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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2010

The development of CACTUS : a wind and marine turbine performance simulation code.

CACTUS (Code for Axial and Cross-flow TUrbine Simulation) is a turbine performance simulation code, based on a free wake vortex method, under development at Sandia National Laboratories (SNL) as part of a Department of Energy program to study marine hydrokinetic (MHK) devices. The current effort builds upon work previously done at SNL in the area of vertical axis wind turbine simulation, and aims to add models to handle generic device geometry and physical models specific to the marine environment. An overview of the current state of the project and validation effort is provided.

17 WIND ENERGY↗
DOE OSTI2010

Computational modeling of composite material fires.

Composite materials behave differently from conventional fuel sources and have the potential to smolder and burn for extended time periods. As the amount of composite materials on modern aircraft continues to increase, understanding the response of composites in fire environments becomes increasingly important. An effort is ongoing to enhance the capability to simulate composite material response in fires including the decomposition of the composite and the interaction with a fire. To adequately model composite material in a fire, two physical model development tasks are necessary; first, the decomposition model for the composite material and second, the interaction with a fire. A porous media approach for the decomposition model including a time dependent formulation with the effects of heat, mass, species, and momentum transfer of the porous solid and gas phase is being implemented in an engineering code, ARIA. ARIA is a Sandia National Laboratories multiphysics code including a range of capabilities such as incompressible Navier-Stokes equations, energy transport equations, species transport equations, non-Newtonian fluid rheology, linear elastic solid mechanics, and electro-statics. To simulate the fire, FUEGO, also a Sandia National Laboratories code, is coupled to ARIA. FUEGO represents the turbulent, buoyantly driven incompressible flow, heat transfer, mass transfer, and combustion. FUEGO and ARIA are uniquely able to solve this problem because they were designed using a common architecture (SIERRA) that enhances multiphysics coupling and both codes are capable of massively parallel calculations, enhancing performance. The decomposition reaction model is developed from small scale experimental data including thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC) in both nitrogen and air for a range of heating rates and from available data in the literature. The response of the composite material subject to a radiant heat flux boundary condition is examined to study the propagation of decomposition fronts of the epoxy and carbon fiber and their dependence on the ambient conditions such as oxygen concentration, surface flow velocity, and radiant heat flux. In addition to the computational effort, small scaled experimental efforts to attain adequate data used to validate model predictions is ongoing. The goal of this paper is to demonstrate the progress of the capability for a typical composite material and emphasize the path forward.

36 MATERIALS SCIENCE↗
DOE OSTI2025

PHOTOPRODUCTION OF np^0 BY DOUBLE-REGGE EXCHANGE

The GlueX experiment is a photoproduction experiment based at Jeferson Lab in Newport News, Virginia. A major aim of GlueX is to look for hybrid mesons, which are a quark and an anti-quark bound by an excited gluonic field that contributes to the quantum numbers. The reaction ¿p ¿ ¿e0p is of particular interest since ¿e is a potential decay mode of states with exotic quantum numbers JPC =1¿+, which are forbidden in the constituent quark model. Finding such a resonance would be a clear sign of non-quark model physics. In concert with the Joint Physics Analysis Center we have developed a model for double-Regge interactions in this channel. These non-resonant processes generate asymmetries in the distributions of decay angles, which could be falsely attributed to the interference between exotic odd partial waves and even partial waves. In previous searches for light exotics we have seen evidence for the necessity of accounting for the presence of these non-resonant productions. We present a double-Regge model for photoproduction of ¿e0 and the application of it by measuring the asymmetry of ¿e0 production in the double Regge limit, as well as a comparison of the measured results to current theoretical predictions.

Barsotti, Rebecca [Indiana Univ. Southeast, New Al↗
DOE OSTI2022

A multiphysics model of the versatile test reactor based on the MOOSE framework

The traditional modeling approach for sodium fast reactor cores relies on separate physics models, where the fuel performance, thermal–hydraulics, and neutronics calculations required to predict the core physics characteristics for nominal conditions are decoupled by relying on user-imposed boundary conditions. Here, this paper aims at evaluating the impact of multiphysics simulations for predicting the core characteristics of the Versatile Test Reactor, which is being designed as a 300-MWt sodium-cooled fast reactor. The purpose of the Versatile Test Reactor is to accelerate the testing of advanced nuclear materials in the United States. The proposed multiphysics model relies on the Griffin reactor physics code, the SAM thermal–hydraulic system code, the BISON fuel performance code, as well as generic Multiphysics Object-Oriented Simulation Environment capabilities implemented in the open-source tensor mechanics module. For k eff calculations, the introduction of a tight coupling between the neutronics, thermo-mechanical and thermal–hydraulics models induces a change of around 543 pcm in the eigenvalue, compared to the traditional standalone neutronics calculation where approximate temperature profiles are used. The multiphysics model is then employed for quantifying the impact of the thermal conductivity uncertainties on some of the key figures of merit, such as the fuel centerline temperature, assembly powers, and keff for nominal core conditions. As anticipated, uncertainties on fuel thermal conductivity mostly impact the fuel centerline temperature, and to a lesser extend the k eff .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Land Surface Emission Modeling to Support Physical Precipitation Retrievals

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization. Working Group.

Peters-Lidard, Christina D.↗
NASA NTRS2000

Diurnal Variability of the Hydrologic Cycle and Radiative Fluxes: Comparisons Between Observation and a GCM

The simulated diurnal cycle is in many ways an ideal test bed for new physical parameterizations. The purpose of this paper is to compare observations from the Tropical Rainfall Measurement Mission, the Earth Radiation Budget Experiment, the International Satellite Cloud Climatology Project, the Clouds and the Earth's Radiant Energy System Experiment, and the Anglo-Brazilian Amazonian Climate Observation Study with the diurnal variability of the Amazonian hydrologic cycle and radiative energy budget as simulated by the Colorado State University general circulation model, and to evaluate improvements and deficiencies of the model physics. The model uses a prognostic cumulus kinetic energy (CKE) to relax the quasi-equilibrium closure of the Arakawa-Schubert cumulus parameterization. A parameter, alpha, is used to relate the CKE to the cumulus mass flux. This parameter is expected to vary with cloud depth, mean shear, and the level of convective activity, but up to now a single constant value for all cloud types has been used. The results of the present study show clearly that this approach cannot yield realistic simulations of both the diurnal cycle and the monthly mean climate state. Improved results are obtained using a version of the model in which alpha is permitted to vary with cloud depth.

Lin, Xin↗
DOE OSTI2024

NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.

42 ENGINEERING↗
DOE OSTI2014

RELAP-7 Numerical Stabilization: Entropy Viscosity Method

The RELAP-7 code is the next generation nuclear reactor system safety analysis code being developed at the Idaho National Laboratory (INL). The code is based on the INL's modern scientific software development framework, MOOSE (Multi-Physics Object Oriented Simulation Environment). The overall design goal of RELAP-7 is to take advantage of the previous thirty years of advancements in computer architecture, software design, numerical integration methods, and physical models. The end result will be a reactor systems analysis capability that retains and improves upon RELAP5's capability and extends the analysis capability for all reactor system simulation scenarios. RELAP-7 utilizes a single phase and a novel seven-equation two-phase flow models as described in the RELAP-7 Theory Manual (INL/EXT-14-31366). The basic equation systems are hyperbolic, which generally require some type of stabilization (or artificial viscosity) to capture nonlinear discontinuities and to suppress advection-caused oscillations. This report documents one of the available options for this stabilization in RELAP-7 -- a new and novel approach known as the entropy viscosity method. Because the code is an ongoing development effort in which the physical sub models, numerics, and coding are evolving, so too must the specific details of the entropy viscosity stabilization method. Here the fundamentals of the method in their current state are presented.

42 ENGINEERING↗
DOE OSTI2013

Scalar dark matter models with significant internal bremsstrahlung

There has been interest recently on particle physics models that may give rise to sharp gamma ray spectral features from dark matter annihilation. Because dark matter is supposed to be electrically neutral, it is challenging to build weakly interacting massive particle models that may accommodate both a large cross section into gamma rays at, say, the Galactic center, and the right dark matter abundance. In this work, we consider the gamma ray signatures of a class of scalar dark matter models that interact with Standard Model dominantly through heavy vector-like fermions (the vector-like portal). We focus on a real scalar singlet S annihilating into lepton-antilepton pairs. Because this two-body final-state annihilation channel is d-wave suppressed in the chiral limit, σ{sub ff-bar}v∝v{sup 4}, we show that virtual internal bremsstrahlung emission of a gamma ray gives a large correction, both today and at the time of freeze-out. For the sake of comparison, we confront this scenario to the familiar case of a Majorana singlet annihilating into light lepton-antilepton pairs, and show that the virtual internal bremsstrahlung signal may be enhanced by a factor of (up to) two orders of magnitude. We discuss the scope and possible generalizations of the model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Dynamic energy system modeling using hybrid physics-based and machine learning encoder–decoder models

Three model configurations are presented for multi-step time series predictions of the heat absorbed by the water and steam in a thermal power plant. The models predict over horizons of 2, 4, and 6 steps into the future, where each step is a 5-minute increment. The evaluated models are a pure machine learning model, a novel hybrid machine learning and physics-based model, and the hybrid model with an incomplete dataset. The hybrid model deconstructs the machine learning into individual boiler heat absorption units: economizer, water wall, superheater, and reheater. Each configuration uses a gated recurrent unit (GRU) or a GRU-based encoder–decoder as the deep learning architecture. Mean squared error is used to evaluate the models compared to target values. The encoder–decoder architecture is over 11% more accurate than the GRU only models. The hybrid model with the incomplete dataset highlights the importance of the manipulated variables to the system. The hybrid model, compared to the pure machine learning model, is over 10% more accurate on average over 20 iterations of each model. Automatic differentiation is applied to the hybrid model to perform a local sensitivity analysis to identify the most impactful of the 72 manipulated variables on the heat absorbed in the boiler. The models and sensitivity analyses are used in a discussion about optimizing the thermal power plant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Closure models for the feedback of energetic particles on plasma turbulence

Energetic particles interact with the plasma surrounding them, resonating with certain types of plasma waves to stabilize them while destabilizing others, and changing the character of the background turbulence in ways that have not been fully quantified or understood. Interaction with the turbulent background plasma is key to the acceleration of many types of energetic particles including high-energy cosmic rays, solar energetic particles, and pick-up ions. The acceleration of particles is a process that would ideally be described by a kinetic model, a type of model that follows a probability distribution function (PDF) for all particles in 7-dimensional (x, y, z, v x , v y , v z , t) space. Because of the high dimensionality of a kinetic model, simulations that solve kinetic equations use the largest computational resources currently available, and are yet unable to simulate a realistic number of particles, reach the large scales necessary for astrophysical problems, and use high-precision numerical methods. Two available alternatives to kinetic plasma models have been explored for this problem, with limited success. One is a multi-fluid model produced by a cumulant discarding closure, which evolves coupled equations for the velocity, magnetic field, and internal energy for both the background plasma and the fluid of energetic particles. However, simulations that solve multi-fluid magnetohydrodynamic (MHD) equations are able to include the interaction with energetic particles only in crude ways, typically as an add-on pressure term. The second alternative is to use a hybrid method to couple a fluid description of the background plasma to a kinetic model or a Fokker–Planck model for the energetic particles. These methods are hampered by the physical modeling of the coupling. In this work, we develop a new model, which follows the PDF for all particles; this can be viewed as a step toward physical realism above a multi-fluid MHD model, while also being more computationally efficient than a kinetic model. The equations we develop model both the background plasma and the energetic particles self-consistently. Over the last decade, similar PDF methods have been developed to a high level of sophistication to model reactive flows and turbulent combustion for engineering applications. For treatment of the feedback of the energetic particles on a background plasma, a PDF closure approach should evaluate the mean characteristics, including the density, with better statistical quality than will particle-sampling procedures.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

Preliminary Statistics from the NASA Alphasat Beacon Receiver in Milan, Italy

NASA Glenn Research Center (GRC) and the Politecnico di Milano (POLIMI) have initiated a joint propagation campaign within the framework of the Alphasat propagation experiment to characterize rain attenuation, scintillation, and gaseous absorption effects of the atmosphere in the 40 GHz band. NASA GRC has developed and installed a KQ-band (20-40 GHz) beacon receiver at the POLIMI campus in Milan, Italy, which receives the 20-40 GHz signals broadcast from the Alphasat Aldo Paraboni TDP5 beacon payload. The primary goal of these measurements is to develop a physical model to improve predictions of communications systems performance within the Q-band. Herein, we provide an overview of the design and data calibration procedure, and present 6 months of preliminary statistics of the NASA propagation terminal, which has been installed and operating in Milan since May 2014. The Q-band receiver has demonstrated a dynamic range of 40 dB at an 8-Hz sampling rate. A weather station with an optical disdrometer is also installed to characterize rain drop size distribution for correlation with physical based models

Radio Transmission↗
NASA NTRS2015

Preliminary Statistics from the NASA Alphasat Beacon Receiver in Milan, Italy

NASA Glenn Research Center (GRC) and the Politecnico di Milano (POLIMI) have initiated a joint propagation campaign within the framework of the Alphasat propagation experiment to characterize rain attenuation, scintillation, and gaseous absorption effects of the atmosphere in the 40 gigahertz band. NASA GRC has developed and installed a K/Q-band (20/40 gigahertz) beacon receiver at the POLIMI campus in Milan, Italy, which receives the 20/40 gigahertz signals broadcast from the Alphasat Aldo Paraboni TDP no. 5 beacon payload. The primary goal of these measurements is to develop a physical model to improve predictions of communications systems performance within the Q-band. Herein, we provide an overview of the design and data calibration procedure, and present 6 months of preliminary statistics of the NASA propagation terminal, which has been installed and operating in Milan since May 2014. The Q-band receiver has demonstrated a dynamic range of 40 decibels at an 8-hertz sampling rate. A weather station with an optical disdrometer is also installed to characterize rain drop size distribution for correlation with physical based models.

RF propagation↗
DOE OSTI2021

Learning-based framework for sensor fault-tolerant building HVAC control with model-assisted learning

As people spend up to 87% of their time indoors, intelligent Heating, Ventilation, and Air Conditioning (HVAC) systems in buildings are essential for maintaining occupant comfort and reducing energy consumption. These HVAC systems in smart buildings rely 'on real-time sensor readings, which in practice often suffer from various faults and could also be vulnerable to malicious attacks. Such faulty sensor inputs may lead to the violation of indoor environment requirements (e.g., temperature, humidity, etc.) and the increase of energy consumption. While many model-based approaches have been proposed in the literature for building HVAC control, it is costly to develop accurate physical models for ensuring their performance and even more challenging to address the impact of sensor faults. In this work, we present a novel learning-based framework for sensor fault-tolerant HVAC control, which includes three deep learning based components for 1) generating temperature proposals with the consideration of possible sensor faults, 2) selecting one of the proposals based on the assessment of their accuracy, and 3) applying reinforcement learning with the selected temperature proposal. Moreover, to address the challenge of training data insufficiency in building-related tasks, we propose a model-assisted learning method leveraging an abstract model of building physical dynamics. Through extensive experiments, we demonstrate that the proposed fault-tolerant HVAC control framework can significantly reduce building temperature violations under a variety of sensor fault patterns while maintaining energy efficiency.

Xu, Shichao↗
DOE OSTI2020

Enabling Numerical Modeling of Extreme-Intensity Laser Produced Dense Plasma

We have developed physics models of extreme intensity laser-matter interaction, x-ray and γ-ray emissions, and x-ray absorption (e.g. photoionization and Auger atomic processes). The atomic processes are solved self-consistently with radiation transport, which is coupled to our collisional particle-in-cell code, PICLS. Together with a significantly improved photoionization model our capability of simulation has been extended to account for detailed atomic and radiation physics during intense optical laser-matter interaction and also the XFEL-matter interaction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2004

Update on the Status of the FLUKA Monte Carlo Transport Code

The FLUKA Monte Carlo transport code is a well-known simulation tool in High Energy Physics. FLUKA is a dynamic tool in the sense that it is being continually updated and improved by the authors. Here we review the progresses achieved in the last year on the physics models. From the point of view of hadronic physics, most of the effort is still in the field of nucleus--nucleus interactions. The currently available version of FLUKA already includes the internal capability to simulate inelastic nuclear interactions beginning with lab kinetic energies of 100 MeV/A up the the highest accessible energies by means of the DPMJET-II.5 event generator to handle the interactions for greater than 5 GeV/A and rQMD for energies below that. The new developments concern, at high energy, the embedding of the DPMJET-III generator, which represent a major change with respect to the DPMJET-II structure. This will also allow to achieve a better consistency between the nucleus-nucleus section with the original FLUKA model for hadron-nucleus collisions. Work is also in progress to implement a third event generator model based on the Master Boltzmann Equation approach, in order to extend the energy capability from 100 MeV/A down to the threshold for these reactions. In addition to these extended physics capabilities, structural changes to the programs input and scoring capabilities are continually being upgraded. In particular we want to mention the upgrades in the geometry packages, now capable of reaching higher levels of abstraction. Work is also proceeding to provide direct import into ROOT of the FLUKA output files for analysis and to deploy a user-friendly GUI input interface.

Pinsky, L.↗
NASA NTRS2011

CEDAR Electrodynamics Thermosphere Ionosphere (ETI) Challenge for Systematic Assessment of Ionosphere/Thermosphere Models: NmF2, hmF2, and Vertical Drift Using Ground-Based Observations

Objective quantification of model performance based on metrics helps us evaluate the current state of space physics modeling capability, address differences among various modeling approaches, and track model improvements over time. The Coupling, Energetics, and Dynamics of Atmospheric Regions (CEDAR) Electrodynamics Thermosphere Ionosphere (ETI) Challenge was initiated in 2009 to assess accuracy of various ionosphere/thermosphere models in reproducing ionosphere and thermosphere parameters. A total of nine events and five physical parameters were selected to compare between model outputs and observations. The nine events included two strong and one moderate geomagnetic storm events from GEM Challenge events and three moderate storms and three quiet periods from the first half of the International Polar Year (IPY) campaign, which lasted for 2 years, from March 2007 to March 2009. The five physical parameters selected were NmF2 and hmF2 from ISRs and LEO satellites such as CHAMP and COSMIC, vertical drifts at Jicamarca, and electron and neutral densities along the track of the CHAMP satellite. For this study, four different metrics and up to 10 models were used. In this paper, we focus on preliminary results of the study using ground-based measurements, which include NmF2 and hmF2 from Incoherent Scatter Radars (ISRs), and vertical drifts at Jicamarca. The results show that the model performance strongly depends on the type of metrics used, and thus no model is ranked top for all used metrics. The analysis further indicates that performance of the model also varies with latitude and geomagnetic activity level.

Shim, J. S.↗
DOE OSTI2017

Validating nuclear models: electron data to interpret neutrino physics

Nuclear models in Monte Carlo event generators are crucial for interpreting neutrino scattering experiments, but are dicult to verify using only neutrino data due to incomplete data for some energy ranges. In particular, we seek to constrain the GENIE neutrino event generator's models. To overcome the uncertainties inherent to neutrino experiments, it is useful to take advantage of more controllable electron scattering experiments to evaluate current models and place constraints on future models. In this preliminary study on the feasibility of this strategy, we evaluate variables sensitive to the choice of nuclear model for the GENIE default model and data from the Jeerson Labs CLAS experiment. We nd some disagreement between them, likely explained by the the use of a dated default and background known to be remaining in the CLAS data that is not accounted for.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗