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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations

Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.

autonomy loops↗
DOE OSTI2020

SHARP-Net: Platform for Self-Healing and Attack Resilient PMU Networks

Synchrophasor technology plays a pivotal role in developing the next generation of wide-area monitoring, protection, and control in the smart grid environment. As technology and communications infrastructures evolve, however, so do the attack surfaces in the synchrophasor network that can be exploited by advanced persistent threat (APT) actors to affect power system stability and reliability. In this paper, we propose a novel platform for developing a self-healing and attack-resilient PMU network (SHARP-Net) by instituting a state-of-the-art intrusion detection system (IDS) with an intrusion mitigation system (IMS) and an alert management system (AMS). In particular, the proposed platform detects anomalies during cyberattacks on phasor data concentrators (PDCs) based on the rules defined in the IDS, then the generated alerts are published to the IMS through the AMS. The proposed IMS proceeds to take automated corrective responses to mitigate cyberattacks by reconfiguring the synchrophasor network to isolate the compromised PDCs, and it orchestrates new PDCs to prevent the future propagation of attacks. Further, the IMS restores the system's observability by reconnecting the new PDCs to make the grid attack-resilient. In this work, the SHARP-Net platform is developed by using Python-based libraries, minimega's software-defined network, and virtual machine orchestration. We implement and validate the proposed SHARP-Net architecture by testing a PMU network in the smart grid environment. SHARP-Net showed promising performance in detecting cyberattacks and mitigating them through the network reconfiguration.

computer architecture↗
DOE OSTI2024

Bias Correction and Statistical Downscaling of Future Solar Irradiance Projections Using the NSRDB

Assessing renewable energy resources under future climate scenarios has been highlighted to understand potential impacts of future climate change in renewable generation on the power sector. Climate model projection has been recognized by the renewable energy community as a useful data set to analyze the impacts of future climate change on renewable resources. However, future climate projections generated from general circulation models (GCMs) contain inherent biases that need to be corrected for accurate analysis of future projections of climate variables. In addition, the coarse spatiotemporal resolution of GCMs needs to be improved for regional climate studies. In this work, we develop statistical methods to downscale future projections of global horizontal irradiance (GHI) in a computationally efficient way. Our approach builds statistical downscaling models that correct bias of climate projection of GHI and downscale the future GHI projection from daily-scale to hourly-scale. The National Solar Radiation Database (NSRDB) is used to calibrate the statistical models and validate the downscaled GHI projections across the contiguous United State (CONUS). Preliminary results show that the statistical approach efficiently downscales climate projections of GHI with a nBIAS of 3%, nMAE of 34 % and nRMSE of 46% calculated against NSRDB for CONUS. This study describes the implemented methodology and initial results as well as future research to create high-resolution climate data sets for solar energy applications.

analytical models↗
DOE OSTI2023

Simulation of Methane Oxycombustion in Supercritical Carbon Dioxide

The Allam-Fetvedt Cycle (AFC) offers the potential for electricity generation with minimal or even negative carbon emissions by using oxycombustion in supercritical carbon dioxide (sCO2). Because of the extreme high temperatures and pressures encountered in these systems, simulation of oxycombustion requires use of a complex equation of state such as the modified Soave-Redlich-Kwong (SRK) equation, coupled with equally complex correlations for transport properties. The current work simulates a model combustor using both an ideal gas equation of state and the SRK equation of state. The model combustor features a jet of CH4 mixing with and reacting with O2 in the sCO2 ambient. Two jet configurations are considered: one of pure CH4, and one of CH4 mixed with sCO2. Comparison of results shows that key output properties such as combustor temperature and flow distribution are impacted by the choice of equations of state. Inspection of simulation results shows that mixing and reaction rates, as well as the uniformity of the flow, are impacted by the choice of equation of state. These results show that even though use of a complex equation of state greatly increases the computational costs of these simulations, it is critical to accurately capturing the physics of these systems.

computational fluid dynamics↗
DOE OSTI2022

Sequential Linearization Method for Bound-Constrained Mathematical Programs with Complementarity Constraints

Here, we propose an algorithm for solving bound-constrained mathematical programs with complementarity constraints on the variables. Each iteration of the algorithm involves solving a linear program with complementarity constraints in order to obtain an estimate of the active set. The algorithm enforces descent on the objective function to promote global convergence to B-stationary points. We provide a convergence analysis and preliminary numerical results on a range of test problems. We also study the effect of fixing the active constraints in a bound-constrained quadratic program that can be solved on each iteration in order to obtain fast convergence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

On Compatible Transfer Operators in Nonsymmetric Algebraic Multigrid

The standard goal for an effective algebraic multigrid (AMG) algorithm is to develop relaxation and coarse-grid correction schemes that attenuate complementary error modes. In the nonsymmetric setting, coarse-grid correction Π will almost certainly be nonorthogonal (and divergent) in any known standard product, meaning ∥Π∥ > 1. This introduces a new consideration, that one wants coarse-grid correction to be as close to orthogonal as possible, in an appropriate norm. In addition, due to nonorthogonality, Π may actually amplify certain error modes that are in the range of interpolation. Relaxation must then not only be complementary to interpolation, but also rapidly eliminate any error amplified by the nonorthogonal correction, or the algorithm may diverge. Here this paper develops analytic formulae on how to construct “compatible” transfer operators in nonsymmetric AMG such that ∥Π∥ = 1 in some standard matrix-induced norm. Discussion is provided on different options for the norm in the nonsymmetric setting, the relation between “ideal” transfer operators in different norms, and insight into the convergence of nonsymmetric reduction-based AMG.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Fast neural Poincare maps for toroidal magnetic fields

We demonstrate how to build symplectic neural networks to approximate Hamiltonian and Poincare maps in this notebook. Two examples are given: a simple pendulum and a pertubed pendulum.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Agent-based Disease Surveillance and Transmission Model

The SARS-CoV-2 pandemic has driven a need for models that can predict transmission among populations and test the effectiveness of proposed interventions to control it such as testing, quarantining, vaccinations, and nonpharmaceutical interventions. Some questions of interest include:1. How rapidly will the virus spread if no action is taken? 2. How frequently should people be tested and quarantined if necessary? 3. Should unvaccinated persons be tested more frequently than the vaccinated? 4. If test results are delayed, how will that affect the spread? 5. How do test false negative rates affect the overall efficacy of testing programs? 6. How do constraints on testing resources impact the overall efficacy of testing programs? 7. How does the patient’s failure to recognize COVID symptoms and quarantine affect the spread? 8. What level of vaccination coverage is needed to suppress the epidemic? 9. What is the risk of a large outbreak (probability exceeding x infections)? 10. What is the cost effectiveness of interventions (dollars per avoided infection)? This report describes the structure of a discrete event simulation model that provides actionable information to address these questions. Parameter inputs and results of analyses have been reported in briefings provided to LLNL management and are not discussed here.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Highlights for DOE ASCR Applied Math Office [Slides]

An efficient Picard-based solver is proposed for a novel energy conserving particle integrator preserving all first-order guiding center drifts and correct gyroradius for large time steps in arbitrary (non-uniform) magnetic fields. This research enables the efficient deployment of the novel asymptotic preserving (AP) particle orbit integrator into modern energy-conserving, implicit particle-in-cell codes, delivering a truly multiscale simulation capability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Data Remapping Between One-Dimensional Meshes

In this report, we describe two approaches to the problem of remapping data from a source mesh (on which data is available) onto a target mesh. We consider two separate methods to solve the problem: Pointwise and Conservative remap, and determine why one is more advantageous when considering different physics applications and elements. We utilize C++ functionalities to derive our findings along with the C++ ”Chronos” library for timing measurements of our studies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Argonne Leadership Computing Facility 2024 Operational Assessment Report

This Operational Assessment Report describes how the Argonne Leadership Computing Facility (ALCF) met or exceeded every goal set by DOE for the calendar year (CY) 2024. In CY 2024, the ALCF operated Polaris, an AMD and NVIDIA-based Hewlett Packard Enterprise (HPE) Apollo 6500 Gen10+ system that provides a powerful platform for breakthrough science and prepares applications and workloads for Aurora, Argonne National Laboratory’s Intel-HPE exascale computer. Since going into production in August 2022, Polaris has supported research teams from the DOE Exascale Computing Project (ECP), which concluded in 2024, and from ALCF’s Aurora Early Science Program (ESP). Polaris delivered a total of 2555.7K node-hours to 17 Innovative and Novel Computational Impact on Theory and Experiment (INCITE) 2024 projects and 601.6K node-hours to ASCR Leadership Computing Challenge (ALCC) projects (12 of which were awarded during the 2023–2024 ALCC year and 11 of which were awarded during the 2024–2025 ALCC year), as well as providing substantial time for Director’s Discretionary (DD) projects (966.2K node-hours). As Table ES.1 shows, Polaris performed exceptionally well in terms of overall availability (97.7 percent), scheduled availability (99.6 percent), and utilization (94.7 percent; Table 2.1). In CY 2024, ALCF supported more than 2,000 users. As of March 18, 2025, ALCF’s users have published 254 papers in peer-reviewed journals and technical proceedings.

97 MATHEMATICS AND COMPUTING↗