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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Radial oscillations of viscous neutron stars: Zero diffusion case

In this article, the spectrum of radial oscillations of neutron stars is systematically studied within two frameworks of viscous relativistic hydrodynamics: the relativistic Navier-Stokes and Israel-Stewart theories. A correspondence is established between the discrete stellar eigenmodes and the continuous dispersion relation of perturbations around a homogeneous fluid, providing a basis for interpreting our numerical results. We analyze the Newtonian limit and assess the impact of relativistic corrections, such as the gravitational redshifting of microscopic relaxation timescales. We show that bulk viscosity can significantly affect the behavior of both hydrodynamic and nonhydrodynamic fundamental modes, and that, depending on the magnitude of the viscous effects, it is the nonhydrodynamic mode that becomes unstable beyond the turning point in a sequence of equilibrium configurations. These results provide a useful step toward systematic studies of neutron star quasinormal modes in the presence of viscosity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

1-D coupled surface flow and transport equations revisited via the physics-informed neural network approach

The de Saint-Venant equation (SVE) and advection–diffusion equation (ADE) are commonly employed to solve solute transport problems in surface water. In this work, we propose a mesh-free method based on the physics-informed neural network (PINN) to solve the one dimensional (1-D) SVE, ADE, and the coupled SVE and ADE (SVE-ADE) under various initial and boundary conditions. The PINN model extends the architecture of deep neural networks (DNNs) with implementation of loss function, which are additionally subject to constraints imposed by the physical laws of SVE and ADE, along with their initial and boundary conditions. In such a manner, PINNs can be quickly steered to the true solution while obeying the physical laws. The results of PINN model are compared with the analytical and/or numerical solutions under various conditions to investigate its accuracy and efficiency in solving the SVE, ADE, and SVE-ADE. Our results indicate PINN can accurately simulate the shock wave morphology and avoid numerical dissipation in unsteady flow condition. The PINN method outweighed traditional numerical methods in several aspects, including its ability to function with small amounts of data, no grid discretization, and random selection of sampling points, etc. Additionally, the PINN method is also suitable for solving inverse problems with sparse and noisy data. With 1% noise and 2000 initial and boundary condition points (N u ), the errors of the estimated flow rate (v) and diffusion coefficient (D) are 0.003% and 0.105%, respectively, which indicate the accuracy and robustness of the proposed method. Finally, our results indicate the capability and robustness of the proposed PINN methodology for solving multi-physics problems, irrespective of the presence of sparse and noisy data in the training dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A fractional model for anomalous diffusion with increased variability: Analysis, algorithms and applications to interface problems

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. Here, we introduce a new fractional operator characterized by a doubly-variable fractional order and possibly truncated interactions. Under certain conditions on the model parameters and on the regularity of the fractional order we show that the corresponding Poisson problem is well-posed. Additionally, we introduce a finite element discretization and describe an efficient implementation of the finite-element matrix assembly in the case of piecewise constant fractional order. Through several numerical tests, we illustrate the improved descriptive power of this new operator across media interfaces. Furthermore, we present one-dimensional and two-dimensional h-convergence results that show that the variable-order model has the same convergence behavior as the constant-order model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Models of primary runaway electron distribution in the runaway vortex regime

Generation of runaway electrons (RE) beams can possibly induce the most deleterious effect of tokamak disruptions. A number of recent numerical calculations have confirmed the formation of a RE bump in their energy distribution by taking into account Synchrontron radiational damping force due to RE’s gyromotions. Here, we present a detailed examination on how the bump location changes at different pitch-angle and the characteristics of the RE pitch-angle distribution. Although REs moving along the magnetic field are preferably accelerated and then populate the phase-space of larger pitch-angle mainly through diffusions, an off-axis peak can still form due to the presence of the vortex structure which causes accumulation of REs at low pitch-angle. A simplified Fokker- Planck model and its semi-analytical solutions based on local expansions around the O point is used to illustrate the characteristics of RE distribution around the O point of the runaway vortex in phase-space. The calculated energy location of the O point together with the local energy and pitch-angle distributions agree with the full numerical solution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Performance prediction of electrohydrodynamic thrusters by the perturbation method

In this paper, we present a novel method for analyzing electrohydrodynamic (EHD) thrusters. The method is based on a perturbation technique applied to a set of drift-diffusion equations, similar to the one introduced in our previous study on estimating breakdown voltage. The thrust-to-current ratio is generalized to represent the performance of EHD thrusters. We have compared the thrust-to-current ratio obtained theoretically with that obtained from the proposed method under atmospheric air conditions, and we have obtained good quantitative agreement. Also, we have conducted a numerical simulation in more complex thruster geometries, such as the dual-stage thruster developed by Masuyama and Barrett [Proc. R. Soc. A 469, 20120623 (2013)]. We quantitatively clarify the fact that if the magnitude of a third electrode voltage is low, the effective gap distance shortens, whereas if the magnitude of the third electrode voltage is sufficiently high, the effective gap distance lengthens.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Current-Assisted Diffusion Bonding of Extruded Ti-22Al-25Nb Alloy by Spark Plasma Sintering: Interfacial Microstructure and Mechanical Properties

Spark plasma sintering (SPS) technology was used to current-assisted bond extruded Ti-22Al-25Nb alloy. The effects of bonding temperature (920-980 °C) and bonding time (10-30 min) on the microstructure evolution and shear strength of this alloy were investigated systematically. The temperature distribution in the specimen during the current-assisted bonding process was also analyzed by numerical simulation. It is noted that the highest temperature was obtained at the bonding interface. As the bonding temperature and bonding time increased, the voids in the interface shrank increasingly until they vanished. A complete metallurgical bonding interface could be produced at 960 °C/20 min/10 MPa, exhibiting the highest shear strength of 269.3 MPa. In addition, the shear strength of the bonded specimen depended on its interfacial microstructure. With increased bonding temperature, the fracture mode transformed from the intergranular fracture at the bonding interface to the cleavage fracture in the substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Role of Interfacial Thermal Resistance in Li-Ion Battery Thermal Management: Preprint

Temperature critically affects the performance, life and safety of lithium-ion batteries. Therefore, it is essential to understand heat generation and dissipation within individual battery cells and battery packs to plan a proper thermal management strategy. One of the key challenges is that interfacial heat transfer of a battery unit is difficult to quantify. The steady-state absolute method and the transient laser-flash-diffusivity method were employed to measure heat conductivities of battery layer stacks and individual battery layer separately. Results show flash diffusivity method gives higher thermal conductivity at both cross-plane and in-plane directions. The difference is primarily caused by interfacial thermal resistance so that it can be estimated by steady-state and transient measurements. To investigate the effects of interfacial thermal transport beyond individual cell level, a multiphysics battery model is used. The model is built upon a multi-scale multi-domain modeling framework for battery packs that accounts for the interplay across multiple physical phenomena. Benefits of a battery module using thermal management materials are quantified through numerical experiments. During a thermal runaway event, it is found interfacial thermal resistance can mitigate thermal runaway in a battery module by significantly reducing heat transfer between cells.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Water vapor oxidation of SiC layer in surrogate TRISO fuel particles

Under accidental conditions for high temperature gas-cooled reactors (HTGR), the SiC layer in tri-structural-isotropic (TRISO) fuel particles can be exposed to water vapor. In this study, oxidation behaviors of surrogate TRISO fuel particles were investigated in a He-20 vol% water vapor mixed atmosphere at temperatures up to 1600 °C. The growth of the crystalline oxide passivation layer with cracks and pores followed a parabolic law with time, where the maximum was 2.3 μm at 1600 °C. The oxide layer and the SiC surface under the oxide became flattened with increasing temperature, as a function of the silica viscosity and the diffusion path of water vapor. Volatilization of the oxide layer was analyzed using a mechanistic model that an inert gas in oxidizing atmospheres could influence the magnitude of volatilization. The fracture load and strength of the oxidized and thinned SiC layer were numerically estimated to decrease from 2.27 to 1.69 N and from 317 to 299 MPa, respectively, with the SiC thickness decrease from 35 to 32 μm. This prediction indicates that the oxidized SiC layer should retain fission products. Additionally, the mechanical integrity of each layer in the TRISO fuel particle after oxidation was evaluated. The results in this work provide important data for the safety analysis of accidental scenarios in HTGRs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Geologic stress modulates fluid mixing at fracture intersections

Fracture intersections are critical links that enable flow and transport in subsurface fracture networks, and their behavior strongly influences fluid mixing in a network. Although all subsurface fractures are subjected to geological stress, we lack a fundamental understanding of how fracture intersection geometry evolves under stress and how these changes influence fluid mixing. Here, we combine 3D printing, 3D X-ray tomographic imaging, and 3D pore-scale numerical simulations to reveal stress-induced changes in intersection geometry and their impact on mixing. Mixing is found to be strongly affected by partial closure of an intersection under stress. As an intersection closes, the void area for fluid flow and diffusion decreases leading to substantial deviations between conventional mixing models and full pore-scale modeling. To address this, we propose a modified mixing model that accounts for intersection deformation, which is essential for accurate modeling of solute transport and mixing through fracture networks.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Orchestration of ErbB3 signaling through heterointeractions and homointeractions

Members of the ErbB family of receptor tyrosine kinases are capable of both homointeractions and heterointeractions. Because each receptor has a unique set of binding sites for downstream signaling partners and differential catalytic activity, subtle shifts in their combinatorial interplay may have a large effect on signaling outcomes. The overexpression and mutation of ErbB family members are common in numerous human cancers and shift the balance of activation within the signaling network. Here we report the development of a spatial stochastic model that addresses the dynamics of ErbB3 homodimerization and heterodimerization with ErbB2. The model is based on experimental measures for diffusion, dimer off-rates, kinase activity, and dephosphorylation. We also report computational analysis of ErbB3 mutations, generating the prediction that activating mutations in the intracellular and extracellular domains may be subdivided into classes with distinct underlying mechanisms. We show experimental evidence for an ErbB3 gain-of-function point mutation located in the C-lobe asymmetric dimerization interface, which shows enhanced phosphorylation at low ligand dose associated with increased kinase activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Ionic transport in high-energy-density matter

Ionic transport coefficients for dense plasmas have been numerically computed using an effective Boltzmann approach. Here, we developed a simplified effective potential approach that yields accurate fits for all of the relevant cross sections and collision integrals. These results have been validated with molecular-dynamics simulations for self-diffusion, interdiffusion, viscosity, and thermal conductivity. Molecular dynamics has also been used to examine the underlying assumptions of the Boltzmann approach through a categorization of behaviors of the velocity autocorrelation function in the Yukawa phase diagram. By using a velocity-dependent screening model, we examine the role of dynamical screening in transport. Implications of these results for Coulomb logarithm approaches are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Osmotic Pressure Gradient Effects on Water Diffusion in Porous Rock: Can They Pervert Permeability Tests?

Abstract Generation of a large network of hydraulic cracks is of key importance not only for the success of fracking of shale but also for the recent scheme of sequestration of CO2 in deep formations of basalt and peridotite, which are mafic and ultramafic rocks that combine chemically with CO2. In numerical simulation of the creation of a fracture network in porous rock, an important goal is to enhance the rock permeability. The objective of this article is to calculate the effect of osmotic pressure gradients caused by gradients of concentration of the ions of Ca, Mg, Na, etc. on the effective permeability of the rock. The basic differential equations are formulated, and their explicit solutions for appropriate initial and boundary conditions are obtained under certain plausible simplifications. The main result is explicit approximate formulas for the critical time before which no water permeation through a test specimen can be observed. Depending on various parameters, this time can be unacceptably long, which is manifested as a zero water outflow. The solution may also explain the unreasonably small permeability values reported for some shales.

Mechanics↗
DOE OSTI2021

Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems

This work combines the Hierarchical Model (HiMod) reduction technique with a standard Proper Orthogonal Decomposition (POD) to solve parametrized partial differential equations for the modeling of advection-diffusion-reaction phenomena in elongated domains (e.g., pipes). This combination leads to what we define as HiPOD model reduction, which merges the reliability of HiMod reduction with the computational efficiency of POD. Two HiPOD techniques are presented and assessed by an extensive numerical verification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Using Behavioral Science to Target LMI and High-Value Solar Installations (Final Technical Report)

This project is a data-driven analysis of approaches to facilitate solar adoption in LMI communities and areas with high potential benefits to the electric grid. The cornerstone of the project was two waves of randomized field experiments. The first wave involved novel approaches to reaching LMI communities based on insights from literature. The second wave involved areas of high potential of solar to the electricity grid, as determined in collaboration with the local utilities in Connecticut. Both waves were followed by surveys to develop insight into the effectiveness of different approaches. A third key element of the project is the development of new agent-based models of solar energy diffusion that explicitly incorporate the real spatial and temporal constraints that influence solar diffusion, based on real-world data on solar adoption. The project also involved outreach and dissemination of key findings to relevant stakeholders, including a guidebook on strategies to accelerate solar deployment to low and moderate income communities, multiple academic publications, and numerous presentations of the research findings.

14 SOLAR ENERGY↗
DOE OSTI2025

Model form and sensitivity analysis of CALPHAD-based nucleation models in b-stabilized Ti alloys

Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.

Rodriguez Negron, A. M.↗
DOE OSTI2016

A Public-Private-Acadmic Partnership to Advance Solar Power Forecasting

The National Center for Atmospheric Research (NCAR) is pleased to have led a partnership to advance the state-of-the-science of solar power forecasting by designing, developing, building, deploying, testing, and assessing the SunCast™ Solar Power Forecasting System. The project has included cutting edge research, testing in several geographically- and climatologically-diverse high penetration solar utilities and Independent System Operators (ISOs), and wide dissemination of the research results to raise the bar on solar power forecasting technology. The partners include three other national laboratories, six universities, and industry partners. This public-private-academic team has worked in concert to perform use-inspired research to advance solar power forecasting through cutting-edge research to advance both the necessary forecasting technologies and the metrics for evaluating them. The project has culminated in a year-long, full-scale demonstration of provide irradiance and power forecasts to utilities and ISOs to use in their operations. The project focused on providing elements of a value chain, beginning with the weather that causes a deviation from clear sky irradiance and progresses through monitoring and observations, modeling, forecasting, dissemination and communication of the forecasts, interpretation of the forecast, and through decision-making, which produces outcomes that have an economic value. The system has been evaluated using metrics developed specifically for this project, which has provided rich information on model and system performance. Research was accomplished on the very short range (0-6 hours) Nowcasting system as well as on the longer term (6-72 hour) forecasting system. The shortest range forecasts are based on observations in the field. The shortest range system, built by Brookhaven National Laboratory (BNL) and based on Total Sky Imagers (TSIs) is TSICast, which operates on the shortest time scale with a latency of only a few minutes and forecasts that currently go out to about 15 min. This project has facilitated research in improving the hardware and software so that the new high definition cameras deployed at multiple nearby locations allow discernment of the clouds at varying levels and advection according to the winds observed at those levels. Improvements over “smart persistence” are about 29% for even these very short forecasts. StatCast is based on pyranometer data measured at the site as well as concurrent meteorological observations and forecasts. StatCast is based on regime-dependent artificial intelligence forecasting techniques and has been shown to improve on “smart persistence” forecasts by 15-50%. A second category of short-range forecasting systems employ satellite imagery and use that information to discern clouds and their motion, allowing them to project the clouds, and the resulting blockage of irradiance, in time. CIRACast (the system produced by the Cooperative Institute for Atmospheric Research [CIRA] at Colorado State University) was already one of the more advanced cloud motion systems, which is the reason that team was brought to this project. During the project timeframe, the CIRA team was able to advance cloud shadowing, parallax removal, and implementation of better advecting winds at different altitudes. CIRACast shows generally a 25-40% improvement over Smart Persistence between sunrise and approximately 1600 UTC (Coordinated Universal Time) . A second satellite-based system, MADCast (Multi-sensor Advective Diffusive foreCast system), assimilates data from multiple satellite imagers and profilers to assimilate a fully three-dimensional picture of the cloud into the dynamic core of WRF. During 2015, MADCast (provided at least 70% improvement over Smart Persistence, with most of that skill being derived during partly cloudy conditions. That allows advection of the clouds via the Weather Research and Forecasting (WRF) model dynamics directly. After WRF-Solar™ showed initial success, it was also deployed in nowcasting mode with coarser runs out to 6 hours made hourly. It provided improvements on the order of 50-60% over Smart Persistence for forecasts up to 1600 UTC. The advantages of WRF-Solar-Nowcasting and MADCast were then blended to develop the new MAD-WRF model that incorporates the most important features of each of those models, both assimilating satellite cloud fields and using WRF-So far physics to develop and dissipate clouds. MAE improvements for MAD-WRF for forecasts from 3-6 hours are improved over WRF-Solar-Now by 20%. While all the Nowcasting system components by themselves provide improvement over Smart Persistence, the largest benefit is derived when they are smartly blended together by the Nowcasting Integrator to produce an integrated forecast. The development of WRF-Solar™ under this project has provided the first numerical weather prediction (NWP) model specifically designed to meet the needs of irradiance forecasting. The first augmentation improved the solar tracking algorithm to account for deviations associated with the eccentricity of the Earth’s orbit and the obliquity of the Earth. Second, WRF-Solar™ added the direct normal irradiance (DNI) and diffuse (DIF) components from the radiation parameterization to the model output. Third, efficient parameterizations were implemented to either interpolate the irradiance in between calls to the expensive radiative transfer parameterization, or to use a fast radiative transfer code that avoids computing three-dimensional heating rates but provides the surface irradiance. Fourth, a new parameterization was developed to improve the representation of absorption and scattering of radiation by aerosols (aerosol direct effect). A fifth advance is that the aerosols now interact with the cloud microphysics, altering the cloud evolution and radiative properties, an effect that has been traditionally only implemented in atmospheric computationally costly chemistry models. A sixth development accounts for the feedbacks that sub-grid scale clouds produce in shortwave irradiance as implemented in a shallow cumulus parameterization Finally, WRF-Solar™ also allows assimilation of infrared irradiances from satellites to determine the three dimensional cloud field, allowing for an improved initialization of the cloud field that increases the performance of short-range forecasts. We find that WRF-Solar™ can improve clear sky irradiance prediction by 15-80% over a standard version of WRF, depending on location and cloud conditions. In a formal comparison to the NAM baseline, WRF-Solar™ showed improvements in the Day-Ahead forecast of 22-42%. The SunCast™ system requires substantial software engineering to blend all of the new model components as well as existing publically available NWP model runs. To do this we use an expert system for the Nowcasting blender and the Dynamic Integrated foreCast (DICast®) system for the NWP models. These two systems are then blended, we use an empirical power conversion method to convert the irradiance predictions to power, then apply an analog ensemble (AnEn) approach to further tune the forecast as well as to estimate its uncertainty. The AnEn module decreased RMSE (root mean squared error) by 17% over the blended SunCast™ power forecasts and provided skill in the probabilistic forecast with a Brier Skill Score of 0.55. In addition, we have also developed a Gridded Atmospheric Forecast System (GRAFS) in parallel, leveraging cost share funds. An economic evaluation based on Production Cost Modeling in the Public Service Company of Colorado showed that the observed 50% improvement in forecast accuracy will save their customers $819,200 with the projected MW deployment for 2024. Using econometrics, NCAR has scaled this savings to a national level and shown that an annual expected savings for this 50% forecast error reduction ranges from $11M in 2015 to $43M expected in 2040 with increased solar deployment. This amounts to a $455M discounted savings over the 26 year period of analysis.

14 SOLAR ENERGY↗
DOE OSTI2016

Phase space effects on fast ion distribution function modeling in tokamaks

Integrated simulations of tokamak discharges typically rely on classical physics to model energetic particle (EP) dynamics. However, there are numerous cases in which energetic particles can suffer additional transport that is not classical in nature. Examples include transport by applied 3D magnetic perturbations and, more notably, by plasma instabilities. Focusing on the effects of instabilities, ad-hoc models can empirically reproduce increased transport, but the choice of transport coefficients is usually somehow arbitrary. New approaches based on physics-based reduced models are being developed to address those issues in a simplified way, while retaining a more correct treatment of resonant wave-particle interactions. The kick model implemented in the tokamak transport code TRANSP is an example of such reduced models. It includes modifications of the EP distribution by instabilities in real and velocity space, retaining correlations between transport in energy and space typical of resonant EP transport. The relevance of EP phase space modifications by instabilities is first discussed in terms of predicted fast ion distribution. Results are compared with those from a simple, ad-hoc diffusive model. It is then shown that the phase-space resolved model can also provide additional insight into important issues such as internal consistency of the simulations and mode stability through the analysis of the power exchanged between energetic particles and the instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗