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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Preserving Superconvergence of Spectral Elements for Curved Domains via $h$ and $p$-Geometric Refinement

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with simplicial or non-tensor-product elements. To overcome the first issue, we propose using h- and p-geometric refinement, which refines the mesh near high-curvature regions and increases the degree of geometric basis functions, respectively. We show that when using mixed-element meshes with tensor-product elements in the interior of the domain, curvature-based geometric refinement near boundaries can improve the accuracy of the interior elements by reducing pollution errors and preserving the superconvergence in nodal solutions. To address the second issue, we introduce a post-processing technique using the adaptive extended stencil finite element method (AES-FEM) to recover the accuracy near the curved boundaries. The combination of curvature-based geometric refinement and accurate post-processing offers an effective and easier-to-implement alternative to methods reliant on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 2D and show up to two orders of magnitude of improvement in the solution accuracy, even when the elements are poorly shaped near boundaries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Classification of machine learning frameworks for data-driven thermal fluid models

Thermal fluid processes are inherently multi-physics and multi-scale, involving mass-momentum-energy transport phenomena at multiple scales. Thermal fluid simulation (TFS) is based on solving conservative equations, for which – except for “first-principles” direct numerical simulation – closure relations (CRs) are required to provide microscopic interactions or so-called sub-grid-scale physics. In practice, TFS is realized through reduced-order modeling, and its CRs as low-fidelity models can be informed by observations and data from relevant and adequately evaluated experiments and high-fidelity simulations. This paper is focused on data-driven TFS models, specifically on their development using machine learning (ML). Five ML frameworks are introduced including physics-separated ML (PSML or Type I ML), physics-evaluated ML (PEML or Type II ML), physics-integrated ML (PIML or Type III ML), physics-recovered (PRML or Type IV ML), and physics-discovered ML (PDML or Type V ML). The frameworks vary in their performance for different applications depending on the level of knowledge of governing physics, source, type, amount and quality of available data for training. Notably, outlined for the first time in this paper, Type III models present stringent requirements on modeling, substantial computing resources for training, and high potential in extracting value from “big data” in thermal fluid research. Here the current paper demonstrates and investigates ML frameworks in three examples. First, we utilize the heat diffusion equation with a nonlinear conductivity model formulated by convolutional neural networks (CNNs) and feedforward neural networks (FNNs) to illustrate the applications of Type I, Type II, Type III, and Type V ML. The results indicate a preference for Type II ML under deficient data support. Type III ML can effectively utilize field data, potentially generating more robust predictions than Type I and Type II ML. CNN-based closures exhibit more predictability than FNN-based closures, but CNN-based closures require more training data to obtain accurate predictions. Second, we illustrate how to employ Type I ML and Type II ML frameworks for data-driven turbulence modeling using reference works. Third, we demonstrate Type I ML by building a deep FNN-based slip closure for two-phase flow modeling. The results show that deep FNN-based closures exhibit a bounded error in the prediction domain.

42 ENGINEERING↗
DOE OSTI2022

Feedback between radiation and transport in photovoltaics

By building on the generalized Hovel model, this work develops an analytical solution to unify photon recycling, light trapping, and carrier transport in solar cells. Enhanced transport due to photon recycling diffusion is considered. While photon recycling diffusion is often negligible, it can significantly support transport in cases where charge diffusion is low but radiative efficiency is high. Next, the diffusion equation is solved to determine carrier collection for planar and textured cells. Results elucidate novel features in the external quantum efficiency (EQE) curve that occur for textured cells with high absorption and limited transport. Then, the effect of limited transport on the radiative recombination of solar cells is investigated in detail. While the traditional treatment of detailed balance uses the applied voltage to calculate a cell's radiative recombination, the present approach uses the spatially resolved quasi-Fermi-level splitting (QFLS). Further, the discrepancy between the models is shown to be inconsequential to performance for cells with low radiative recombination (Si) or with high mobilities (lowly doped GaAs). However, for cells with high radiative recombination and low mobility (highly doped GaAs, polycrystalline CdTe, and thin-film perovskites), incorporating variation in QFLS in the determination of radiative recombination can become necessary for accurate photovoltaic modeling.

14 SOLAR ENERGY↗
NASA NTRS2004

Characteristics of Electromagnetic Pulse Propagation in Metal

It is well known that the solution of the diffusion equation for an electromagnetic field with a time harmonic term, e(sup iwt), is in the form of a traveling wave whose amplitude attenuates over distance into a conducting medium. As the attenuation is an increasing function of frequency, the high frequency components attenuate more rapidly than those of low ones upon entering a well conducting object. At the same time, the phase velocity of an individual component is also an increasing function of frequency causing a broadening of the pulse traveling inside a conductor. In the results of our previous study of numerical simulations, the problem of using a gaussian input pulse was immediately clear. First, having the dominant frequency components distributed around zero, the movement of the peak was not well defined. Second, with the amplitude of fourier components varying slowly over a wide range, the dispersion-induced blurring of the peak position was seen to be severe. For the present study, we have used a gaussian modulated single frequency sinusoidal wave, i. e., the carrier, as an input pulse in an effort to improve the issues related to the unclear movement of peak and dispersion as described above. This was based on the following two anticipated advantages: First, the packet moves in a conductor at the group velocity calculated at the carrier frequency, which means it is well controllable. Second, the amplitude of frequency components other than that of the carrier can be almost negligible, such that the effect of dispersion can be significantly reduced. A series of experiments of transmitting electromagnetic pulses through aluminum plates of various thickness was performed to test the validity of the above points. The results of numerical simulation based on wave propagation are discussed with respect to the experimental results. Finally, a simple simulation was performed based on diffusion of a continuous sine wave input and the results are compared with those of a single frequency sinusoidal wave observed over time at difference locations inside a conductor.

Namkung, M.↗
DOE OSTI2017

A novel approach to evaluate soil heat flux calculation: An analytical review of nine methods

Abstract There are no direct methods to evaluate calculated soil heat flux (SHF) at the surface ( G 0 ). Instead, validation and cross evaluation of methods for calculating G 0 usually rely on the conventional calorimetric method or the degree of the surface energy balance closure. However, there is uncertainty in the calorimetric method itself, and factors apart from G 0 also contribute to nonclosure of the surface energy balance. Here we used a novel approach to evaluate nine different methods for calculating SHF, including the calorimetric method and methods based on analytical solutions of the heat diffusion equation. The SHF ( G z ) measured by a self‐calibrating SHF plate at a depth of z = 5 cm below the surface (hereafter G m _5 cm ) was deployed as a reference. Each SHF calculation method was assessed by comparing the calculated G z at the same depth (hereafter G c _5 cm ) with G m _5 cm . The calorimetric method and simple measurement method performed best in determining G c _5 cm but still underestimated G m _5 cm by 19% during the daytime. Possible causes for this underestimation include errors and uncertainties in SHF measurements and soil thermal properties, as well as the phase lag between G c _5 cm and G m _5 cm . Our results indicate that the calorimetric method achieves the most accurate SHF estimates if self‐calibrating SHF plates are deployed at two depths (e.g., 5 cm and 10 cm), soil temperature and water content measurements are made in a few depths between the two plates, and soil thermal properties are accurately quantified.

Gao, Zhongming↗
DOE OSTI2018

An Extended Trajectory Mechanics Approach for Calculating the Path of a Pressure Transient: Derivation and Illustration

Following an approach used in quantum dynamics, an exponential representation of the hydraulic head transforms the diffusion equation governing pressure propagation into an equivalent set of ordinary differential equations. Using a reservoir simulator to determine one set of dependent variables leaves a reduced set of equations for the path of a pressure transient. Unlike the current approach for computing the path of a transient, based on a high-frequency asymptotic solution, the trajectories resulting from this new formulation are valid for arbitrary spatial variations in aquifer properties. For a medium containing interfaces and layers with sharp boundaries, the trajectory mechanics approach produces paths that are compatible with travel time fields produced by a numerical simulator, while the asymptotic solution produces paths that bend too strongly into high permeability regions. The breakdown of the conventional asymptotic solution, due to the presence of sharp boundaries, has implications for model parameter sensitivity calculations and the solution of the inverse problem. For example, near an abrupt boundary, trajectories based on the asymptotic approach deviate significantly from regions of high sensitivity observed in numerical computations. In contrast, paths based on the new trajectory mechanics approach coincide with regions of maximum sensitivity to permeability changes.

42 ENGINEERING↗
DOE OSTI2022

Modelling of edge plasma dynamics with active wall boundary conditions

A self-consistent 2D model is presented for transport in boundary plasma and plasma-facing material walls. Plasma dynamics in the domain is represented by a 2D collisional plasma fluid model in the edge-plasma code UEDGE, and transport of hydrogen and heat in the wall is represented by a system of reaction–diffusion equations in the 1D wall code FACE. To account for variation of parameters along the wall, in the coupled model multiple instances of the FACE code run in parallel. Here, the coupled model provides a tool for investigating a range of dynamic plasma–material interactions phenomena in 2D. For demonstration of its capability, one application of particular interest is the role of active wall in tokamak strike point sweeping proposed for mitigation of divertor heat loads. In the present study, the coupled calculations are applied to investigation of the impact of heat and hydrogen transport in the material wall on the divertor plasma and target heat load during sweeping of the target strike point for parameters of a high-power tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Kinetic Simulations of Cu Doping in Chlorinated CdSeTe PV Absorbers

This paper reports on 1D kinetic modeling of p-type doping formation in Cu-doped chlorinated CdSeTe photovoltaic (PV) absorbers with graded Se profiles. Following the recent progress in kinetic simulations of the defect chemistry in stoichiometric CdTe films, this work extends simulation capabilities to a domain of semiconductor alloy films with graded stoichiometries. The defect formation energies and ionization levels, as well as the diffusion and reaction barriers used in the reaction-diffusion equations are calculated from the first principles. A new formalism is employed to account for the uncertainty of the defect formation energies in semiconductor alloys caused by unknown local surrounding. Finally, the developed methodology is used to model a practical fabrication process of p-type doping formation in graded CdSeTe absorbers and to study the effect of alloy stoichiometry on the doping activation.

14 SOLAR ENERGY↗
DOE OSTI2020

Learning compact physics‐aware delayed photocurrent models using dynamic mode decomposition

Abstract Radiation‐induced photocurrent in semiconductor devices can be simulated using complex physics‐based models, which are accurate, but computationally expensive. This presents a challenge for implementing device characteristics in high‐level circuit simulations where it is computationally infeasible to evaluate detailed models for multiple individual circuit elements. In this work we demonstrate a procedure for learning compact delayed photocurrent models that are efficient enough to implement in large‐scale circuit simulations, but remain faithful to the underlying physics. Our approach utilizes dynamic mode decomposition (DMD), a system identification technique for learning reduced‐order discrete‐time dynamical systems from time series data based on singular value decomposition. To obtain physics‐aware device models, we simulate the excess carrier density induced by radiation pulses by solving numerically the ambipolar diffusion equation, then use the simulated internal state as training data for the DMD algorithm. Our results show that the significantly reduced‐order delayed photocurrent models obtained via this method accurately approximate the dynamics of the internal excess carrier density—which can be used to calculate the induced current at the device boundaries—while remaining compact enough to incorporate into larger circuit simulations.

Hanson, Joshua↗
DOE OSTI2020

Nonoverlapping Localized Exponential Time Differencing Methods for Diffusion Problems

In this paper, we propose nonoverlapping localized exponential time differencing (ETD) methods for diffusion problems. The model time-dependent diffusion equation is first reformulated on subdomains based on the nonoverlapping domain decomposition, in which Neumann boundary conditions are imposed on the interfaces for the subdomain problems and Dirichlet type conditions are enforced to form a space-time interface problem. After spatial discretization by standard central finite differences and temporal integration with the first or second order ETD methods, the fully discrete interface problem is obtained. Such an interface problem is then solved iteratively either at each time step or over the whole time interval: the former involves the solution of stationary problems in each subdomain at each iteration while the latter involves the solution of time-dependent subdomain problems at each iteration. For both approaches, we prove that localized ETD solutions conserve mass exactly and converge in time to the exact space semidiscrete solution. Numerical experiments in two dimensions are also presented to illustrate the performance of the proposed methods.

Mass conservation↗
DOE OSTI2026

Reactive Transport Modeling with Physics-Informed Machine Learning for Critical Minerals Applications

This study presents a physics-informed neural network (PINN) framework for reactive transport modeling for simulating fast bimolecular reactions in porous media. Accurate characterization of cAhemical interactions and product formation in surface and subsurface environments is essential for advancing critical mineral extraction and related geoscience applications. The proposed methodology sequentially addresses the flow and diffusion–reaction subproblems. The flow field is computed using a mixed formulation, while the diffusion–reaction system is modeled via two uncoupled tensorial diffusion equations reformulated in terms of chemical invariants. PINNs are employed to solve the governing equations, enabling data-efficient, mesh-free prediction of chemical concentration fields. The framework is validated through a series of benchmark problems involving flow in heterogeneous porous media. Initial verification is conducted using patch tests for the flow field, followed by validation of the transport problem with emphasis on preserving non-negativity of concentrations. The complete fast bimolecular reaction scenario is then solved, yielding spatial distributions of reactants and product species. Results demonstrate that the PINNs-based approach effectively captures sharp, mixing-limited reaction fronts and dispersive mixing behavior, offering reliable predictions of reactive plume evolution. These capabilities are crucial for evaluating long-term subsurface behavior in applications such as fluid storage, energy extraction, and efficient extraction of critical minerals.

42 ENGINEERING↗
DOE OSTI2018

An asymmetric backward problem for the inhomogeneous parabolic equation with time-dependent diffusivity

In this paper, we deal with an asymmetric case of the non-homogeneous backward parabolic problem associated with time-dependent diffusivity in polar coordinates which arises in describing the heat transfer in cylinder. In general, this problem is severely ill-posed by the Hadamard instability. To subdue the instability of this problem, we apply the modified quasi-boundary value method. According to some a priori assumptions on the exact solution, we get an explicit error estimate of Hölder type for all t∈(0,T]. In addition, a numerical experiment is given to illustrate the efficiency and flexibility of our method.

42 ENGINEERING↗
DOE OSTI2017

Pore-network model of evaporation-induced salt precipitation in porous media: The effect of correlations and heterogeneity

Salt transport and precipitation in porous media constitute a set of complex and fascinating phenomena that are of considerable interest to several important problems, ranging from storage of CO 2 in geological formations, to soil fertility, and protection of pavements and roads, as well as historical monuments. The phenomena occur at the pore scale and are greatly influenced by the heterogeneity of the pore space morphology. In this paper, we present a pore-network (PN) model to study the phenomena. Vapor diffusion, capillary effect at the brine-vapor interface, flow of brine, and transport of salt and its precipitation in the pores that plug the pores partially or completely are all accounted for. The drying process is modeled by the invasion percolation, while transport of salt in brine is accounted for by the convective-diffusion equation. We demonstrate that the drying patterns, the clustering and connectivity of the pore throats in which salt precipitation occurs, the saturation distribution, and the drying rate are all strongly dependent upon the pore-size distribution, the correlations among the pore sizes, and the anisotropy of the pore space caused by stratification that most natural porous media contain. In particular, if the strata are more or less parallel to the direction of injection of the gas that dries out the pore space (air, for example) and/or causes salt precipitation (CO 2 , for example), the drying rate increases significantly. Moreover, salt tends to precipitate in clusters of neighboring pores that are parallel to the open surface of the porous medium.

42 ENGINEERING↗
DOE OSTI2018

Control rod treatment for FEM based radiation transport methods

This paper presents a novel control rod treatment for finite element method (FEM) based reactor physics simulations. The new method falls into the class of homogenization methods which treat material interfaces within mesh elements by defining a representative, homogenized nuclear cross section set. In contrast to existing homogenization based cusping treatments that attempt to approximate flux-volume weighting of the cross sections, we propose to exactly integrate terms appearing in the variational form of the transport or diffusion equation over mixed material elements. This goal is achieved by defining smoothly varying cross sections in elements that straddle material boundaries. It is shown that the smoothly varying cross sections can be obtained by projecting the piecewise set of cross sections onto the set of Legendre polynomials up to a finite order. Implementation of smoothly varying cross sections is supported within the Rattlesnake radiation multiphysics code that is currently under development at the Idaho National Laboratory. Homogenization methods traditionally suffer from cusping effects that originate from overestimation of absorption cross sections in strongly neutron-absorbing materials as found in control rods. We demonstrate that the presented method is (1) highly effective in removing cusping effects and (2) provides accurate results based on the C5G7-TD benchmark, a time-dependent version of the C5G7 benchmark.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Orders of magnitude reduction in the thermal conductivity of polycrystalline diamond through carbon, nitrogen, and oxygen ion implantation

Despite the exceptional thermal and mechanical functionalities of diamond, its superlative properties are highly subject to the presence of point defects, dislocations, and interfaces. Here, polycrystalline diamond is ion implanted with C 3+ , N 3+ , and O 3+ ions at an energy of 16.5 MeV, producing an amorphous layer at the projected range and a damaged crystalline region between the surface and amorphous layer. Using time-domain thermoreflectance in combination with thermal penetration depth calculations based upon the multilayer heat diffusion equation, it is determined that reductions in the thermal conductivity can span nearly two orders of magnitude while still maintaining a polycrystalline structure within the regions thermally probed. Dynamical diffraction simulations of high-resolution x-ray diffraction measurements demonstrate the formation of a strained layer localized at the end of range, with much lower levels of strain near the surface. Furthermore, within the polycrystalline region above the amorphous layer, the average number of displacements-per-atom from the ion irradiation is found to be < 1%, with mass impurity concentrations much less than 1%. These low defect concentrations within the thermally probed region demonstrate the remarkably large impact that dilute levels of defects from the ion implantation can have on the thermal conductivity of diamond.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Multi-scale topology optimization of multi-material structures with controllable geometric complexity — Applications to heat transfer problems

This study presents a topology optimization method to design assemblies of periodic cellular materials with controllable geometric complexity. The framework is based on a novel multi-scale and multi-material design model in which the structure, the layout of the material subdomains, and their micro-structures are optimized concurrently. To allow a tight control over its geometrical complexity, the layout at the macro-scale is described by level-set fields, parameterized by geometric primitives. The micro-scale geometry is represented through a density approach. A nonlinear programming algorithm drives the optimization process using design sensitivities computed by the discrete adjoint method. The proposed design framework is studied with heat transfer problems. Practical design problems, such as a heat sink and a thermal storage unit with phase change are discussed. The macro-scale analysis model relies on a generalized transient diffusion equation. At the micro-scale, homogenization is used to compute equivalent material properties. The numerical examples in this study show that the optimized multi-scale multi-material layouts outperform the corresponding mono-scale structures while maintaining geometric simplicity at the macro-scale level.

42 ENGINEERING↗
DOE OSTI2020

An open source fast fluid dynamics model for data center thermal management

Although computational fluid dynamics (CFD) has been widely adopted to improve data center thermal management, the high computational demand limits its applications, such as multivariate optimal design and operation. Fast fluid dynamics (FFD), which has been applied for fast airflow simulation, shows great potential. However, few research applied FFD for optimal design and operation of data center thermal management. This research improves the FFD model for data centers and conducts a comprehensive evaluation and demonstration. First, the FFD model is improved by solving the advection and diffusion equations together using an upwind scheme instead of a semi-Lagrangian advection solver in the conventional FFD model. Second, new features for data centers are added, such as a pressure correction method to simulate plenum airflow and dynamic boundary conditions for IT racks. The new FFD model is first validated with two indoor environment cases and the results show that the new FFD model has slightly better overall prediction accuracy and faster speed compared to the conventional FFD model. It is also observed that both FFD models achieve acceptable accuracy, except for a few localized disparities with experimental data, which might be due to simplified handling of turbulence viscosity near the boundaries. Furthermore, validation with a real data center shows that the FFD model achieves a similar level of accuracy as CFD when compared to the experimental measurements with some level of uncertainties. It is then demonstrated for data center optimal design and operation, which saves 53.4–58.8% of annual energy while still meeting the thermal requirements. In conclusion, with a much faster speed and comparable accuracy compared to CFD, the FFD model parallelized on a graphics processing unit is promising for practical model-based data center early design and operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

TRANSP-based closed-loop simulations of current profile optimal regulation in NSTX-Upgrade

Active control of the toroidal current density profile is critical for the upgraded National Spherical Torus eXperiment device (NSTX-U) to maintain operation at the desired high-performance, MHD-stable, plasma regime. Initial efforts towards current density profile control have led to the development of a control-oriented, physics-based, plasma-response model, which combines the magnetic diffusion equation with empirical correlations for the kinetic profiles and the non-inductive current sources. The developed control-oriented model has been successfully tailored to the NSTX-U geometry and actuators. Moreover, a series of efforts have been made towards the design of model-based controllers, including a linear-quadratic-integral optimal control strategy that can regulate the current density profile around a prescribed target profile while rejecting disturbances. In this work, the tracking performance of the proposed current-profile optimal controller is tested in numerical simulations based on the physics-oriented code TRANSP. Furthermore, these high-fidelity closed-loop simulations, which are a critical step before experimental implementation and testing, are enabled by a flexible framework recently developed to perform feedback control design and simulation in TRANSP.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗