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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Coordinated Frequency Regulation in Grid-Forming Storage Network via Safety-Consensus

Inverter-based storages are poised to play a prominent role in future power grid with massive renewable generation. Grid-forming inverters (GFMs) are emerging as a dominant technology with synchronous generators (SG)-like characteristics through primary control loops. Advanced secondary-layer control schemes, e.g., consensus algorithms, allow GFM-interfaced storage units to participate in frequency regulations and restore nominal frequency following grid disturbances. However, it is imperative to ensure critical frequency safety limits are not violated while the grid transitions from pre- to post-disturbance operating point. This paper presents a novel safety-enforced consensus method, having three distinct objectives: safe transient frequency evolution, minimizing frequency deviation, and coordinated power sharing. The proposed technique is illustrated using a GFM-interfaced grid-wide storage network on the IEEE 68-bus system under multiple grid transient scenarios.

consensus control↗
DOE OSTI2021

Tension-free Dirac strings and steered magnetic charges in 3D artificial spin ice

3D nano-architectures presents a new paradigm in modern condensed matter physics with numerous applications in photonics, biomedicine, and spintronics. They are promising for the realization of 3D magnetic nano-networks for ultra-fast and low-energy data storage. Frustration in these systems can lead to magnetic charges or magnetic monopoles, which can function as mobile, binary information carriers. However, Dirac strings in 2D artificial spin ices bind magnetic charges, while 3D dipolar counterparts require cryogenic temperatures for their stability. Here, we present a micromagnetic study of a highly frustrated 3D artificial spin ice harboring tension-free Dirac strings with unbound magnetic charges at room temperature. We use micromagnetic simulations to demonstrate that the mobility threshold for magnetic charges is by 2 eV lower than their unbinding energy. By applying global magnetic fields, we steer magnetic charges in a given direction omitting unintended switchings. The introduced system paves the way toward 3D magnetic networks for data transport and storage.

36 MATERIALS SCIENCE↗
DOE OSTI2019

DataFed: Towards Reproducible Research via Federated Data Management

The increasingly collaborative, globalized nature of scientific research combined with the need to share data and the explosion in data volumes present an urgent need for a scientific data management system (SDMS). An SDMS presents a logical and holistic view of data that greatly simplifies and empowers data organization, curation, searching, sharing, dissemination, etc. We present DataFed - a lightweight, distributed SDMS that spans a federation of storage systems within a loosely-coupled network of scientific facilities. Unlike existing SDMS offerings, DataFed uses high-performance and scalable user management and data transfer technologies that simplify deployment, maintenance, and expansion of DataFed. DataFed provides web-based and command-line interfaces to manage data and integrate with complex scientific workflows. DataFed represents a step towards reproducible scientific research by enabling reliable staging of the correct data at the desired environment.

Stansberry, Dale↗
DOE OSTI2022

Supervised Learning for Distribution Secondary Systems Modeling: Improving Solar Interconnection Processes

The current interconnection process and hosting capacity analysis for distributed energy resources (DERs), such as photovoltaics (PV) and battery energy storage systems, are based on analyzing grid network constraints (voltage and thermal) using only medium-voltage distribution network models. This is because most utilities do not have secondary low-voltage system models that connect service transformers and residential customers. This is important because in many cases the main impact of interconnecting DERs could occur on the low-voltage distribution systems. This paper proposes a supervised learning method to approximate local secondary models to improve the interconnection process. The proposed supervised learning method includes a decision tree model that predicts the secondary topology and a logistic regression model that predicts conductor types. The case studies demonstrate the benefits of including secondary low-voltage circuits in the interconnection process. We report the proposed modeling methodology is readily scalable and thus can reduce the cost and effort of PV interconnection for the industry and stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2026

Wyoming Carbon Blueprint A Roadmap for Statewide Carbon Capture and Storage

Wyoming stands at a pivotal point in defining its energy future, and the Wyoming Carbon Blueprint positions the state to lead the nation in carbon management through a coordinated buildout of carbon capture, transportation, utilization, and geologic storage. Building on Wyoming’s long history as a major producer of coal, oil, and natural gas, and supported by favorable policies, skilled labor, and robust subsurface resources, the Blueprint outlines a pathway to develop one of the world’s first open-access carbon hubs capable of capturing between 10 and 25 million tonnes of CO₂ per year within five years, and up to 45 million tonnes within a decade. In doing so, it advances the concept of “No Carbon Left Behind”: a statewide strategy that prevents stranded CO₂ by aligning capture, transport, and storage systems into a single coherent infrastructure network.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High Performance Computing Systems Tools, Visualization, and Management

High Performance Computing (HPC) systems are complex setups of servers, storage devices, network switches, and cables that are specifically designed to accommodate hundreds of users running highly computationally intensive applications at a time. These applications require numerous softwares, licenses, and various levels of storage as well. All of these resources must be monitored and managed by HPC administrators, which presents a daunting task. In this project, I created numerous software tools as part of an HPC Visualization and Management system, which is now used by HPC administrators on a daily basis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

How fast can one resize a distributed file system?

Efficient resource utilization becomes a major concern as large-scale distributed computing infrastructures keep growing in size. Malleability, the possibility for resource managers to dynamically increase or decrease the amount of resources allocated to a job, is a promising way to save energy and costs. However, state-of-the-art parallel and distributed storage systems have not been designed with malleability in mind. The reason is mainly the supposedly high cost of data transfers required by resizing operations. Nevertheless, as network and storage technologies evolve, old assumptions about potential bottlenecks can be revisited. In this study, we evaluate the viability of malleability as a design principle for a distributed storage system. We specifically model the minimal duration of the commission and decommission operations. To show how our models can be used in practice, we evaluate the performance of these operations in HDFS, a relevant state-of-the-art distributed file system. We show that the existing decommission mechanism of HDFS is good when the network is the bottleneck, but can be accelerated by up to a factor 3 when storage is the limiting factor. We also show that the commission in HDFS can be substantially accelerated. With the highlights provided by our model, we suggest improvements to speed both operations in HDFS. We discuss how the proposed models can be generalized for distributed file systems with different assumptions and what perspectives are open for the design of efficient malleable distributed file systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

U.S. Department of Energy Solar District Cup Collegiate Design Competition

The Solar District Cup is a multidisciplinary collegiate competition that challenges student teams to design and model standalone solar and solar-plus-storage systems for multiple buildings on a local electrical distribution network, such as a college campus, across a development, or in a district. Students learn cross-cutting skills that prepare them to become part of the next generation of the distributed energy workforce. Student teams act as renewable energy developers proposing to solar and solar-plus-storage system requests. Students, faculty, and prospective employers can benefit from knowing about this program and what students learn--either immediately as participants, mentors, or judges, or as potential employers of Solar District Cup alumni. RE+ is also one of our competition partners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Intelligent Hierarchical Resilient Operation of Distribution Systems: Implementation and Validation in a Power Hardware-in-the-Loop Simulation Testbed

This paper reports on the structure of a power hardware-in-the-loop (PHIL) simulation testbed that implements, tests, and validates a novel AI-based hierarchical resilient operation model for distribution systems. The testbed implements the central and distributed controllers of the hierarchical resilient operation model and integrates a Digital Real-Time Simulator (DRTS), protective relays, a Real-Time Automation Controller (RTAC), a Software Defined Network (SDN) switch, and a battery energy storage (BES) system. The testbed provides comprehensive real-time visualization and monitoring capability as an advanced situational awareness and operator interface solution. The IEEE 33-node system is used as a test case to test and validate the operation of the model in normal operation and recovery operation after major outages in a fully automated fashion.

Ganjkhani, Mehdi↗
DOE OSTI2023

On the Feasibility of Market Manipulation and Energy Storage Arbitrage via Load-Altering Attacks

Around the globe, electric power networks are transforming into complex cyber–physical energy systems (CPES) due to the accelerating integration of both information and communication technologies (ICT) and distributed energy resources. While this integration improves power grid operations, the growing number of Internet-of-Things (IoT) controllers and high-wattage appliances being connected to the electric grid is creating new attack vectors, largely inherited from the IoT ecosystem, that could lead to disruptions and potentially energy market manipulation via coordinated load-altering attacks (LAAs). In this article, we explore the feasibility and effects of a realistic LAA targeted at IoT high-wattage loads connected at the distribution system level, designed to manipulate local energy markets and perform energy storage (ES) arbitrage. Realistic integrated transmission and distribution (T&D) systems are used to demonstrate the effects that LAAs have on locational marginal prices at the transmission level and in distribution systems adjacent to the targeted network.

25 ENERGY STORAGE↗
DOE OSTI2025

Threat Hunt Guide for BESS Environments

The rapid digitalization of the electric grid - driven by the integration of inverter-based resources (IBRs), battery energy storage systems (BESS), and advanced grid control platforms - has significantly enhanced grid efficiency, visibility, and flexibility. However, this evolution also introduces new cybersecurity risks, particularly through supply chain dependencies and operational blind spots at the grid edge. To address these challenges, Idaho National Laboratory (INL), through the Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) Rapid Risk initiative, conducted a series of rapid risk assessment engagements with energy organizations across the United States. Drawing on lessons learned from these engagements, INL developed the following threat hunting guide for asset owners and operators (AOOs) to enhance their cybersecurity visibility within BESS and IBR systems. The guide demonstrates how to use passive network monitoring to baseline device behavior, detect adversarial activity, and investigate anomalies without disrupting operations. By implementing these practices, energy sector stakeholders can improve coordination between cybersecurity and operations teams and strengthen the resilience of distributed energy resources (DERs) within the modern power grid. Prior to implementing any network monitoring, packet capture, or threat hunting activity described in this guide, AOOs are strongly advised to review applicable governance frameworks, legal requirements, and organizational policies. This guide is intended for informational and educational purposes only. It does not replace compliance with any federal, state, or local cybersecurity mandates or industry standards. Implementation of described configurations, technologies, or analytic workflows is performed at the discretion and responsibility of the asset owner and operator.

25 - ENERGY STORAGE↗
DOE OSTI2021

Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1

PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.

Arnold, Daniel↗
DOE OSTI2025

Recent Experience with the CMS Data Management System

The CMS[1] experiment manages a large-scale data infrastructure, currently handling over 200 PB of disk and 500 PB of tape storage and transferring more than 1 PB of data per day on average between various WLCG[2] sites. Utilizing Rucio[3] for high-level data management, FTS[4] for data transfers, and a variety of storage and network technologies at the sites, CMS confronts inevitable challenges due to the system’s growing scale and evolving nature. Key challenges include managing transfer and storage failures, optimizing data distribution across different storages based on production and analysis needs, implementing necessary technology upgrades and migrations, and efficiently handling user requests. The data management team has established comprehensive monitoring to supervise this system and has successfully addressed many of these challenges. The team’s efforts aim to ensure data availability and protection, minimize failures and manual interventions, maximize transfer throughput and resource utilization, and provide reliable user support. This paper details the operational experience of CMS with its data management system in recent years, focusing on the encountered challenges, the effective strategies employed to overcome them and the ongoing challenges as we prepare for future demands.

Öztürk, Hasan [CERN]↗
DOE OSTI2024

Software defined networking moving target defense honeypot

Disclosed herein are systems, methods, and storage media for thwarting cyber-attacks and data theft. A computing system receives packets and compares with a configuration resource. The computing system determines that the packet does not match the configuration resource and transmits a packet to a decoy environment via an SDN switch. The decoy environment is configured to generate time-out, service unavailable, or restricted access messages. In some embodiments, the computing system determines the packet does match the configuration and transmits the packet to a production network via an SDN switch. The SDN switch is communicatively connected to the decoy environment through a first channel and communicatively connected to a production environment through a separate second channel. The computing system is further configured to create and transmit to the SDN switch, rules to manage transmitting the packet to either the decoy environment or the production environment.

Lyle, Joshua A.↗
DOE OSTI2017

Water NSTF Design, Instrumentation, and Test Planning

The following report serves as a formal introduction to the water-based Natural convection Shutdown heat removal Test Facility (NSTF) program at Argonne. Since 2005, this US Department of Energy (DOE) sponsored program has conducted large scale experimental testing to generate high-quality and traceable validation data for guiding design decisions of the Reactor Cavity Cooling System (RCCS) concept for advanced reactor designs. The most recent facility iteration, and focus of this report, is the operation of a 1/2 scale model of a water-RCCS concept. Several features of the NSTF prototype align with the conceptual design that has been publicly released for the AREVA 625 MWt SC-HTGR. The design of the NSTF also retains all aspects common to a fundamental boiling water thermosiphon, and thus is well poised to provide necessary experimental data to advance basic understanding of natural circulation phenomena and contribute to computer code validation. Overall, the NSTF program operates to support the DOE vision of aiding US vendors in design choices of future reactor concepts, advancing the maturity of codes for licensing, and ultimately developing safe and reliable reactor technologies. In this report, the top-level program objectives, testing requirements, and unique considerations for the water cooled test assembly are discussed, and presented in sufficient depth to support defining the program’s overall scope and purpose. A discussion of the proposed 6-year testing program is then introduced, which outlines the specific strategy and testing plan for facility operations. The proposed testing plan has been developed to meet the toplevel objective of conducting high-quality test operations that span across a broad range of single- and two-phase operating conditions. Details of characterization, baseline test cases, accident scenario, and parametric variations are provided, including discussions of later-stage test cases that examine the influence of geometric variations and off-normal configurations. The facility design follows, including as-built dimensions and specifications of the various mechanical and liquid systems, design choices for the test section, water storage tank, and network piping. Specifications of the instrumentation suite are then presented, along with specific information on performance windows, measurement uncertainties, and installation locations. Finally, descriptions of the control systems and heat removal networks are provided, which have been engineered to support precise quantification of energy balances and facilitate well-controlled test operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Evaluating Burst Buffer Placement in HPC Systems

Burst buffers (BBs) are increasingly exploited in contemporary supercomputers to bridge the performance gap between compute and storage systems. The design of BBs, particularly the placement of these devices and the underlying network topology, impacts both performance and cost. As the cost of other components such as memory and accelerators is increasing, it is becoming more important that HPC centers provision BBs tailored to their workloads.This work contributes a provisioning system to provide accurate, multi-tenant simulations that model realistic application and storage workloads from HPC systems. The framework aids HPC centers in modeling their workloads against multiple network and BB configurations rapidly. In experiments with our framework, we provide a comparison of representative Oak Ridge Leadership Computing Facility (OLCF) I/O workloads against multiple BB designs. We analyze the impact of these designs on latency, I/O phase lengths, contention for network and storage devices, and choice of network topology.

Khetawat, Harsh↗
DOE OSTI2018

Planning of distributed data production for High Energy and Nuclear Physics

Modern experiments in High Energy and Nuclear Physics heavily rely on distributed computations using multiple computational facilities across the world. One of the essential types of the computations is a distributed data production where petabytes of raw files from a single source has to be processed once (per production campaign) using thousands of CPUs at distant locations and the output has to be transferred back to that source. The data distribution over a large system does not necessary match the distribution of storage, network and CPU capacity. Therefore, bottlenecks may appear and lead to increased latency and degraded performance. In this paper we propose a new scheduling approach for distributed data production which is based on the network flow maximization model. In our approach a central planner defines how much input and output data should be transferred over each network link in order to maximize the computational throughput. Such plans are created periodically for a fixed planning time interval using up-to-date information on network, storage and CPU resources. The centrally created plans are executed in a distributed manner by dedicated services running at participating sites. In conclusion, our simulations based on the log records from the data production framework of the experiment STAR (Solenoid Tracker at RHIC) have shown that the proposed model systematically provides a better performance compared to the simulated traditional techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗