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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 253 records · Page 14

Leveraging Computational Storage Devices in Campaign Storage [Slides]

Computational storage provides new ways of accelerating data-intensive applications. In-drive data management schemes matter (O_DIRECT, clustered index). Layer violation: “cheating” one filesystem may be possible; cheating multiple layers of filesystems is hard (FS internal load balancing, fail over, compression, concurrency control). The future directions include block-based acceleration to object-based acceleration.

97 MATHEMATICS AND COMPUTING↗

Deployment of inference as a service at the US CMS Tier-2 data centers

Coprocessors, especially GPUs, will be a vital ingredient of data production workflows at the HL-LHC. At CMS, the GPU-as-a-service approach for production workflows is implemented by the SONIC project (Services for Optimized Network Inference on Coprocessors). SONIC provides a mechanism for outsourcing computationally demanding algorithms, such as neural network inference, to remote servers, where requests from multiple clients are intelligently distributed across multiple GPUs by a load-balancing service. This talk highlights the recent progress in deploying SONIC at selected U.S. CMS Tier-2 data centers. Using realistic CMS Run3 data processing workflows, such as those containing transformer-based algorithms, we demonstrate how SONIC is integrated into the production-like environment to enable accelerated inference offloading. We will present developments from both the client and server sides, including production job and data center configurations for NVIDIA and AMD GPUs. We will also present performance scaling benchmarks and discuss the challenges of operating SONIC in CMS production, such as server discovery, GPU saturation, fallback server logic, etc.

Holzman, Burt↗

Exploring DAOS as a Burst Buffer for a 100 Gbps DAQ Real-Time Streaming System

We present an experimental evaluation of a burst buffer for a real-time DAQ streaming system designed to transmit instrument data to remote data centers. The system is based on EJ-FAT, a load balancing system capable of Nx 100Gbps streams, distributing data from event sources to processing nodes. We explore applying the DAOS system as a burst buffer to serve a number of purposes: improve resiliency, elasticity and add new functions into the processing pipeline. In the evaluation a sender transmits events over a 100Gbps network to a receiver integrated with DAOS to store the reassembled events using DAOS APIs. We evaluate the system for possible bottlenecks and provide end-to-end evaluation with a burst buffer using DAOS storage abstractions. We show that a receiver node can support 38.1 Gbps. This proves the viability of our approach and allows us to extend this work to investigate scale-out properties and new streaming optimizations.

Mei, Xinxin↗

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↗

Advancing Grid Resilience through Smart Charge Management: Findings from Maryland’s Pilot

This report presents research findings from a four-year Smart Charge Management (SCM) pilot program conducted by Maryland’s largest electric utilities—Baltimore Gas and Electric (BGE), Potomac Electric Power Company (Pepco), and Delmarva Power & Light (DPL)—to evaluate strategies for optimizing electric vehicle (EV) charging loads and enhancing grid stability. Supported by the U.S. Department of Energy (DOE), Argonne National Laboratory collaborated with all project partners and examined the effectiveness of Time-of-Use (TOU) and Load Balancing (LB) strategies in managing peak demand, deferring costly infrastructure upgrades, and reducing grid constraints at the feeder level.

24 POWER TRANSMISSION AND DISTRIBUTION↗

EJFAT Scientific Perspective

Presented new computing model to the test by deploying the EJFAT system alongside a data-stream processing framework running the production-level CLAS12 event reconstruction application. In this experiment, a continuous stream of CLAS12 Level-1 identified events was processed in real-time using the EJFAT load balancer, distributing the workload across 90 computing nodes located across the U.S. This marks the first-ever large-scale, real-time distributed data stream processing experiment, demonstrating that scientific data-streaming pipelines can efficiently scale across four dimensions, thanks to EJFAT’s advanced hardware and software capabilities.

Gyurjyan, Vardan [Thomas Jefferson National Accele↗

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DUNE Rucio Server Scalabiilty Studies

The DUNE collaboration has an ongoing production effort to simulate the full detectors and to analyze the various prototypes that are currently running. Rucio is used to manage the 40PB of files made to date. When 500 or more jobs were sending output to Rucio simultaneously via Rucio upload, we observed timeouts, unhandled exceptions, and Rucio server restarts due to slow performance. In collaboration with the core Rucio team we did a full review of the Rucio upload code and identified several optimizations that can be made. We also have deployed the Ingress load balancer in front of our Rucio servers and added a database connection pooling utility. These changes led to significant improvement both in reliability and scalability, yet we anticipate even better performance will eventually be required. We describe in this paper the initial state of the system, the various debugging processes that were used, and our plans to further improve scalability.

Calcutt, J. [Brookhaven Natl. Lab.]↗

Fast GPU-Based Generation of Large Graph Networks From Degree Distributions

Synthetically generated, large graph networks serve as useful proxies to real-world networks for many graph-based applications. The ability to generate such networks helps overcome several limitations of real-world networks regarding their number, availability, and access. Here, we present the design, implementation, and performance study of a novel network generator that can produce very large graph networks conforming to any desired degree distribution. The generator is designed and implemented for efficient execution on modern graphics processing units (GPUs). Given an array of desired vertex degrees and number of vertices for each desired degree, our algorithm generates the edges of a random graph that satisfies the input degree distribution. Multiple runtime variants are implemented and tested: 1) a uniform static work assignment using a fixed thread launch scheme, 2) a load-balanced static work assignment also with fixed thread launch but with cost-aware task-to-thread mapping, and 3) a dynamic scheme with multiple GPU kernels asynchronously launched from the CPU. The generation is tested on a range of popular networks such as Twitter and Facebook, representing different scales and skews in degree distributions. Results show that, using our algorithm on a single modern GPU (NVIDIA Volta V100), it is possible to generate large-scale graph networks at rates exceeding 50 billion edges per second for a 69 billion-edge network. GPU profiling confirms high utilization and low branching divergence of our implementation from small to large network sizes. For networks with scattered distributions, we provide a coarsening method that further increases the GPU-based generation speed by up to a factor of 4 on tested input networks with over 45 billion edges.

97 MATHEMATICS AND COMPUTING↗

Editorial: Advanced water splitting technologies development: Best practices and protocols

As the level of deployment and utilization of renewable energy sources, including wind and solar, continues to rise, large-scale, long-term energy storage technologies that could accommodate weekly and seasonal energy fluctuations will play a significant role in the overall deployment of renewable energies in the future. Harnessing and storing renewable energy resources via electrochemical, photoelectrochemical, or thermochemical processes by converting renewable energy into sustainable (energy storage) fuels have the potential to meet the long-term, terawatt scale energy storage challenge. Renewable hydrogen production is the cornerstone for sustainable fuel production and deep decarbonization of multiple sectors in our society. Cost-competitive clean hydrogen provides value to applications, such as 1) in the transportation sector for fuel cell vehicles, 2) in the electric grid sector for system stability and load balancing, and 3) in the industrial sector with metal refineries, cement production, and biomass upgrading (carbon-free fertilizer production). In addition, coupling clean renewable hydrogen with the carbon and nitrogen cycles enables known and well-established thermal-chemical processes to generate renewable hydrocarbon fuels and ammonia. The Advanced Water Splitting Technologies (AWST): low temperature electrolysis (LTE), high temperature electrolysis (HTE), photoelectrochemical (PEC) and solar thermo-chemical hydrogen (STCH) provide four unique and parallel approaches to produce low cost, low greenhouse gas (GHG) emission hydrogen at scale (Figure 1). Cost competitive clean hydrogen production using these four technologies is a current high priority focus for governments and industry. In June of 2022, the U.S. Department of Energy (DOE) launched the first in a series of Earthshot Initiatives. The Hydrogen Shot, “1 1 1” aims to reduce the cost of clean hydrogen by more than 80% to one dollar per one kilogram in 1 decade ($\$$1/kg H 2 ). The European Green Deal and the International Energy Agency (IEA) have implemented a strong focus on green hydrogen production for a clean and secure energy future.

benchmarking, low temperature electrolysis↗

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (0A148), volume 1

Data obtained in wind tunnel tests are presented. The objectives of the tests were to: (1) obtain pressure distributions, forces and moments over the vehicle 5 Orbiter in the terminal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes. Testing was conducted over a Mach number range from 0.6 to 1.4 with Reynolds number variations from 4.57 million to 2.74 million per foot. Model angle-of-attack was varied from -4 to 16 degrees and angles of side slip ranged from -8 to 8 degrees.

Hawthorne, P. J.↗

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (OA148), volume 5

Data obtained in wind tunnel test OA148 are presented. The objectives of the test series were to: (1) obtain pressure distributions, forces and moments over the vehicle 5 orbiter in the thermal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes.

Hawthorne, P. J.↗

Terminal area energy management regime investigations utilizing an 0.030-scale model (47-0) of the space shuttle vehicle orbiter configuration 140A/B/C/R in the Ames Research Center 11 x 11 foot transonic wind tunnel (OH/48)

Data obtained in a wind tunnel test were examined to: (1) obtain pressure distributions, forces and moments over the vehicle 5 Orbiter in the terminal area energy management (TAEM) and approach phases of flight; (2) obtain elevon and rudder hinge moments in the TAEM and approach phases of flight; (3) obtain body flap and elevon loads for verification of loads balancing with integrated pressure distributions; and (4) obtain pressure distributions near the short OMS pods in the high subsonic, transonic and low supersonic Mach number regimes. Testing was conducted over a Mach number range from 0.6 to 1.4 with Reynolds number variations from 7.57 x 1 million to 2.74 x 1 million per foot. Model angle of attack was varied from -4 to 16 degrees and angles of sideslip ranged from -8 to 8 degrees.

Hawthorne, P. J.↗

Preliminary results of the first static calibration of the RSRA helicopter active-isolator rotor balance system

The helicopter version of the Rotor Systems Research Aircraft (RSRA) is designed to make simultaneous measurements of all rotor forces and moments in flight analogous to a wind tunnel balance. Loads are measured by a combination of load cells, strain gages, and hydropneumatic active isolators which use pressure gages to measure loads. Complete evaluation of system performance required calibration of the rotor force and moment measuring system when installed in the aircraft. Measurement system responses to rotor loads obtained during the first static calibration of the RSRA helicopter are plotted and discussed. Plots of the raw transducer data are included.

Acree, C. W., Jr.↗

Numerical analysis of the first static calibration of the RSRA helicopter active-isolator rotor balance system

The helicopter version of the Rotor Systems Research Aircraft (RSRA) is designed to make simultaneous measurements of all rotor forces and moments in a manner analogous to a wind-tunnel balance. Loads are measured by a combination of load cells, strain gages, and hydropneumatic active isolators with built-in pressure gages. Complete evaluation of system performance requires calibration of the rotor force- and moment-measurement system when installed in the aircraft. Derivations of calibration corrections for various combinations of calibration data are discussed.

Acree, C. W., Jr.↗

EOS: A project to investigate the design and construction of real-time distributed embedded operating systems

The EOS project is investigating the design and construction of a family of real-time distributed embedded operating systems for reliable, distributed aerospace applications. Using the real-time programming techniques developed in co-operation with NASA in earlier research, the project staff is building a kernel for a multiple processor networked system. The first six months of the grant included a study of scheduling in an object-oriented system, the design philosophy of the kernel, and the architectural overview of the operating system. In this report, the operating system and kernel concepts are described. An environment for the experiments has been built and several of the key concepts of the system have been prototyped. The kernel and operating system is intended to support future experimental studies in multiprocessing, load-balancing, routing, software fault-tolerance, distributed data base design, and real-time processing.

Campbell, R. H.↗