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DOE OSTI2022

Stardust Network Measurement Components (esnet-stardust-components) v1

This software contains a set of components that allow us to measure and analyze the use and performance of computer networks using existing off the shelf Open Source components organized into a scalable and extensible system. The components were developed for and used within ESnet's Stardust Measurement Environment. The components are used to collect, process and display network measurement data in an architecture that employs a combination of Elasticsearch, Logstash and Grafana. The advantage of this approach is we can tailor system behavior to our analytical needs and expand its capability with new types of network measurement without waiting for a commercial vendor to support our fairly niche use cases. Additionally we have existing collaborations within our community that came about from prior research efforts that will benefit from the release of this software so that others can also contribute features.

Balas, Edward↗

DOE OSTI2022

Modeling mesoscale fission gas behavior in UO2 by directly coupling the phase field method to spatially resolved cluster dynamics

Abstract Fission gas release within uranium dioxide nuclear fuel occurs as gas atoms diffuse through grains and arrive at grain boundary (GB) bubbles; these GB bubbles grow and interconnect with grain edge bubbles; and grain edge tunnels grow and connect to free surfaces. In this study, a hybrid multi-scale/multi-physics simulation approach is presented to investigate these mechanisms of fission gas release at the mesoscale. In this approach, fission gas production, diffusion, clustering to form intragranular bubbles, and re-solution within grains are included using spatially resolved cluster dynamics in the Xolotl code. GB migration and intergranular bubble growth and coalescence are included using the phase field method in the MARMOT code. This hybrid model couples Xolotl to MARMOT using the MultiApp and Transfer systems in the MOOSE framework, with Xolotl passing the arrival rate of gas atoms at GBs and intergranular bubble surfaces to MARMOT and MARMOT passing evolved GBs and bubble surface positions to Xolotl. The coupled approach performs well on the two-dimensional simulations performed in this work, producing similar results to the standard phase field model when Xolotl does not include fission gas clustering or re-solution. The hybrid model performs well computationally, with a negligible cost of coupling Xolotl and MARMOT and good parallel scalability. The hybrid model predicts that intragranular fission gas clustering and bubble formation results in up to 70% of the fission gas being trapped within grains, causing the increase in the intergranular bubble fraction to slow by a factor of six. Re-solution has a small impact on the fission gas behavior at 1800 K but it has a much larger impact at 1000 K, resulting in a twenty-times increase in the concentration of single gas atoms within grains. Due to the low diffusion rate, this increase in mobile gas atoms only results in a small acceleration in the growth of the intergranular bubble fraction. Finally, the hybrid model accounts for migrating GBs sweeping up gas atoms. This results in faster intergranular bubble growth with smaller initial grain sizes, since the additional GB migration results in more immobile gas clusters reaching GBs.

Kim, Dong-Uk↗

DOE OSTI2022

2022 AI Testbed Expeditions Report

By exploiting the coherent properties of a light source, coherent diffraction imaging (CDI) is able to obtain the sample image at a nanoscale resolution using the measured diffraction pattern. Bragg Coherent Diffraction Imaging (BCDI) has become valuable for recovering the displacement and strain field of crystals, providing a valuable tool in material science and solid-state physics. X-ray ptychography is another emerging CDI technique that can produce a high-resolution image of the extended sample and has become popular in many research areas (e.g., materials science, biology, electronics, and optics characterization). CDI including BCDI and ptychography has become an established technique in Synchrotron Facilities including the Advanced Photon Source (APS) and will greatly benefit from the 100x coherent flux increase of the upcoming APS Upgrade (APSU). The current image formation process in CDI employs iterative phase retrieval algorithms, which is a time-consuming and computationally expensive process. Especially after APSU, the traditional iterative methods will not be able to match the experimental data acquisition speed. We employ deep learning (DL) approach to replace the iterative approaches, therefore allowing hundreds of times faster recovery of the object. We developed AutoPhaseNN, a DL-based approach which learns to solve the inverse problem without labeled data. Taking 3D BCDI as a representative technique, AutoPhaseNN has been demonstrated to be one hundred times faster than traditional iterative phase retrieval methods while providing comparable image quality. The current network is trained with 64 x 64 x 64 data size, to achieve higher resolution imaging, we will need to scale the network to input and train/infer 3D arrays of size 256 x 256 x 256 (today) and of size 2560x2560x2560 (APSU). However, the scalability of the network is restricted due to the memory-intensive training process. To perform the training for a 256 x 256 x 256 data size, the required memory exceeds the capacity of the current machine. In this project, we explore using Sambanova system to train the network for the direct data inversion for CDI.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Electrify Monterey Bay

The Electrify Monterey Bay project, delivered by Central Coast Energy Services (CCES) under DOE Weatherization Assistance Program Enhancement & Innovation (E&I) funding, was designed to demonstrate scalable, low-income residential electrification across the Monterey Bay region over a 36-month performance period. The original production goal was to electrify at least 50 households; CCES exceeded this benchmark by completing electrification work in 86 households. Targeting criteria prioritized households located in disadvantaged communities and/or with an energy burden >6.5% (defined as average household energy costs divided by average household countable income). Across participating households, the average energy burden was 28%, indicating a high-need population and supporting the program’s equity and affordability objectives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Data Associated with "Identifying Suitable Front Contacts for High-Efficiency Cd(Se,Te) Solar Cells on Space-Qualified Cover Glass"

This is data associated with the publication " Identifying Suitable Front Contacts for High-Efficiency Cd(Se,Te) Solar Cells on Space-Qualified Cover Glass " by Aesha P. Patel, Ryan Muzzio, Matthew R. Young, Robert Morrissey, Suresh Chaulagain, B. Edward Sartor, Prabodika N. Kaluarachchi, Christian Velez, Joshua A. Brown, Joel N. Duenow, Stephen Glynn, Michael J. Heben, Zhaoning Song, Nikolas J. Podraza, Adam B. Phillips, Randy J. Ellingson, Matthew O. Reese. All data associated with each figure in the manuscript and supplementary should be available in this dataset. A readme file is also included to provide some guidance. Abstract: Deployment of photovoltaics in space requires devices that combine high-efficiency, low areal mass, and resilience to harsh environments. Historically, high-efficiency multijunction III–V materials have dominated space power systems; however, their high cost and limited manufacturing throughput motivate the exploration of scalable alternatives. While CdTe-based thin-film photovoltaics offer an attractive option, their performance on non-conventional substrates can suffer from front-contact instability under higher-temperature processing. Here, the role of front-contact chemistry in limiting cell performance is investigated using CdTe-based devices fabricated on 150 μm thick Ceria-doped space-qualified 0214 Corning glass. A matrix of four transparent conducting oxides (TCOs: CTO, AZO, ITO, IZO) combined with two n-type emitters (MZO, IGO) reveals chemical stability at the front interface—rather than absorber composition alone—governs recombination losses, voltage deficits, and device reproducibility. Chemically stable front-contact combinations suppress elemental diffusion and interfacial degradation, resulting in significantly improved carrier lifetimes and junction quality. These insights are validated through record-certified Cd(Se,Te) cell efficiencies of 18.4% under AM1.5G and 16.2% under AM0 illumination on ultra-thin glass. Beyond CdTe, this work provides a general framework for the rational selection of TCO/emitter interfaces in superstrate thin-film photovoltaics, including emerging technologies like metal halide perovskites, while enabling high-efficiency, lightweight photovoltaics for space applications.

14 SOLAR ENERGY↗

NASA NTRS2011

Spectrally Tailored Pulsed Thulium Fiber Laser System for Broadband Lidar CO2 Sensing

Thulium doped pulsed fiber lasers are capable of meeting the spectral, temporal, efficiency, size and weight demands of defense and civil applications for pulsed lasers in the eye-safe spectral regime due to inherent mechanical stability, compact "all-fiber" master oscillator power amplifier (MOPA) architectures, high beam quality and efficiency. Thulium fiber's longer operating wavelength allows use of larger fiber cores without compromising beam quality, increasing potential single aperture pulse energies. Applications of these lasers include eye-safe laser ranging, frequency conversion to longer or shorter wavelengths for IR countermeasures and sensing applications with otherwise tough to achieve wavelengths and detection of atmospheric species including CO2 and water vapor. Performance of a portable thulium fiber laser system developed for CO2 sensing via a broadband lidar technique with an etalon based sensor will be discussed. The fielded laser operates with approximately 280 J pulse energy in 90-150ns pulses over a tunable 110nm spectral range and has a uniquely tailored broadband spectral output allowing the sensing of multiple CO2 lines simultaneously, simplifying future potentially space based CO2 sensing instruments by reducing the number and complexity of lasers required to carry out high precision sensing missions. Power scaling and future "all fiber" system configurations for a number of ranging, sensing, countermeasures and other yet to be defined applications by use of flexible spectral and temporal performance master oscillators will be discussed. The compact, low mass, robust, efficient and readily power scalable nature of "all-fiber" thulium lasers makes them ideal candidates for use in future space based sensing applications.

Heaps, William S.↗

NASA NTRS2012

Scalable Integrated Multi-Mission Support System (SIMSS) Simulator Release 2.0 for GMSEC

Scalable Integrated Multi-Mission Support System (SIMSS) Simulator Release 2.0 software is designed to perform a variety of test activities related to spacecraft simulations and ground segment checks. This innovation uses the existing SIMSS framework, which interfaces with the GMSEC (Goddard Mission Services Evolution Center) Application Programming Interface (API) Version 3.0 message middleware, and allows SIMSS to accept GMSEC standard messages via the GMSEC message bus service. SIMSS is a distributed, component-based, plug-and-play client-server system that is useful for performing real-time monitoring and communications testing. SIMSS runs on one or more workstations, and is designed to be user-configurable, or to use predefined configurations for routine operations. SIMSS consists of more than 100 modules that can be configured to create, receive, process, and/or transmit data. The SIMSS/GMSEC innovation is intended to provide missions with a low-cost solution for implementing their ground systems, as well as to significantly reduce a mission s integration time and risk.

Kim, John↗

NASA NTRS2016

Transitioning Autonomous Systems Technology Research to a Flight Software Environment

NASA has developed methods and algorithms for autonomous spacecraft operations,including automated planning and scheduling, fault diagnostics and impact determination,procedure management and display. Making the transition from technology research tooperational flight software requires overcoming significant technical, programmatic andcultural challenges. Technology research is aimed at developing methods that performspecific functions correctly, but the resulting software may not be designed for flightprocessors with limited CPU, memory and network resources, and may not be easilyintegrated into spacecraft flight software. Our objective in the Autonomous Systems andOperations Project is to make significant strides toward the transformation from technologyto operational use. Our focus was twofold: maturing research grade autonomy software intoa flight software environment using broadly accepted languages and tools; and integratingautonomy applications with each other and with representative systems and their data andcommand interfaces. For a target flight software environment, we chose Core FlightSoftware, developed by Goddard Space Flight Center as a common operating systemindependent framework. Our hardware integration environment was provided by theIntegrated Power and Avionics Systems (iPAS) Lab at Johnson Space Center, in whichvarious subsystem development has been conducted to address engineering challenges forthe vehicles and systems required for long-duration missions into the solar system. The iPASand its network of connected facilities provides realistic subsystem hardware or simulationsof spacecraft power, life support, guidance, navigation and control, and command and datahandling subsystems. Interfaces between autonomy applications and the subsystems beingassessed and controlled were developed, assessed and refined. The hardware and softwareenvironment using CFS and the iPAS facility has proven to be a highly flexible and realisticenvironment in which to rapidly integrate applications in an iterative, low cost setting. Usingthe integration environment we have developed, we will turn our focus to performance andsizing analysis to determine the computational requirements for full-scale deployment ofautonomy technology. Scalability of reasoners and the spacecraft models upon which theyoperate, and robustness across the full range of spacecraft conditions and environments willbe explored and improved. We are making significant contributions to the future programsthat will build the spacecraft that will take humans beyond the Earth-Moon system, in whichprogram Systems Engineers will be able to accurately and confidently design in accurate,robust and mature autonomous operations systems.

Flight Software↗

NASA NTRSDate not supplied

A Partitioned - Task Parallel Implementation of the NASA Multiscale Analysis Tool for High Performance Computing

The NASA Multiscale Analysis Tool (NASMAT) is a platform for multiscale modeling of composites which can perform analysis of materials with any arbitrary number of length scales. The platform supports modularity, scalability, and interoperability using recursive procedures and data structures. A Macro solver driven parallelization scheme often limits the capability of NASMAT to scale as it has access to limited memory and number of cores (often one core/thread) and often forces to implement macro solver specific changes to the platform. In this work, a partitioned task-parallel approach is adopted, where the parallelization strategy adopted for NASMAT is independent of the macro solver and the computational resources are managed independently. The programming architecture takes into account the hierarchy of multiple scales (task-dependence) and the heterogeneous nature (dynamic load balancing) of computation through implementation of a hierarchy-informed task parallel model. The partitioned nature of the framework further extends the “plug and play” capability of NASMAT. preCICE, an open-source library for coupling multiphysics solver in a partitioned manner, is adopted to integrate NASMAT with an external macro solver by implementing a NASMAT adapter for preCICE. Speedup and scalability of the framework is studied for micromechanical models of varying size.

task-parallel↗

NASA NTRSDate not supplied

Attitude Dynamics of On-orbit Refueling Configurations

On-orbit refueling is a key enabling technology that will allow a significant increase in the amount of payload mass delivered beyond low-Earth orbit. Despite the potential benefits, there are numerous concerns regarding the operability and scalability of this critical technology. This paper explores the attitude dynamics of two docked spacecraft performing propellant transfer. A vector-dyadic equation is derived to account for the change over time in the mass distribution and the position of the mass center of the stack and moving mass terms omitted in previous literature. Subsequently, the result is applied to two SpaceX-inspired refueling configurations to assess the relative magnitudes of the various terms in the vector-dyadic equation in comparison to the gravity gradient torque.

vector-dyadic equation↗

DOE OSTI2023

Hydrogen Energy Storage System at Borrego Springs Towards an H2 Enabled 100 Renewable Microgrid

San Diego Gas & Electric's Borrego Springs Microgrid is one of the largest microgrids in the USA, serving 2500 residential customers, 300 commercial and industrial customers, and has a peak demand of approximately 14 MW. This microgrid is located at the end of a long transmission line, and is subjected to extreme weather events like storms, wildfires, and flooding, which frequently cause grid outages. The microgrid currently relies on 3.65 MW of diesel-powered generators to provide grid-forming services during these outages, which results in greenhouse gas and criteria pollutant emissions. However, the microgrid has access to approximately 37 MW of installed solar generation and struggles with overgeneration and curtailment. 1.5 MW/4.5 MWh of grid-scale batteries have been installed to capture some the overgeneration and provide resiliency, but a longer-duration low-greenhouse gas emission energy storage solution is needed. In our project, the team will evaluate in the lab and demonstrate in the field a grid-forming fuel cell inverter that can provide grid-forming services while utilizing hydrogen's energy storage scalability. We will first utilize NREL's Renewable Energy Integration and Optimization (REopt) platform to perform analyses on future microgrid scenarios that use hydrogen assets to reduce or eliminate the need for diesel backup generators. We will then evaluate the grid-forming inverter through power hardware-in-the-loop and controller hardware-in-the-loop experiments at ARIES, and de-risk the field deployment and operation of hydrogen assets in the microgrid setting. Finally, this project will demonstrate the operation of the fuel cell inverter and updated microgrid controller by operating in grid-forming mode in the Borrego Springs microgrid.

Borrego Springs↗

DOE OSTI2024

Hydrogen Energy Storage System at Borrego Springs Towards an H2 Enabled 100% Renewable Microgrid

blackstart with fuel cells↗

DOE OSTI2020

An open source analysis framework for large-scale building energy modeling

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis tools for effectively visualizing large-scale simulation results. This article discusses the OpenStudio® Analysis Framework: a scalable analysis framework for building energy modelling that was developed to overcome the three barriers listed above. The framework is open-source and scalable to facilitate wider adoption and has a clearly defined application programming interface upon which other applications can be built. It runs on high-performance computing systems, within cloud infrastructure, and on laptops, and uses a common workflow to enable different classes of algorithms. Lessons learned from previous development efforts are also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Passive sensing of a microparticle modified hybrid, fiber-reinforced composite

The widespread commercial adoption of high-performance, fiber-reinforced composites has pushed research interests toward the next generation of composites. These new composites are tasked with integrating additional functionalities into the structures without causing a trade-off in mechanical performance. One such functionality that has received significant interest is sensing. This is especially important for composites using high-performance fibers (e.g., carbon fiber) because their strain-to-failure is relatively low, resulting in brittle fracture. Besides, fiber damage can be hidden within the composite, potentially leading to premature catastrophic failure if not detected. In prior research, we demonstrated continuous feed-through deposition of ceramic nanoparticles on carbon fiber’s surface that simultaneously enhanced both the piezoresistive response and interlaminar shear strength. In this work, a similar continuous feed-through deposition process was used to demonstrate passive sensing and energy harvesting by integrating ferroelectric microparticles on the surface of electrically nonconductive fibers. The sensing and energy harvesting capabilities were characterized by mechanically straining composite beams and measuring the power generated. The improvements in mechanical properties are shown through interlaminar shear strength tests. Therefore, this research aims to demonstrate a high throughput, commercially scalable approach to coat fibers with ferroelectric microparticles that enable passive sensing as well as improved mechanical performance when fabricated into a fiber-reinforced composite.

Bowland, Christopher↗

DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗

NASA NTRSDate not supplied

Design Concepts for an Optimized, Modular, and Scalable Liquid Amine Test Stand

The Air Revitalization Labs at NASA Ames Research Center (ARC) is investigating liquid amines to for their performance removing spacecraft carbon dioxide (CO2) for crewed space missions. Development of the current one-crew scale amine test stand stems from several modifications to a test stand initially built at NASA Johnson Space Center (JSC) This sub-scale system has been modified to incorporate a flow spreader for the inlet air stream, an updated contactor design for CO2 capture, a degasser to regenerate the liquid sorbent and recover the captured CO2, and a condenser to reduce water loss. Results from the existing integrated liquid amine test stand have provided valuable insight, but continued performance optimization requires design and build of a new integrated test system. New design concepts will institute a modular configuration to allow for interfacing with novel contactor and degasser architecture, parallel or series flow pathways for the air stream and liquid sorbent, and scaling up to a 4-crew CO2 removal system.

Tiago Faria Costa↗

DOE OSTI2024

Membrane Development for CO2 Capture from Steel Manufacturing

The U.S. government is targeting a net-zero carbon-emission economy by 2050, offering an exciting opportunity for membrane-based CO2 capture from various industrial point sources. Given that industrial flue gas has low CO2 partial pressures and high volumetric flow rates, high-permeance membranes are needed to make membrane technology economically viable for large-scale deployment. Thin film composite (TFC) membranes are necessary for this implementation because they can provide high permeance by forming a thin selective layer on top of a porous support. This presentation will report the rational design and fabrication of NETL’s highly permeable non-aging TFCs achieved by: synthesizing a high-performance rubbery selective material; developing a high-porosity membrane support; optimizing coating methods to assemble the two materials into scalable membranes; and scaling up membrane supports and TFCs via a roll-to-roll process. The novel rubbery selective material shows mixed-gas CO2 permeability of 930 Barrer and CO2/N2 selectivity of 44, exceeding the 2008 Robeson upper bound. The resulting TFCs yield remarkably high CO2 permeance of 4,500 GPU and CO2/N2 selectivity of 34 at 23ºC. Moreover, the TFCs exhibit not only excellent performance stability (or non-aging behavior) for 1,000 hours in the lab, but also maintain their separation properties in a 700-hour field test at the U.S. DOE’s National Carbon Capture Center using real humid flue gas.

Tran, Thien↗

DOE OSTI2025

Multilayered Cu-Carbon Nanotube Composites for Advanced Conductors

Improving the efficiency of electrical components is critical in reducing energy consumption for various industrial and residential applications, ranging from rotating machinery to all electric devices and electric vehicle (EV) components to power grid systems. Substituting Cu wires with reduced resistance conductors that incorporate carbon nanotubes (CNTs) into Cu─ultraconductive Cu (UCC) composites─has recently been considered a promising strategy to improve energy efficiency, power density, and/or performance across various applications. Here, in this study, we created stable material formulations [CNT-containing polyvinylpyrrolidone (PVP) in dimethylformamide (DMF) solution] and utilized commercially viable fabrication approaches (electrospinning and magnetron sputtering) that produced high-performance multilayered tape-based UCC composite architectures. Increasing the CNT volume fraction by sequential layering of the structure with additional Cu-CNT layers showed a nearly stepwise improved performance in electrical and mechanical properties. This study also provides valuable insight into the effectiveness of nitrogen doping in modifying the conductivity of the CNT matrix. Fabricated prototypes demonstrated a >10% increase in current carrying capacity and >10% improvement in mechanical strength compared to those obtained on pure Cu. We believe that the properties demonstrated here, combined with the scalable manufacturing pathway of our approach, pave the way in designing future advanced conductors for diverse energy efficient and high-performance electrical systems and applications.

Carbon nanotubes↗