Search NASA⌕ Search

SEARCH · Search NASA

Results for “storage architectures”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Second Target Station Project: STS Cross-Directorate Workshop on Hydrogen Fuel

Hydrogen, particularly green hydrogen produced through electrolysis using renewable energy, is poised to play a critical role in decarbonizing the global economy. Its ability to address the intermittency of renewable energy sources and decarbonize hard-to-electrify sectors positions it as a vital component of a sustainable energy future. Interest in hydrogen as a clean energy carrier is in a decade of unprecedented growth, with dozens of countries having released national hydrogen strategies contributing to a global hydrogen economy. In 2021, the Department of Energy (DOE) announced the Hydrogen Shot, the first of the Energy Earthshot Initiatives, which aims to lower the cost of clean hydrogen to $\$$1/kg by 2031. This initiative was followed by a considerable increase in funding for hydrogen technologies through the Bipartisan Infrastructure Law (BIL), with $\$$18 billion recently announced for regional demonstration projects (Hydrogen Hubs) and another $\$$11.5 billion aimed at research and development of electrolyzers, fuel cells, manufacturing, and recycling. The 2023 U.S. National Clean Hydrogen Strategy and Roadmap identifies the cost of clean hydrogen as a critical challenge for achieving economic scale. This includes the cost of hydrogen production by electrolysis, delivery and dispensing, onboard storage, and end-use technologies like fuel cells. Fundamental research and development into catalysts, component architectures, and material durability are critical to lower the costs of these vital technologies aimed at achieving a net-zero carbon emission economy by 2050.

08 HYDROGEN↗
DOE OSTI2022

An overview of the operation architectures and energy management system for multiple microgrid clusters

The emerging novel energy infrastructures, such as energy communities, smart building-based microgrids, electric vehicles enabled mobile energy storage units raise the requirements for a more interconnective and interoperable energy system. It leads to a transition from simple and isolated microgrids to relatively large-scale and complex interconnected microgrid systems named multi-microgrid clusters. In order to efficiently, optimally, and flexibly control multi-microgrid clusters, cross-disciplinary technologies such as power electronics, control theory, optimization algorithms, information and communication technologies, cyber-physical, and big-data analysis are needed. This paper introduces an overview of the relevant aspects for multi-microgrids, including the outstanding features, architectures, typical applications, existing control mechanisms, as well as the challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Multi-resolution enhancement for full-spectrum neural representations

Scientific data acquisition continues to outpace storage and analysis capabilities, making voxel-basedrepresentations increasingly intractable. Implicit neural representations (INRs) offer a promising solutionby encoding signals through coordinate-based neural networks, serving as surrogates of data, withcomputational and storage requirements scaling with network complexity rather than data dimensionality.However, smaller INRs struggle to faithfully represent multiscale structures, high-frequency informationand fine textures that constitute a large proportion of scientific measurements. We propose WIEN-INR, atheoretically guided hierarchical INR framework that distributes modelling across resolution scales andenables improved representation capacity through a novel enhancement network to recover subtle details.This multiscale architecture allows smaller networks to retain the full spatial-frequency content of thesignal as well as preserve training efficiency and lower storage cost. Evaluated on distinct raw experimentalmeasurements across scales and complexities, WIEN-INR represents a practical step towards a broaderadoption of neural representations in scientific workflows, delivering compact, robust and high-fidelityrepresentations.

Ni, Yuan [SLAC National Accelerator Laboratory (SL↗
DOE OSTI2020

In situ compression artifact removal in scientific data using deep transfer learning and experience replay

The massive amount of data produced during simulation on high-performance computers has grown exponentially over the past decade, exacerbating the need for streaming compression and decompression methods for efficient storage and transfer of this data---key to realizing the full potential of large-scale computational science. Lossy compression approaches such as JPEG when applied to scientific simulation data realized as a stream of images can achieve good compression rates but at the cost of introducing compression artifacts and loss of information. This paper develops a unified framework for in situ compression artifact removal in which the fully convolutional neural network architectures are combined with scalable training, transfer learning, and experience replay to achieve superior accuracy and efficiency while significantly decreasing the storage footprint as compared with the traditional optimization-based approaches. We demonstrate the proposed approach and compare it with compressed sensing postprocessing and other baseline deep learning models using climate simulations and nuclear reactor simulations, both of which are driven by hyperbolic partial differential equations. Our approach when applied to remove the compression artifacts on the JPEG-compressed nuclear reactor simulation data (using a transfer-trained model that was pretrained on the climate simulation data and updated incrementally as the nuclear reactor simulation progressed), achieved a significant improvement---mean peak signal-to-noise ratio of 42.438 as compared with 27.725 obtained with the compressed sensing approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Structural, Criticality, and Radiation Dose Calculations to Support SNF Loading into a DOE Standard Canister

The DOE Standard Canister Demonstration Project includes the development of an internal support structure (ISS) for the 4.6-m-long and 45.7-cm-diameter canister. This study presents structural evaluations, criticality safety assessments, and dose rate calculations conducted within the scope of the ISS design process to support smooth canister loading operations and to ensure safe storage, transportation, and disposal of Peach Bottom 1 Core II (PB2) and Fort St. Vrain (FSV) SNF, currently stored at INL’s CPP-603 facility. The ISS includes a 316L stainless-steel basket that holds 12 PB2 SNF rods. The PB2 basket rests on top of six individual, 78.7-cm-long, 316L stainless-steel columns that are equally spaced and welded to the inner canister wall at the lower end of the shell. These columns represent the FSV basket and can hold one FSV SNF element. An A92014 T6 aluminum spacer disc is bolted to the bottom plate of the PB2 basket to vertically restrain the FSV SNF element after the PB2 basket is placed inside the canister above the FSV basket. The structural evaluations of the ISS followed applicable ASME BPVC.III.3 guidelines and included finite element (FE) analyses of the PB2 basket structure; analyses of welds and bolds; buckling analyses of selected components, and acceptability assessments of the expected basket deformations under loading operations. The criticality safety assessments used the Monte Carlo N-Particle (MCNP) software architecture Version 6.2, including ENDF/B-V continuous-energy cross-section libraries, considering intact SNF in a single storage overpack or two multistorage overpack configurations and intact or failed SNF configured for disposal. The dose rate computations are based on source terms taken from the DOE Spent Fuel Database. The isotopic composition was decay corrected for the year 2022 using the ORIGEN module in the SCALE suite. A 19-group photon spectrum and a 27-group neutron-source spectrum were generated and used in MCNP to calculate estimated dose-equivalent rates, both on DOE Standard Canister contact and at a radial distance of 1 m from the canister surface. The results of this study indicate a structurally sound system that can uphold its criticality safety functions throughout its intended operational phases. Furthermore, this study provides confidence that sufficient radiological protection is technically achievable.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Multimaterial 3D Printing in Activating Bath Enables In Situ Polymerization of Thermosets with Intricate Geometries and Diverse Elastic Behaviors

Polydicyclopentadiene, p(DCPD), is a high‐performance thermoset valued for its exceptional toughness, strength, and stiffness. When copolymerized with 1,5‐cyclooctadiene (COD), its mechanical properties can be tuned from glassy to rubbery at room temperature. While frontal polymerization enables a rapid and energy‐efficient route to 3D print DCPD‐based materials, challenges such as ink shelf life and gravitational distortion, especially in direct ink writing of soft COD‐rich formulations, must be considered. Here, a complementary chemical strategy is presented, embedded 3D printing, that enables localized in situ polymerization of printed DCPD/COD inks within a reactive support matrix. The matrix provides both physical support and a reservoir of chemical activator, which diffuses into the ink, activates a latent bis(N‐heterocyclic carbene) Ru precatalyst, and initiates ring‐opening metathesis polymerization. Curing begins at the ink–matrix interface and propagates inward via diffusion, stabilizing the interface and preventing capillary‐driven deformation regardless of the matrix yield stress. This approach eliminates the need for cold storage, external curing, or photoinitiation, significantly expanding the processing window. Using this method, diverse thermosetting and elastomeric architectures are fabricated with features as small as 5 µm and aspect ratios of 100, including interlinked chains, shallow spherical shells exhibiting snap‐through buckling, and hair‐like fin arrays inaccessible through traditional techniques.

chemical activation↗
DOE OSTI2025

Scanning Electrochemical Microscopy: An Evolving Toolbox for Revealing the Chemistry within Electrochemical Processes

The parallel development of ultramicroelectrodes (UMEs) and groundbreaking scanning probe microscopy techniques in the late 1980s led to the development of the scanning electrochemical microscope. Scanning electrochemical microscopy (SECM) was born from the idea of using a tiny electrode to measure the local electrochemical behavior at operating electrodes. From its foundations, the technique displayed an inherent versatility in measuring sample properties beyond topography. It allowed experimenters to measure and map chemical reactions occurring at diverse interfaces, from inspecting the reversibility of redox mediators at metal electrodes, to detecting the hallmarks of cellular respiration on living plant leaves. Related but distinct electrochemical scanning probe techniques, such as electrochemical atomic force microscopy (EC-AFM), scanning ion conductance microscopy (SICM), and scanning electrochemical cell microscopy (SECCM) have developed in parallel. These techniques have demonstrated exquisite spatial resolution down to the nanoscale regime. However, it is the proposition of this review that SECM remains unmatched at revealing the chemical aspects of electrochemistry. Furthermore, it is our intention to review and demonstrate that the versatile architecture of SECM continues to evolve and address fundamental and emerging challenges in the fields of energy storage and conversion, chemical biology, materials science, and environmental chemistry, among others.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Modular scalable power conversion

A cascaded architecture composed of interconnected blocks that are each designed to process constant power and eliminate bulk energy storage are provided. Further, local controls within each block natively achieve both block- and system-level aims, making the system modular and scalable. Further methods of providing power conversion using such interconnected clocks are also provided.

Maksimovic, Dragan↗
DOE OSTI2026

Pathways to High-Performance Salt Hydrate Thermochemical Energy Storage Materials and Systems

Thermochemical materials (TCMs) based on salt hydrates are promising for thermal energy storage as they combine high energy densities with low reaction temperatures. However, their adoption is hindered by poor structural integrity and degradation under hygrothermal cycling. Storage performance is governed not only by the chemical reaction, but also by the coupled thermo-chemo-mechanical behavior that evolves with cycling. Understanding and controlling this coupling across length scales (material-to-reactor) is necessary to improve TCM stability and lifetime. In this perspective, we discuss the shortcomings of current characterization approaches and emphasize the need for measuring transport properties and structural transformations using in situ techniques that capture the dynamic evolution of these materials. We also outline opportunities for multiscale modeling frameworks that link thermodynamics and mechanics, enabling predictive evaluation of composite architectures designed for cycling stability. We conclude by identifying research questions that must be addressed to transform TCMs into viable energy storage technologies.

Composites↗
DOE OSTI2025

Role of Polymer Architecture in CO 2 Capture from Air Using Supported Poly(alkylenimine)s: Linear vs Branched Polymers

Direct air capture (DAC) of CO 2 coupled with geologic storage is a promising climate change mitigation strategy, with some applications employing amines supported on porous solids as CO 2 sorbents. While branched poly(ethylenimine) (PEI) is the standard benchmark amine material, it suffers from limited oxidative stability. Poly(propylenimine) (PPI), as an alternative, has previously demonstrated improved resistance to degradation under harsh oxidative conditions. Linear and branched PEI are commercially available, though at different molecular weights, while PPI is not commercially available. For this reason, a comparative study of all four polymers (linear PEI, branched PEI, linear PPI, branched PPI) has not been reported for DAC. In this study, we synthesize and compare low-molecular-weight (∼800 g/mol) linear (L) and branched (B) PEI and PPI supported on a model support, SBA-15 silica. These materials are evaluated for CO 2 adsorption under dry, DAC-relevant conditions (400 ppm of CO 2 , 30 °C). LPPI exhibited the highest amine efficiency at all loadings, reaching a maximum of 0.14 mmol CO 2 /mmol N, outperforming BPEI, while LPEI consistently showed the lowest uptake capacity. Temperature-programmed desorption reveals that the structure of the amine polymer impacts the CO 2 binding strength, with branched polymers displaying higher desorption energies of 102−111 kJ/mol. In situ infrared spectroscopy experiments show that all sorbents preferentially capture CO 2 as ammonium carbamate. Isobaric CO 2 uptake studies further underscore the influence of polymer mobility and support pore crowding on performance, while demonstrating the sorbents’ performance at elevated temperatures and CO 2 concentrations. All materials demonstrated good stability over 25 adsorption−desorption cycles using thermal regeneration in an inert gas purge, with only BPPI displaying a 10−11% decrease in capacity/amine efficiency during cycling, possibly due to the loss of low molecular weight, oligomeric amines. This is the first side-by-side comparison of the CO 2 sorption properties of linear and branched PEI and PPI with similar molecular weights. These findings highlight the significant role of polymer architecture in CO 2 capture efficiency and inform future designs of durable, high-performance DAC sorbents.

adsorbents↗
DOE OSTI2022

Gradient Architecture Design in Scalable Porous Battery Electrodes

Because it has been demonstrated to be effective toward faster ion diffusion inside the pore space, low-tortuosity porous architecture has become the focus in thick electrode designs, and other possibilities are rarely investigated. Here, to advance current understanding in the structure-affected electrochemistry and to broaden horizons for thick electrode designs, we present a gradient electrode design, where porous channels are vertically aligned with smaller openings on one end and larger openings on the other. With its 3D morphology carefully visualized by Raman mapping, the electrochemical properties between opposite orientations of the gradient electrodes are compared, and faster energy storage kinetics is found in larger openings and more concentrated active material near the separator. As further verified by simulation, this study on gradient electrode design deepens the knowledge of structure-related electrochemistry and brings perspectives in high-energy battery electrode designs.

25 ENERGY STORAGE↗
DOE OSTI2022

Thick Electrode Design for Facile Electron and Ion Transport: Architectures, Advanced Characterization, and Modeling

The demand for lithium ion batteries continues to expand for powering applications such as portable electronics, grid-scale energy storage, and electric vehicles. As the application requirements advance, the innovation of lithium ion batteries toward higher energy density and power output is required. Along with the investigation of new materials, an important strategy for increasing battery energy content is to design electrodes with high areal loading to minimize the fraction of nonactive materials such as current collectors, separators, and packaging components, resulting in significant gains in energy content and the reduction of the system-level cost. However, the adoption of thick high areal loading electrodes has been impeded by sluggish charge transport and mechanical instability. With conventional slurry cast electrodes, battery function significantly deteriorates with increases in electrode thickness due to high cell polarization and the incomplete utilization of active materials. Thus, a consideration of approaches that facilitate an understanding and eventual adoption of high-loading electrodes is warranted to enable the deliberate advancement of next-generation batteries. Herein, this Account considers three aspects critical to the science and technology of thick high-loading electrodes. The first discussion covers recent approaches to the design and fabrication of high-loading electrodes. Ensuring electrical contact throughout the electrode is accomplished through the manipulation of conductive additives or using a conductive scaffold within the electrode. Ion transport can be facilitated through electrode design and fabrication approaches that deliberately control the electrode porosity and tortuosity. Second, advanced characterization methodologies are presented as the ability to determine the origins of transport limitations provide the insight needed to deliberately approach future designs. Spectroscopic and diffraction methods have been used to characterize the 2D and 3D pore structure and composition of the electrodes. Furthermore, operando methods that yield spatially and temporally resolved information regarding the progression of the electrochemical reaction are highlighted. The third aspect considered is the utilization of modeling. Physically based continuum models linked with the results of experimental characterization have been demonstrated and then allow the rapid simulation of a variety of deliberate electrode designs and their impacts on functional electrochemistry. Variables relevant to the designs can be tested by the model under a series of use conditions to identify those of most promise for a specific application. Finally, an outlook on future opportunities for high-loading battery electrode research is provided to inform and entice practitioners in the field to pursue these important directions of inquiry.

25 ENERGY STORAGE↗
DOE OSTI2022

Construction of Nitrogen-abundant Graphyne Scaffolds via Mechanochemistry-Promoted Cross-Linking of Aromatic Nitriles with Carbide Toward Enhanced Energy Storage

The 2D graphyne-related scaffolds linked by carbon–carbon triple bonds have demonstrated promising applications in the field of catalysis and energy storage due to their unique features including high conductivity, permanent porosity, and electron-rich properties. However, the construction of related scaffolds is still mainly limited to the cross-linking of CaC 2 with multiple substituted aromatic halogens and there is still a lack of efficient methodology capable of introducing high-concentration heteroatoms within the architectures. The development of alternative and facile synthesis procedures to afford nitrogen-abundant graphyne materials is highly desirable yet challenging in the field of energy storage, particularly via the facile mechanochemical procedure under neat and ambient conditions. Here, in this study, graphyne materials with abundant nitrogen-containing species (nitrogen content of 6.9–29.3 wt.%), tunable surface areas (43–865 m 2 g -1 ), and hierarchical porosity are produced via the mechanochemistry-driven pathway by deploying highly electron-deficient multiple substituted aromatic nitriles as the precursors, which can undergo cross-linking reaction with CaC 2 to afford the desired nitrogen-doped graphyne scaffolds efficiently. Unique structural features of the as-synthesized materials contributed to promising performance in supercapacitor-related applications, delivering high capacitance of 254.5 F g -1 at 5 mV s -1 , attractive rate performance, and good long-term stability.

25 ENERGY STORAGE↗
DOE OSTI2025

Cybersecurity Considerations for Hydrogen Infrastructure in Airport Environments

This report explores key cybersecurity concerns and best practices within environments that serve as reference points for the development of hydrogen fueling infrastructure for aviation. This cybersecurity analysis leverages prior NREL studies: 1) hydrogen fueling station component validation to identify vulnerabilities and failure events documented in physical equipment, and 2) electric aircraft charging infrastructure analysis to explore primary cybersecurity vulnerabilities. It reviews the criticality of digitized technologies in sustaining hydrogen fuel production, storage, and fueling systems, noting cybersecurity concerns that are universal to power systems and industrial control systems in general. In considering cybersecurity vulnerabilities within a future landscape of hydrogen energy for aviation applications, a reference architecture was intended to reveal the points of connection between assets and the potential sensors that are vulnerable to manipulation in the event of compromised access or communication within a SCADA system. A generalized reference architecture can help stakeholders, engineers, or strategists understand connections, criticalities, and standard practices when it comes to designing and planning for new systems. There are several gaps to account for in assessing the future of hydrogen production, storage, and fueling for aviation. Engaging stakeholders, including aircraft manufacturers, electric utilities, site property owners, and local communities, will inform decision-making around site structure, operations, and resources for future hydrogen fueling infrastructure to understand operational needs and cybersecurity awareness. Cybersecurity mitigation strategy must consider physical attack vectors that emerge with the integration of hydrogen systems into existing airport security requirements. The cybersecurity risk assessment contained in this report is an entry point into potential future granular-level analyses to be conducted as part of hazard and risk assessments for safe aviation hydrogen infrastructure, determining how the scale of hydrogen fuel infrastructure for aviation impacts the volume of cyber attack vectors, and what, if any, are the vulnerabilities associated with different types of on-board hydrogen systems. In this nascent development phase, assessing how best to integrate cybersecurity practices into an evolving U.S. aviation landscape provides critical insights into building increased awareness and stakeholder engagement to support a cyber-resilient infrastructure.

08 HYDROGEN↗
DOE OSTI2025

Non-solvents as physical blowing agents in printable silicone foams

Silicone foams were produced by dispersing an incompatible liquid phase (i.e. a non-solvent) into an uncured, liquid silicone. The formulation and processing parameters were varied to see the effect on porosity and pore morphology. Specifically, two fluorosilanes were added to stabilize the inclusion of fluorinated solvents as blowing agents. As the floruosilane content increased, the void content increased up to about 44 vol. % when the fluorosilane comprised 18 wt. % of the initial formulation. Fumed silica that was treated with a fluorinated silane was also used to try to stabilize the dispersed liquid. While the fumed silica content did not have a strong effect on the total void content, the morphology changed when silica content changed. Various fluorinated solvents with distinct chemical structures were used as the non-solvent and then removed after curing of the silicone. The interaction of the internal non-solvent phase and the silicone phase was expected to influence the porosity. These insights highlight how the manipulation of formulation and processing parameters, focusing on the inclusion of fluorosilanes and fluorinated solvents, contributes to the understanding of how incompatible liquid phases interact with silicone matrices to control porosity and pore morphology. Additionally, these interactions also influenced processability, leading to formulations that could be printed. Higher content of non-solvent inclusions could increase the yield stress and storage modulus of an uncured formulation, leading to the ability to tune intrastrand porosity while a 3D printed architecture could be modified to introduce porosity between the strands. Furthermore, in addition to fluorinated solvents, we also considered non-fluorinated solvents since these may be more industrially relevant in the future. Overall, this approach provides an alternative route to producing porous foams that can be 3D printed, which could be useful for applications like cushioning and protective gear.

physical blowing agent↗
DOE OSTI2021

Agent-Based Distributed Energy Resources for Supporting Intelligence at the Grid Edge

This article proposes a novel multi-agent framework that can link various forms of resources and power electronic systems into distributed energy resources (DER). The proposed multiagent architecture can also integrate DERs to a central controller for optimization and control to support the grid. To demonstrate the flexibility of this novel framework, the developed agent system is applied to a set of end-use systems. Furthermore, the agent framework is validated in hardware using controller-hardware-in-the-loop simulation platform.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

MATAR: A performance portability and productivity implementation of data-oriented design with Kokkos

There is a need for simple, fast, and memory-efficient multidimensional data structures for dense and sparse storage that arise with numerical methods and in software applications. The data structures must perform equally well across multiple computer architectures, including CPUs and GPUs. For this purpose, we developed MATAR, a C++ software library that allows for simple creation and use of intricate data structures that is also portable across disparate architectures using Kokkos. Here, the performance aspect is achieved by forcing contiguous memory layout (or as close to contiguous as possible) for multidimensional and multi-size dense or sparse MATrix and ARray (hence, MATAR) types. Our results show that MATAR has the capability to improve memory utilization, performance, and programmer productivity in scientific computing. This is achieved by fitting more work into the available memory, minimizing memory loads required, and by loading memory in the most efficient order. This document describes the purpose of the work, the implementation of each of the data types, and the resulting performance both in some simple baseline test cases and in an application code.

97 MATHEMATICS AND COMPUTING↗