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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 217 records · Page 12

Wettability variation and its impact on CO 2 storage capacity at the Wyoming CarbonSAFE storage hub: An experimental approach

Meeting global and national net zero carbon emission targets will require geologic carbon disposal. The U.S. Department of Energy (DOE) has accordingly funded significant research in this area, including the Wyoming CarbonSAFE project at Dry Fork Station (DFS) in Campbell County, Wyoming. This work studied wettability on micro- and macro-scales, CO 2 storage potential, and the correlation between the two to support the Wyoming CarbonSAFE project’s subsurface assessment. During the study, a target formation’s wettability was found to affect how much CO 2 can be stored in a given formation. Here, in this study, representative rock samples were selected from the target storage formations— Lakota, Hulett, and Minnelusa—based on the heterogeneity of the lithology, permeability, and porosity of the respective formations. The rock samples are all fine-grained sandstone with variable cementation and bedding structure, including different scales of laminated bedding. The porosity and permeability vary within the range of 9.0–14.3% and 0.1–28.9 mD, respectively. These rock samples were prepared for the micro-scale wettability (contact angle measurement), macro-scale wettability (wettability index derived from unsteady-state flow characterization for the core plugs), and CO 2 storage evaluation. The macro-scale experiments suggested that wettability appeared to dominate the CO 2 storage potential performance during the drainage process, where less water-wet behavior promoted higher CO 2 storage potential. The micro-scale wettability tests showed that the rock samples at the studied reservoir conditions behaved water-wet and became more water-wet as pressure increased. This kind of wettability change discourages further CO 2 storage potential yet benefits the CO 2 residual trapping as the CO 2 injection proceeds for the studied area. The results allow the recommendation of the best reservoir candidate for storage based on wettability that affects CO 2 storage. The work presented in this study provides valuable insights into wettability’s effect on the CO 2 storage capacity and wettability’s importance when identifying the optimal CO 2 storage formation to meet the project’s goals.

58 GEOSCIENCES↗

Freestanding Ammonium Vanadate Composite Cathodes with Lattice Self-Regulation and Ion Exchange for Long-Lasting Ca-Ion Batteries

Calcium-ion batteries (CIBs) have emerged as a promising alternative for electrochemical energy storage. The lack of high-performance cathode materials severely limits the development of CIBs. Vanadium oxides are particularly attractive as cathode materials for CIBs, and preinsertion chemistry is often used to improve their calcium storage performance. However, the room temperature cycling lifespan of vanadium oxides in organic electrolytes still falls short of 1000 cycles. Here, based on preinsertion chemistry, the cycling life of vanadium oxides is further improved by integrated electrode and electrolyte engineering. Utilizing a tailored Ca electrolyte, the constructed freestanding (NH 4 ) 2 V 6 O 16 ·1.35H 2 O@graphene oxide@carbon nanotube (NHVO-H@GO@CNT) composite cathode achieves a 305 mAh g -1 high capacity and 10 000 cycles record-long life. Additionally, for the first time, a Ca-ion hybrid capacitor full cell is assembled and delivers a capacity of 62.8 mAh g -1 . The calcium storage mechanism of NHVO-H@GO@CNT based on a two-phase reaction and the exchange of NH 4 + and Ca 2+ during cycling are revealed. The lattice self-regulation of V—O layers is observed and the layered vanadium oxides with Ca 2+ pillars formed by ion exchange exhibit higher capacity. This work provides novel strategies to enhance the calcium storage performance of vanadium oxides via integrated structural design of electrodes and electrolyte modification.

25 ENERGY STORAGE↗

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

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

97 MATHEMATICS AND COMPUTING↗

Effect of storage and LEO cycling on manufacturing technology IPV nickel-hydrogen cells

Yardney Manufacturing Technology (MANTECH) 50 A-hr space weight individual pressure vessel nickel-hydrogen cells were evaluated. This consisted of investigating: the effect of storage and charge/discharge cycling on cell performance. For the storage test the cells were precharged with hydrogen, by the manufacturer, to a pressure of 14.5 psia. After undergoing activation and acceptance tests, the cells were discharged at C/10 rate (5A) to 0.1 V or less. The terminals were then shorted. The cells were shipped to NASA Lewis Research Center where they were stored at room temperature in the shorted condition for 1 year. After storage, the acceptance tests were repeated at NASA Lewis. A comparison of test results indicate no significant degradation in electrical performance due to 1 year storage. For the cycle life test the regime was a 90 minute low earth orbit at deep depths of discharge (80 and 60 percent). At the 80 percent DOD the three cells failed on the average at cycle 741. Failure for this test was defined to occur when the cell voltage degraded to 1 V prior to completion of the 35 min discharge. The DOD was reduced to 60 percent. The cycle life test was continued.

Smithrick, John J.↗

Effect of storage and LEO cycling on manufacturing technology IPV nickel-hydrogen cells

Yardney Manufacturing Technology (MANTECH) 50 A-hr space weight individual pressure vessel nickel-hydrogen cells were evaluated. This consisted of investigating: the effect of storage and charge/discharge cycling on cell performance. For the storage test the cells were precharged with hydrogen, by the manufacturer, to a pressure of 14.5 psia. After undergoing activation and acceptance tests, the cells were discharged at C/10 rate (5A) to 0.1 V or less. The terminals were then shorted. The cells were shipped to NASA Lewis Research Center where they were stored at room temperature in the shorted condition for 1 year. After storage, the acceptance tests were repeated at NASA Lewis. A comparison of test results indicate no significant degradation in electrical performance due to 1 year storage. For the cycle life test the regime was a 90 minute low earth orbit at deep depths of discharge (80 and 60 percent). At the 80 percent DOD the three cells failed on the average at cycle 741. Failure for this test was defined to occur when the cell voltage degraded to 1 V prior to completion of the 35 min discharge. The DOD was reduced to 60 percent. The cycle life test was continued.

Smithrick, John J.↗

Nature-inspired lotus-shaped fins combined with hybrid nanoparticles and metal foam for high-performance latent heat thermal energy storage

Latent heat thermal energy storage (LHTES) systems play a critical role in renewable energy integration by providing high energy density and nearly isothermal operation during phase transitions. However, their performance is often limited by slow melting/charging rates, which motivates the search for enhanced heat transfer designs. This study investigates the melting behavior of RT-82 phase change material (PCM) using novel lotus-shaped fins combined with copper metal foam and conductive graphene nanoparticles and carbon nanotubes. A two-dimensional enthalpy-porosity model in ANSYS Fluent was developed to simulate the charging/melting process, capturing non-thermal equilibrium between the foam and PCM/nano-PCM. In this study, effects of fin geometry, nanoparticle concentration, and foam porosity on melting dynamics and cost-performance trade-offs were investigated. Results showed that natural convection accelerated melting by ~12% compared to conduction-only scenarios. Optimized lotus-shaped fins with higher fin density (T3F4 and T3F10) achieved up to 63% faster melting relative to sparse configurations. Graphene nanoparticles improved thermal conductivity, with a 6% volume fraction, by reducing melting time by ~6.9%, while their combination with 75% porosity foam achieved a maximum reduction in the melting time of ~51% compared to pure PCM. Cost-performance analysis identified T3F4 as the most balanced design, offering rapid thermal response without excessive material costs, while moderate-density designs like T3S6 provided economical alternatives with acceptable performance. These results highlight the performance enhancement that can be achieved by integrating bio-inspired fins, nanoparticles, and foams, into compact and efficient LHTES for solar heating, building thermal management, and industrial waste-heat recovery applications.

25 ENERGY STORAGE↗

Lustre Unveiled: Evolution, Design, Advancements, and Current Trends

The Lustre filesystem serves as a vital element in high-performance parallel storage, meeting the rising demands of scientific, research, and enterprise environments. Widely deployed across HPC environments, ranging from small-scale applications in AI/ML, to domains like oil and gas, drug discovery, and meteorology, and manufacturing, Lustre addresses the universal challenge of efficiently accessing vast and ever-increasing volumes of data. Lustre is the filesystem of choice on six out of the top 10 fastest supercomputers in the world today, over 65% of the top 100, and also for over 60% of the top 500. Despite its widespread popularity, there is a lack of a complete and up-to-date reference, covering Lustre’s evolution, design, and various advancements made over the years. In this journal, we aim to fill this gap by providing a comprehensive journey of Lustre, including its history with significant contributions to HPC, detailed architecture and design elements, exploration of advancements added through its evolution, and future directions. Additionally, we present a comparison of Lustre with other prominent storage technologies of the era. To illustrate the current state of Lustre, we analyze several filesystem trends, including utilization, performance, and usage patterns on Orion, the Lustre filesystem on the first exascale supercomputer Frontier. We hope that this journal serves as a comprehensive educational reference for the current and future generations interested in HPC filesystem storage aspects.

97 MATHEMATICS AND COMPUTING↗

Uncovering I/O demands on HPC platforms: Peeking under the hood of Santos Dumont

High-Performance Computing (HPC) platforms are required to solve the most diverse large-scale scientific problems in various research areas, such as biology, chemistry, physics, and health sciences. Researchers use a multitude of scientific softwares, which have different requirements. These include input and output operations, which directly impact performance due to the existing difference in processing and data access speeds. Thus, supercomputers must efficiently handle mixed workload when storing data from the applications. Understanding the set of applications and their performance running in a supercomputer is paramount to understanding the storage system's usage, pinpointing possible bottlenecks, and guiding optimization techniques. This research proposes a methodology and visualization tool to evaluate a supercomputer's data storage infrastructure's performance, taking into account the diverse workload and demands of the system over a long period of operation. As a study case, we focus on the Santos Dumont supercomputer, identifying inefficient usage, problematic performance factors, and providing guidelines on how to tackle those issues.

97 MATHEMATICS AND COMPUTING↗

Performance evaluation of underground thermal storage integrated dual-source heat pump systems

The increasing demand for electricity stresses the existing electric grids. Buildings consume 73% of all U.S. electricity and are responsible for 30% of U.S. greenhouse gas emissions. Integrating thermal energy storage (TES) in building heating/cooling systems, which consume considerable electricity, can mitigate the challenges to electric grids. Here, this study reports on a novel thermal energy storage device integrated heat pump system to reshape the building electricity demand profile while maintaining thermal comfort. The annual performance of the proposed system has been evaluated through a dynamic system simulation with high fidelity in the Modelica platform. The dynamic model of the novel hybrid component named ‘dual purpose underground thermal battery’ was developed and validated. It was then incorporated into the system model. Given a time-of-use tariff, a rule-based control strategy was designed to shift the electric demand and switch the heat pump source for a typical single-family house in different climate zones of the United States. The system performance of the new TES-integrated dual-source heat pump was compared with that of a conventional air-source heat pump system. The results indicate that the proposed system can reduce the annual HVAC electricity cost by up to 52% while saving 45.2% on electricity consumption. In the Northern areas, the annual peak load of the HVAC system can be reduced by 64.9%. However, this reduction is less in the Southern areas as the system’s higher efficiency in winter dominates the overall energy-saving potential.

25 ENERGY STORAGE↗

Influence of Thermal Energy Storage Integration Strategy on System Performance and Refrigerant Charge for Small-Scale R290 Heat Pumps

As small-scale (2.5 – 5 kW) heat pumps across the US increase straining the grid during peak hours, integrated heat pump thermal energy storage (HP-TES) systems can assist by load shifting. However, challenges arise when assembling these systems, as direct refrigerant-phase change material (PCM) heat exchangers (HXs) increase refrigerant charge, and indirect secondary loops degrade HP-TES performance. In this work, direct and indirect HP-TES configurations were sized using commercially available HXs to compare the available load shift time and performance at similar refrigerant charges. For the same indirect 5 kW HP-TES refrigerant charge, directly HP-TES can operate up to 72 and 145 minutes in cooling and heating modes, respectively, using small diameter tubes. Using Modelica, COP increases for direct and indirect HP-TES were 22% and 9%, respectively, given the parasitic losses in the indirect HP-TES. Overall, small-scale direct HP-TES can have comparable refrigerant charges with indirect HP-TES maximizing COP improvements.

25 ENERGY STORAGE↗

An Efficient Storage-Driven Machine Learning Model for Performance in the Era of Multimodal Scientific Data

Scientific workflows are increasingly relying on machine learning (ML), simulation, and hybrid techniques to predict, understand, and optimize the behavior of complex experiments. High-performance computing has greatly improved researchers’ ability to acquire diverse data modalities in these workflows. Recent studies suggest that the performance of machine learning models can be improved by integrating data from various sources. Unfortunately, these workloads pose unprecedent pressure on the network storage to meet the demands associated with accessing these multimodal data. To mitigate the impact of intensive IO, we propose a solution that utilizes a multi-tier High-Performance Computing (HPC) distributed storage and data processing framework, placing computation where the data resides for better performance. By adopting this project, the scientific community will gain new opportunities to explore multimodal storage-driven possibilities, integrating multiple scientific data sources with advanced streaming frameworks. Additionally, our framework effectively utilizes computing resources and bridges the gaps identified by HPC experts. Our proposed approach tackles scalability and persistence challenges by leveraging native persistency, which has posed difficulties in traditional approaches. Furthermore, we seek to enhance fault-tolerance and load-balance of computations by leveraging real-time streaming in diverse scientific computing environments, thereby propelling advanced scientific computing research into the next generation.

97 MATHEMATICS AND COMPUTING↗

The SERI solar energy storage program

In support of the DOE thermal and chemical energy storage program, the solar energy storage program (SERI) provides research on advanced technologies, systems analyses, and assessments of thermal energy storage for solar applications in support of the Thermal and Chemical Energy Storage Program of the DOE Division of Energy Storage Systems. Currently, research is in progress on direct contact latent heat storage and thermochemical energy storage and transport. Systems analyses are being performed of thermal energy storage for solar thermal applications, and surveys and assessments are being prepared of thermal energy storage in solar applications. A ranking methodology for comparing thermal storage systems (performance and cost) is presented. Research in latent heat storage and thermochemical storage and transport is reported.

Copeland, R. J.↗

High performance network and channel-based storage

In the traditional mainframe-centered view of a computer system, storage devices are coupled to the system through complex hardware subsystems called input/output (I/O) channels. With the dramatic shift towards workstation-based computing, and its associated client/server model of computation, storage facilities are now found attached to file servers and distributed throughout the network. We discuss the underlying technology trends that are leading to high performance network-based storage, namely advances in networks, storage devices, and I/O controller and server architectures. We review several commercial systems and research prototypes that are leading to a new approach to high performance computing based on network-attached storage.

Katz, Randy H.↗

Dielectronic Recombination In Active Galactic Nuclei

XMM-Newton and Chandra observations of active galactic nuclei (AGN) show rich spectra of X-ray absorption lines. These observations have detected a broad unresolved transition array (UTA) between approx. 15-17 A. This is attributed to inner-shell photoexcitation of M-shell iron ions. Modeling these UTA features is currently limited by uncertainties in the low-temperature dielectronic recombination (DR) data for M-shell iron. In order to resolve this issue, and to provide reliable iron M-shell DR data for plasma modeling, we are carrying out a series of laboratory measurements using the heavy-ion Test Storage Ring (TSR) at the Max-Plank-Institute for Nuclear Physics in Heidelberg, Germany. Currently, laboratory measurements of low temperature DR can only be performed at storage rings. We use the DR data obtained at TSR, to calculate rate coefficients for plasma modeling and to benchmark theoretical DR calculations. Here we report our recent experimental results for DR of Fe XIV forming Fe XIII.

Lukic, D. V.↗

MOSIQS: Persistent Memory Object Storage With Metadata Indexing and Querying for Scientific Computing

Scientific applications often require high-bandwidth shared storage to perform joint simulations and collaborative data analytics. Shared memory pools provide a chance to satisfy such needs. Recently, a high-speed network such as Gen-Z utilizing persistent memory (PM) offers an opportunity to create a shared memory pool connected to compute nodes. However, there are several challenges to use scientific applications on the shared memory pool directly such as scalability, failure-atomicity, and lack of scientific metadata-based search and query. In this paper, we propose MOSIQS, a persistent memory object storage framework with metadata indexing and querying for scientific computing. We design MOSIQS based on the key idea that memory objects on PM pool can live beyond the application lifetime and can become the sharing currency for applications and scientists. MOSIQS provides an aggregate memory pool atop an array of persistent memory devices to store and access memory objects to accelerate scientific computing. MOSIQS uses a lightweight persistent memory key-value store to manage the metadata of memory objects, which enables memory object sharing. To facilitate metadata search and query over millions of memory objects resident on memory pool, we introduce Group Split and Merge (GSM), a novel persistent index data structure designed primarily for scientific datasets. GSM splits and merges dynamically to minimize the query search space and maintains low query processing time while overcoming the index storage overhead. MOSIQS is implemented on top of PMDK. We evaluate the proposed approach on many-core server with an array of real PM devices. Experimental results show that MOSIQS gains a 100% write performance improvement and executes multi-attribute queries efficiently with 2.7× less index storage overhead offering significant potential to speed up scientific computing applications.

97 MATHEMATICS AND COMPUTING↗

Vacuum Pump-Down of the Annular Insulation Space for Large Field-Erected Liquid Hydrogen Storage Tanks

Insulation systems are critical to liquid hydrogen storage tank performance. Tanks in the capacity range of 100 to 1,000 m 3 are typically shop built and designed with high-vacuum (HV) multi-layer insulation (MLI), whereas storage vessels larger than 1,000 m 3 are typically field-erected and supplied with bulk fill insulation working at moderate vacuum (MV) levels (1-100 millitorr). For large, field-erected vessels, two types of bulk fill insulation typically used: perlite and hollow glass microspheres (glass bubbles). Selection of either material is driven by a tradeoff between CAPEX and OPEX, such as the material and construction cost versus operating thermal performance and maintenance. In either case, the vacuum level needed to achieve optimum performance is likely to drive the field testing and commissioning portion of the construction schedule. A primary goal of this paper is to present practical experience and data for warm vacuum pressure (WVP) and cold vacuum pressure (CVP) levels. Recommended WVP levels needed prior to cooldown consider both perlite powder and glass bubbles. Pumping time expected to achieve target vacuum levels, considering a variety of factors, is also discussed. Recommendations for a standard practice in vacuum-insulated tank commissioning are based on historical NASA data, and those collected during recent projects.

A M Swanger↗

High-performance data format for scientific data storage and analysis

Here, in this article, we present the High-Performance Output (HiPO) data format developed at Jefferson Laboratory for storing and analyzing data from Nuclear Physics experiments. The format was designed to efficiently store large amounts of experimental data, utilizing modern fast compression algorithms. The purpose of this development was to provide organized data in the output, facilitating access to relevant information within the large data files. The HiPO data format has features that are suited for storing raw detector data, reconstruction data, and the final physics analysis data efficiently, eliminating the need to do data conversions through the lifecycle of experimental data. The HiPO data format is implemented in C++ and JAVA, and provides bindings to FORTRAN, Python, and Julia, providing users with the choice of data analysis frameworks to use. In this paper, we will present the general design and functionalities of the HiPO library and compare the performance of the library with more established data formats used in data analysis in High Energy and Nuclear Physics (such as ROOT and Parquete). In columnar data analysis, HiPO surpasses established data formats in performance and can be effectively applied to data analysis in other scientific fields.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗