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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Treatment of Launch Vehicle Flight Control Stability Margin Reductions for Crewed Missions with Emphasis on Slosh Dynamics

NESC’s perspective for crewed spaceflight: Acceptance of flight control gain/phase stability margin reductions from industry standards should be accompanied by an adequately extensive technical treatment, including: •Analyzing the fundamental physics involved, with applicable simulation tool verification (particularly if results are dissimilar among rules of thumb, linear tools, nonlinear analysis, and flight data) •Conducting sensitivity studies in time and frequency domains to analyze effects of possible parameter and system variations •Studying the effects of the consequence of instability associated with offending modes by running stressing cases in time domain •Assessing alternative flight control designs to demonstrate that present design appropriately balances overall vehicle risk (i.e., quantitatively delineate chosen tradeoffs between various stability margins and vehicle performance in the context of risk/consequence) Work presented here represents an example summary of expected engineering work to flight-certify crewed missions with unstable slosh modes and reduced stability margins

Launch Vehicle Flight Control↗
NASA NTRSDate not supplied

Machine learning based noise reduction for satellite products: application to solar-induced fluorescence retrievals using simulated and real data

In the past two decades, global satellite measurements of terrestrial chlorophyll solar-induced fluorescence (SIF) have been used widely for a number of different applications related to physiology, phenology, and productivity of plants. However, SIF retrievals are inherently noisy due to the relatively small SIF spectral signature in comparison with observational noise. In this work, we examine how a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network can be used to reduce noise and other artifacts in satellite level 2 (L2) products. We first apply the approach in a controlled environment in which radiance spectra are simulated with a full atmospheric and surface radiative transfer model for different scenarios including various SIF values that are known. Various levels of noise can be added to the simulated spectra. Resulting noisy and noise-reduced SIF retrievals are compared with the true values to assess performance. We then apply the noise reduction approach to real SIF derived from instruments flying on meteorological satellites. The results are evaluated by comparing SIF retrievals from different platforms with each other and with other independent data sets, showing enhanced capability to capture seasonal and interannual variability in SIF.

Chlorophyll fluorescence↗
DOE OSTI2021

Efficient Active Learning for Gaussian Process Classification by Error Reduction

Active learning sequentially selects the best instance for labeling by optimizing an acquisition function to enhance data/label efficiency. The selection can be either from a discrete instance set (pool-based scenario) or a continuous instance space (query synthesis scenario). In this work, we study both active learning scenarios for Gaussian Process Classification (GPC). The existing active learning strategies that maximize the Estimated Error Reduction (EER) aim at reducing the classification error after training with the new acquired instance in a onestep-look-ahead manner. The computation of EER-based acquisition functions is typically prohibitive as it requires retraining the GPC with every new query. Moreover, as the EER is not smooth, it can not be combined with gradient-based optimization techniques to efficiently explore the continuous instance space for query synthesis. To overcome these critical limitations, we develop computationally efficient algorithms for EER-based active learning with GPC. Further, we derive the joint predictive distribution of label pairs as a one-dimensional integral, as a result of which the computation of the acquisition function avoids retraining the GPC for each query, remarkably reducing the computational overhead. We also derive the gradient chain rule to efficiently calculate the gradient of the acquisition function, which leads to the first query synthesis active learning algorithm implementing EER-based strategies. Our experiments clearly demonstrate the computational efficiency of the proposed algorithms. We also benchmark our algorithms on both synthetic and real-world datasets, which show superior performance in terms of sampling efficiency compared to the existing state-of-the-art algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Synthesis of High Surface Area VS2 for Nitrogen Reduction

Ammonia synthesis from dinitrogen provides a critical chemical feedstock to agriculture worldwide. The dominant process for ammonia synthesis is the Haber-Bosch process, which is fossil-fuel dependent and energy intensive. The electrochemical nitrogen reduction reaction (NRR) could provide a more environmentally friendly route to industrial ammonia synthesis. We have worked to realize electrochemical NRR by developing transition metal dichalcogenide NRR catalysts. In the first part of this presentation, a VS2-based NRR electrocatalyst, which has shown promising activity and selectivity, will be presented. The synthesis of this VS2-based catalyst is straightforward and results in few-layer VS2 or VSx, (x < 2) nanoflakes. Additionally, the proposed mechanism of NRR on VS2 will be discussed, and we will discuss DFT simulation of NRR on VS2 and MoS2 as well as planned in-situ Raman experiments to probe this mechanism. In the second part of this presentation, we will share several lessons learned during our early NRR research including important points of electrochemical cell design and experimental controls to reduce environmental ammonia contamination of experiments. Finally, we will address areas of opportunity for electrochemical NRR.

dichalcogenide↗
DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗
DOE OSTI2023

Conservation Voltage Reduction with Distributed Energy Resource Management System, Grid-Edge, and Legacy Devices

Distribution utilities use conservation voltage reduction (CVR) to obtain energy savings and lower peak demand by reducing bus voltages. Traditionally, the CVR is accomplished by controlling the legacy assets such as load tap changers, voltage regulators, and capacitor banks. The deployment of the advanced distribution management system (ADMS) and distributed energy resource management system (DERMS) enables the integration of distributed energy resources into the distribution networks and provide the grid services including CVR. This paper studies the coordinated operation of an ADMS and a DERMS in achieving CVR and voltage regulation. A commercial ADMS uses legacy devices and Edge-of-Network Grid Optimization (ENGO) devices to obtain energy savings through CVR. A prototype DERMS dispatches the photovoltaic smart inverters based on real-time optimal power low to ensure voltage regulation across the feeder. The results show that the coordinated operation of ADMS and DERMS is effective in achieving CVR and voltage regulation. Specifically, energy savings of up to 4.7% are observed in the real utility distribution system used in this study.

advanced distribution management system↗
DOE OSTI2023

Evaluation of Composite Materials for Heliostat Cost Reduction

This is an evaluation of composite materials for heliostat cost reduction, including the motivation, reference heliostat model, characteristic wind loads, selection of pultruded structural composites, and technoeconomic analysis using equivalent deformation.

composite materials↗
DOE OSTI2024

Impacts of the Inflation Reduction Act on Consumer Energy Expenditures

The Inflation Reduction Act introduced or expanded a suite of federal tax credits for clean electricity generation and customer adoption of electric (and other highly efficient) end-use equipment. These incentives are expected to drive changes in both the electricity generation mix and demand for electricity (especially for space heating and light-duty vehicles), which are highly interconnected. In this session, Caitlin Murphy, Group Manager and Senior Analyst in NREL's Strategic Energy Analysis Center, will present findings from her team's recent state-level analysis on the combined effects of various IRA incentives on customer expenditures for electricity, natural gas, and gasoline. She will present and explain the regional variations observed in their analysis, based on interactions between end-use equipment cost and performance and projections for future energy prices.

air source heat pump↗
DOE OSTI2024

ION Work Reduction Opportunity Realization Demonstration

The purpose of this research was to realize one of the advanced training work reduction opportunities first presented in the Idaho National Laboratory (INL) report, “Process for Significant Nuclear Work Function Innovation Based on Integrated Operations Concepts” (INL/EXT-21-64134) [1], with a nuclear power plant (NPP) research partner. Researchers modernized two trainings: (1) an accredited instructor-led training (ILT) overview course on Westinghouse DS 480-volt (V) circuit breakers to a multimedia-focused computer-based-training (CBT) learning module, and (2) an on-demand chaptered video on how to properly rack and un-rack a Westinghouse DS 480-V circuit breaker. These modernized work products were developed and implemented in a manner consistent with the industry guidelines found in Institution of Nuclear Power Operations (INPO) Teaching and Learning 23-001 [2]. Researchers calculated that the modernized accredited training course reduced the time necessary to prepare and deliver the training material by a factor of 8:1. The amount of time learners spend in class could be reduced by this same factor. In other words, if a course took 8 hours to deliver a class, the new CBT instruction would take just over 1 hour. The researchers noted that the requirement for any practicum training by the learners with the instructor(s) would remain in place. But through interviews with new and experienced learners, the researchers discovered that the confidence of these learners in performing the racking and un-racking of the circuit breaker improved as a result of using the new modernized CBT process. Additionally, the learners who tested the modernized work products enjoyed the modernized CBT and the learning video significantly more than current in-class learning methods. These are encouraging results for the nuclear industry, as this modernization of training can be applied to other classes and is scalable across the industry. In line with the Integrated Operations for Nuclear (ION) model, positive workload analysis supports the investment of resources in modernizing NPP training processes and infrastructure. Implementation of the advanced training technologies in this report is likely to result in substantive long-term workload benefits to instructors and learners and result in hard-dollar savings on contractor spends. Additionally, investment in these modernized training processes will result in improved learner proficiency. The results of this research can be applied to additional operator, technical, and general training topics to provide additional workload and learning benefits in addition to what was explored.

42 ENGINEERING↗
DOE OSTI2020

Dual 3D Ceramic Textile Electrodes: Fast Kinetics for Carbon Oxidation Reaction and Oxygen Reduction Reaction in Direct Carbon Fuel Cells at Reduced Temperatures

Abstract Direct carbon fuel cells (DCFCs) are an efficient energy‐conversion technology capable of generating electricity with carbon‐dioxide‐capture chemistry with solid carbon as fuels. The efficiency and performance of DCFCs depend on the kinetics of the carbon oxidation reactions (COR) and the oxygen reduction reactions (ORR), each occurring at anode and cathode, respectively. The limited active sites paired with reduced temperatures greatly decrease the efficiency of the electrochemical reactions. Ultraporous dual‐3D ceramic textiles (dual‐3DCT) are integrated into electrolyte‐supported DCFCs to enhance charge and mass transfer at the electrodes. Improved COR at the anode is achieved by the synergy between the 3DCT NiO–Ce 0.8 Gd 0.2 O 1.95 (GDC) structure and optimal carbon fuel choice. In a comparative study, DCFCs using graphitic carbon (GC) as fuel show the best COR performance when compared to DCFCs utilizing alternative fuels such as carbon black (CB) and activated carbon (AC). The 3DCT Sm 0.5 Sr 0.5 CoO 3‐δ –GDC (SSC–GDC) composite cathode shows electrochemical performance superior to that of the conventional screen‐printed SSC–GDC. A peak power density of 392 mW cm −2 at 600 °C is obtained in a DCFC using the 3DCT‐anode/electrolyte/3DCT‐cathode configuration, an unprecedented value for any reported DCFC as of yet. This points toward promising applications of dual‐3DCT electrodes for reduced‐temperature DCFCs.

Bian, Wenjuan↗
DOE OSTI2022

Tailored Persistent Radical‐containing Heterotrimetal‐Organic Framework for Boosting Efficiency of Visible/NIR Light‐driven Photocatalytic CO 2 Reduction

Abstract Promoting light absorption range of photocatalysts is of great significance to improve solar light‐driven photocatalytic CO 2 reduction efficiency. Herein, a new viologen‐based multicomponent heterotrimetallic metal–organic framework (MOF) [Cu 3 Th 6 ( µ 3 ‐O) 4 ( µ 3 ‐OH) 4 (cpb) 12 ][Fe III (CN) 6 ] 6 (IHEP‐14) with an unprecedented (6, 18)‐connected she ‐ d topology is presented. Upon UV irradiation, this MOF undergoes ligand and iron photoreduction, and a single‐crystal‐to‐single‐crystal transformation to generate persistent radical‐containing MOF [Cu 3 Th 6 ( µ 3 ‐O) 4 ( µ 3 ‐OH) 4 (cpb • ) 12 ][Fe II (CN) 6 ] 6 (IHEP‐15). This radical‐containing MOF shows excellent stability without fading after at least 2 months in air. Besides extending the photoabsorption to a wider wavelength range covering from 200 to 2,500 nm, the generation of persistent radical in IHEP‐15 also largely enhances its CO 2 adsorption capacity by a factor of three due to the strong affinity between π orbital of the radical and the π system of CO 2 . These attributes endow IHEP‐15 with excellent visible/NIR light‐driven CO 2 photoreduction activity, with CO production rates under visible and NIR irradiation of 570.3 and 209.3 µmol h −1 g −1 , respectively. Notably, the latter is a record high for NIR‐induced CO production among all MOFs reported so far.

Hu, Kong‐Qiu↗
DOE OSTI2025

Topotactic Reduction‐Driven Crystal Field Excitations in Brownmillerite Manganite Thin Films

Topotactic reduction of perovskite oxides offers a powerful approach for discovering novel phenomena, such as superconducting infinite-layer nickelates and polar metallicity, and is commonly accompanied by the emergence of multiple valence states and/or complex crystal fields of transition metals. However, understanding the complex interplay between crystal chemistry, electronic structure, and physical properties at the spin- and orbital-resolved levels in these reduced systems remains elusive. Here, in this study, x-ray absorption spectroscopy, resonant inelastic x-ray scattering (RIXS), and density functional theory calculations are used to uncover topotactic metal-insulator transition and orbital-specific crystal field excitations in brownmillerite La 0.67 Ca 0.33 MnO 2.5 thin films. The Mn valence states are found to be Mn 2+ /Mn 3+ , along with their corresponding populations at octahedral and tetrahedral sites, which effectively weaken the Mn-O hybridization compared to the parent perovskite phase. As a result, La 0.67 Ca 0.33 MnO 2.5 films exhibit an antiferromagnetic insulating ground state. Moreover, by combining the RIXS measurements on selected single-valence manganites, specifically MnO, LaMnO 3 , and CaMnO 3 , with orbital- and spin-resolved density-of-states calculations, the study identifies the dd excitations of octahedrally and tetrahedrally coordinated Mn 2+ /Mn 3+ ions, directly linking the microscopic electronic structure to the macroscopic magnetic/electrical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Designed Iron Single Atom Catalysts for Highly Efficient Oxygen Reduction Reaction in Alkaline and Acid Media

Abstract Single atom catalysts (SACs) have attracted much attentions due to their advantages of high catalysis efficiency and excellent selectivity. However, for industrial applications, synthesis of SACs in large and practical quantities is very important. The challenge is to develop synthesis methods with controllability and scalability. Herein, a well‐characterized and scalable method is demonstrated to synthesize atomically dispersed iron atoms coordinated with nitrogen on graphene, SAFe @ NG, with high atomic loading (≈4.6 wt%) through a one‐pot pyrolysis process. The method is scalable for the fabrication of Fe SACs with high quantities. The Fe–N–G catalyst exhibits high intrinsic oxygen reduction reaction (ORR) performance, reaching half potential of 0.876 and 0.702 V in alkaline and acidic solutions, respectively, with excellent microstructure stability. Furthermore, the density functional theory (DFT) simulation confirms that the Fe atoms in coordination with four nitrogen atoms, FeN4, in graphene is the active center for the 4‐electron ORR process. This work demonstrates an efficient design pathway for single atom catalysts as highly active and stable electrocatalysts for high‐performance ORR applications.

Zhao, Shiyong↗
DOE OSTI2020

Biaxial Strains Mediated Oxygen Reduction Electrocatalysis on Fenton Reaction Resistant L1 0 ‐PtZn Fuel Cell Cathode

Abstract PtM alloy catalysts (e.g., PtFe, PtCo), especially in an intermetallic L1 0 structure, have attracted considerable interest due to their respectable activity and stability for the oxygen reduction reaction (ORR) in proton exchange membrane fuel cells (PEMFCs). However, metal‐catalyzed formation of ·OH from H 2 O 2 (i.e., Fenton reaction) by Fe‐ or Co‐containing catalysts causes severe degradation of PEM/catalyst layers, hindering the prospects of commercial applications. Zinc is known as an antioxidant in Fenton reaction, but is rarely alloyed with Pt owing to its relatively negative redox potential. Here, sub‐4 nm intermetallic L1 0 ‐PtZn nanoparticles (NPs) are synthesized as high‐performance PEMFC cathode catalysts. In PEMFC tests, the L1 0 ‐PtZn cathode achieves outstanding activity (0.52 A mg Pt −1 at 0.9 V iR ‐free , and peak power density of 2.00 W cm −2 ) and stability (only 16.6% loss in mass activity after 30 000 voltage cycles), exceeding the U.S. DOE 2020 targets and most of the reported ORR catalysts. Density function theory calculations reveal that biaxial strains developed upon the disorder‐order (A1L1 0 ) transition of PtZn NPs would modulate the surface PtPt distances and optimize PtO binding for ORR activity enhancement, while the increased vacancy formation energy of Zn atoms in an ordered structure accounts for the improved stability.

Liang, Jiashun↗
DOE OSTI2020

Hierarchical Polyelemental Nanoparticles as Bifunctional Catalysts for Oxygen Evolution and Reduction Reactions

Efficient electrocatalysts are critical in various clean energy conversion and storage systems. Polyelemental nanomaterials are attractive as multi-functional catalysts due to their wide compositions and synergistic properties. However, controlled synthesis of polyelemental nanomaterials is difficult due to their complex composition. Herein, we present a one-step synthetic strategy to fabricate a hierarchical polyelemental nanomaterial, which contains ultrasmall precious metal nanoparticles (IrPt, ~5 nm) anchored on spinel-structure transition metal oxide nanoparticles. The polyelemental nanoparticles serve as excellent bifunctional catalysts for the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR). The mass catalytic activity of the polyelemental nanoparticles is 7-times higher than that of Pt in ORR and 28-times that of Ir in OER at the same overpotentials, demonstrating the high activity of the bifunctional electrocatalyst. We attribute this outstanding performance to the controlled multiple elemental composition, mixed chemical states, and large electroactive surface area. The hierarchical nanostructure and polyelemental design of these nanoparticles offers a general and powerful alternative material for catalysis, solar cells, and more.

25 ENERGY STORAGE↗