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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three-dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals and alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2023

High-pressure CO 2 dissociation with nanosecond pulsed discharges

Herein we investigate the conversion of CO 2 into CO and O 2 with nanosecond repetitively pulsed (NRP) discharges in a high-pressure batch reactor. Stable discharges are obtained at up to 12 bar. By-products are measured with gas chromatography. The energy efficiency is determined for a range of processing times, pulse energy, and fill pressures. It is only weakly sensitive to the plasma operating parameters, i.e the extent of CO 2 conversion is almost linearly-dependent on the specific energy invested. A conversion rate as high as 14% is achieved with an energy efficiency of 23%. For long processing times, saturation in the yield and a drop in efficiency are observed, due to the increasing role of three-body recombination reactions, as described by zero-dimensional detailed kinetic modeling. The modeling reveals the presence of three-stage kinetics between NRP pulses, controlled by electron-impact CO 2 dissociation, vibrational relaxation, and neutral elementary kinetics. Transport effects are shown to be important for CO 2 conversion at high pressures. For fill pressures beyond 10 bar, CO 2 may locally transit into supercritical states. The supercritical plasma kinetics may bypass atomic oxygen pathways and directly convert CO 2 into O 2 . This work provides a detailed analysis of plasma-based high-pressure CO 2 conversion, which is of great relevance to future large-scale sustainable carbon capture, utilization, and storage.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Characterization of the Hamamatsu 8-inch R14688-100 PMT

Large-scale optical neutrino and dark-matter detectors rely on large-area photomultiplier tubes (PMTs) for cost-effective light detection. The new R14688-100 8-inch PMT developed by Hamamatsu provides state-of-the-art timing resolution of around 1 ns (FWHM), which can help improve vertex reconstruction and enable Cherenkov and scintillation light separation in scintillation-based detectors. This PMT also provides excellent charge resolution, allowing for precision photoelectron counting and improved energy reconstruction. The Eos experiment is the first large-scale optical detector to utilize these PMTs. Here, in this manuscript, we present a characterization of the R14688-100 single photoelectron response, such as the transit-time spreads, the dark-rates, and the afterpulsing. The single photoelectron response measurements are performed for the 206 PMTs that will be used in Eos.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Spin-filter tunneling detection of antiferromagnetic resonance with electrically tunable damping

Antiferromagnetic spintronics offers the potential for higher-frequency operations and improved insensitivity to magnetic fields compared to ferromagnetic spintronics. However, previous electrical techniques to detect antiferromagnetic dynamics have utilized large, millimeter-scale bulk crystals. In this work, we demonstrate direct electrical detection of antiferromagnetic resonance in structures on the few-micrometer scale using spin-filter tunneling in platinum ditelluride (PtTe 2 )/bilayer chromium sulfide bromide (CrSBr)/graphite junctions in which the tunnel barrier is the van der Waals antiferromagnet CrSBr. This sample geometry allows not only efficient detection but also electrical control of the antiferromagnetic resonance through spin-orbit torque from the PtTe 2 electrode. The ability to efficiently detect and control antiferromagnetic resonance enables detailed studies of the physics governing these high-frequency dynamics.

Cham, Thow Min Jerald [Cornell University, Ithaca,↗
DOE OSTI2023

Review of capture cross sections relevant for intentional nuclear forensics

The NA-22 Intentional Forensics Venture is developing a system for tagging nuclear fuel using various methods of information encoding. One of the main methods under development is the insertion of isotopically enriched tracers into the fuel. In order to aid in the understanding of the neutronic performance of these taggants, we assess the quality of the nuclear data underpinning simulations, which are driven by the neutron-capture cross sections. We present these cross sections of naturally occurring isotopes of the elements provided in the neutron sublibrary of the planned ENDF/B-VIII.1 Feb. 2023 library release. We make this assessment using a rubric designed for this effort, which quantifies orthogonal features related to the overall quality. The quality metric highlights 6 aspects: experimental data, resonance evaluations, integral metrics, covariances, fission products, and documentation. We focus on energy ranges relevant for reactor applications. We also discuss additional sources for new, high-quality cross-section data that may be utilized on the time scale of the venture, including existing global data, new experiments, and computational methods. Finally, overall outlook is presented with conclusions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Durable, High-Performance Unitized Reversible Fuel Cells Based on Proton Conductors

The main objective of this project was to develop robust, highly efficient, and economically viable H + -conducting membrane-based, unitized reversible fuel cell (H-URFC) technology for large-scale co-located energy storage and power generation. Another objective of this project is to gain a profound understanding of the degradation mechanisms of key stack materials and interfaces using various in situ, ex situ, and operando measurements guided by theoretical analysis. Nanostructured components will be integrated into cell design and the interfaces between electrodes and electrolyte will be modified with active bi-functional catalysts and protective coatings in order to achieve >70% roundtrip efficiency at 1 A/cm2 in both the fuel cell and the electrolysis modes. The end goal of the project is to advance the technology to the point that a university-industry collaboration can be established to scale up the technology for early adoption, and eventually enabling a pathway to large-scale energy storage that utilizes chemical storage and conversion for electrical grid balancing.

08 HYDROGEN↗
DOE OSTI2024

Next Generation Solid Oxide Fuel Cell Module Development

The overall objective of this project was to develop a transformative Solid Oxide Fuel Cell (SOFC) building block configuration comprised of multi-stack arrays that can be utilized in large-scale power plants. This transformative design signified the benefits of lower performance degradation coupled with improved reliability, low cost, smaller packaging for easier transport and installation, and improved maintenance and field serviceability characteristics. The project goal was to design and fabricate a scalable hot module for housing an array of SOFC stacks and to demonstrate the characteristics of the module gas distribution, insulation and instrumentation, and DC power take-off. The approach was to validate the design of a stack prototype scalable to megawatt (MW) class systems using FuelCell Energy’s Compact SOFC Architecture (CSA) stacks. The scope of work was intended to design, build, and test a compact and low-cost multi-stack sub-module with flexibility to house CSA stacks and scalable to 350 kW which could ultimately be deployed in construction of MW-class systems.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

IceNet for FireBox - A Berkeley Warehouse-Scale Computer

Berkeley’s FireBox is a next-generation warehouse-scale computer (WSC) that utilizes the energy-efficiency and bandwidth density of integrated silicon-photonic interconnects to enable a new high-bandwidth and low-latency network fabric connecting thousands of compute nodes to petabytes of DRAM and Flash storage. The high bandwidth, low latency and high connectivity of FireBox’s WSC network fabric (IceNet) will enable dramatic improvements in the overall system energy efficiency enabling fine-grain power control on system resources (processors, links and memory/storage components). IceNet is a special 3-stage photonic Clos network architected to achieve ultra-low-latency connectivity between processor nodes and memory, drastically cutting down on the energy wasted in resource idling (processors and memory stalled due to pending network requests). This is achieved by integration of the first and last switch stages into processor/memory hub clients and by heavy over-provisioning of the high-radix middle switches (FlareSwitches). A key hardware component developed in this program is an active laser power management photonic integrated circuits called LightSpark. It interacts with the FlareSwitch and provides laser power to a subset of occupied switch ports, increasing the utilization of laser light in the photonic network by an order of magnitude. In addition to guiding the laser power where it is needed, the laser-power management module enables both wavelength and laser redundancy, significantly increasing the robustness of the system. The goal of the IceNet fabric is to enable communication between 1000s of processor nodes and PBs of memory/storage with <100ns latency, <10pJ/b wall-plug energy cost at multiple Pb/s of available connectivity bandwidth. These metrics represent two-orders of magnitude improvement with respect to the status of current data-center technology.

42 ENGINEERING↗
DOE OSTI2023

Development of an Energy Services Interface for the EGoT

The Energy Services Interface (ESI) is a set of rules that ensure private, secure, and trustworthy information exchange between Grid Service Providers (GSPs) and utility customers. Large-scale adoption of Distributed Energy Resources (DERs) will be necessary for GSPs to dispatch effective grid services, and to stimulate technological innovations in DER and DERMS (DER Management Systems) technologies, as well as novel grid service programs. The ESI promotes these objectives by advancing a set of rules and interoperability requirements that define bi-directional, service-oriented, logical interfaces between GSPs and customers’ DERs, with expectations for privacy, security, and trust. The ESI rules and interoperability requirements establish boundaries between customers and GSPs that delineate the functions and responsibilities that must be implemented by the developers of Energy Grid of Things (EGoT) ecosystem products. These rules impose constraints on the implementation of a DERMS. The ESI interoperability requirements are based on the Interoperability Maturity Model (IMM), developed by the Grid Modernization Laboratory Consortium. By emphasizing private, secure, and trustworthy information exchange, and by mandating a service-oriented and interoperable architecture, the ESI promotes the development of an EGoT ecosystem that motivates customer participation and technological innovation. Interoperability will encourage innovation by reducing barriers to entry and increasing confidence of stakeholders. Customers will be willing to participate in DER service programs that establish trust and emphasize customer choice. Large-scale customer participation ensures GSPs have ample DER resources to provide grid services that have significant impact on grid reliability and reduce electricity cost for consumers. This in turn signals economic opportunities that encourage innovation, resulting in the development of a robust EGoT ecosystem.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Alternative Method for Performing As-Built, As-Irradiated Neutronics Analyses

Neutronics analyses have been used to assist in the design, development, and qualification of miniature fuel (MiniFuel) experiments irradiated in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) since their conception almost a decade ago. In recent years, upon completion of a MiniFuel target’s irradiation, neutronics analyses that reflect the as-built, as-irradiated conditions of an experiment have also been performed to validate postirradiation examination (PIE) efforts. Several radiation transport and depletion/activation software wrapper programs have been developed to increase the fidelity of these calculations; at ORNL, a program called HFIRCON is the primary software method employed. However, the utilization of these wrapper programs comes at a cost. To produce accurate results, the radiation transport portion of these analyses requires significant time and resources to execute. Therefore, this report discusses an alternative methodology for calculating some of the desired output for PIE validation—specifically, the output used in evaluating the experiment’s fuel burnup—without complete reliance on ORNL’s wrapper program. The alternative method is not a new software but rather a procedure for utilizing the depletion/activation software, SCALE, in conjunction with limited input data and reasonable assumptions to bypass most of the radiation transport calculations and thereby reduce the time required for the completion of a standard analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals an d alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

3D printed materials, stress-strain behavior, mult↗
DOE OSTI2022

Making Grid-interactive Efficient Buildings a “Win” for Both Customers and Utilities

Buildings account for more than 70% of U.S. electricity use and at least one-third of U.S. economy-wide CO2 emissions. Changing the timing and overall amount of electricity consumption in buildings would significantly reduce energy costs to consumers and facilitate the transition to a decarbonized economy. Grid-interactive efficient buildings (GEBs) incorporate energy efficiency, smart technologies, and active use of distributed energy resources (DERs) to provide these benefits. As the link between the customer and the power system, utilities are central to widespread deployment of GEBs. Yet, despite the significant cost savings and operational benefits of GEBs for utilities, deployment has remained limited. This paper explores emerging models for enabling utilities to facilitate GEB adoption. Building off foundational research conducted to develop the U.S. DOE’s A National Roadmap for Grid-Interactive Efficient Buildings, we describe the most novel recent examples of ways in which utilities and regulators have made demand-side innovation a win for both the customer and the utility. Emerging concepts include: (1) performance incentive mechanisms to align GEB deployment with utility financial motivations, (2) the use of subscription pricing (i.e., fixed monthly bills) to promote load flexibility and energy efficiency, (3) rate-basing utility-controlled behind-the-meter assets, and (4) coupling energy efficiency and load flexibility with electrification proposals to ensure that customer benefits are maximized. The paper concludes with a discussion about prospects for widespread GEB deployment and utilization by utilities, and how to scale efforts.

Satchwell, Andrew↗
DOE OSTI2021

Fuel Properties and Kinetics

The Co-Optimization of Fuels and Engines (CoOptima) program is focused on a two-pronged approach to develop new, lower net-carbon fuels and advanced engine technologies in tandem. This effort brings nine national labs and several university and industry partners together to simultaneously identify new fuel candidates and to further engine technology development in the light-, medium-, and heavy-duty vehicle sectors with a focus on fuel economy and emission reduction. The fuel properties and kinetics project is aimed at achieving a better understanding of fuel property kinetics and how they impact engine performance such that more efficient and lower emitting engines can be made a reality. Several promising biofuel candidates were identified through tiered screening approaches and were evaluated utilizing unique bench-scale measurement techniques. Kinetic models were developed to describe autoignition and soot pre-cursor formation mechanisms to identify the most promising candidates that advanced various combustion strategies.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Nanoparticle Surface Passivation Strategies to Improve the Cycle and Calendar Lifetime of Silicon Anodes in Standard Carbonate Electrolytes

Silicon Lithium alloys (SiLix) as the anode active material in a Li-Ion battery configuration offer possible energy densities paralleled only by pure lithium metal. However, the extreme mechanical deformation of alloying and dealloying SiLix through charge/discharge cycles paired with the highly reactive interface of SiLix which generates an interfacial layer known as the solid-electrolyte-interphase are large barriers to industrial adoption of high-silicon-content negative electrodes. Moreover, these challenges are magnified when the thickness of the electrode is brought to relevant levels (>3 mg/cm2). Here, I describe our efforts to address these challenges by utilizing single-nanometer-scale silicon nanoparticles to reduce capacity fade related to mechanical failure. I also detail our efforts to modify the silicon surface through interfacial chemical engineering strategies to passivate the silicon surface. This development three different majority silicon electrodes (50-74 wt%) to achieve cycle capacity retention of greater than 73% through 1000 charge/discharge cycles against capacity-matched NMC-based cathodes and calendar lifetimes greater than one year. This research is a part of the multi-national lab Silicon Consortium Project.

anodes↗
DOE OSTI2023

Comparison of FAST Experiments to BISON Simulations

The Fission Accelerated Steady-State Test (FAST) experiments utilize the effects of scaling to accelerate the burnup experienced by the fuel. This experimental technique offers a unique opportunity to evaluate the effects of scaling on fuel and cladding material modelling. Currently, models used in the BISON fuel performance code for metallic fuel performance are calibrated for EBR-II conditions and geometries. Comparing BISON simulations to FAST experimental data will allow for the identification of shortcomings in the models for conditions outside the EBR-II paradigm. FAST experiments have been performed on U-Zr and U-10Mo fuel types with HT9 cladding. Initial comparisons of simulated cladding strains to experimental results show that the BISON simulations consistently overpredict cladding strain in the fuel region but underpredict the cladding strain in the plenum region. This indicates potential issues with the simulation of swelling and gas pressure at smaller geometries. Further comparison with fission gas release measurements is planned as data becomes available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

CHALLENGES IN THE DEVELOPMENT OF THE ELECTROREFINING PROCESS AT Y-12

In order to ensure future capabilities of the Y-12 site as older buildings retire, a new process was developed, the Metal Purification Process. The purpose of this new process is to provide a simpler and more efficient uranium metal purification that the previous multi-staged, complex chemical processes. The basis for this technology currently exists in the US DOE complex, but it has not been utilized on a large scale for uranium at higher enrichments. The system requires larger-geometry vessels and furnaces in order to meet the through-put requirements. The crux of the process is the electrorefining cell, consisting of several concentric liners and an unfavorable geometry cylindrical crucible. Within the crucible, a molten Li-CL-KCL-UCL3 salt electrolyte is present. ‘Dirty’ metal is placed into a loading basket and loaded into an electrorefining cell. Here, the metal reacts into the molten salt within the cell to form UCL3, while ‘clean’ metal simultaneously plates out from the salt electrolyte in the form of metal dendrites. These dendrites are then collected and removed from the cell. After removal from the cell, the dendrites are taken to a furnace to remove adhered salts. Then, the salt-free dendrites are moved to a separate furnace for consolidation into the final product form. The development of the Criticality Safety Evaluation for this complex system brought with it many NCS Challenges and lessons learned. These challenges include: design decisions for ensuring subcriticalty in the electrorefining cell during abnormal conditions, the interface of the main glovebox system with auxiliary systems such as the purification system and designated storage, implementation of mass tracking, and concerns from production and operation regarding the movement of material within the system.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Relating Aerial Infrared Thermography Defects to Photovoltaic Performance: Preprint

In this research, we examine the relationship between aerial IR defect analysis and photovoltaic (PV) performance data for twelve utility- and commercial-scale solar sites in the United States. To do this, we fuse the site diagram geoJSON's, aerial infrared thermography (aIRT) defect analyses, and associated inverter time series, allowing for a direct comparison between site defects and time series data. Defect analyses were provided by Zeitview, under its Solar Insights platform. Following the data fusion process, we look at the relationship between system performance and aIRT defects. We investigate the relationship between degradation and hotspot defects, as well as the relationship between AC power data and offline strings and misaligned modules. In general, system degradation was not affected by long-term or balance-of-system (BoS) defects as they occurred infrequently in the data set. However, for one system, a near statistically significant relationship (p-value=0.057) was found when comparing the degradation of inverter blocks with several multi-hotspot defects to all other inverter blocks without this particular defect. There was strong alignment when comparing short-term recoverable module defects such as stuck trackers and offline strings to time series data. In general, we found that when an inverter block has more than 80% of modules flagged for one of these defects, its AC power time data is flat-lined and the inverter block is not producing.

aerial inspection↗