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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Integrated System and Application Continuous Performance Monitoring and Analysis Capability (Final)

Scientific applications run on high-performance computing (HPC) systems are critical for many national security missions within Sandia and the NNSA complex. However, these applications often face performance degradation and even failures that are challenging to diagnose. To provide unprecedented insight into these issues, the HPC Development, HPC Systems, Computational Science, and Plasma Theory & Simulation departments at Sandia crafted and completed their FY21 ASC Level 2 milestone entitled "Integrated System and Application Continuous Performance Monitoring and Analysis Capability." The milestone created a novel integrated HPC system and application monitoring and analysis capability by extending Sandia’s Kokkos application portability framework, Lightweight Distributed Metric Service (LDMS) monitoring tool, and scalable storage, analysis, and visualization pipeline. The extensions to Kokkos and LDMS enable collection and storage of application data during run time, as it is generated, with negligible overhead. This data is combined with HPC system data within the extended analysis pipeline to present relevant visualizations of derived system and application metrics that can be viewed at run time or post run. This new capability was evaluated using several week-long, 290-node runs of Sandia’s ElectroMagnetic Plasma In Realistic Environments (EMPIRE) modeling and design tool and resulted in 1TB of application data and 50TB of system data. EMPIRE developers remarked this capability was incredibly helpful for quickly assessing application health and performance alongside system state. In short, this milestone work built the foundation for expansive HPC system and application data collection, storage, analysis, visualization, and feedback framework that will increase total scientific output of Sandia’s HPC users.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Execute BEE workflows on private cloud infrastructure (STNS01-22 BEE - FY21 P6-2)

Scope and objectives: BEE provides a portable, modular, HPC-focused workflow engine capable of managing containerized applications at scale. In FY21 BEE will expand its capabilities to provide more sophisticated handling of workflows. The ability to archive, clone, and re-run workflows will be added to BEE. The kinds of resources that BEE can use to execute workflow tasks will be expanded to include public and private clouds, such as Google Cloud Platform and OpenStack.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Structural Health Monitoring of Microreactor Safety Systems Using Convolutional Neural Networks

Microreactors, a class of modular reactors with net power output of less than 20 MWth, have innovative applications in nuclear and nonnuclear industries due to their portability, reliability, resilience, and high capacity factors. In order to operate microreactors on a wider scale, it is essential to bring down maintenance life-cycle costs while ensuring the integrity of operating such systems. Autonomous operations in microreactors using augmented digital-twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. Structural health monitoring (SHM) is a key component of nuclear DT frameworks. Artificial neural networks can be beneficial to detect degradation in the nuclear safety systems, such as piping equipment systems, by monitoring the sensor data obtained from the plant and its corresponding structures, systems and components. In this report, an SHM methodology is presented which uses convolutional neural networks to determine degraded locations and their corresponding degradation-severity levels at various locations of nuclear piping equipment systems. A simple pipe system, subjected to seismic loads, is selected to design the post-hazard SHM framework. The effectiveness of the proposed SHM methodology is demonstrated by obtaining high accuracy in detecting degraded locations as well as the severity levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

A Platform-Independent X-ray Diffraction Diagnostic for Phase Transition Kinetics in Traditional and Synthetic Microstructure Materials (LDRD Project 213088 Final Report)

Pulsed-power generators using the magnetic loading technique are able to produce well-controlled continuous ramp compression of condensed matter for high-pressure equation-of-state studies. X-ray diffraction (XRD) data from dynamically compressed samples provide direct measurements of the elastic compression of the crystal lattice, onset of plastic flow, strength-strain rate dependence, structural phase transitions, and density of crystal defects such as dislocations. Here, we present a cost effective, compact X-ray source for XRD measurements on pulsed-power-driven ramp-loaded samples. This combination of magnetically-driven ramp compression of materials with single, short-pulse XRD diagnostic will be a powerful capability for the dynamic materials community. The success in fielding this new XRD diagnostic dramatically improves our predictive capability and understanding of rate-dependent behavior at or near phase transition. As Sandia plans the next-generation pulse-power driver platform, a key element needed to deliver new state-of-the-art experiments will be having the necessary diagnostic tools to probe new regimes and phenomena. These diagnostics need to be as versatile, compact, and portable as they are powerful. The development of a platform-independent XRD diagnostic gives Sandia researchers a new window to study the microstructure and phase dynamics of materials under load. This project has paved the way for phase transition research in a variety of materials with mission interest.

36 MATERIALS SCIENCE↗
DOE OSTI2021

First Annual Report on Development of Microwave Resonant Cavity Transducer for Fluid Flow Sensing: Development of Sensor Performance Model of Microwave Cavity Flow Meter for Advanced Reactor High Temperature Fluids

We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity, which can be fabricated from stainless steel, and as such is expected to be resilient to radiation, high temperature and corrosive environment of MSCR and SFR. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. Feasibility of the sensor was initially investigated with analytical derivations and with COMSOL RF Module computer simulations of resonant frequency spectral shift due to uniform load. We also investigated the mechanical integrity of the flowmeter’s membrane through analytical modelling and COMSOL Structural Mechanics Module computer simulations. Both the analytic model and COMSOL model showed that maximum stresses on the plate, which are at the radial boundary of the plate, are three orders of magnitude smaller than the material’s yield strength and ultimate tensile strength. This indicates that the sensor is at a low risk of mechanical failure. Using results from models, we have developed an initial design for a microwave K-band sensor. A cylindrical resonator prototype was fabricated from brass for the initial tests. The external dimensions of the cavity are matched to the flange of a standard WR-42 waveguide. Microwave field is coupled into the resonant cavity through a subwavelength-size aperture. A test article was developed consisting of a piping Tee with a bulkhead WR-42 microwave waveguide installed in a leak-proof assembly. A microwave waveguide circulator was installed in the setup to suppress the effect of reflections at the cavity entrance by increasing the isolation between the input and the output port. Preliminary spectral characterization of cavity spectral response was performed with a portable PXIe chassis microwave VNA with a custom GUI. Preliminary dry tests of the transducer response were conducted with a set of calibrated weights. Transducer frequency shift was shown to be monotonically increasing with increasing pressure. The next steps will involve investigation of the transducer performance for water flow sensing.

42 ENGINEERING↗
DOE OSTI2021

Development of High Capacity Energy Storage Materials

Hydrogen fuel cells have the potential to offer energy and power density advantages over lithium ion batteries in automotive and portable power applications when paired with an appropriate hydrogen storage system. Development of the ideal hydrogen storage material has been immensely sought after but plagued by limitations present in each type of material. These limitations typically include nonidealistic operational temperatures, low capacities, excessive costs, lack of reversibility, or evolution of impurities which irreversibly damage fuel cell performance. Many complex metal hydrides possess suitable hydrogen capacities but unfortunately suffer from impurity release. In order to address this problem, our team has explored in-situ catalyst doping of alkali metal amides to demonstrate methodologies to reduce ammonia release. The incorporation of iridium metal in lithium amide significantly reduces the ammonia release and decomposes the ammonia to provide additional hydrogen. Furthermore, we demonstrate, for the first time, high resistance of low temperature fuel cells to ammonia in comparison with typical proton exchange membrane fuel cells. The utilization of these two approaches in tandem provides a novel pathway for the development and implementation of high capacity energy storage materials for fuel cell applications.

25 ENERGY STORAGE↗
DOE OSTI2021

Immobilization of Uranium in a Wetland 8-km Downstream from an Industrial Source (Report)

A three-day walk-over survey with portable gamma detecting equipment was conducted over a uranium-contaminated wetland located 8-km downstream from a former fuel fabrication facility. 97,000 spectra were collected, individually processed to extract uranium activity data, and then integrated with topographical information (LIDAR) to create maps. These maps reveal that 50 years after being released into the environment, 11% of the uranium is retained in the 9-ha wetland area. Combined with measurement collected closer to the source, it was determined that 94% of the released uranium is presently being held in downstream wetlands. This demonstrates that wetlands can be very effective at immobilizing contaminants for long durations. The survey also showed that previous flyover maps overestimated the size of the contaminated areas by 140% but had the advantage of being completed in orders-of-magnitude fewer labor hours. Depending on project needs, the walk-over technique may be useful to include in tandem with flyover measurements to acquire maps with greater sensitivity and spatial resolution.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Streaming Generalized Canonical Polyadic Tensor Decompositions

In this paper, we develop a method which we call OnlineGCP for computing the Generalized Canonical Polyadic (GCP) tensor decomposition of streaming data. GCP differs from traditional canonical polyadic (CP) tensor decompositions as it allows for arbitrary objective functions which the CP model attempts to minimize. This approach can provide better fits and more interpretable models when the observed tensor data is strongly non-Gaussian. In the streaming case, tensor data is gradually observed over time and the algorithm must incrementally update a GCP factorization with limited access to prior data. In this work, we extend the GCP formalism to the streaming context by deriving a GCP optimization problem to be solved as new tensor data is observed, formulate a tunable history term to balance reconstruction of recently observed data with data observed in the past, develop a scalable solution strategy based on segregated solves using stochastic gradient descent methods, describe a software implementation that provides performance and portability to contemporary CPU and GPU architectures and integrates with Matlab for enhanced usability, and demonstrate the utility and performance of the approach and software on several synthetic and real tensor data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Depowering of Batteries to Reduce Cost of Ownership

(1) Executive Summary: End of life batteries (EOLBs) present a cost and safety liability for their owners and stakeholders. This is due flammability, energy, and power with EOLBs. Current approaches include cumbersome, expensive packaging, specialized shipping, regulated storage, and they are responsible for over half of the cost of recycling. They all expensively and inadequately address symptoms. OnTo has developed and proven a simple way to resolve the problem systemically, through depowering of lithium-ion batteries (and most any battery other than lead). The low-cost process removes flammability, power, and energy in EOLBs through non-toxic chemical processing. The opportunity for commerce of inert scrap is at least $5 billion greater than the commerce in hazardous scrap, all made possible through OnTo’s technology for efficiency and safety. (2) Depowering Improves Safety and Decreases Cost of Battery Ownership: OnTo’s depowering technology will remove half of the cost of EOLB management and recycling. Without this technology, EOLB recycling will always be a liability. EOLB is hazardous due to inherent flammability of electrolyte and lithium. The shipping and commerce of EOLBs is costly and dangerous all along the chain of custody from owner, dealership/shop, shipper, second-life sorter, (shipper again), and finally to the destination facility recycler. OnTo’s depowering service renders inert most any EOLB packs, modules, and cells. The technology uses a brief, non-toxic treatment applicable to most any chemistry. The industry needs a safe, simple, modular, and inexpensive method to render EOLBs as inert scrap. OnTo’s deactivation system is scalable to the needs of any customer along the EOLB chain of custody. (3) Evidence of Successful Depowering: Untreated batteries will catch fire and explode under abuse conditions such as heat or crush. Slide 2 below shows that untreated batteries will blow-up and expel their internal components with heating, after OnTo’s depowering treatment, the same battery is inert with the same heat treatment (Fig. 7 in the slide). Depowering also removes electrolyte reactivity, eliminating the production of HF and other toxins (Fig 6. in the slide) The depowering process is applicable to large, 26 Ah cells. Fig. 5 in the slide shows the removal of all the electrolyte from whole cells. Removal of flammable material from an EOLB contributes to the inert behavior. OnTo developed this technology through a project supported by the US Department of Energy EERE program, with partners including Seattle King County Metro Transit. While OnTo has generated evidence of successful depowering of batteries, in 2020, a follow-on voucher opportunity for third party analysis of depowered cells and materials was approved through CalTestBed. The expertise of the battery and materials research groups at Lawrence Berkeley National Laboratory will characterize these depowered cells to provide better understanding of the materials level changes in depowering. (4) Pilot Plant for Depowering EOLBs: Making the spoke work in hub-and-spoke While other companies are marketing the hub-and-spoke approach for recycling EOLBs, they rely on dangerous, expensive shredding methods with flimsy IP protection. OnTo offers the only patented, proven ability to depower EOLBs from most any chemistry – at half of the capital cost required for shredding, while eliminating the liability, danger, and waste streams inherent with shredding. The proposed commercial pilot facility is (5) OnTo Technology LLC Company: OnTo develops advanced battery recycling innovations that produce manufacturing quality electrode materials from recycled batteries. Their patented Cathode-healing™ and Deactivation/Depowering processes improve safety and reduce the cost of recycling. OnTo’s breakthrough technologies produce advanced materials for manufacturing batteries useful in applications from portable power to electric vehicles. Contact: Steve Sloop OnTo Technology LLC, 63221 Service Road, STE F, Bend, OR 97703, ssloop@onto-technology.com , 541-389-7897

deactivation↗
DOE OSTI2021

Computational Astrophysics in the Era of Technological Heterogeneity [Slides]

The HPC landscape is changing and we’re headed toward an era where compute specialization will be prevalent. There are opportunities for co-design that can influence this future. Technological heterogeneity will be a major challenge unless we shift our approach to developing the computational tools for astrophysics. Parthenon provides convenient functionality and a bright future for block structured AMR applications. Phoebus is a new (soon-to-be) open source code for relativistic astro that promises excellent performance, portability, and unique physics capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Deep Learning Based Approach to Integrate MyShake's Trigger Data with ShakeAlert for Faster and Robust EEW Alerts

Earthquake Early Warning (EEW) systems depend on the dense seismic network to make fast and accurate earthquake detections to issue useful early alerts. The recent development and implementation of the ShakeAlert system is relying on the west coast seismic network to detect and estimate the earthquake parameters in real-time. While working on making improvements on the current system, one potential approach is to include more seismic recordings from various sources, such as the low-cost smartphone seismic network, such as the MyShake network, or the Google Android smartphones, since these smartphone seismic networks have much more portable stations (phones) to potentially provide useful data to the system. This report summarizes the initial exploration of using a deep learning approach to combine the data from both traditional seismic stations and the smartphone data in California. Due to the heterogeneity nature of the data, we aggregate data from the phones (using simulation data), as well as that from traditional seismic stations to grid cells. By generating real-time triggering ratio grid cell maps, the designed deep learning algorithm can process the data from multiple sources and detect the earthquake faster than only using that from a traditional seismic network.

58 GEOSCIENCES↗
DOE OSTI2022

Battery500 Consortium: Development of High Capacity Cathodes and Robust Solid Electrolytes

As the world have witnessed the tremendous development in portable electronic devices as well as electric vehicles, the current generation lithium-ion battery is unlikely to satisfy the bourgeon of market and the demand of the customers. A next generation battery, with cell energy density higher than 500 Wh kg -1 , needs to be developed to meet the growth of the industry. With its high theoretical capacity (3,860 mAh g -1 , or 2,061 mAh cm -3 ) and low electrochemical potential (–3.04 V versus the standard hydrogen electrode), lithium metal has been regarded as the ideal candidate for the next generation battery anode. In fact, Lithium metal anode is irreplaceable for Lithium-Sulfur chemistry. However, the continuous formation of inactive Li, which eventually leads the loss of reversible capacity of the cell, has prevented lithium metal to be used as anode in commercial rechargeable cells. The ultimate goal of the project is to propose a pathway to enable Li metal battery for stable cycling at 99.9% of Coulombic efficiency with energy density higher than 500 Wh kg -1 . A variety of advanced characterization tools, electrolyte systems, 3D current collectors and failure analysis methodologies have been developed throughout the project during the past 5 years. The UCSD effort is carried out by the groups of Ping Liu and Shirley Meng.

25 ENERGY STORAGE↗
DOE OSTI2022

Elucidating the Determinants of Alkali Ionic Conductivity in Oxide and Sulfide Frameworks

The aim of this project is to elucidate the structural and chemical factors determining alkali conductivity in oxide and sulfide frameworks using large scale first principles calculations and topological analysis. The facile conduction of alkali ions in oxide and sulfide host structures is of critical importance in energy storage. Today, the dominant form of energy storage in portable electronics is the rechargeable alkali-ion battery, a device that functions entirely on the basis of the reversible transport of alkali ions. The Li+/Na+ conductivity of a cathode has a direct influence on the rate capability of a Li/Na-ion battery, i.e., the speed at which it can be charged and discharged. Alkali conductivity is arguably of even greater importance in the solid electrolytes currently being investigated for high safety, high energy all-solid-state batteries. The research performed in this project has provided critical new insights into the diffusion mechanisms in state-of-the-art alkali superionic conductors such as Li 7 P 3 S 11 , Li 3 OCl 1-x Br x anti-perovskite, argyrodite Li 6 PS 5 Cl. Two potential novel lithium superionic conductors (Li 3 Y(PS 4 ) 2 and Li 5 PS 4 Cl 2 ) with improved electrochemical stabilities were predicted. We have also conducted in-depth studies into alkali conduction in several important classes of electrodes, including the layered P2 NaMO 2 oxides and the highly promising novel disordered rock salt Li 3+x V 2 O 5 anode for high-rate applications. This project has resulted in more than 10 peer-reviewed articles in highly regarded journals as well as a new open-source software framework (pymatgen-analysis-diffusion) that is widely used by the materials research community for the study of diffusion in materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Spiner

Spiner is a library for storing, indexing, and interpolating multidimensional data in a performance-portable way. It’s intended to run on CPUs, GPUs and everything in-between. You can create a table on a CPU, copy it to a GPU, and interpolate on it in a GPU kernel, for example. Spiner also defines (via hdf5) a file format that bundles data together with instructions for interpolating it. This means you don’t have to specify anything to start interpolating, simple load the file and evaluate where you want.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Workflows Community Summit: Tightening the Integration between Computing Facilities and Scientific Workflows

Scientific workflows are used almost universally across science domains for solving complex and largescale computing and data analysis problems. The importance of workflows is highlighted by the fact that they have underpinned some of the most significant discoveries of the past decades. Many of these workflows have significant computational, storage, and communication demands, and thus must execute on a range of large-scale computer systems, from local clusters to public clouds and upcoming exascale HPC platforms. Managing these executions is often a significant undertaking, requiring a sophisticated and versatile software infrastructure. Historically, infrastructures for workflow execution consisted of complex, integrated systems, developed in-house by workflow practitioners with strong dependencies on a range of legacy technologies—even including sets of ad hoc scripts. Due to the increasing need to support workflows, dedicated workflow systems were developed to provide abstractions for creating, executing, and adapting workflows conveniently and efficiently while ensuring portability. While these efforts are all worthwhile individually, there are now hundreds of independent workflow systems. These workflow systems are created and used by thousands of researchers and developers, leading to a rapidly growing corpus of workflows research publications. The resulting workflow system technology landscape is fragmented, which may present significant barriers for future workflow users due to many seemingly comparable, yet usually mutually incompatible, systems that exist. In order to tackle some of the challenges described above, the DOE-funded ExaWorks and NSF-funded WorkflowsRI projects have organized in 2021 a series of events entitled the “Workflows Community Summit”. The third edition of the “Workflows Community Summit” explored workflows challenges and opportunities from the perspective of computing centers and facilities. This third summit builds on two prior summits (https://workflowsri.org/summits) that (i) established a high level vision for workflows research; and (ii) explored technical approaches for realizing that vision. The third summit brought together a small group of facilities representatives with the aim to understand how workflows are currently being used at each facility, how facilities would like to interact with workflow developers and users, how workflows fit with facility roadmaps, and what opportunities there are for tighter integration between facilities and workflows. This report documents and organizes the wealth of information provided by the participants before, during, and after the summit.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

STNS01-44 BEE – FY22-1: Enhanced BEE Client [Slide]

BEE provides a portable, modular, HPC-focused workflow engine capable of managing containerized applications at scale. In FY22 BEE is completing enhancements and refinements that will complete the major development work of the workflow system. The first major milestone is the development of a graphical client. The second milestone will be the ability for BEE to automatically restart checkpointed tasks. The final milestone for FY22 will be the ability to launch and manage multiple simultaneous workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Comprehensive Framework for Valuation of Ecosystem Services in the Context of Hydropower

While models to value ecosystem services exist, they suffer from a lack of “portability” in the sense that a single modelling framework developed for one site cannot be imported and applied to another. Additionally, benefit estimations are often fragmented, incomplete, incomparable, and in heterogenous metrics, thus preventing aggregation to arrive at one comprehensive value. In the context of hydropower, the methods, as well as the metrics used to value the associated ecosystem services, vary between stakeholders (e.g., competing water users, agencies, etc.), detracting from the ability to assess the total value of a hydropower project, water management schemes, or comparing value between competing water users. Further, current methods to value water neglect non-market ecosystem services’ values by failing to account for externalities, resulting in misallocation of costs (e.g., obligatory stakeholder payments for water use) and misinterpretation of hydropower benefits. The benefit-cost ratios in hydropower development are often incomplete because non-market benefits are excluded (e.g., benefits, such as fish habitat resiliency and agricultural water reliability, derived from hydropower development). An approach to enable consistent, standardized hydropower benefit-cost analyses does not currently exist. This paper conceptualizes a methodology to standardize ecosystem services valuation in the context of hydropower projects through the integration of the U.S. Environmental Protection Agency’s existing Final Ecosystem Goods and Services Classification System framework and economic valuation techniques, and demonstrates the applicability of this methodology through a limited proof-of-concept application (the New Waddell Plant, a pumped hydroelectric energy storage facility in Phoenix, AZ). The beauty of our proposed framework lies in its ability to be imported and applied to any other pumped storage facility after accounting for site-specific features.

13 HYDRO ENERGY↗
DOE OSTI2021

NEAMS-Multiphysics Technical Assistance in FY21

The Multiphysics Object Oriented Simulation Environment (MOOSE) [1] is a massively parallel finite-element/volume package for multiphysics simulation in science and engineering. The package focuses on providing rapid-development capabilities for engineering applications by leveraging well-built features from libMesh [2] and the Portable Extensible Toolkit for Scientific Computation (PETSc) [3]. Fiscal year 2021 (FY-21) was the first year with funding dedicated to supporting MOOSE-derived applications relevant to the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program. In this report we outline the work done to support NEAMS applications such as BISON, Griffin, Pronghorn, and System Analysis Module (SAM).

42 ENGINEERING↗