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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

SpF: Enabling Petascale Performance for Pseudospectral Dynamo Models

Pseudospectral (PS) methods possess a number of characteristics (e.g., efficiency, accuracy, natural boundary conditions) that are extremely desirable for dynamo models. Unfortunately, dynamo models based upon PS methods face a number of daunting challenges, which include exposing additional parallelism, leveraging hardware accelerators, exploiting hybrid parallelism, and improving the scalability of global memory transposes. Although these issues are a concern for most models, solutions for PS methods tend to require far more pervasive changes to underlying data and control structures. Further, improvements in performance in one model are difficult to transfer to other models, resulting in significant duplication of effort across the research community.We have developed an extensible software framework for pseudospectral methods called SpF that is intended to enable extreme scalability and optimal performance. High-level abstractions provided by SpF unburden applications of the responsibility of managing domain decomposition and load balance while reducing the changes in code required to adapt to new computing architectures. The key design concept in SpF is that each phase of the numerical calculation is partitioned into disjoint numerical kernels that can be performed entirely in-processor. The granularity of domain-decomposition provided by SpF is only constrained by the data-locality requirements of these kernels. SpF builds on top of optimized vendor libraries for common numerical operations such as transforms, matrix solvers, etc., but can also be configured to use open source alternatives for portability. SpF includes several alternative schemes for global data redistribution and is expected to serve as an ideal testbed for further research into optimal approaches for different network architectures.In this presentation, we will describe the basic architecture of SpF as well as preliminary performance data and experience with adapting legacy dynamo codes. We will conclude with a discussion of planned extensions to SpF that will provide pseudospectral applications with additional flexibility with regard to time integration, linear solvers, and discretization in the radial direction.

Pseudospectral (PS)↗
NASA NTRS1991

Low-Speed Wind-Tunnel Test of an Unpowered High-Speed Stoppable Rotor Concept in Fixed-Wing Mode

An experimental investigation of the M85, a High Speed Rotor Concept, was conducted at the NASA Langley 14 x 22 foot Subsonic Tunnel, assisted by NASA-Ames. An unpowered 1/5 scale model of the XH-59A helicopter fuselage with a large circular hub fairing, two rotor blades, and a shaft fairing was used as a baseline configuration. The M85 is a rotor wing hybrid aircraft design, and the model was tested with the rotor blade in the fixed wing mode. Assessments were made of the aerodynamic characteristics of various model rotor configurations. Variation in configurations were produced by changing the rotor blade sweep angle and the blade chord length. The most favorable M85 configuration tested included wide chord blades at 0 deg sweep, and it attained a system lift to drag ratio of 8.4.

Lance, Michael B.↗
DOE OSTI2021

OpenMC

OpenMC is an open source, community-developed framework for performing Monte Carlo particle transport calculations.It is capable of simulating neutron and photon transport below ~50 MeV and also includes a model for bremsstrahlung production of photons by electrons/positrons. Fixed source, k-eigenvalue, and subcritical multiplication problems can be solved. Problem geometries can be modeled either using constructive solid geometry or a CAD representation. A flexible and efficient tally system enables a wide variety of physical quantities to be tallied and analyzed. OpenMC can run in parallel using a hybrid MPI and OpenMP programming model and has been extensively tested on leadership class supercomputers. A built-in Bateman equation solver enables the modeling of material composition changes due to irradiation. One of the unique features of OpenMC is its rich, extensible Python and C/C++ programming interfaces that enable programming pre- and post-processing, multigroup cross section generation, workflow automation, multiphysics coupling, and the visualization of geometry and tally results. In addition to the core Monte Carlo transport solver and associated APIs, OpenMC includes a Python-based nuclear data interface that enables power users to inspect, modify,and perform various types of nuclear data processing on ENDF, ACE, and OpenMC¿s native HDF5 files

ROMANO, PaulK.↗
NASA NTRS1995

Prediction of the interplanetary magnetic field strength

A new model of the coronal and interplanetary magnetic field can predict both the interplanetary magnetic field strength and its polarity from measurements of the photospheric magnetic field. The model includes the effects of the large-scale horizontal electric currents flowing in the inner corona, of the warped heliospheric current sheet in the upper corona, and of volume currents flowing in the region where the solar wind plasma totally controls the magnetic field. The model matches the MHD solution for a simple dipole test case better than earlier source surface and current sheet models. The strength and polarity of the radial interplanetary magnetic field component predicted for quiet time samples in each year from 1977 to 1986 agree with observations made near the Earth's orbit better than the hybrid MHD-source surface model (Wang and Sheeley, 1988). The results raise the question of whether coronal holes are the only solar source of the interplantary magnetic field in the solar wind. If some interplanetary flux originates outside coronal holes, the model can match the observed field using the accepted 1.8 saturation correction factor for lambda 5250 A magnetograph observations. Requiring open flux to come exclusively from coronal holes requires and additional factor of two.

Zhao, Xuepu↗
DOE OSTI2022

Hybrid AI-ML and FE-based Digital Twin Predictive Modeling Framework for a PWR Coolant System Components: Updates on Multi-Time-Series-3D-Location Dependent Usages Factor Prediction

The long-term operation (LTO) of nuclear power plants (NPP) beyond their original design life of 40 years can lead to more material damage associated with cyclic fatigue under thermal-mechanical loading cycles and associated long-term exposure of reactor material to the deleterious reactor-coolant environments. However, under this LTO condition, the reactor components can still safely operate but may require more frequent Nondestructive Evaluation (NDE) of reactor components. Requiring frequent NDE inspections may lead to frequent NPP shutdowns which can lead to power outages and additional NDE inspection cost-related economic loss. The economic loss can be minimized by reducing uncertainty in life estimation of safety-critical pressure boundary components and by implementing a more digital approach such as using upcoming digital-twin (DT) technology for predicting the structural states (e.g., time and location dependent inside/outside thickness temperature, stress, strain, plastic deformation, etc.) and associated fatigue life of a component in real time. The DT framework is based on limited experimental data, Artificial-intelligence (AI)-Machine-Learning (ML) and multiphysics-computationalmechanics such as finite element- (FE) based models. Given the real-time thermal-hydraulic process measurements from several existing plant sensors, the overall goal of the DT framework is to predict the cumulative usages factors or equivalent fatigue lives in real time and at any random 3D location of the components. This includes inaccessible locations such as inside the thickness or location of a component. This prediction can be at thousands to millions of 3D point clouds or locations like conventional FE-based models, but without running an FE model in real time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Recent and Planned Improvements to the System Advisor Model (SAM)

This talk will focus on recent and planned modeling improvements to the NREL System Advisor ModelTM (SAM), with recently released features including PV hourly clipping correction, expanded geographic scope of SAM's NSRDB interface to Europe and Africa, and additional options for hybrids. Upcoming improvements include a case comparison feature, improved visualizations, and extensions of PVWatts for battery modeling and utility rate calculations.

batteries↗
NASA NTRS1990

A graphical language for reliability model generation

A graphical interface capability of the hybrid automated reliability predictor (HARP) is described. The graphics-oriented (GO) module provides the user with a graphical language for modeling system failure modes through the selection of various fault tree gates, including sequence dependency gates, or by a Markov chain. With this graphical input language, a fault tree becomes a convenient notation for describing a system. In accounting for any sequence dependencies, HARP converts the fault-tree notation to a complex stochastic process that is reduced to a Markov chain which it can then solve for system reliability. The graphics capability is available for use on an IBM-compatible PC, a Sun, and a VAX workstation. The GO module is written in the C programming language and uses the Graphical Kernel System (GKS) standard for graphics implementation. The PC, VAX, and Sun versions of the HARP GO module are currently in beta-testing.

Howell, Sandra V.↗
NASA NTRS2015

Solid Rocket Motor Combustion Instability Modeling in COMSOL Multiphysics

Combustion instability modeling of Solid Rocket Motors (SRM) remains a topic of active research. Many rockets display violent fluctuations in pressure, velocity, and temperature originating from the complex interactions between the combustion process, acoustics, and steady-state gas dynamics. Recent advances in defining the energy transport of disturbances within steady flow-fields have been applied by combustion stability modelers to improve the analysis framework [1, 2, 3]. Employing this more accurate global energy balance requires a higher fidelity model of the SRM flow-field and acoustic mode shapes. The current industry standard analysis tool utilizes a one dimensional analysis of the time dependent fluid dynamics along with a quasi-three dimensional propellant grain regression model to determine the SRM ballistics. The code then couples with another application that calculates the eigenvalues of the one dimensional homogenous wave equation. The mean flow parameters and acoustic normal modes are coupled to evaluate the stability theory developed and popularized by Culick [4, 5]. The assumption of a linear, non-dissipative wave in a quiescent fluid remains valid while acoustic amplitudes are small and local gas velocities stay below Mach 0.2. The current study employs the COMSOL multiphysics finite element framework to model the steady flow-field parameters and acoustic normal modes of a generic SRM. The study requires one way coupling of the CFD High Mach Number Flow (HMNF) and mathematics module. The HMNF module evaluates the gas flow inside of a SRM using St. Robert's law to model the solid propellant burn rate, no slip boundary conditions, and the hybrid outflow condition. Results from the HMNF model are verified by comparing the pertinent ballistics parameters with the industry standard code outputs (i.e. pressure drop, thrust, ect.). These results are then used by the coefficient form of the mathematics module to determine the complex eigenvalues of the Acoustic Velocity Potential Equation (AVPE). The mathematics model is truncated at the nozzle sonic line, where a zero flux boundary condition is self-satisfying. The remaining boundaries are modeled with a zero flux boundary condition, assuming zero acoustic absorption on all surfaces. The results of the steady-state CFD and AVPE analyses are used to calculate the linear acoustic growth rate as is defined by Flandro and Jacob [2, 3]. In order to verify the process implemented within COMSOL we first employ the Culick theory and compare the results with the industry standard. After the process is verified, the Flandro/Jacob energy balance theory is employed and results displayed.

Fischbach, Sean R.↗
NASA NTRS2004

Improved Ionospheric Electrodynamic Models and Application to Calculating Joule Heating Rates

Improved techniques have been developed for empirical modeling of the high-latitude electric potentials and magnetic field aligned currents (FAC) as a function of the solar wind parameters. The FAC model is constructed using scalar magnetic Euler potentials, and functions as a twin to the electric potential model. The improved models have more accurate field values as well as more accurate boundary locations. Non-linear saturation effects in the solar wind-magnetosphere coupling are also better reproduced. The models are constructed using a hybrid technique, which has spherical harmonic functions only within a small area at the pole. At lower latitudes the potentials are constructed from multiple Fourier series functions of longitude, at discrete latitudinal steps. It is shown that the two models can be used together in order to calculate the total Poynting flux and Joule heating in the ionosphere. An additional model of the ionospheric conductivity is not required in order to obtain the ionospheric currents and Joule heating, as the conductivity variations as a function of the solar inclination are implicitly contained within the FAC model's data. The models outputs are shown for various input conditions, as well as compared with satellite measurements. The calculations of the total Joule heating are compared with results obtained by the inversion of ground-based magnetometer measurements. Like their predecessors, these empirical models should continue to be a useful research and forecast tools.

Weimer, D. R.↗
NASA NTRS1993

A new interface element for connecting independently modeled substructures

A new interface element based on the hybrid variational formulation is presented and demonstrated. The element provides a means of connecting independently modeled substructures whose nodes along the common boundary need not be coincident. The interface element extends previous work to include connecting an arbitrary number of substructures, the use of closed and generally curved interfaces, and the use of multiple, possibly nested, interfaces. Several applications of the element are presented and aspects of the implementation are discussed.

Ransom, Jonathan B.↗
DOE OSTI2023

Hierarchical Flexibility Offering Strategy for Integrated Hybrid Resources in Real-time Energy Markets

This paper proposes a hierarchical model for determining the energy flexibility offering strategy of integrated hybrid resources (IHRs) in power distribution systems to participate in real-time energy markets. The proposed model utilizes the scalability, fast response time, and uncertainty observation of deep reinforcement learning (DRL) to overcome the scalability issue of operating numerous flexible resources and deliverability of energy flexibility to the real-time markets in the presence of the network constraints. To that end, the power distribution system is divided into multiple IHRs, where different types of flexible loads, energy storage systems, and solar plants with controllable inverters are operated through local IHR controllers, trained by deep deterministic policy gradient (DDPG) algorithm. Active power request and reactive power capacity of IHRs are then transmitted to a central flexibility controller, where a quadratic optimization model ensures the deliverability of the energy flexibility to the real-time energy market by satisfying the distribution network constraints. The proposed model is implemented on the 123-bus test power distribution system, demonstrating the capability of DRL-based hierarchical model for scalable operation of IHRs in order to offer deliverable energy flexibility to the real-time energy market.

Majidi, Majid↗
NASA NTRS2014

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

GEOS-5↗
DOE OSTI2025

Hybrid Powered Command Trailers Cost-Benefit Analysis Tool: User Guide and Examples

U.S. Forest Service (USFS) wildfire base camps use portable power for electrical needs, including yurts and trailers from which logistics staff work during the incident. These yurts and trailers are conventionally powered by portable diesel generators. Hybrid portable power systems consisting of a combination of solar photovoltaics (PV), battery energy storage systems (BESS), and/or backup diesel generators have been used in recent years and were piloted by the National Technology and Development Program (NTDP) on incidents in fall 2024 as part of NTDP's Portable Power Project. As part of that project, this work included the development of two Excel-based tools and two reports explaining the tools. The first tool, the Incident Energy Systems Model, is an Excel-based tool that models the power output of hybrid portable power systems powering yurts and/or trailers at fire camps over a typical day. The associated report (published separately) outlines a user guide for the model and walks through two scenarios. The two scenarios are 1) trailers powered by rooftop solar PV, batteries, and a back-up diesel generator, and 2) trailers powered by ground mount solar PV, batteries, and a back-up diesel generator. The second tool is a high-level cost-benefit analysis of the same two types of portable power systems, and is location independent.

14 SOLAR ENERGY↗
NASA NTRS1997

Physics of Boundaries and their Interactions in Space Plasmas

This report describes the work done by SciberNet, Inc. during the month of October. We are working on the further refinement of the model used in our large-scale hybrid simulations of the magnetopause. Specifically, we are experimenting with several ways of modeling the effects of cold magnetospheric ions into our simulations. In addition, we are preparing two presentations for the upcoming Fall AGU highlighting the results of these simulations. We have also made progress in our development of a new kinetic linear code which we are using to study the linear properties of the Kelvin-Helmholtz instability at the magnetopause. We have extended the code from the electrostatic limit to the fully electromagnetic regime and are currently in the process of debugging and testing the code. Finally, we have made several test runs with our 2-D hybrid code for the magnetopause. The inflow-outflow boundary conditions are working properly. However, there are issues related to the setup and evolution of the original equilibrium that we are still trying to resolve. Finally, we are preparing several presentations for the upcoming Fall AGU.

Omidi, Nojan↗
NASA NTRS2015

A Vertically Flow-Following, Icosahedral Grid Model for Medium-Range and Seasonal Prediction. Part 1: Model Description

A hydrostatic global weather prediction model based on an icosahedral horizontal grid and a hybrid terrain following/ isentropic vertical coordinate is described. The model is an extension to three spatial dimensions of a previously developed, icosahedral, shallow-water model featuring user-selectable horizontal resolution and employing indirect addressing techniques. The vertical grid is adaptive to maximize the portion of the atmosphere mapped into the isentropic coordinate subdomain. The model, best described as a stacked shallow-water model, is being tested extensively on real-time medium-range forecasts to ready it for possible inclusion in operational multimodel ensembles for medium-range to seasonal prediction.

mathematical models↗
DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗