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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

Defining Power Efficient Residential Electric Appliances and Equipment

While the long-established concept of "energy efficiency" has successfully reduced energy consumption and bills in homes, it is no longer sufficient to address the modern challenges of electrical load growth, infrastructure upgrades and associated affordability challenges. We introduce the concept of “power efficiency” for household appliances and equipment, providing a framework to support affordable home modernization and grid management. Energy efficiency is the measure of energy used (kWh) to provide comfort/conveniences, power efficiency is the measure of power used (kW) to provide those same comforts/conveniences. Energy efficiency was needed because energy is a limited resource and expensive. Now power efficiency is needed because power delivery into a building is a limited resource and expensive. We propose a new set of metrics for defining and measuring power efficiency by investigating how current appliance nameplate ratings are established, and assessing the availability and use of existing data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Operational Evolution of FTS3: A DevOps Driven Approach to Elastic Operations

The File Transfer Service (FTS3) is a distributed data movement service developed at CERN and widely used to transfer data across the Worldwide LHC Computing Grid (WLCG). At Fermilab, FTS3 supports data transfers for multiple experiments, including Intensity Frontier experiments such as DUNE, enabling reliable data movement between WebDAV endpoints in Europe and the Americas.​ At CHEP 2021, we reported on the initial containerized deployment of FTS3 on OKD, the community Kubernetes distribution of Red Hat OpenShift. In this work, we present the subsequent evolution of this deployment, focusing on new operational capabilities introduced to improve scalability, robustness, and long-term maintainability.​ We describe the adoption of more secure and reproducible container build workflows, the integration of DevOps-driven operational practices, and enhancements in monitoring and automation. A key new result is the introduction of horizontal scaling and elastic resource management, allowing FTS3 components to dynamically adapt to workload variations while maintaining service reliability. We also discuss improvements in fault tolerance and operational procedures derived from production experience.​ Finally, we summarize lessons learned from operating FTS3 as a Kubernetes-native service and outline how these developments have improved the resilience and efficiency of data movement operations at Fermilab.

Munoz Flores, Victor Leopoldo [Fermilab]↗

Aerodynamic results of a separation effects test on a 0.01-scale model (52-OTS) of integrated SSV in the AEDC/VKF 40-by-40 inch supersonic wind tunnel A, volume 1

Experimental aerodynamic investigations were conducted, during the period July 18-19, 1974, in the AEDC/VKF Tunnel A facility on a 0.01-scale model (52-OTS) of the integrated space shuttle vehicle, including only one SRB. The purpose of the investigation was to obtain data for close-in proximity (SRB to orbiter/tank) effects with the orbiter/tank combination at relatively high alpha and beta attitudes, and with the SRB separation motors off. The AEDC Captive Trajectory System (CTS), which supported the SRB, was used in conjunction with the tunnel primary sector (supporting the orbiter/tank) to obtain grid type separation effects data. The one symmetrical SRB model was used interchangeably to obtain both right-hand and left-hand SRB data. Free-stream data were also obtained for the orbiter/tank and for the SRB. This data was used to provide baselines for proximity effects. The entire investigation was conducted at a free-stream Mach number of 4.5 with unit Reynolds number ranging from 4.0 to 6.5 million per foot.

Campbell, J. H., II↗

Aerodynamic results of a separation effects test on a 0.010-scale model (52-OTS) of the integrated SSV in the AEDC/VKF 40-by-40 inch supersonic wind tunnel A (IA111), volume 1

Graphical data obtained during experimental wind tunnel aerodynamic investigations of a 0.010 scale model (52-OTS) of the integrated space shuttle vehicle was presented. The purpose of this investigation was to obtain data with the solid rocket booster (SRB) in proximity to the orbiter/external tank (O/ET), over a large O/ET initial angle of attack and sideslip range, as well as data on the SRB alone (greatly separated from the O/ET). A captive trajectory system, which supported the SRB, was used with the tunnel primary sector (supporting the O/ET) to obtain grid type separation effects data. One symmetrical SRB model was used interchangeably to obtain right-hand and left-hand SRB data. The entire investigation was conducted at a free-stream Mach number of 4.5 at unit Reynolds number of 3.95 and 5.9 million per foot.

Chee, E.↗

Aerodynamic results of a separation effects test on a 0.010-scale model (52-OTS) of the integrated SSV in the AEDC/VKF 40-by-40 inch supersonic wind tunnel A (IA111), volume 2

Tabular data obtained during experimental wind tunnel aerodynamic investigations of a 0.010 scale model (52-OTS) of the integrated space shuttle vehicle was presented. The purpose of this investigation was to obtain data with the solid rocket booster (SRB) in proximity to the orbiter/external tank (O/ET), over a large O/ET initial angle of attack and sideslip range, as well as data on the SRB alone (greatly separated from the O/ET). A captive trajectory system, which supported the SRB, was used with the tunnel primary sector (supporting the O/ET) to obtain grid type separation effects data. One symmetrical SRB model was used interchangeably to obtain right-hand and left-hand SRB data. The entire investigation was conducted at free-stream Mach number of 4.5 at unit Reynolds number of 3.95 and 5.9 million per foot.

Chee, E.↗

Immobile Robots: AI in the New Millennium

A new generation of sensor rich, massively distributed, autonomous systems are being developed that have the potential for profound social, environmental, and economic change. These include networked building energy systems, autonomous space probes, chemical plant control systems, satellite constellations for remote ecosystem monitoring, power grids, biosphere-like life support systems, and reconfigurable traffic systems, to highlight but a few. To achieve high performance, these immobile robots (or immobots) will need to develop sophisticated regulatory and immune systems that accurately and robustly control their complex internal functions. To accomplish this, immobots will exploit a vast nervous system of sensors to model themselves and their environment on a grand scale. They will use these models to dramatically reconfigure themselves in order to survive decades of autonomous operations. Achieving these large scale modeling and configuration tasks will require a tight coupling between the higher level coordination function provided by symbolic reasoning, and the lower level autonomic processes of adaptive estimation and control. To be economically viable they will need to be programmable purely through high level compositional models. Self modeling and self configuration, coordinating autonomic functions through symbolic reasoning, and compositional, model-based programming are the three key elements of a model-based autonomous systems architecture that is taking us into the New Millennium.

Williams, Brian C.↗

NASA Exhibits

A series of NASA presentations for the Supercomputing 2001 conference are summarized. The topics include: (1) Mars Surveyor Landing Sites "Collaboratory"; (2) Parallel and Distributed CFD for Unsteady Flows with Moving Overset Grids; (3) IP Multicast for Seamless Support of Remote Science; (4) Consolidated Supercomputing Management Office; (5) Growler: A Component-Based Framework for Distributed/Collaborative Scientific Visualization and Computational Steering; (6) Data Mining on the Information Power Grid (IPG); (7) Debugging on the IPG; (8) Debakey Heart Assist Device: (9) Unsteady Turbopump for Reusable Launch Vehicle; (10) Exploratory Computing Environments Component Framework; (11) OVERSET Computational Fluid Dynamics Tools; (12) Control and Observation in Distributed Environments; (13) Multi-Level Parallelism Scaling on NASA's Origin 1024 CPU System; (14) Computing, Information, & Communications Technology; (15) NAS Grid Benchmarks; (16) IPG: A Large-Scale Distributed Computing and Data Management System; and (17) ILab: Parameter Study Creation and Submission on the IPG.

Deardorff, Glenn↗

The Sensitivity of Coded Mask Telescopes

Simple formulae are often used to estimate the sensitivity of coded mask X-ray or gamma-ray telescopes, but t,hese are strictly only applicable if a number of basic assumptions are met. Complications arise, for example, if a grid structure is used to support the mask elements, if the detector spatial resolution is not good enough to completely resolve all the detail in the shadow of the mask or if any of a number of other simplifying conditions are not fulfilled. We derive more general expressions for the Poisson-noise-limited sensitivity of astronomical telescopes using the coded mask technique, noting explicitly in what circumstances they are applicable. The emphasis is on using nomenclature and techniques that result in simple and revealing results. Where no convenient expression is available a procedure is given which allows the calculation of the sensitivity. We consider certain aspects of the optimisation of the design of a coded mask telescope and show that when the detector spatial resolution and the mask to detector separation are fixed, the best source location accuracy is obtained when the mask elements are equal in size to the detector pixels.

Skinner, Gerald K.↗

Comparison Study of Machine Learning Techniques to Predict Flight Energy Consumption for Advanced Air Mobility

This paper addresses the need to predict the flight energy consumption of aerial vehicles in the presence of wind using machine learning techniques. The presented work is critical to achieving sustainable and efficient operations for Advanced Air Mobility (AAM) and to evaluating the readiness of the ground-supporting energy infrastructure, e.g., electric grid and AAM portals. The flight energy consumption is described using the "energy per meter" (EPM) metric. We present a comparison study of influential machine learning techniques in predicting EPM using real-world flight test data. We presented new results of using the Decision Tree, Random Forest, and linear regression techniques, along with our previous results using the Recurrent Neural Network and Feed Forward Neural Network techniques. The comparison results show that the Linear Regression method outperforms other methods on the basis of the Mean Squared Error and error variance.

Machine Learning↗

C2C: Clean Energy to Communities

The Clean Energy to Communities (C2C) program advances community-led clean energy progress by providing local governments, electric utilities, and community-based organizations with cuttingedge analysis and validation from the U.S. Department of Energy's national laboratories. The program offers tailored support across the renewable power, grid, mobility, and buildings sectors that ranges from short term consultation with energy experts to multi-year technical assistance partnerships and direct funding.

C2C↗

Grid Technology as a Cyberinfrastructure for Delivering High-End Services to the Earth and Space Science Community

Grid technology consists of middleware that permits distributed computations, data and sensors to be seamlessly integrated into a secure, single-sign-on processing environment. In &is environment, a user has to identify and authenticate himself once to the grid middleware, and then can utilize any of the distributed resources to which he has been,panted access. Grid technology allows resources that exist in enterprises that are under different administrative control to be securely integrated into a single processing environment The grid community has adopted commercial web services technology as a means for implementing persistent, re-usable grid services that sit on top of the basic distributed processing environment that grids provide. These grid services can then form building blocks for even more complex grid services. Each grid service is characterized using the Web Service Description Language, which provides a description of the interface and how other applications can access it. The emerging Semantic grid work seeks to associates sufficient semantic information with each grid service such that applications wii1 he able to automatically select, compose and if necessary substitute available equivalent services in order to assemble collections of services that are most appropriate for a particular application. Grid technology has been used to provide limited support to various Earth and space science applications. Looking to the future, this emerging grid service technology can provide a cyberinfrastructures for both the Earth and space science communities. Groups within these communities could transform those applications that have community-wide applicability into persistent grid services that are made widely available to their respective communities. In concert with grid-enabled data archives, users could easily create complex workflows that extract desired data from one or more archives and process it though an appropriate set of widely distributed grid services discovered using semantic grid technology. As required, high-end computational resources could be drawn from available grid resource pools. Using grid technology, this confluence of data, services and computational resources could easily be harnessed to transform data from many different sources into a desired product that is delivered to a user's workstation or to a web portal though which it could be accessed by its intended audience.

Hinke, Thomas H.↗

Grid Resiliency using Hydro-based Microgrids During Wildfires

The primary objective of this project is to assess the techno-economic viability of hydropower resources with supplementary investments, including microgrid controllers, storage solutions, load banks, additional generation like diesel generators, communication links, and transmission infrastructure. The aim is to enable these systems to operate autonomously (in islanded mode) and ensure grid resiliency during and after wildfire events. The project seeks to establish a comprehensive framework for setting up hydropower-based microgrids, from risk estimation to final investment decisions. These microgrids can provide critical support during emergencies and offer additional grid stability and revenue opportunities during regular operations and other system contingencies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

STM/S Grid LDOS Data and Analysis Code for Deciphering Majorana Zero Modes in Topological Superconductor

This dataset provides raw millikelvin scanning tunneling microscopy/spectroscopy (STM/S) grid spectroscopy data and Python analysis scripts supporting the manuscript “Deciphering Majorana Zero Modes in Topological Superconductor FeTe0.55Se0.45 with Machine-Learning-Assisted Spectral Deconvolution.” The dataset includes a raw grid spectroscopy file acquired on FeTe0.55Se0.45 at 40 mK under magnetic field, together with Python/Jupytext analysis scripts used for STM/S data processing, visualization, spectral deconvolution, Lorentzian peak fitting, feature extraction, machine-learning-assisted clustering, and figure generation. These files support the analysis of vortex-core local density of states and the identification of zero-bias-peak-related spectral components from complex in-gap states. The dataset is intended to provide a citable archival record of the data and analysis code associated with the published manuscript and to support transparency and reproducibility of the reported STM/S and machine-learning workflow.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Computational support of the laminar flow supersonic wind tunnel, CNSFV code development, Maglev, and grid generation

This final report covers the work done on corporate agreement NCC2-616 over a period of 5 1/2 years. It is broken into three segments of approximately 1 1/2 to 2 years each. The report is a summary report and is not intended to be comprehensive of all the work done under this corporate agreement. A more complete coverage of the work done is obtained from the papers and reports listed in the 'Papers' section. Additional reporting of significant work was done through 'Technical Highlights' and 'Research and Technical Summaries'. A listing of copies are given in the 'Technical Highlights and R and T' section. The work was also reported in a series of seminars, conference meetings, branch reviews, workshops, and project reviews. A list of these talks is given in the 'Presentation' section. Also during this time three students ranging from high school to graduate level were supervised. A list of the students and the type of work accomplished is given in the 'Mentoring' section. The report concludes with the 'Appendices' sections which include the three papers produced during the last 1 1/2 years of this corporate agreement.

Klopfer, Goetz H.↗

Parallel Grid Manipulations in Earth Science Calculations

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center is moving its data assimilation system to massively parallel computing platforms. This parallel implementation of GEOS DAS will be used in the DAO's normal activities, which include reanalysis of data, and operational support for flight missions. Key components of GEOS DAS, including the gridpoint-based general circulation model and a data analysis system, are currently being parallelized. The parallelization of GEOS DAS is also one of the HPCC Grand Challenge Projects. The GEOS-DAS software employs several distinct grids. Some examples are: an observation grid- an unstructured grid of points at which observed or measured physical quantities from instruments or satellites are associated- a highly-structured latitude-longitude grid of points spanning the earth at given latitude-longitude coordinates at which prognostic quantities are determined, and a computational lat-lon grid in which the pole has been moved to a different location to avoid computational instabilities. Each of these grids has a different structure and number of constituent points. In spite of that, there are numerous interactions between the grids, e.g., values on one grid must be interpolated to another, or, in other cases, grids need to be redistributed on the underlying parallel platform. The DAO has designed a parallel integrated library for grid manipulations (PILGRIM) to support the needed grid interactions with maximum efficiency. It offers a flexible interface to generate new grids, define transformations between grids and apply them. Basic communication is currently MPI, however the interfaces defined here could conceivably be implemented with other message-passing libraries, e.g., Cray SHMEM, or with shared-memory constructs. The library is written in Fortran 90. First performance results indicate that even difficult problems, such as above-mentioned pole rotation- a sparse interpolation with little data locality between the physical lat-lon grid and a pole rotated computational grid- can be solved efficiently and at the GFlop/s rates needed to solve tomorrow's high resolution earth science models. In the subsequent presentation we will discuss the design and implementation of PILGRIM as well as a number of the problems it is required to solve. Some conclusions will be drawn about the potential performance of the overall earth science models on the supercomputer platforms foreseen for these problems.

Sawyer, W.↗

Performance Evaluation of Vertical Federated Machine Learning Against Adversarial Threats on Wide-Area Control System: Preprint

Federated machine learning (FL) is gaining significant popularity to develop cybersecurity solutions in power grids because of its advanced capability to support decentralized data handing at local devices, its privacy preservation, and its low-bandwidth requirement. However, the evolving adversarial machine learning (AML) threats raise significant concerns for the cybersecurity of FL architectures. The FL-based split neural network (SplitNN) achieves high performance through the decentralized training of local neural network models while preserving data privacy across multiple entities. In this paper, we propose a methodology for evaluating the performance of a vertical FLbased anomaly detector against different types of AML attacks, including denial-of-service attacks, adversarial data injection attacks, and replay attacks on the trained local models deployed in the grid network. For a case study, we consider the modified IEEE 13-bus system, and we develop SplitNN-based binary and multiclass classification models to detect, locate, and identify different types of data integrity attacks on the volt-watt control with two pooling layers: maximum pooling and AvgPool. Our experimental results, computed through performance metrics, reveal that the severity of these AML attacks varies with the integrated pooling mechanism, the type of classification model, and the nature of the cyberattack. Further, the AML attacks negatively impacted the prediction time per sample for the pretrained SplitNN during the online testing.

adversarial threats↗

Enabling Grid-Forming Control Under Unbalanced Conditions

Standalone microgrids often experience unbalanced loading and faults, which can cause grid-forming control designed for balanced conditions to produce oscillatory responses. To address this issue, a compact time-domain transformation appropriate for inverter control is proposed, allowing the conversion of unbalanced three-phase signals to positive and negative synchronous reference frames. This transformation supports the development of a grid-forming control with fault ride-through, featuring frequency and voltage droop controllers and nested current and voltage control loops that seamlessly integrate an enhanced current limiter. The effectiveness of the proposed control and transformation is demonstrated through analytical results and electromagnetic transient simulation.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Advanced Computing is at the Forefront of a New “Moonshot” Revolutionizing the North American Power Grid

In the 50+ years since the first humans landed on the moon, computing has grown at breakneck speed. We are faced with another challenge that is just as daunting, and just as important to overcome-modernizing the North American electric power grid-and high-performance computing (HPC) systems with specialized software will be an important element in rising to this challenge. We describe at a high level how software developed in the ExaSGD project addresses this "moonshot" goal by utilizing exascale computing and a novel high performance solver software stack to support the mission of decarbonizing power grid operations in an environment of uncertain weather and climate. To reach the exascale benchmark the team has made a number of first-of-their-kind innovations, including novel method for stochastic optimization, fine grained parallel methods for modeling power systems, and GPU resident sparse numerical linear solvers.

17 WIND ENERGY↗