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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

SAMMY Modernization Efforts [Slides]

This presentation details several SAMMY modernization and maintenance goals, as well as the efforts made towards these goals and future plans for SAMMY.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Technology Strategy Assessment: Findings from Storage Innovations 2030 Thermal Energy Storage

The concept of thermal energy storage (TES) can be traced back to early 19th century, with the invention of the ice box to prevent butter from melting. Modern TES development began with building heating and cooling and concentrated solar thermal technologies for power generation in the early 1900s and late 1970s, respectively. TES systems provide many advantages compared with other long-duration energy storage (LDES) technologies, which include low costs, long operational lives, high energy density, synchronous power generation capability with inertia that inherently stabilizes the grid, and the ability to output both heat and electricity. TES Use Cases TES technologies can couple with most renewable energy systems, including wind, photovoltaic, and concentrated solar thermal energy, and can be used for heat-to-heat, heat-to-electricity, electricity-to-heat, and electricity-to-electricity (bidirectional electricity) applications. The three types of TES that have heat as an input or output are grouped together for the purposes of this report. Retrofitting retired thermal power plants can be a potential cost-effective option for TES with electricity output because they both use a similar thermal-to-electricity type of conversion. Additionally, TES can directly serve heat demand for buildings and industrial processes, displacing fossil fuels to achieve broad decarbonization. Bidirectional Electricity Figure 1 shows a bidirectional electricity TES (ETES) architecture that is emerging as a prime technology for LDES at a grid scale. The ETES technology can utilize existing TES technology infrastructures, has no geological limitations (such as mountains and water for pumped storage hydro, underground natural caverns for compressed-air energy storage, etc.), and is capable of deployment anywhere in the United States and the world for broad uses. Particularly, ETES technology can be placed at retired fossil-fueled thermal power plants to reuse decommissioned assets, protect job security in associated communities, and provide resilient and high-inertia (i.e., spinning) power to the grid. Heat Input and Output There also are many ways to integrate TES within heat-to-electricity, heat-to-heat, and electricity-to-heat applications, such as those used in concentrating solar power (CSP), buildings, district heating, and industry process heat applications. These categories can be further classified for low- and high-temperature applications. High-temperature thermal energy storage (HTTES) heat-to-electricity TES applications are currently associated with CSP deployments for power generation. TES with CSP has been deployed in the Southwestern United States with rich solar resources and has proved its value to the electric grid. Electricity-to-heat and heat-to-heat HTTES applications present great potential for decarbonizing energy-intensive industrial process heat applications [8, 9], such as iron ore processing, iron smelting, cement production, glass manufacturing, mineral processing, and chemical production. Some industrial processes require process heat at temperatures > 1,400°C, so HTTES can be utilized to reduce fuel consumption in those processes through fuel, oxidizer, and process material pre-heating. Thermal energy storage for augmenting existing industrial process heat applications makes a much more attractive economic case because the energy penalty due to thermal-to-electric conversion is eliminated. Co-located applications of power production and heat also can add to the value stacking of integrating utility-scale TES; however, these scenarios are very case specific and not practically possible in many cases. These constraints are primarily attributed to the existing infrastructure being designed, developed, and constructed for many decades around the most economically feasible technologies, such as electricity and a selection of fossil fuels for heat input. Low-temperature TES can be utilized for building and district heating and cooling, as well as some process heat applications in electricity-to-heat and heat-to-heat configurations. Lower temperature TES (LTTES) can be added to heat pump equipment (electric input), either directly interacting with the refrigerant in the condenser or evaporator, or through a secondary heat transfer fluid. It also can be integrated in the building envelope or within the ducts of the heating, ventilation, and air conditioning (HVAC) system. Cost-effective integration of TES into buildings adds significant cost, and it is one of the key barriers preventing the commercialization and deployment of TES. The optimal strategy for integrating TES with buildings has yet to be determined for various applications of TES. Nevertheless, thermal storage materials are far less costly per unit of energy stored than electricity storage materials. This means that thermal storage has the potential to reduce the cost to society of energy storage.

25 ENERGY STORAGE↗
DOE OSTI2016

Revised Extended Grid Library

The Revised Eolus Grid Library (REGL) is a mesh-tracking library that was developed for use with the MCNP6TM computer code so that (radiation) particles can track on an unstructured mesh. The unstructured mesh is a finite element representation of any geometric solid model created with a state-of-the-art CAE/CAD tool. The mesh-tracking library is written using modern Fortran and programming standards; the library is Fortran 2003 compliant. The library was created with a defined application programmer interface (API) so that it could easily integrate with other particle tracking/transport codes. The library does not handle parallel processing via the message passing interface (mpi), but has been used successfully where the host code handles the mpi calls. The library is thread-safe and supports the OpenMP paradigm. As a library, all features are available through the API and overall a tight coupling between it and the host code is required. Features of the library are summarized with the following list: Can accommodate first and second order 4, 5, and 6-sided polyhedra; any combination of element types may appear in a single geometry model; parts may not contain tetrahedra mixed with other element types; pentahedra and hexahedra can be together in the same part; robust handling of overlaps and gaps; tracks element-to-element to produce path length results at the element level; finds element numbers for a given mesh location; finds intersection points on element faces for the particle tracks; produce a data file for post processing results analysis; reads Abaqus .inp input (ASCII) files to obtain information for the global mesh-model; supports parallel input processing via mpi; and support parallel particle transport by both mpi and OpenMP.

Martz, Roger L.↗
DOE OSTI2026

Digital Assurance for Grid Reliability in the Era of Large Load Growth

The rapid expansion of large electric loads is reshaping the operational and regulatory landscape of the U.S. electric grid. These facilities are reaching new scales of expansion, now exceeding a gigawatt per site, and their highly sensitive, digitally driven behaviors introduce new reliability risks. Recent grid events, including large load losses following routine transmission disturbances, highlight the consequences of limited ride-through capability, inconsistent protection settings, inadequate modeling, and lack of behind-the-meter visibility. Parallels to earlier integration challenges of new grid technologies suggest that the grid’s existing processes, standards, and interconnection frameworks are no longer adequate for emerging large loads. This brief synthesizes lessons from the evolution of inverter-based resource regulation and applies them to large-load integration. It identifies critical gaps in modeling accuracy, interconnection processes, performance standards, and compliance mechanisms. Technical recommendations emphasize advanced monitoring, improved modeling, coordinated communication protocols, modernized substations, and structured behind-the-meter control schemes. Collectively, these measures provide a roadmap to maintain bulk power system reliability while enabling the continued growth of large, electrified digital infrastructure.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products

Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km × 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

MERRA-2 reanalysis↗
NASA NTRS2012

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth's energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into account

Robert, J. Brent↗
NASA NTRS2012

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into account.

Roberts, J. Brent↗
DOE OSTI2017

Toward Exascale Earthquake Ground Motion Simulations for Near-Fault Engineering Analysis

Modernizing SW4 for massively parallel time-domain simulations of earthquake ground motions in 3D earth models increases resolution and provides ground motion estimates for critical infrastructure risk evaluations. Simulations of ground motions from large (M ≥ 7.0) earthquakes require domains on the order of 100 to500 km and spatial granularity on the order of 1 to5 m resulting in hundreds of billions of grid points. Surface-focused structured mesh refinement (SMR) allows for more constant grid point per wavelength scaling in typical Earth models, where wavespeeds increase with depth. In fact, MR allows for simulations to double the frequency content relative to a fixed grid calculation on a given resource. The authors report improvements to the SW4 algorithm developed while porting the code to the Cori Phase 2 (Intel Xeon Phi) systems at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory. As a result, investigations of the performance of the innermost loop of the calculations found that reorganizing the order of operations can improve performance for massive problems.

58 GEOSCIENCES↗
NASA NTRS1991

The computation of three-dimensional flows using unstructured grids

A general method is described for automatically discretizing, into unstructured assemblies of tetrahedra, the three-dimensional solution domains of complex shape which are of interest in practical computational aerodynamics. An algorithm for the solution of the compressible Euler equations which can be implemented on such general unstructured tetrahedral grids is described. This is an explicit cell-vertex scheme which follows a general Taylor-Galerkin philosophy. The approach is employed to compute a transonic inviscid flow over a standard wing and the results are shown to compare favorably with experimental observations. As a more practical demonstration, the method is then applied to the analysis of inviscid flow over a complete modern fighter configuration. The effect of using mesh adaptivity is illustrated when the method is applied to the solution of high speed flow in an engine inlet.

Morgan, K.↗
DOE OSTI2025

Generic Discretization Library

The GenDiL library is a collection of C++ software abstractions designed to discretize and solve partial differential equations (PDEs) for high-performance computing (HPC) applications. Its primary focus is on modern C++ generic programming, which helps ensure portability across various hardware architectures. The central idea behind the library is to provide building blocks for numerical algorithms-such as discretization methods and iteration patterns-so that domain experts can focus on the math, rather than the low-level details of hardware or implementation. By defining abstractions for data types, iteration over computational grids, and scheduling of operations, the library isolates the high-level PDE algorithms from the platform-specific optimizations needed to achieve efficient performance.

Dudouit, Yohann [Lawrence Livermore National Labor↗
DOE OSTI2020

Preparing Distribution Utilities for Utility-Scale Storage and Electric Vehicles: A Novel Analytical Framework

Emerging distributed energy resources (DERs)—such as solar photovoltaics (PV), battery energy storage systems (BESS), and electric vehicles (EVs)—are expected to increase substantially in India in the coming years following policy-driven targets of the Government of India to modernize its electricity system, reduce greenhouse gas emissions (GHGs), and improve air quality. These emerging technologies can pose challenges to distribution utilities, forcing overhauls in planning and operational practices. They can also create challenges in power system infrastructure planning and cause more frequent system operational violations (e.g., network voltage bounds and loading thresholds) if not properly integrated. The impacts on the localized power distribution grid from these emerging technologies manifest in increased infrastructure investments and erratic shifts in demand patterns. These impacts are not yet well understood, and analytic solutions are not readily available. To address these challenges, the National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL), developed an advanced power distribution system impact analysis framework of BRPL’s distribution system. This framework helps analyze the readiness of the power distribution network to accommodate emerging technologies and the potential opportunities they might introduce. The framework has been predominantly set up to evaluate distributed PV, BESS, and EVs. In this collaboration between NREL and BRPL, we developed and evaluated the framework on two distribution feeders in the BRPL territory for various scenarios of BESS and EVs. BESS are evaluated for their effectiveness on the grid to mitigate present and future feeder overloading scenarios, and they are subsequently analyzed for their costs compared to the costs of traditional upgradation measures. Scenarios include assessing the effects of EV density on grid infrastructure upgrades and interlinking EV management with BESS integration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Inertia Emulation Control using Demand Response via 5G Communications

Building energy equipment is moving rapidly towards Internet of Things (IoT)-driven devices to provide consumer connectivity and device management. These device-level interfaces along with 5G communications will be leveraged to develop control architectures to engage a large number of monitoring and control devices and provide real-time and reliable energy services. Emerging 5G networks have high potential to provide the communication technology for demand response, with fast transfer speed, high reliability, and high number of connections. Guaranteed inertial response to limit frequency fluctuations is one of the main challenges in modern power systems due to the increased penetration of renewable generation, and it is largely affected by communication delays and packet losses. This paper analyzes inertial response and rate of change of frequency in a power system model with inverter-interfaced air conditioners. The control loop considers time delays and packet losses to show the need to switch to 5G networks in future smart grids.

Morovati, Samaneh↗
DOE OSTI2016

Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC)U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRAtends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1)MERRAshows a spurious negative trend in Nebraska andKansas, which ismost likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over theGulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. The increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

Evaluation of NASA's MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

MERRA↗
NASA NTRS2018

GEOS-5 Seasonal Forecast System: ENSO Prediction Skill and Bias

The GEOS-5 AOGCM known as S2S-1.0 has been in service from June 2012 through January 2018 (Borovikov et al. 2017). The atmospheric component of S2S-1.0 is Fortuna-2.5, the same that was used for the Modern-Era Retrospective Analysis for Research and Applications (MERRA), but with adjusted parameterization of moist processes and turbulence. The ocean component is the Modular Ocean Model version 4 (MOM4). The sea ice component is the Community Ice CodE, version 4 (CICE). The land surface model is a catchment-based hydrological model coupled to the multi-layer snow model. The AGCM uses a Cartesian grid with a 1 deg × 1.25 deg horizontal resolution and 72 hybrid vertical levels with the upper most level at 0.01 hPa. OGCM nominal resolution of the tripolar grid is 1/2 deg, with a meridional equatorial refinement to 1/4 deg. In the coupled model initialization, selected atmospheric variables are constrained with MERRA. The Goddard Earth Observing System integrated Ocean Data Assimilation System (GEOS-iODAS) is used for both ocean state and sea ice initialization. SST, T and S profiles and sea ice concentration were assimilated.

GEOS-↗
DOE OSTI2025

Resilient Distributed Frequency Regulation of Renewable Generators under Communication Interruptions

Modern power systems (MPSs) face significant challenges due to the high penetration of renewable energy sources (RESs) and new types of loads such as electric vehicles (EVs). Traditional load frequency control (LFC) methods struggle with the intermittent, stochastic nature of RESs, the near-zero inertia of power-electronics-based generators, and the mobility of controllable loads and battery systems. This paper introduces a novel resilient distributed frequency regulation method to address these issues. The proposed method employs a state space model to represent the dynamic behavior of participating power sources while accounting for stochastic switching processes to model structural and parameter variations caused by disruptions such as generator connection/disconnection, communication interruptions, and physical faults. By integrating these dynamic and stochastic components, the method treats power grids as a comprehensive stochastic hybrid system. Our method enhances conventional frequency control by incorporating local stability control, neighborhood control decoupling, and coordination feedback. Theoretical analyses establish the stability, convergence, and resilience of the proposed method, and its effectiveness is validated through case studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Implementation of Feldman-Cousins Corrections and Oscillation Calculations in the HPC Environment for the NOvA Experiment

Analysis of neutrino oscillation data involves a combination of complex fitting procedures and statistical correction techniques that are used to determine the full three-flavor PMNS parameters and constraint contours. These techniques rely on computationally intensive “multi-universe” stochastic modeling. The process of calculating these contours and corrections can dominate final stages of the data analysis and become a bottleneck for examining the ef-fect of systematic variations on the final results. As part of the DOE SciDAC-4 sponsored research program, we present a new implementation of a neutrino oscillation fitting and framework to carry out calculations of Feldman-Cousins corrections. This implementation is specifically designed and optimized to operate on modern High-Performance Computing (HPC) facilities. We present the performance of the system in calculating allowed regions for the NOvA experiment based on 8.9 x 1020 and 6.9 x 1020 protons-on-target (POT) neutrino and antineutrino datasets, and compare the performance of this new implementation run at the NERSC supercomputing facility with that from methods used previously by the NOvA collaboration running on grid computing facilities.

Sousa, Alexandre↗