed set of tools are tested in the context of optimizing airport shuttles routes within the Dallas Fort Worth International Airport (DFW). In addition to shuttle spatial positioning, and passenger demand information, high-fidelity vehicle data was collected using data loggers installed on DFW shuttles. Results show that 20% energy reduction in shuttle operations is possible with a modest two-minute increase in average passenger wait times. The tools developed in this research effort are designed to be generalizable and can help optimize shuttle operations planning at any major airport.

air travel↗
DOE OSTI2024

Dynamic Behavior of Spatially Confined Sn Clusters and Its Application in Highly Efficient Sodium Storage with High Initial Coulombic Efficiency

Advanced battery electrodes require a cautious design of microscale particles with built-in nanoscale features to exploit the advantages of both micro- and nano-particles relative to their performance attributes. Herein, the dynamic behavior of nanosized Sn clusters and their host pores in carbon nanofiber) during sodiation and desodiation is revealed using a state-of-the-art 3D electron microscopic reconstruction technique. For the first time, the anomalous expansion of Sn clusters after desodiation is observed owing to the aggregation of clusters/single atoms. Pore connectivity is retained despite the anomalous expansion, suggesting inhibition of solid electrolyte interface formation in the sub-2-nm pores. Taking advantage of the built-in nanoconfinement feature, the CNF film with nanometer-sized interconnected pores hosting Sn clusters (≈2 nm) enables high utilization (95% at a high rate of 1 A g –1 ) of Sn active sites while maintaining an improved initial Coulombic efficiency of 87%. Finally, the findings provide insights into electrochemical reactions in a confined space and a guiding principle in electrode design for battery applications.

36 MATERIALS SCIENCE↗
NASA NTRS1951

Comparison of measured efficiencies of nine turbine designs with efficiencies predicted by two empirical methods

Empirical methods of Ainley and Kochendorfer and Nettles were used to predict performances of nine turbine designs. Measured and predicted performances were compared. Appropriate values of blade-loss parameter were determined for the method of Kochendorfer and Nettles. The measured design-point efficiencies were lower than predicted by as much as 0.09 (Ainley and 0.07 (Kochendorfer and Nettles). For the method of Kochendorfer and Nettles, appropriate values of blade-loss parameter ranged from 0.63 to 0.87 and the off-design performance was accurately predicted.

FLOW-TURBINES↗
DOE OSTI2021

GFCCLib: Scalable and efficient coupled-cluster Green's function library for accurately tackling many-body electronic structure problems

Coupled-cluster Green’s function (GFCC) calculation has drawn much attention in the recent years for targeting the molecular and material electronic structure problems from a many-body perspective in a systematically improvable way. However, GFCC calculations on scientific computing clusters usually suffer from expensive higher di- mensional tensor contractions in the complex space, expensive inter-process communi- cation, and severe load imbalance, which limits it’s routine use for tackling electronic structure problems. Here we present a numerical library prototype that is specifically designed for large-scale GFCC calculations. The design of the library is focused on a systematically optimal computing strategy to improve its scalability and efficiency. The performance of the library is demonstrated by the relevant profiling analysis of running GFCC calculations on remote giant computing clusters. The capability of the library is highlighted by computing a wide near valence band of a fullerene C60 molecule for the first time at the GFCCSD level that shows excellent agreement with the experimental spectrum.

Peng, Bo↗
DOE OSTI2024

Pathways of CdS Quantum Dot Degradation during Photocatalysis: Implications for Enhancing Stability and Efficiency for Organic Synthesis

CdS quantum dots (QDs) are widely employed as photocatalysts for reactions such as hydrogen evolution, and their degradation under aerobic aqueous conditions is well understood. However, despite evidence of aggregation and precipitation of CdS QD photocatalysts under anaerobic conditions, catalyst speciation and degradation under such conditions are underexplored. In this work, we demonstrate that during a reductive dehalogenation reaction, CdS QDs undergo surface ligand etching, which leads to a loss of colloidal stability and the formation of microcrystalline cadmium metal deposits. We hypothesize that this results from the accumulation of electrons on the QD surface. In addition, we demonstrate mild surface sulfur oxidation and the formation of an ammonium salt byproduct of a commonly used hole quencher. Furthermore, this work adds to our atomic-level understanding of the reactions occurring at the QD surface during photocatalysis, so that we can design more stable and efficient photocatalysts for organic synthesis.

cadmium sulfide↗
DOE OSTI2022

Ultralow-Loading Pt/Zn Hybrid Cluster in Zeolite HZSM-5 for Efficient Dehydroaromatization

Minimizing Pt loading without sacrificing catalytic performance is critical, particularly for designing cost-efficient hydrocarbon transformation catalysts. Here, we show that ultralow-loading (0.001–0.05 wt %) Pt- and Zn-functionalized HZSM-5 catalysts, prepared through simple ion exchange and impregnation, are highly active and stable for light alkane dehydroaromatization (DHA). The specific activity of benzene, toluene, and xylene is up to 8.2 mol/g Pt /min (or 1592 min –1 ) over the 0.001 wt % Pt–Zn 2 /HZSM-5 catalyst during ethane DHA at 550 °C under atmospheric pressure. Additionally, such bimetallic Pt x –Zn y /HZSM-5 catalysts are highly stable in contrast to the monometallic Pt/HZSM-5 catalysts. The rate constant of deactivation (k deactiv ), according to the first-order generalized power law equation model, for the bimetallic catalysts is up to 120 times lower than that of the monometallic counterparts, depending on the Pt loading. In conclusion, this breakthrough is achieved through the formation of the [Pt 1 –Zn n ] δ+ hybrid cluster, instead of Pt 0 cluster–proton adducts, in the micropores of the ZSM-5 zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Toward a second generation fuel efficient supersonic cruise aircraft structural design for efficiency

The unique challenge of this concept to the structural designer is discussed. The potential of the application of advanced structural design concepts and new titanium fabrication processes is emphasized. Highlighted are the results of a detailed structural analysis, including weight and flutter, showing successful use of the ATLAS structural design and analysis system. It is concluded that blending of the structure may not have an adverse impact on structural efficiency, weight, and manufacturing complexity.

Hoy, J. R.↗
DOE OSTI2021

Conductive Metallophthalocyanine Framework Films with High Carrier Mobility as Efficient Chemiresistors

Abstract The poor electrical conductivity of two‐dimensional (2D) crystalline frameworks greatly limits their utilization in optoelectronics and sensor technology. Herein, we describe a conductive metallophthalocyanine‐based NiPc‐CoTAA framework with cobalt(II) tetraaza[14]annulene linkages. The high conjugation across the whole network combined with densely stacked metallophthalocyanine units endows this material with high electrical conductivity, which can be greatly enhanced by doping with iodine. The NiPc‐CoTAA framework was also fabricated as thin films with different thicknesses from 100 to 1000 nm by the steam‐assisted conversion method. These films enabled the detection of low‐concentration gases and exhibited remarkable sensitivity and stability. This study indicates the enormous potential of metallophthalocyanine‐based conductive frameworks in advanced stand‐off chemical sensors and provides a general strategy through tailor‐make molecular design to develop sensitive and stable chemical sensors for the detection of low‐concentration gases.

Yue, Yan↗
DOE OSTI2021

Enhanced Data Efficiency Using Deep Neural Networks and Gaussian Processes for Aerodynamic Design Optimization

Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space and their ability to generate high-fidelity gradients that can then be used in a gradient-based optimizer. This makes them very well suited for high-fidelity simulation based aerodynamic shape optimization of highly parametrized geometries such as aircraft wings. However, the development of adjoint-based solvers involve careful mathematical treatment and their implementation require detailed software development. Furthermore, they can become prohibitively expensive when multiple optimization problems are being solved, each requiring multiple restarts to circumvent local optima. In this work, we propose a machine learning enabled, surrogate-based framework that replaces the expensive adjoint solver, without compromising on predicting predictive accuracy. Specifically, we first train a deep neural network (DNN) from training data generated from evaluating the high-fidelity simulation model on a model-agnostic design of experiments on the geometry shape parameters. The optimum shape may then be computed by using a gradient-based optimizer coupled with the trained DNN. Subsequently, we also perform a gradient-free Bayesian optimization, where the trained DNN is used as the prior mean. We observe that the latter framework (DNN-BO) improves upon the DNN-only based optimization strategy for the same computational cost. Overall, this framework predicts the true optimum with very high accuracy, while requiring far fewer high-fidelity function calls compared to the adjoint-based method. Furthermore, we show that multiple optimization problems can be solved with the same machine learning model with high accuracy, to amortize the offline costs associated with constructing our models. Our methodology finds applications in the early stages of aerospace design. (C) 2021 Published by Elsevier Masson SAS.

Renganathan, S. Ashwin↗