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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Measuring binary fluidization of nonspherical and spherical particles using machine learning aided image processing

Abstract The binary fluidization of Geldart D type nonspherical wood particles and spherical low density polyethylene (LDPE) particles was investigated in a laboratory‐scale bed. The experiment was performed for varying static bed height, wood particles count, as well as superficial gas velocity. The LDPE velocity field were quantified using particle image velocimetry (PIV). The wood particles orientation and velocity are measured using particle tracking velocimetry (PTV). A machine learning pixel‐wise classification model was trained and applied to acquire wood and LDPE particle masks for PIV and PTV processing, respectively. The results show significant differences in the fluidization behavior between LDPE only case and binary fluidization case. The effects of wood particles on the slugging frequency, mean, and variation of bed height, and characteristics of the particle velocities/orientations were quantified and compared. This comprehensive experimental dataset serves as a benchmark for validating numerical models.

Li, Cheng↗
DOE OSTI2020

An extended/generalized phase-field finite element method for crack growth with global-local enrichment

In this paper, an extended/generalized finite element method (XFEM/GFEM) for simulating quasistatic crack growth based on a phase-field method is presented. The method relies on approximations to solutions associated with two different scales: a global scale, that is, structural and discretized with a coarse mesh, and a local scale encapsulating the fractured region, that is, discretized with a fine mesh. A stable XFEM/GFEM is employed to embed the displacement and damage fields at the global scale. The proposed method accommodates approximation spaces that evolve between load steps, while preserving a fixed background mesh for the structural problem. In addition, a prediction-correction algorithm is employed to facilitate the dynamic evolution of the confined crack regions within a load step. Several numerical examples of benchmark problems in two- and three-dimensional quasistatic fracture are provided to demonstrate the approach.

multiscale↗
DOE OSTI2017

Convection Effects During Bulk Transparent Alloy Solidification in DECLIC-DSI and Phase-Field Simulations in Diffusive Conditions

In order to study the dynamical formation and evolution of cellular and dendritic arrays under diffusive growth conditions, three-dimensional (3D) directional solidification experiments were conducted in microgravity on a model transparent alloy onboard the International Space Station using the Directional Solidification Insert in the DEvice for the study of Critical LIquids and Crystallization. Selected experiments were repeated on Earth under gravity-driven fluid flow to evidence convection effects. Both radial and axial macrosegregation resulting from convection are observed in ground experiments, and primary spacings measured on Earth and microgravity experiments are noticeably different. The microgravity experiments provide unique benchmark data for numerical simulations of spatially extended pattern formation under diffusive growth conditions. The results of 3D phase-field simulations highlight the importance of accurately modeling thermal conditions that strongly influence the front recoil of the interface and the selection of the primary spacing. The modeling predictions are in good quantitative agreements with the microgravity experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nonlocal Flocking Dynamics: Learning the Fractional Order of PDEs from Particle Simulations

Flocking refers to collective behavior of a large number of interacting entities, where the interactions between discrete individuals produce collective motion on the large scale. We employ an agent-based model to describe the microscopic dynamics of each individual in a flock, and use a fractional partial differential equation (fPDE) to model the evolution of macroscopic quantities of interest. The macroscopic models with phenomenological interaction functions are derived by applying the continuum hypothesis to the microscopic model. Instead of specifying the fPDEs with an ad hoc fractional order for nonlocal flocking dynamics, we learn the effective nonlocal influence function in fPDEs directly from particle trajectories generated by the agent-based simulations. We demonstrate how the learning framework is used to connect the discrete agent-based model to the continuum fPDEs in one- and two-dimensional nonlocal flocking dynamics. In particular, a Cucker–Smale particle model is employed to describe the microscale dynamics of each individual, while Euler equations with nonlocal interaction terms are used to compute the evolution of macroscale quantities. The trajectories generated by the particle simulations mimic the field data of tracking logs that can be obtained experimentally. They can be used to learn the fractional order of the influence function using a Gaussian process regression model implemented with the Bayesian optimization. We show in one- and two-dimensional benchmarks that the numerical solution of the learned Euler equations solved by the finite volume scheme can yield correct density distributions consistent with the collective behavior of the agent-based system solved by the particle method. Furthermore, the proposed method offers new insights into how to scale the discrete agent-based models to the continuum-based PDE models, and could serve as a paradigm on extracting effective governing equations for nonlocal flocking dynamics directly from particle trajectories.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

ONIX: An open-source depletion code

Open Source software enables innovative, community-based software development. ONIX brings this concept to the field of depletion calculations. It is an open-source depletion software to be used for nuclear reactor simulations, for fissile material production analysis as well as for nuclear arms control applications. ONIX provides a module to solve the depletion equation using a Chebyshev Rational Approximation Method. For the generation of one-group cross sections, it includes a coupling interface for the open-source neutron transport code, OpenMC, as well as a module to read pre-computed values in a stand-alone mode. ONIX has special features to optimize nuclear data libraries, to update isomeric branching ratio during burnup, and to support automation of simulations for nuclear archaeology. In conclusion, ONIX has been validated against results from numerical and experimental benchmarks, and its results agree with other methods within expected error ranges.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Nonequilibrium steady state and heat transport in nonlinear open quantum systems: Stochastic influence action and functional perturbative analysis

In this paper, we show that a nonequilibrium steady state (NESS) exists at late times in open quantum systems with weak nonlinearity by following its nonequilibrium dynamics with a perturbative analysis. We consider an oscillator chain containing three-types of anharmonicity: cubic α- and quartic β-type Fermi–Pasta–Ulam–Tsingou (FPUT) nearest-oscillator interactions and the on-site (pinned) Klein–Gordon (KG) quartic self-interaction. Assuming weak nonlinearity, we introduce a stochastic influence action approach to the problem and obtain the energy flows in different junctures across the chain. The formal results obtained here can be used for quantum transport problems in weakly nonlinear quantum systems. For α-type anharmonicity, we observe that the first-order corrections do not play any role in the thermal transport in the NESS of the configuration we considered. For KG and β-types anharmonicity, we work out explicitly the case of two weakly nonlinearly coupled oscillators, with results scalable to any number of oscillators. We examine the late-time energy flows from one thermal bath to the other via the coupled oscillators, and show that both the zeroth- and the first-order contributions of the energy flows become constant in time at late times, signaling the existence of a late-time NESS to first order in nonlinearity. Our perturbative calculations provide a measure of the strength of nonlinearity for nonlinear open quantum systems, which may help control the mesoscopic heat transport distinct from or close to linear transport. Furthermore, our results also give a benchmark for the numerical challenge of simulating heat transport. Our setup and predictions can be implemented and verified by investigating heat flow in an array of Josephson junctions in the limit of large Josephson energy with the platform of circuit QED.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Thermodynamic model of a thermal storage air conditioning system with dynamic behavior

A thermodynamic model was developed to predict transient behavior of a thermal storage system, using phase change materials (PCMs), for a novel electric vehicle climate conditioning application. The main objectives of the paper are to consider the system's dynamic behavior, such as a dynamic air flow rate into the vehicle's cabin, and to characterize the transient heat transfer process between the thermal storage unit and the vehicle's cabin, while still maintaining accurate solution to the complex phase change heat transfer. The system studied consists of a heat transfer fluid circulating between either of the on-board hot and cold thermal storage units, which we refer to as thermal batteries, and a liquid-air heat exchanger that provides heat exchange with the incoming air to the vehicle cabin. Each thermal battery is a shell-and-tube configuration where a heat transfer fluid flows through parallel tubes, which are surrounded by PCM within a larger shell. The system model incorporates computationally inexpensive semianalytic solution to the conjugated laminar forced convection and phase change problem within the battery and accounts for airside heat exchange using the Number of Transfer Units (NTUs) method for the liquid-air heat exchanger. Using this approach, we are able to obtain an accurate solution to the complex heat transfer problem within the battery while also incorporating the impact of the airside heat transfer on the overall system performance. The implemented model was benchmarked against a numerical study for a melting process and against full system experimental data for solidification using paraffin wax as the PCM. Through modeling, we demonstrate the importance of capturing the airside heat exchange impact on system performance, and we investigate system response to dynamic operating conditions, e.g., air recirculation. (C) 2013 Elsevier Ltd. All rights reserved.

Fleming, E↗
DOE OSTI2022

Energetically consistent model reduction for metriplectic systems

The metriplectic formalism is useful for describing complete dynamical systems which conserve energy and produce entropy. This creates challenges for model reduction, as the elimination of high-frequency information will generally not preserve the metriplectic structure which governs long-term stability of the system. Based on proper orthogonal decomposition, a provably convergent metriplectic reduced-order model is formulated which is guaranteed to maintain the algebraic structure necessary for energy conservation and entropy formation. Further, numerical results on benchmark problems show that the proposed method is remarkably stable, leading to improved accuracy over long time scales at a moderate increase in cost over naive methods.

42 ENGINEERING↗
DOE OSTI2016

A blended continuous–discontinuous finite element method for solving the multi-fluid plasma model

The multi-fluid plasma model represents electrons, multiple ion species, and multiple neutral species as separate fluids that interact through short-range collisions and long-range electromagnetic fields. The model spans a large range of temporal and spatial scales, which renders the model stiff and presents numerical challenges. To address the large range of timescales, a blended continuous and discontinuous Galerkin method is proposed, where the massive ion and neutral species are modeled using an explicit discontinuous Galerkin method while the electrons and electromagnetic fields are modeled using an implicit continuous Galerkin method. This approach is able to capture large-gradient ion and neutral physics like shock formation, while resolving high-frequency electron dynamics in a computationally efficient manner. The details of the Blended Finite Element Method (BFEM) are presented. The numerical method is benchmarked for accuracy and tested using two-fluid one-dimensional soliton problem and electromagnetic shock problem. The results are compared to conventional finite volume and finite element methods, and demonstrate that the BFEM is particularly effective in resolving physics in stiff problems involving realistic physical parameters, including realistic electron mass and speed of light. The benefit is illustrated by computing a three-fluid plasma application that demonstrates species separation in multi-component plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

An explicitly solvable energy-conserving algorithm for pitch-angle scattering in magnetized plasmas

In this work, we develop an Explicitly Solvable Energy-Conserving (ESEC) algorithm for the Stochastic Differential Equation (SDE) describing the pitch-angle scattering process in magnetized plasmas. The Cayley transform is used to calculate both the deterministic gyromotion and stochastic scattering, affording the algorithm to be explicitly solvable and exactly energy conserving. An unusual property of the SDE for pitch-angle scattering is that its coefficients diverge at the zero velocity and do not satisfy the global Lipschitz condition. Consequently, when standard numerical methods, such as the Euler-Maruyama (EM), are applied, numerical convergence is difficult to establish. For the proposed ESEC algorithm, its energy-preserving property enables us to overcome this obstacle. We rigorously prove that the ESEC algorithm is order 1/2 strongly convergent. This result is confirmed by detailed numerical studies. For the case of pitch-angle scattering in a magnetized plasma with a constant magnetic field, the numerical solution is benchmarked against the analytical solution, and excellent agreements are found.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A score-based diffusion model approach for adaptive learning of stochastic partial differential equation solutions

In this paper, we propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a recursive Bayesian inference setting. SPDEs play a central role in modeling complex physical systems under uncertainty, but their numerical solutions often suffer from model errors and reduced accuracy due to incomplete physical knowledge and environmental variability. To address these challenges, we encode the governing physics into the score function of a diffusion model using simulation data and incorporate observational information via a likelihood-based correction in a reverse-time stochastic differential equation. This enables adaptive learning through iterative refinement of the solution as new data becomes available. To improve computational efficiency in high-dimensional settings, we introduce the ensemble score filter, a training-free approximation of the score function designed for real-time inference. Numerical experiments on benchmark SPDEs demonstrate the accuracy and robustness of the proposed method under sparse and noisy observations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Distributed Tomographic Reconstruction with Quantization

Conventional tomographic reconstruction typically depends on centralized servers for both data storage and computation, leading to concerns about memory limitations and data privacy. Distributed reconstruction algorithms mitigate these issues by partitioning data across multiple nodes, reducing server load and enhancing privacy. However, these algorithms often encounter challenges related to memory constraints and communication overhead between nodes. In this paper, we introduce a decentralized Alternating Directions Method of Multipliers (ADMM) with configurable quantization. By distributing local objectives across nodes, our approach is highly scalable and can efficiently reconstruct images while adapting to available resources. To overcome communication bottlenecks, we propose two quantization techniques based on K-means clustering and JPEG compression. Numerical experiments with benchmark images illustrate the tradeoffs between communication efficiency, memory use, and reconstruction accuracy.

Miao, Runxuan↗
DOE OSTI2019

Energy transfer for storage or recovery in capacitive deionization using a DC-DC converter

Energy recovery from capacitive deionization (CDI) has the potential to increase overall desalination efficiency. We here define the storage (one-way) and utilization (round-trip) efficiencies between a CDI cell and an energy storage device using a generic direct current/direct current (DC/DC) converter circuit. Presented is a closed-form analytical model for the case of a supercapacitor (SC) as the energy storage device and a buck-boost converter as the DC/DC converter. The model is benchmarked with a numerical model, showing good agreement. Also presented is a comparison among energy transfer methods wherein desalination productivity is fixed. For constant current operation, this condition requires higher currents to compensate for the inactive time introduced by the converter. For fixed productivity, the mean current of the converter circuit approaches the constant current value for higher initial voltages and lower capacitances in the supercapacitor. Finally, we show the effect of relevant parameters of the SC in the storage and utilization efficiency. The model predicts storage and utilization efficiencies of at least 90% for an initial voltage of 1 V or higher and reasonable CDI and SC parameters. Finally, we provide engineering operational parameters to maximize the efficiency of energy transfer and guidance in the selection of electronic components.

25 ENERGY STORAGE↗
DOE OSTI2024

Visualization of post-detonation fireball flowfields and comparison to CFD modeling

Visualization of flow structures within post-detonation fireballs has been performed for benchmark validation of numerical simulations. Custom pressed PETN explosives with a 12-mm diameter hemispherical form factor were used to produce a spherically symmetric post-detonation flow with low soot yield. Hydroxyl-radical planar laser induce fluorescence (OH-PLIF) was employed to visualize the structure ranging from approximately 10 μs to 35 μs after shock breakout from the explosive pellet. Fireball simulations were performed using the HyBurn Computational Fluid Dynamics (CFD) package. Experimental OH-PLIF results were compared to synthetic OH-PLIF from post-processing of CFD simulations. From the comparison of experimental and synthetic OH-PLIF images, CFD is shown to replicate much of the flow structure observed in the experiments, revealing potential differences in turbulent length scales and OH kinetics. Furthermore, results provide significant advancement in experimental resolution of these harsh turbulent combustion environments and validate physical models thereof.

Detonator↗
DOE OSTI2024

Spatially distributed atmospheric boundary layer properties in Houston – A value-added observational dataset

Abstract In 2022, Houston, TX became a nexus for field campaigns aiming to further our understanding of the feedbacks between convective clouds, aerosols and atmospheric boundary layer (ABL) properties. Houston’s proximity to the Gulf of Mexico and Galveston Bay motivated the collection of spatially distributed observations to disentangle coastal and urban processes. This paper presents a value-added ABL dataset derived from observations collected by eight research teams over 46 days between 2 June - 18 September 2022. The dataset spans 14 sites distributed within a ~80-km radius around Houston. Measurements from three types of instruments are analyzed to objectively provide estimates of nine ABL parameters, both thermodynamic (potential temperature, and relative humidity profiles and thermodynamic ABL depth) and dynamic (horizontal wind speed and direction, mean vertical velocity, updraft and downdraft speed profiles, and dynamical ABL depth). Contextual information about cloud occurrence is also provided. The dataset is prepared on a uniform time-height grid of 1 h and 30 m resolution to facilitate its use as a benchmark for forthcoming numerical simulations and the fundamental study of atmospheric processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Planar shock-induced bubble collapse and jetting in water captured via X-ray phase contrast imaging

Shock wave–bubble interactions in water manifest rich dynamics driven by a combination of strong pressure and density mismatches. They have a wide variety of applications, including the injection of pharmaceuticals, and through scaling, enable the exploration of various aspects of high-energy-density systems such as inertial confinement fusion. In this work, the interaction between a micrometric nitrogen bubble and a planar shock wave, characterized by a Mach number of M = 1.24 and a peak pressure of p max = 0.57 , is experimentally recorded using ultra-high-speed x-ray phase contrast imaging. Highly resolved radiographs provide access to all phase discontinuities along the beam path, offering quantities such as the time-varying bubble size, the speed of a jet produced during the bubble collapse, and the time evolution of the shock wave front, which are critical benchmark data for numerical scheme validation. This study addresses the lack of well-characterized, repeatable, and high spatiotemporal resolution experiments at negative Atwood numbers by providing shock–bubble visualization and corresponding numerical simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Impact of CH 4 addition on the electron properties and electric field dynamics in a Ar nanosecond-pulsed dielectric barrier discharge

Non-equilibrium plasmas derive their low temperature reactivity from producing and driving energetic electrons and active species under large electric fields. Therefore, the impact of reactants on the plasma properties including electron number density, electric field, and electron temperature is critical for applications such as plasma CH 4 reforming. Due to experimental complexity, electron properties and the electric field are rarely measured together in the same discharge. Here, we combine time-resolved Thomson scattering and electric field induced second harmonic generation (EFISH) to probe electron temperature, electron density, and electric field strength in a 60 Torr CH 4 /Ar nanosecond-pulsed dielectric barrier discharge (ns-DBD) while varying the CH 4 mole fraction from 0 to 8%. These measurements are compared to a 1-D numerical model to benchmark its predictions and identify areas of uncertainty. Nonlinear coupling between CH 4 addition, electron temperature, electron density, and the electric field was directly observed. Contrary to previous measurements in He, the electron temperature increased with CH 4 mole fraction. This rise in electron temperature is identified as electron heating by residual electric fields that increased with larger CH 4 mole fraction. Moreover, the electron number density has been found to decrease rapidly with the increase of methane mole fraction. Comparison of these measurements with the model yielded better agreement at higher CH 4 mole fractions and with the usage of ab initio calculated Ar electron-impact cross-sections from the B-spline R-matrix (BSR) database. Furthermore, the calculated plasma properties are shown to be sensitive to the residual surface charge implanted on the quartz dielectric surfaces. Without considering surface charge in the simulations, the calculated electric field profiles agreed well with the measurements, but the electron properties were underpredicted by more than a factor of three. Therefore, measurements of either the electric field or electron properties measurements alone are insufficient to fully validate modelling predictions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗