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At least 1,639 records · Page 91

A mixed volume grid approach for the Euler and Navier-Stokes equations

An approach for solving the compressible Euler and Navier-Stokes equations upon meshes composed of nearly arbitrary polyhedra is described. Each polyhedron is constructed from an arbitrary number of triangular and quadrilateral face elements, allowing the unified treatment of tetrahedral, prismatic, pyramidal, and hexahedral cells, as well the general cut cells produced by Cartesian mesh approaches. The basics behind the numerical approach and the resulting data structures are described. The accuracy of the mixed volume grid approach is assessed by performing a grid refinement study upon a series of hexahedral, tetrahedral, prismatic, and Cartesian meshes for an analytic inviscid problem. A series of laminar validation cases are made, comparing the results upon differing grid topologies to each other, to theory, and experimental data. A computation upon a prismatic/tetrahedral mesh is made simulating the laminar flow over a wall/cylinder combination.

Coirier, William J.↗

5G Energy FRAME Report on 5G for Grid Use Case (Year 3 Final Report)

This report provides an extensive overview of the interrelationships among energy, communication, and computing—especially in the context of decarbonization goals, challenges, and opportunities. Technical examples enabled by 5G technologies and their performance are presented, discussed, based on the experiment performed at Pacific Northwest National Laboratory. This is the first use case focused on using 5G for the U.S. power grid and will be referred to as the 5G for Grid Use Case from here on. Specifically, this use case looks at the workflow, which integrates the performance data of a real-world 5G communication testbed and a grid transmission and distribution co-simulation platform. The cross-domain information flow and logic design are illustrated with a combination of power grid contingencies and events. Lastly, a summary of the project achievement and outcome is provided, along with a technology roadmap envisioned by the project team.

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Flexible AI Models for Grid Resilience

The rapid growth in size and complexity of artificial intelligence (AI) and machine learning (ML) models has led to increased energy demands, posing a threat to the reliability of the existing power grid. This project addresses the challenge of highly intermittent and energy-intensive inference workloads by (1) developing fidelity-adaptive neural networks capable of dynamic response to grid conditions and (2) integrating these networks with power flow simulations to assess their impact on power grid reliability. We will explore both top-down and bottom-up approaches to create hierarchies of submodels that provide a controlled trade-off between power draw and prediction accuracy. The top-down method utilizes NN pruning to reduce a flagship model into progressively smaller, energy-efficient variants. The bottom-up approach employs geometrically principled weight setting strategies to construct depth-efficient models from the ground up. A real-time hardware-in-the-loop (HIL) platform will be developed to simulate a scaled AC power grid, integrating live AI workload power draw and enabling dynamic model switching in response to grid feedback. This work will provide a novel framework for evaluating the impact of flexible AI/ML workloads on grid performance and establish new methodologies for energy-aware computing in data centers. The outcomes will demonstrate that adaptive AI/ML can play a critical role in improving grid stability while advancing NREL's leadership in energy-efficient computing research.

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Heat Transfer on a Film-Cooled Rotating Blade Using Different Turbulence Models

A three-dimensional Navier Stokes code has been used to compute the heat transfer coefficient on a film-cooled, rotating turbine blade. The blade chosen is the ACE rotor with five rows containing 93 film cooling holes covering the entire span. This is the only film-cooled rotating blade over which experimental data is available for comparison. Over 2.278 million grid points are used to compute the flow over the blade including the tip clearance region. using Wilcox's k-omega model, Coakley's q-omega model, and the zero-equation Baldwin-Lomax (B-L) model. A reasonably good comparison with the experimental data is obtained on the suction surface for all the turbulence models. At the leading edge, the B-L model yields a better comparison than tile two-equation models. On the pressure surface however the comparison between the experimental data and the prediction from the k-omega model is much better than from the other two models. Overall, the k-omega model provides the best comparison with the experimental data. However, the two-equation models require at least 40% more computational resources than the B-L model.

Garg, Vijay K.↗

External-Compression Supersonic Inlet Design Code

A computer code named SUPIN has been developed to perform aerodynamic design and analysis of external-compression, supersonic inlets. The baseline set of inlets include axisymmetric pitot, two-dimensional single-duct, axisymmetric outward-turning, and two-dimensional bifurcated-duct inlets. The aerodynamic methods are based on low-fidelity analytical and numerical procedures. The geometric methods are based on planar geometry elements. SUPIN has three modes of operation: 1) generate the inlet geometry from a explicit set of geometry information, 2) size and design the inlet geometry and analyze the aerodynamic performance, and 3) compute the aerodynamic performance of a specified inlet geometry. The aerodynamic performance quantities includes inlet flow rates, total pressure recovery, and drag. The geometry output from SUPIN includes inlet dimensions, cross-sectional areas, coordinates of planar profiles, and surface grids suitable for input to grid generators for analysis by computational fluid dynamics (CFD) methods. The input data file for SUPIN and the output file from SUPIN are text (ASCII) files. The surface grid files are output as formatted Plot3D or stereolithography (STL) files. SUPIN executes in batch mode and is available as a Microsoft Windows executable and Fortran95 source code with a makefile for Linux.

Slater, John W.↗

Propeller aircraft interior noise model: User's manual for computer program

A computer program entitled PAIN (Propeller Aircraft Interior Noise) has been developed to permit calculation of the sound levels in the cabin of a propeller-driven airplane. The fuselage is modeled as a cylinder with a structurally integral floor, the cabin sidewall and floor being stiffened by ring frames, stringers and floor beams of arbitrary configurations. The cabin interior is covered with acoustic treatment and trim. The propeller noise consists of a series of tones at harmonics of the blade passage frequency. Input data required by the program include the mechanical and acoustical properties of the fuselage structure and sidewall trim. Also, the precise propeller noise signature must be defined on a grid that lies in the fuselage skin. The propeller data are generated with a propeller noise prediction program such as the NASA Langley ANOPP program. The program PAIN permits the calculation of the space-average interior sound levels for the first ten harmonics of a propeller rotating alongside the fuselage. User instructions for PAIN are given in the report. Development of the analytical model is presented in NASA CR 3813.

Wilby, E. G.↗

Ensemble Federated Machine Learning‐Based Cybersecurity Situational Awareness in Microgrid Network

Cyber-physical microgrids are vulnerable to stealthy cybersecurity threats that disguise their actions through the exploitation of system knowledge. Such actions can severely impacts microgrids deployed in defense bases, slowing the response time of military forces during national emergencies. Several machine-learning algorithms have been proposed to detect intrusions in the grid networks; however, these traditional machine-learning algorithms lack data privacy and are subject to several adversarial machine-learning threats. This paper proposes a novel federated machine learning (FML)-based three-model framework to detect and identify stealthy data-integrity attacks while ensuring data privacy in microgrid networks. The proposed architecture uses a variational mode decomposition technique to extract derived features from incoming measurement and control datasets. The extraction of these derived features allows FML models to learn minute variations in data patterns that allow them to perform significantly better than the models trained with generic datasets consisting of raw features. Our experimental results show the efficient performance of the proposed methodology against different types of data integrity attacks while considering primary and secondary controllers in microgrids. Further, the applied FML-integrated random forest ensemble algorithm outperforms the existing generic FML algorithms during noisy and noise-free datasets with prediction latencies of only 91–134 µs per sample within the 0.1 s sampling interval and requires communication bandwidth of around ∼8.25 KB/s at the control center and ∼2.7 KB/s per edge client for communication.

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Computation of shock wave/target interaction

Computational results of shock waves impinging on targets and the ensuing diffraction flowfield are presented. A number of two-dimensional cases are computed with finite difference techniques. The classical case of a shock wave/cylinder interaction is compared with shock tube data and shows the quality of the computations on a pressure-time plot. Similar results are obtained for a shock wave/rectangular body interaction. Here resolution becomes important and the use of grid clustering techniques tend to show good agreement with experimental data. Computational results are also compared with pressure data resulting from shock impingement experiments for a complicated truck-like geometry. Here of significance are the grid generation and clustering techniques used. For these very complicated bodies, grids are generated by numerically solving a set of elliptic partial differential equations.

Mark, A.↗

LDCM Grid Prototype (LGP)

The LGP successfully demonstrated that grid technology could be used to create a collaboration among research scientists, their science development machines, and distributed data to create a science production system in a nationally distributed environment. Grid technology provides a low cost and effective method of enabling production of science products by the science community. To demonstrate this, the LGP partnered with NASA GSFC scientists and used their existing science algorithms to generate virtual Landsat-like data products using distributed data resources. LGP created 48 output composite scenes with 4 input scenes each for a total of 192 scienes processed in parallel. The demonstration took 12 hours, which beat the requirement by almost 50 percent, well within the LDCM requirement to process 250 scenes per day. The LGP project also showed the successful use of workflow tools to automate the processing. Investing in this technology has led to funding for a ROSES ACCESS proposal. The proposal intends to enable an expert science user to produce products from a number of similar distributed instrument data sets using the Land Cover Change Community-based Processing and Analysis System (LC-ComPS) Toolbox. The LC-ComPS Toolbox is a collection of science algorithms that enable the generation of data with ground resolution on the order of Landsat-class instruments.

Weinstein, Beth↗

A new NASA/MSFC mission analysis global cloud cover data base

A global cloud cover data set, derived from the USAF 3D NEPH Analysis, was developed for use in climate studies and for Earth viewing applications. This data set contains a single parameter - total sky cover - separated in time by 3 or 6 hr intervals and in space by approximately 50 n.mi. Cloud cover amount is recorded for each grid point (of a square grid) by a single alphanumeric character representing each 5 percent increment of sky cover. The data are arranged in both quarterly and monthly formats. The data base currently provides daily, 3-hr observed total sky cover for the Northern Hemisphere from 1972 through 1977 less 1976. For the Southern Hemisphere, there are data at 6-hr intervals for 1976 through 1978 and at 3-hr intervals for 1979 and 1980. More years of data are being added. To validate the data base, the percent frequency of or = 0.3 and or = 0.8 cloud cover was compared with ground observed cloud amounts at several locations with generally good agreement. Mean or other desired cloud amounts can be calculated for any time period and any size area from a single grid point to a hemisphere. The data base is especially useful in evaluating the consequence of cloud cover on Earth viewing space missions. The temporal and spatial frequency of the data allow simulations that closely approximate any projected viewing mission. No adjustments are required to account for cloud continuity.

Brown, S. C.↗

Survey Parameters and Availability of Low-level Aeromagnetic Data for Geomagnetic Field Modelling

Since aeromagnetic surveying started immediately after World War II, a considerable area of the earth's surface both onshore (in excess of 25 million sq. km) has been magnetically surveyed. For about the first 15 years or so, fluxgate magnetometers were employed in aeromagnetic surveys, but the introduction of proton free-precession magnetometers resulted in absolute readings being recorded. Proton precession magnetometers have now been replaced to a large extent by the more sensitive optical absorption magnetometers. Some care has to be taken to calibrate aeromagnetic survey systems and this is best done using a calibration range tied to a magnetic observatory so that accuracies of 10nT or better are achieved for the total field values recorded. Survey navigation has always posed a problem for aeromagnetic surveys, especially offshore. Over land, vertically pointed 35 mm cameras were initially used to recover the aircraft track using a combination of aerial photos and topographic maps. Over featureless areas, it was necessary to utilize existing electronic positioning systems such as Loran C or set up special navigation systems. The advent of the satellite-based Global Positioning Systems (GPS) has to a larger extent solved the navigational problem because there is now almost continuous worldwide coverage to 10 m accuracy in the differential mode. The resultant aeromagnetic data is normally compiled into contour maps in which the diurnal variation and aircraft heading effects are removed. The resultant digital data are normally made publicly available both in gridded and profile form along with the published contour maps. Most aeromagnetic coverage has been obtained in the developed western countries, but elsewhere a considerable amount of surveying has been carried out; as an example, some 80 percent of Africa has been surveyed mostly as a result of aid programs. The data is usually held by the national geological survey or equivalent organizations, but in a number of cases the data (e.g., for the Magnetic Anomaly Map of North America) is also held by the World Data Centres.

Hood, Peter↗

A physical interpretation of brightness temperatures observed by the microwave sounding units based upon raobs

Ten years (1979-1988) of Microwave Sounding Unit (MSU) data from five satellites were calibrated and processed using procedures described by Spence and Christy (1990) and Spenser et al. (1990). The data are averaged at one month and 2.5-deg grid resolution, and the monthly anomalies in channel 2 are computed from annual cycles measured at each gridpoint. The anomalies at gridpoints are then compared with anomalies computed from radiosonde data.

Spencer, Roy W.↗

IFCPT S-Duct Grid-Adapted FUN3D Computations for the Third Propulsion Aerodynamics Works

Contributions of the unstructured Reynolds-averaged Navier-Stokes code, FUN3D, to the 3rd AIAA Propulsion Aerodynamics Workshop are described for the diffusing IFCPT S-Duct. Using workshop-supplied grids, results for the baseline S-Duct, baseline S-Duct with Aerodynamic Interface Plane (AIP) rake hardware, and baseline S-Duct with flow control devices are compared with experimental data and results computed with output-based, off-body grid adaptation in FUN3D. Due to the absence of influential geometry components, total pressure recovery is overpredicted on the baseline S-Duct and S-Duct with flow control vanes when compared to experimental values. An estimate for the exact value of total pressure recovery is derived for these cases given an infinitely refined mesh. When results from output-based mesh adaptation are compared with those computed on workshop-supplied grids, a considerable improvement in predicting total pressure recovery is observed. By including more representative geometry, output-based mesh adaptation compares very favorably with experimental data in terms of predicting the total pressure recovery cost-function; whereas, results computed using the workshop-supplied grids are underpredicted.

Davis, Zach S.↗

Investigating tectonic and bathymetric features of the Indian Ocean using MAGSAT magnetic anomaly data

MAGSAT Investigator-B tapes were preprocessed by (1) removing all data points with obvious erroneous values and location errors; (2) removing smaller spikes (typically 15 nT or more), and deleting data tracks with fewer than 20 points; and (3) removing a linear trend from each track. The remaining data were recorded on tape for use by the equivalent source mapping (ESMAP) program which uses a least squares algorithm to fit the magnetization parameter of the grid of equivalent source dipoles in the crust to satellite data acquired at different times and locations. ESMAP was implemented on the TASC computing system and modified to read preprocessed MAGSAT tapes and interface with TASC plotting software. Some verification of the software was accomplished. Gridded 1-degree mean values of gravity anomaly and sea surface undulation computed from SEASAT radar altimeter were obtained and brought on line.

Lazarewicz, A. R.↗

EMT data generation

The integration of inverter-based resources (IBRs) in power systems is accelerating, bringing with it significant benefits such as reduced greenhouse gas emissions, improved grid resilience, and increased energy independence. Despite these advantages, the widespread adoption of IBRs introduces several challenges, including issues related to grid stability, increased operational complexity, and the need for updated regulatory frameworks. To address these challenges, IEEE released Standard 2800 in 2022, which sets forth the necessary interconnection capabilities and performance criteria for IBRs connected to transmission and sub-transmission systems. This standard outlines the performance requirements to ensure the reliable integration of IBRs into the bulk power system. Furthermore, in 2023, the North American Electric Reliability Corporation (NERC) published a reliability guideline for electromagnetic transient (EMT) modeling of BPS-connected IBRs. This guideline provides recommendations for developing EMT model requirements, performing model quality checks, and implementing verification practices specifically for EMT models representing BPS-connected inverter-based resources in reliability studies conducted by transmission planners and planning coordinators. These standards and guidelines have a profound impact on EMT studies for transmission networks, influencing system stability analyses, grid recovery and resynchronization processes, fault ride-through evaluations, protection and coordination strategies, advanced control methodologies, and the inclusion of IBRs in transient models of transmission networks. As a result, the generation of EMT data is crucial for conducting various transient-based studies to understand the impact of IBRs. EMT data generation use cases serve as the basis for scenarios in event detection and identification use cases, providing comprehensive details about EMT data generation for transmission grids with inverter-based resources. These use cases supply sufficient training and validation datasets for subsequent EMT analysis algorithms.

Xia, Qianxue↗

Strategies for Flood Resilience and Grid Investment Among Iowa's Electric Distribution Utilities

Flooding poses a growing threat to Iowa's electric distribution system, yet utilities face significant data and modeling challenges in planning effective resilience investments. This report provides a foundational assessment of how distribution utilities in Iowa, investor-owned, municipal, and cooperative, approach resilience planning, with a focus on flood risk. It combines hazard characterization, review of state and utility practices, and application of NLR's Energy Resilience Analysis for Distribution Systems (ERAD) and Capacity Expansion Decision Support for Distribution Networks (CADET) tools. Using FEMA floodplains, Iowa Flood Center depth grids, and utility infrastructure data, the analysis quantifies asset exposure, simulates outage risks, and evaluates resilience strategies such as pole hardening, undergrounding, and substation protection. Results indicate that while feeder-level upgrades provide incremental benefits, the most significant reductions in outage risk are achieved through targeted substation interventions. The report highlights key data gaps, such as limited elevation data and fragility functions, and underscores the need for probability-weighted investment frameworks to address both frequent and catastrophic flood events. These insights aim to support utilities, state agencies, and federal partners in prioritizing resilience investments that safeguard Iowa's electric grid against future flooding.

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The Impact of Clean Grid Transition on Wastewater Sector Greenhouse Gas Emissions

This study examines the spatial and temporal impacts of the U.S. clean energy grid transition on related greenhouse gas (GHG) emissions from the wastewater treatment industry. By analyzing data from 17,156 water resource recovery facilities (WRRFs) and state-specific grid decarbonization scenarios, the results project a 60% reduction in Scope 2 emissions by 2050, driven by the national shift to renewable energy. However, regional disparities are prominent, with northeastern and western states achieving the most significant reductions, while the Ohio Valley and Rockies are likely to experience higher emissions due to the reliance on fossil fuels. This study offers the first assessment of clean grid impacts on the WRRFs and highlights the need for targeted, region-specific strategies across different emission scopes. This research provides insights for policymakers and stakeholders in the wastewater sector, emphasizing the critical role of grid decarbonization in achieving GHG reduction goals.

Li, Xiatong↗

Accessing and Visualizing scientific spatiotemporal data

This paper discusses work done by JPL 's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids These tools do one or more of the following tasks visualize local data sets for local users, visualize local data sets for remote users, and access and visualize remote data sets The tools are used for various types of data, including remotely sensed image data, digital elevation models, astronomical surveys, etc The paper attempts to pull some common elements out of these tools that may be useful for others who have to work with similarly large data sets.

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