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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Nanostructures for Electrical Energy Storage (NEES) (2020 Final Technical Report)

Nanostructures for Electrical Energy Storage (NEES, www.efrc.umd.edu) was an Energy Frontier Research Center supported by the DOE Office of Science, Basic Energy Sciences, from 8/1/2009 to 7/31/2020. Led by the University of Maryland, NEES enjoyed extensive collaborations with its funded partners, including two DOE Laboratories and six universities. The NEES vision has been to reveal a set of scientific insights and design principles that can underpin a next-generation electrical energy storage approach, building on advances in nanoscale science and technology to achieve simultaneous high power and high energy over extended charge/discharge cycling. The vision is motivated by the recognition that scaling into the nano regime opens the door to new physical phenomena and that the tools enlisted in nanoscale research provide major new opportunities for the synthesis not only of materials at molecular scale but for structures at nano scale and above. NEES has translated this vision into its research program based on two observations. First, while the behavior of ions and electrons in electrolytes and in electrode materials is crucial to electrical energy storage (or more appropriately electrochemical energy storage), it is the transport of ion and electron charge between different structural components of a storage device that ultimately determine its performance. With it well recognized that the choice of electrode materials typically constrain ion transport kinetics as well as maximum ion concentration, the search for better electrode materials has been a primary driver of battery research. At the same time the synthesis of electrodes is typically based on aggregation of particles with varying size, shape, and orientation in the electrode. Together with the presence of additional materials to impart electrical conductivity and cohesion to the composite electrode, change in electrode materials is necessarily accompanied by structural changes at the nano/micro scale that are difficult to categorize and manage. From the beginning, NEES’ vision has been to create and study simpler, highly controlled spatial arrangements of known materials as battery components (electrodes, current collectors, and electrolyte) and to understand how design and structure above the molecular scale determines the energy storage performance available from known materials. Second, advances in nanoscience dramatically expanded the portfolio of synthesis methods, structural motifs, and new phenomena available for research. Some of these gave rapid access to new building blocks at the deep nanoscale (e.g., carbon nanotubes grown by self-assembly, nanoscale arrays formed by electrochemical self-alignment, monolayer films controlled by self-limiting reaction). Such advances served as the enabler for the NEES vision to be pursued experimentally through study of 3D structures created and controlled at the nano, micro, and meso scales. Here, we use meso as in the BES MESO Report, implying not only intermediate or varying length scales, but very much the way behavior is influenced by other factors including aggregation of nanocomponents at different densities and spatial configurations, statistical variations in the aggregates, hierarchical architectures in which they can be assembled, or local 3D configurations that result from the architectures. Over its life cycle, NEES has pursued two overarching goals: (1) to understand the scientific fundamentals of electrochemical storage from the nanoscale to the mesoscale; and (2) to create and learn from innovative, controlled, heterogeneous nanostructures, where such nanostructures can enable the first goal and serve as models for future paradigms in energy storage. Specific goals have included: Synthesize heterogeneous nanostructures comprised of multiple materials arranged in controlled fashion and characterize their behavior; Demonstrate and elucidate design principles for achieving simultaneous high power and high energy; Develop materials processes which enable precision control of thin layers and 3D structures; Investigate the impact of artificial interphases on electrode stability during ion insertion/deinsertion; Create dense arrays of nanostructures to understand how the architecture of these assemblies, along with nanostructure design, influences energy storage behavior at the mesoscale; Identify and understand the consequences of nanoconfinement and local inhomogeneities in 3D mesoscale arrays; Develop and apply computational models to stimulate, guide and interpret experiments.

25 ENERGY STORAGE↗
DOE OSTI2024

Machine Learning Based Prediction of Airflow Maldistribution in A-Type Heat Exchangers

Airflow maldistribution is one of the primary causes of performance degradation in air-to refrigerant heat exchangers (HX) and has been shown to decrease heat transfer by as much as 35%. As a result, many units are oversized to meet the target capacity, resulting in increased system cost and refrigerant charge. Several studies have explored how characteristics like package type and HX geometry impact the flow profile, but results are restricted to a limited range of parameters and cannot be extrapolated to new designs. In this work, a machine learning (ML) model is trained to predict the inlet flow profile of dry air entering A-type HXs across a broad range of geometries and conditions. Flow profiles are generated using a porous media CFD model and used to train an Artificial Neural Network (ANN) which exhibits maximum and average relative L2 norm errors of 0.48 and 0.05. Additionally, these predictions take less than a second to generate resulting in a speed up factor of 2.42E5 compared to CFD. Component-level simulations are conducted to determine the performance degradation resulting from the predicted airflow maldistribution profiles. The new ML model will enable rapid and accurate prediction of performance degradation resulting from airflow maldistribution in A-type HXs, allowing for more accurate and cost-effective HX design.

42 ENGINEERING↗
DOE OSTI2024

Comprehensive Comparative Analysis: VSI-based vs. CSI-based Motor Drive Systems with Sinusoidal Output Voltage

The emergence of wide-bandgap (WBG) power devices opens opportunities for current source inverters (CSIs) to provide a promising alternative drive configuration for motor drive applications. The sinusoidal output voltage of CSI offers significant advantages for numerous motor drive applications, including reducing the risks associated with motor terminal overvoltages and bearing discharge currents. This paper compares the performance of CSIs and voltage source inverters (VSIs) with the same performance capabilities. More specifically, sine filters are added to the VSI output terminals to match the CSI performance, and a front-end boost converter is added to the VSI to match the CSI’s voltage-boost capability. The results show that the CSI active components require 48% less volume than the VSI, combined with other performance advantages that make it an appealing candidate for some future motor drive applications.

current source inverter, motor drive system, passi↗
DOE OSTI2021

It’s Time to Talk About HPC Storage: Perspectives on the Past and Future

High-performance computing (HPC) storage systems are a key component of the success of HPC to date. Recently, we have seen major developments in storage-related technologies, as well as changes to how HPC platforms are used, especially in relation to artificial intelligence and experimental data analysis workloads. Additionally, these developments merit a revisit of HPC storage system architectural designs. In this article, we discuss the drivers, identify key challenges to status quo posed by these developments, and discuss directions future research might take to unlock the potential of new technologies for the breadth of HPC applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Melting temperature, emissivity, and thermal conductivity of rare-earth silicates for thermal and environmental barrier coatings

In recent years, rare-earth silicates have become the industry standard for coating state-of-the-art SiC ceramic matrix composite (CMC) gas turbine engine components, due to their low volatility, high melting point, and thermal shock resistance. Current research is focused on designing rare-earth silicate based thermal-environmental barrier coatings (T/EBCs) with improved resistance to CMAS (CaO-MgO-Al 2 O 3 -SiO 2 ), steam, and crack formation, while maintaining high temperature performance and stability. Here, in this work we compare the high temperature performance of a variety of single and multi-component rare-earth mono- and disilicates (MS, DS) and rare earth apatites by measuring their melting points and spectrally averaged visible emissivities using laser heating and radiation pyrometry. We also report room temperature thermal conductivity measured by time-domain thermoreflectance (TDTR).

Environmental barrier coatings↗
DOE OSTI2026

Benchmarking state-of-the-art theory and empirical models of pionless neutrino-argon scattering in GENIE

Upcoming experiments need improved simulations of neutrino scattering. This work uses the popular GENIE event generator to test a variety of neutrino interaction models against recent MicroBooNE measurements of pionless charged-current interactions. The GENIE code can easily interchange model components, including nucleon form factor parameterizations, quasielastic cross-section calculations, treatments of the nuclear ground state and hadronic final-state interactions. Leveraging this software capability in comparisons with MicroBooNE data, the performance of some of GENIE’s most theoretically sophisticated model components is evaluated and contrasted with more empirically-driven alternatives.

Neutrino cross section↗
DOE OSTI2021

Improving Thermal Stability of Perovskite Solar Cells by Suppressing Ion Migration Using Copolymer Grain Encapsulation

Thermal stability of organic–inorganic hybrid perovskites (OIHPs) remains as one of the critical challenges against the stable operation of perovskite solar cells (PSCs) in direct sunlight with elevated temperatures. Here, we show that the addition of a polystyrene-co-polyacrylonitrile (SAN) copolymer can significantly enhance thermal stability of OIHPs and improve the stability of the corresponding PSCs by suppressing the migration of organic cations in OHIP. The methylammonium lead iodide (MAPI) with SAN incorporated within the perovskite layer featured a superior thermal stability compared to pure MAPI without SAN, only displaying an average of 5–15% decrease in PCE even after continuous thermal aging for 24 h at 100 °C. The secondary ion mass spectrometry revealed that the thermal degradation of the pure MAPI was largely associated with MA+ out-migration. Conducting atomic force microscopy analysis further indicated that the incorporated SAN led to a suppression of ionic currents present at the grain boundaries of the perovskite film, which was understood by high immiscibility between SAN and MA+ components as confirmed by the experimentally estimated Flory–Huggins parameter between them. This study newly identifies a potential of using polymer grain encapsulation for enhancing thermal stability of OIHPs and their solar cell performance by suppressing the out-diffusion of cationic organic components.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Prototype HB650 Cryomodule Heat Loads Simulations

During the design stages of the PIP-II cryomodules, many analytical calculations and FEA have been performed on simpler geometry in order to estimate the heat loads and also to optimize the design. To better analyze the cryomodule cold tests, simulations have been performed with MATLAB to determine the temperature of the main components during cool down and to determine the heat loads of the cryomodule. These simulations have been applied to the High Beta 650 MHz prototype cryomodule design and compared to the cold tests performed on it.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Multivariate Curve Resolution (MCR) using Principal Components Inputs and Rigorous Equality and Inequality Constraints

This MATLAB pseudocode perform multivariate curve resolution (MCR) using PCA scores & loadings of data as inputs. It employs rigorous least squares equality and inequality constraints for all elements in the solution factor matrices. It also can be used to perform nonnegative matrix factorization. SAND2020-12650 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Van Benthem, Mark↗
DOE OSTI2024

Sensitivity Analysis for the Component Design App: Analysis of Success Assured Data

A new tool has been developed to perform variance-based global sensitivity analysis (VBGSA) on data from a set-based concurrent engineering software called Success Assured (SA). The tool is part of a digital component design app, which is currently in production as an Accelerated Digital Engineering Pathfinder at Sandia National Laboratories. When working with complex digital models, it is important to understand relationships between inputs and outputs, i.e., how “sensitive” model outputs are to changes in model inputs. After extensive research and trials of various sensitivity analysis methods, it was determined that estimation of Sobol’ indices for VBGSA with Monte Carlo simulation, paired with simple surrogate models, produces the best results for SA data. This tool increases understanding of SA models and streamlines the creation of SA datasets. This report details the methodology and implementation of this sensitivity analysis tool so others can understand it and implement it.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Singular value decomposition and similarity renormalization group evolution of nuclear interactions

One of the main challenges for ab initio nuclear many-body theory is the growth of computational and storage costs as calculations are extended to heavy, exotic, and structurally complex nuclei. Here, we investigate the factorization of nuclear interactions as a means to address this issue. We perform Singular Value Decompositions of nucleon-nucleon interactions in partial wave representation and study the dependence of the singular value spectrum on interaction characteristics like regularization scheme and resolution scales. We develop and implement the Similarity Renormalization Group (SRG) evolution of the factorized interaction, and demonstrate that this SVD-SRG approach accurately preserves two-nucleon observables. We find that low-resolution interactions allow the truncation of the SVD at low rank, and that a small number of relevant components is sufficient to capture the nuclear interaction and perform an accurate SRG evolution, while the Coulomb interaction requires special consideration. The rank is uniform across all partial waves, and almost independent of the basis choice in the tested cases. This suggests an interpretation of the relevant singular components as mere representations of a small set of abstract operators that can describe the interaction and its SRG flow. Following the traditional workflow for nuclear interactions, we discuss how the transformation between the center-of-mass and laboratory frames creates redundant copies of the partial wave components when implemented in matrix representation, and we discuss strategies for mitigation. Lastly, we test the low-rank approximation to the SRG-evolved interactions in many-body calculations using the In-Medium SRG. By including nuclear radii in our analysis, we verify that the implementation of the SRG using the singular vectors of the interaction does not spoil the evolution of other observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

In situ data acquisition and real-time analysis system

A testing system for evaluating the performance of an electrical/electronic UUT under dynamic operating conditions. The testing system includes a dynamic testing component (e.g., a centrifuge) for applying a stimulus to the UUT, and an iDAQ system configured to perform in situ data acquisition and real-time data analysis. The iDAQ system may also be subject to the stimulus. The iDAQ system includes a processor (e.g., an SoC) component, a power supply, a CR/I component, an IR component, and a single enclosure. The processor component may control the dynamic testing component, including varying in real-time the stimulus applied to the UUT. The processor component may include multiple input channels, and a high current/voltage subcomponent of the power supply may be configured to supply up to five hundred volts.

Benyhesan, Mohammad K.↗
DOE OSTI2021

n ‐Type Rigid Semiconducting Polymers Bearing Oligo(Ethylene Glycol) Side Chains for High‐Performance Organic Electrochemical Transistors

Abstract N‐type conjugated polymers as the semiconducting component of organic electrochemical transistors (OECTs) are still undeveloped with respect to their p‐type counterparts. Herein, we report two rigid n‐type conjugated polymers bearing oligo(ethylene glycol) (OEG) side chains, PgNaN and PgNgN, which demonstrated an essentially torsion‐free π‐conjugated backbone. The planarity and electron‐deficient rigid structures enable the resulting polymers to achieve high electron mobility in an OECT device of up to the 10 −3 cm 2 V −1 s −1 range, with a deep‐lying LUMO energy level lower than −4.0 eV. Prominently, the polymers exhibited a high device performance with a maximum dimensionally normalized transconductance of 0.212 S cm −1 and the product of charge‐carrier mobility μ and volumetric capacitance C* of 0.662±0.113 F cm −1 V −1 s −1 , which are among the highest in n‐type conjugated polymers reported to date. Moreover, the polymers are synthesized via a metal‐free aldol‐condensation polymerization, which is beneficial to their application in bioelectronics.

Chen, Xingxing↗
DOE OSTI2022

Carbon Dioxide Capture Chemistry of Amino Acid Functionalized Metal-Organic Frameworks in Humid Flue Gas

Here, metal-organic framework-808 has been functionalized with 11 amino acids (AA) to produce a series of MOF-808-AA structures. The adsorption of CO 2 under flue gas conditions revealed that glycine- and DL-lysine-functionalized MOF-808 (MOF-808-Gly and -DL-Lys) have the highest uptake capacities. Enhanced CO 2 capture performance in the presence of water was observed and studied using single-component sorption isotherms, CO 2 /H 2 O binary isotherm, and dynamic breakthrough measurements. The key to the favorable performance was uncovered by deciphering the mechanism of CO 2 capture in the pores and attributed to the formation of bicarbonate as evidenced by 13 C and 15 N solid-state nuclear magnetic resonance spectroscopy studies. Based on these results, we examined the performance of MOF-808-Gly in simulated coal flue gas conditions and found that it is possible to capture and release CO 2 by vacuum swing adsorption. MOF-808-Gly was cycled at least 80 times with full retention of performance. This study significantly advances our understanding of CO 2 chemistry in MOFs by revealing how strongly bound amine moieties to the MOF backbone create the chemistry and environment within the pores, leading to the binding and release of CO 2 under mild conditions without application of heat.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

An Enhanced Vertical Ground Heat Exchanger Model for Whole-Building Energy Simulation

This paper presents an enhanced vertical ground heat exchanger (GHE) model for whole-building energy simulation (WBES). WBES programs generally have computational constraints that affect the development and implementation of component simulation sub-models. WBES programs require models that execute quickly and efficiently due to how the programs are utilized by design engineers. WBES programs also require models to be formulated so their performance can be determined from boundary conditions set by upstream components and environmental conditions. The GHE model developed during this work utilizes an existing response factor model and extends its capabilities to accurately and robustly simulate at timesteps that are shorter than the GHE transit time. This was accomplished by developing a simplified dynamic borehole model and then exercising that model to generate exiting fluid temperature response factors. This approach blends numerical and analytical modeling methods. The existing response factor models are then extended to incorporate the exiting fluid temperature response factor to provide a better estimate of the GHE exiting fluid temperature at short simulation timesteps.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Multiplexing Focusing Analyzer for Efficient Stress-Strain Measurements

Statement of the problem or situation that is being addressed. Although thermal and cold neutron scattering is widely used and is critical for success in many areas of materials science and engineering, relatively low neutron fluxes severely limit applications of not only laboratory neutrons generators, but also large national neutron facilities. State-of-the-art thermal and cold neutron sources are large expensive national facilities, which serve diverse community of scientific and industrial users. The constant need to improve the instruments performance, stems from the fact that neutron methods are gaining in popularity, and becoming more and more powerful, while new neutron sources are not being constructed to keep pace with the developments and needs of the scientific community. Small research reactors at universities and National Labs, and laboratory-based neutron generators, are necessary not only for education and training, but also when samples cannot be transported to other facilities. However, the standard neutron techniques, which were developed for high-flux facilities, require much higher efficiencies to be used effectively with the low fluxes of small sources. Thus, the efficient use of neutron sources, such as with our proposed analyzer, is important for the progress and broader use of these neutron techniques. General statement of how this problem is being addressed. We propose to design and demonstrate novel diffractive optical device, which will enable very efficient residual stress neutron diffractometers. The proposed device will be a multi-foil analyzer, where each foil is constructed of focusing bent single crystals of Si. Such device will enable polychromatic residual stress neutron diffraction. At large national facilities, such as at Oak Ridge National Laboratory, these analyzers would enable very fast measurements for determining residual stress tensors, raster large samples or screen multiple samples. Commercial Applications and Other Benefits The outcome of this project would be the demonstration of commercial devices, novel neutron optical components, which could be utilized to improve the performance of existing instruments or build novel neutron scattering instruments at DOE neutron facilities and commercial laboratory neutron sources. These new devices will widen the scope of research conducted using neutrons and enable measurements not feasible at present. Summary for Members of Congress Thermal and cold neutron beams are a powerful materials science probe, which provide unique information about the structure of matter. The proposed innovations expand the reach of neutron-based investigations to new materials and industries by enabling new instrumentation capabilities, thereby greatly enhancing and expanding the role of small, laboratory-based neutron instrumentation, and improving education and training of neutron users.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

High performance heat exchangers for next generation hybrid cooler (CRADA Final Report)

The evaporative cooling process has been successfully deployed in multiple energy conversion processes such as power generation, process cooling, heating, ventilation & cooling (HVAC), and commercial and industrial refrigeration. The heat exchanger is a very common yet extremely critical component of such systems. The device is important since the performance of the overall cooling system heavily relies on the thermal-hydraulic efficiency of the heat exchanger. The possible wet operation as evaporative cooling heat exchanger complicates the issue. Indeed, based on the hybrid nature of operation (fully dry, partially wet, fully wet) the efficiency can vary significantly and can cause performance variation for the whole system. Understanding the importance of the issue, Oak Ridge National Laboratory (Contractor) and Baltimore Aircoil Company (Participant) propose an activity focused on the analysis of the existing heat exchanger technology used in air and evaporative cooling processes and design, development and demonstration of a novel heat exchanger design based on porous materials. The potential candidates include metallic wire meshes and metal foams carefully designed for the proposed application. Prior research has indicated that these materials have great potential for deployment in thermal systems, particularly heat sinks and heat exchangers. It is expected that the successful completion of the project will lead to novel heat exchanger technology for hybrid systems (capable of dry and wet operation) by exploring newly emerging materials and their potential for heat transfer application. The overall goal is to develop a next generation heat exchanger technology which can be deployed in evaporative cooling systems. The impact of the such development is significant since, it will not only make the overall system highly efficient but will also, reduce the total refrigerant charge in the heat exchanger, a critical aspect for the deployment of refrigerants with lower Global Warming Potential (GWP).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Initial Fracture Propagation Modeling of Graphite Components with Grizzly

Graphite has historically been extensively used in power reactor cores and will be used in multiple types of advanced reactors currently under development. These graphite structural components can experience significant stresses due to nonuniform volumetric strains induced by irradiation and thermal expansion, which can lead to fracture. Robust tools for predicting fracture initiation and propagation in graphite structural components in nuclear reactors are important for evaluating component integrity, developing design standards, and interpreting experimental results to characterize graphite performance. The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program has been developing degradation models for other structural components in nuclear reactors within the Grizzly and BlackBear codes. This report documents an effort to develop initial capabilities for modeling graphite fracture within these codes, building on prior efforts to model fracture in other materials. Major elements of this effort include developing a new system for modeling fracture nucleation and growth in two dimensions using the extended finite element method and incorporating a damage and plasticity model. These capabilities are applied here to model a representative graphite component and a splitting disc experiment used to obtain tensile strength.

36 MATERIALS SCIENCE↗