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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 OSTI2020

Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications

User-space HPC data services are emerging as an appealing alternative to traditional parallel file systems, because of their ability to be tailored to application needs while eliminating unnecessary overheads incurred by POSIX compliance. The High Energy Physics (HEP) community is progressively turning towards such services to enable high-throughput accesses under heavy concurrency to billions of event data produced by instruments and consumed by subsequent analysis workflows. Such services would benefit from the possibility to be rescaled up and down to adapt to changing workloads, as experimental campaigns progress, in order to optimize resource usage. This paper formalizes rescaling a distributed storage system as a multi objective optimization problem considering three criteria: load balance, data balance, and duration of the rescaling operation. We propose a heuristic for rapidly finding a good approximate solution, while allowing users to weight the criteria as needed. The heuristic is evaluated with Pufferscale, a new rescaling manager for microservice-based distributed storage systems. To validate our approach in a real-world ecosystem, we showcase the use of Pufferscale as a means to enable storage malleability in the HEPnOS storage system for HEP applications.

Distributed Storage System↗
DOE OSTI2024

Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System

Despite quantum computing's rapid development, current systems remain limited in practical applications due to their limited qubit count and quality. Various technologies, such as superconducting, trapped ions, and neutral atom quantum computing technologies are progressing towards a fault tolerant era, however they all face a diverse set of challenges in scalability and control. Recent efforts have focused on multi-node quantum systems that connect multiple smaller quantum devices to execute larger circuits. Future demonstrations hope to use quantum channels to couple systems, however current demonstrations can leverage classical communication with circuit cutting techniques. This involves cutting large circuits into smaller subcircuits and reconstructing them post-execution. However, existing cutting methods are hindered by lengthy search times as the number of qubits and gates increases. Additionally, they often fail to effectively utilize the resources of various worker configurations in a multi-node system. To address these challenges, we introduce FitCut, a novel approach that transforms quantum circuits into weighted graphs and utilizes a community-based, bottom-up approach to cut circuits according to resource constraints, e.g., qubit counts, on each worker. FitCut also includes a scheduling algorithm that optimizes resource utilization across workers. Implemented with Qiskit and evaluated extensively, FitCut significantly outperforms the Qiskit Circuit Knitting Toolbox, reducing time costs by factors ranging from 3 to 2000 and improving resource utilization rates by up to 3.88 times on the worker side, achieving a system-wide improvement of 2.86 times.

Kan, Shuwen [Fordham University]↗
DOE OSTI2014

A new architecture for fast ultrasound imaging

Some ultrasound imaging applications require high frame rate, for example 3D imaging and automated inspections of large components. Being the signal-processing throughput of the system the main bottleneck, parallel beamforming is required to achieve hundreds to thousands of images per second. Simultaneous A-scan line beamforming in all active channels is required to reach the intended high frame rate. To this purpose, a new parallel beamforming architecture that exploits the currently available processing resources available in state-of-the-art FPGAs is proposed. The work aims to get the optimal resource usage, high scalability and flexibility for different applications. To achieve these goals, the basic beamforming function is reformulated to be adapted to the DSP-cell architecture of state-of-the-art FPGAs. This allows performing simultaneous dynamic focusing on multiple A-scan lines. Some realistic examples are analyzed, evaluating resource requirements and maximum operating frequency. For example, a 128-channel system, with 128 scan lines and acquiring at 20 MSPS, can be built with 4 mid-range FPGAs, achieving up to 18000 frames per second, just limited by the maximum PRF. The gold standard Synthetic Transmit Aperture method (also called Total Focusing Method) can be carried out in real time at a processing rate of 140 high-resolution images per second (16 cm depth on steel)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Light-dependent governance of cell shape dimensions in cyanobacteria

The regulation of cellular dimension is important for the function and survival of cells. Cellular dimensions, such as size and shape, are regulated throughout the life cycle of bacteria and can be adapted in response to environmental changes to fine-tune cellular fitness. Cell size and shape are generally coordinated with cell growth and division. Cytoskeletal regulation of cell shape and cell wall biosynthesis and/or deposition occurs in a range of organisms. Photosynthetic organisms, such as cyanobacteria, particularly exhibit light-dependent regulation of morphogenes and generation of reactive oxygen species and other signals that can impact cellular dimensions. Environmental signals initiate adjustments of cellular dimensions, which may be vitally important for optimizing resource acquisition and utilization or for coupling the cellular dimensions with the regulation of subcellular organization to maintain optimal metabolism. Although the involvement of cytoskeletal components in the regulation of cell shape is widely accepted, the signaling factors that regulate cytoskeletal and other distinct components involved in cell shape control, particularly in response to changes in external light cues, remain to be fully elucidated. In this review, factors impacting the inter-coordination of growth and division, the relationship between the regulation of cellular dimensions and central carbon metabolism, and consideration of the effects of specific environment signals, primarily light, on cell dimensions in cyanobacteria will be discussed. Current knowledge about the molecular bases of the light-dependent regulation of cellular dimensions and cell shape in cyanobacteria will be highlighted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.

Mayhorn, Ebony T.↗
DOE OSTI2023

Insights into Methodologies and Stochastic Optimization of Thermal Energy Storage-Coupled Advanced Reactor Systems: A Comparison of Methods for Accessing Long-Term Sub-System Sizing Adequacy

This paper investigates the potential of coupling Thermal Energy Storage (TES) with Advanced Reactors (ARs) to address uncertainties posed by climate change in deep decarbonized power systems. The TES Use-case Team at Idaho National Laboratory (INL) has examined the potential of storing thermal energy from ARs during low demand periods and optimizing discharge during peak-priced hours, in both steady-state and transient conditions. Building on this groundwork, this study bridges the gaps in optimal sizing of the sub-system of TES-coupled AR systems using Risk Analysis Virtual Environment (RAVEN) and Holistic Energy Resource Optimization Network (HERON), INL?s framework for grid optimization. By applying this framework, we present statistically-robust optimal charge, discharge including balance of plant (BOP), and storage sizing for the High-Temperature Gas-Cooled Reactor (HTGR) with 203 MWth output. To this end, we generated synthetic price samples for 30 years using 2018 ? 2021 real-time market data from ERCOT, PJM and MISO. Our results reveals that the TES-coupled HTGR system is highly effective in maximizing revenue from electricity sales. We observed a substantial increase of 40 % in ERCOT and a noteworthy 15 % increase in PJM and MISO when compared to the conventional BOP without TES. This improvement is achieved through regionally-tailored sub-system sizing, which ranges from 398 to 416 MWth for the discharge system and 610 to 1029 MWth for the TES. We find that the average electricity price directly impacts the overall economics, while price volatility influences storage size. Additional sensitivity analyses were performed to access the impact of key assumptions on system economics and sizing, differentiating the optimization window (i.e., 24 ? 219 hours of chronological observations) and by imposing storage continuity condition in tracking TES cycles. We observed that at the 120-hour of the optimization window, a reasonable balance between computation time and accuracy was achieved. Our analysis also highlights the significance of conducting multi-day cycle analysis (> 120-hour) for TES to capture interaction between electricity prices and storage dynamics, providing a comprehensive understanding of TES behavior that AR developers should integrate into their plant designs.

25 ENERGY STORAGE↗
DOE OSTI2024

Assessment of the polygeneration approach in wastewater treatment plants for enhanced energy efficiency and green hydrogen/ammonia production

Wastewater treatment plants (WWTPs) offer opportunities to optimize resource utilization and enhance energy efficiency. Here, this study provides a comprehensive analysis of using the polygeneration approach in WWTPs to reduce grid energy dependence, optimize energy distribution, and utilize surplus energy for hydrogen (H 2 ) and ammonia (NH 3 ) production. Several models were employed, including photovoltaic (PV) cells, parabolic trough collectors (PTCs), steam methane reforming, and polymer electrolyte membranes, to assess the feasibility of this approach. Three scenarios were evaluated and compared: Scenario 1 (Baseline) represents the current situation, Scenario 2 maximizes the Net Present Value (NPV), and Scenario 3 minimizes NH 3 production costs. Real data from As-Samra WWTP in Jordan was used to accurately assess the feasibility of each scenario. The results show that Scenario 2 offers the highest profitability and efficiency, with a NPV of 87.48 million USD and an annual NH 3 production of 15,417 tons, reducing both grid dependency and biogas fuel consumption. Both Scenarios 2 and 3 demonstrate the ability to meet thermal demands efficiently while generating significant revenue from NH 3 production. Scenario 3, in particular, achieves competitive H 2 and NH 3 production costs. Environmentally, Scenario 2 significantly reduces annual greenhouse gas emissions by 12.66 kilotons of CO 2eq , with near-zero carbon intensity for thermal energy due to solar reliance. In conclusion, the polygeneration approach offers a promising pathway for WWTPs to achieve greater sustainability, economic gains, and reduced environmental impact, providing valuable insights for decision-makers.

42 ENGINEERING↗
DOE OSTI2024

Integrating Quantum Computing with High-Performance Computing: A Streamlined Approach

In recent years, quantum computing has demon-strated the potential to revolutionize specific algorithms and applications by solving problems exponentially faster than classical computers. However, its widespread adoption for general computing remains a future prospect. This paper discusses the integration of quantum computing within High-Performance Computing (HPC) environments, focusing on a resource management framework designed to streamline quantum simulators' use and enhance runtime performance and efficiency. The proposed framework facilitates hybrid applications' transition from simulation backends to real quantum hardware, optimizing resource utilization and providing a flexible infrastructure for developing and testing quantum algorithms.

Shehata, Amir↗
DOE OSTI2025

Capacity optimization of nuclear power integration to meet dynamic industrial demand

To decarbonize their industrial facilities, The Dow Chemical Company has collaborated with Idaho National Laboratory (INL) to study the integration of nuclear power with an industrial chemical facility. Using Holistic Energy and Resource Optimization Network developed at INL for optimizing and analyzing integrated energy systems, a nuclear microreactor system was sized and evaluated for dynamic dispatch to Dow Silicones Corporation’s Carrollton, KY (USA) site for iloxane production. It was found that a 180 MW th system (12 × 15MW th ) with 75.1 MWh th of thermal energy storage could provide heat and power to the chemical facilities. In the process, this would reduce electricity imports by 99.9 % and reduce the Scope 1 and 2 emissions of the site by 292,100 tonnes CO 2 /yr (98.8 %). The primary novelty of this work is a first of a kind design and optimization of a microreactor powered integrated energy system to provide heat and power to a chemical plant using real plant data. This analysis will pave the way for future studies using dispatchable clean energy sources to reduce carbon emissions and commodity industries’ reliance on fossil fuels.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Sustainable Hydropower in Lower Mekong Countries: Technical Assessment and Training Travel Report Thailand

The U.S. Agency for International Development (USAID), through their partnership with the U.S. Department of the Interior (DOI), requested the support of Oak Ridge National Laboratory (ORNL) to provide specialized technical assistance as part of the Smart Infrastructure for the Mekong (SIM) Program in Thailand. Introduced in July 2013 by U.S. Secretary of State John Kerry, SIM is a U.S. Government Inter-Agency program that provides Lower Mekong partner countries with targeted, demand-driven technical and scientific assistance to support environmentally sound, climate conscious and socially equitable infrastructure, clean energy development, and water resources optimization. The U.S. Government is committed to supporting sustainable economic development within the region by providing tools, best practices, technical assistance, and lessons learned for the benefit of partner countries. In response to a request from the Electricity Generating Authority of Thailand (EGAT), a SIM project was developed with two main activities: 1) to promote hydropower sustainability and efficiency through technical assessment training at two existing hydropower assets in Thailand, and 2) the design and implementation of one national and two or three regional science and policy workshops, to be co-hosted with EGAT, to build common understanding of and commitment to environmental and social safeguards for Mekong Basin hydropower projects. The U.S. Department of Energy (DOE) is leading the technical assessment (Activity 1), and has contracted ORNL to provide expert technical assistance focused on increasing efficiency at existing projects, with the goal of increasing renewable energy generation at little to no capital cost. ORNL is the leading national laboratory in hydropower analysis, with a nationally recognized and highly qualified team of scientists addressing small to large-scale systems (basin-, regional-, and national-scale) energy generation optimization analysis for DOE. The mission of the ORNL Water Power Program is to develop technologies, decision-support tools, and methods of analysis that enable holistic management of water-dependent energy infrastructure and natural resources in support of the DOE Energy Efficiency and Renewable Energy Office (DOE-EERE), Federal hydropower agencies, Federal Energy Regulatory Commission (FERC), Nuclear Regulatory Commission (NRC), energy producers, and other entities. In support of SIM, ORNL completed technical assessments of two hydropower plants owned and operated by the Electricity Generating Authority of Thailand (EGAT): Vajiralongkorn (VRK), with an installed capacity of 300 MW, and Rajjaprabha (RPB), with an installed capacity of 240MW. Technical assessment is defined as the assessment of hydropower operation and performance, and the identification of potential opportunities for performance improvement through plant optimization. At each plant, the assessment included an initial analysis of hydropower operating and performance metrics, provided by dam owners. After this analysis, ORNL engaged with the plant management team in a skills exchange, where best practices, operational methods, and technical challenges were discussed. The technical assessment process was outlined to plant management followed by a presentation of preliminary results and analysis based on 50 days of operational data. EGAT has agreed to provide a full year of operational data so a complete and detailed assessment that captures seasonal variability can be completed. The results of these assessments and discussions will be used to develop a set of best practices, training, and procedure recommendations to improve the efficiency of the two assessed plants.

13 HYDRO ENERGY↗
DOE OSTI2026

Port Technical Assistance Program: A Proposed Initiative to Support U.S. Ports Through Energy Innovation

This document highlights the crucial importance of the maritime sector within the United States (U.S.) economy, serving as a key node for trade and global goods transportation. U.S. ports are currently grappling with challenges posed by rising shipping demands, the health impacts of diesel fuel reliance, and the technology adoptions of global trade partners due to increasing environmental regulations. This document proposes forming a technical assistance program, led by Pacific Northwest National Laboratory (PNNL), to help U.S. ports transition to sustainable energy solutions that not only improve environmental and community outcomes, but also enhance resilience to unexpected weather events and reduce pressure on local utilities. Coordinated by PNNL, this initiative would offer a web-based platform of consolidated resources and tools for comprehensive strategic planning and cost-benefit analysis. It also seeks to establish a collaborative network between ports and national laboratories to facilitate the sharing of best practices. The document suggests that optimizing resource allocation and providing tailored support could be achieved through strategic categorization of ports within this network, with relevant attributes and examples detailed in the report. The anticipated benefits of such a program could include increased efficiency and cost savings in port operations and the advancement of scientific innovation via alternative energy research. Also, it could enhance economic growth and competitiveness in international trade by enabling ports to meet shipping demands and develop resilient critical infrastructure through informed, long-term strategies.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Virtual Resource Management Framework (CRADA Final Report)

There is a need for advanced and widespread business automation within the nuclear industry to drive down operational costs while sustaining or improving safe operations. While there are many business process automation platforms commercially available, the difficulty is that business processes typically rely on a mixture of resource types to accomplish the desired activities and there is no universal software framework virtualizing diverse resource types for the purpose of automation. In this context, we are referring to any capability, physical or intangible, that can be used by an organization to achieve its objectives as a resource. To deploy business automation broadly and enable integrated operations for nuclear (ION), a framework is needed to represent all resource types and their associated disparate data within a plant and to enable seamless flow of resource information to the technologies used for process automation and resource optimization.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Harnessing Virtual Power Plants Reliably: Enabling tools for increased observability, controllability, operation, and aggregation of distributed energy resources

Harnessing virtual power plants enhances the integration of distributed energy resources into utility grids for a sustainable energy future. Virtual power plants (VPPs) aggregate DERs to enhance resource adequacy and reduce emissions. U.S. utilities are exploring various technologies to manage DERs effectively. FERC Order 2222 allows DERs to participate in both wholesale and retail markets. Enhancing observability and controllability of behind-the-meter (BTM) DERs is essential for reliable grid operations. A hierarchical control architecture can improve coordination among residential energy resources. Field tests showed nearly 20% energy savings and 30% peak power reduction during grid events. Effective management of DERs requires enhanced situational awareness to prevent grid congestion. Integrating DER management systems (DERMS) with existing planning tools can improve operational security. Near-real-time grid models can validate optimal resource set points against resource uncertainty. Traditional uninterruptible power supplies (UPS) can be upgraded to support grid services and become part of VPPs. Upgrading UPS systems can reduce costs by 75% and unlock significant battery capacity. New battery management systems and grid-aware controllers are essential for optimizing UPS performance. Continued research and development are necessary to address challenges in integrating DERs into utility grids. Encouraging customer participation in pilot programs is vital for the evolution of VPPs. Here, the shift towards price-responsive DERs and VPPs is expected to enhance energy distribution efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement: Preprint

Distribution system resilience enhancement is an important topic to ensure customers have access to the power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecasts. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗
DOE OSTI2023

Outage Forecast-Based Preventative Scheduling Model for Distribution System Resilience Enhancement

Distribution system resilience enhancement is an important topic to ensure customers have access to power supply during extreme events. In fact, certain weather-related extreme events can be predicted ahead of time. Therefore, it is important to investigate how to predict grid outages using extreme weather forecasts, and how outage predictions can be incorporated into distribution system resilience enhancement. In this paper, a preventative scheduling model for distribution systems is proposed. The model targets at allocating resources, especially mobile responsive resources such as mobile backup generators and mobile energy storage systems, to prepare for an extreme event in the day-ahead context. To achieve efficient resource allocation and scheduling, a machine learning-based outage prediction module is developed to predict vulnerable or risky segments of the distribution system based on historical operating records and extreme weather event forecast. By integrating the outage prediction results into the scheduling model, optimal resource allocation can be derived to help distribution systems prepare for an upcoming event and improve resilience performance. A real distribution feeder in North Carolina, U.S. is used in the case study to validate the proposed approach.

distributed energy resources↗
DOE OSTI2022

First Wave of Incentive-Driven CCS Projects in North Dakota

Conference poster presented at American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, Texas, March 28–30, 2022. While the central interior of North America offers a tremendous storage resource, optimization will be key to meaningfully reducing the more than 2.6 billion tons of CO 2 emitted annually from large point sources in the United States. These initial projects tend to have the most favorable economics and are often able to take advantage of the best geology, with little to no competition for resource. This initial wave of projects is informing investment in and creating the opportunity for innovation that will enable the next wave of incentive-based CCS projects. Such innovation is critical for reducing costs, enhancing the design and operability of the next wave of CCS projects, and realizing more of the 250 billion tons of storage resource in North Dakota.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

PRP Comments for ICF Q1/Q2 FY17 Experiments 3/10/16

The PRP generally endorsed the Program plan during the short time for discussions. We agree that the strategy to develop a hohlraum that is symmetric and has low laser-plasma instabilities and to develop an alternative method for supporting the capsule is the best path forward for making progress in understanding ignition performance. The Program is oriented toward a milestone in 2020 for “determining the efficacy of NIF for ignition and credible physics-scaling to multi-megajoule yields for all ICF approaches.” We are concerned that the time and resources are not sufficient to vet all of the various approaches that are being pursued to make an informed decision by this date. For NIF to meet this goal, a process will be needed to to select the most promising paths forward. We recommend that the Program develop this process for selecting the path forward to optimize resources. We were glad to see that the direct drive program took our comments under consideration. We think that the proposed experiments have the program headed in a better direction. The PRP had only a short time to discuss the detailed experimental proposals. The following are comments on the detailed proposals. We did not have time to discuss them as a group. They represent individual opinions and provided to you as feedback to your proposals.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Retargetable Optimizing Compilers for Quantum Accelerators via a Multi-Level Intermediate Representation

In this work, we present a multi-level quantum-classical intermediate representation (IR) that enables an optimizing, retargetable compiler for available quantum languages. Our work builds upon the Multi-level Intermediate Representation (MLIR) framework and leverages its unique progressive lowering capabilities to map quantum languages to the LLVM machine-level IR. We provide both quantum and classical optimizations via the MLIR pattern rewriting sub-system and standard LLVM optimization passes, and demonstrate the programmability, compilation, and execution of our approach via standard benchmarks and test cases. In comparison to other standalone language and compiler efforts available today, our work results in compile times that are 1000x faster than standard Pythonic approaches, and 5-10x faster than comparative standalone quantum language compilers. Our compiler provides quantum resource optimizations via standard programming patterns that result in a 10x reduction in entangling operations, a common source of program noise. We see this work as a vehicle for rapid quantum compiler prototyping.

43 PARTICLE ACCELERATORS↗