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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Vacuum magnetic fields with exact quasisymmetry near a flux surface. Part 1. Solutions near an axisymmetric surface

While several results have pointed to the existence of exactly quasisymmetric fields on a surface (Garren & Boozer, Phys. Fluids B, vol. 3, 1991, pp. 2805–2821; 2822–2834; Plunk & Helander, J. Plasma Phys. , vol. 84, 2018, 905840205), we have obtained the first such solutions using a vacuum surface expansion formalism. We obtain a single nonlinear parabolic partial differential equation for a function $\eta$ such the field strength satisfies $B = B(\eta )$ . Closed-form solutions are obtained in cylindrical, slab and isodynamic geometries. Numerical solutions of the full nonlinear equations in general axisymmetric toroidal geometry are obtained, resulting in a class of quasihelical local vacuum equilibria near an axisymmetric surface. The analytic models provide additional insight into general features of the nonlinear solutions, such as localization of the surface perturbations on the inboard side. The local solutions thus obtained can be continued globally only for special initial surfaces.

Physics↗
DOE OSTI2024

On the force exerted on a non-spherical asymmetric dust grain from homogeneous, stationary, isotropic, non-magnetized plasma

Whereas the conventional wisdom suggests that the force between non-magnetized homogeneous, stationary, isotropic plasma, and the dust grain is only possible for the case of relative plasma–grain velocity, it is shown that stationary non-spherical asymmetric dust grain immersed in stationary, non-magnetized, isotropic plasma can experience a force caused by the grain–plasma interactions. The component of the force due to scattering of plasma particles in the limit of infinite Debye length is considered analytically. Both the particle scattering and absorption force components are modeled numerically in the limits of infinite and finite Debye length using a newly developed 2D3V Aspherical Particle-in-Cell code. The code simulates interactions of dust grain of selected non-spherical asymmetric shape with plasmas using dust shape conforming coordinates. Here, the simulations confirm the existence of the force on non-spherical asymmetric grain in stationary non-magnetized plasma and show that the plasma screening effects can lead to reversal of the force direction.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Numerical assessment of triply periodic minimal surfaces for direct air capture of carbon dioxide

Direct air capture (DAC) systems often consist of packing material wetted by a capture fluid that reacts with CO 2 in the airstream. The efficiency of the contactor is determined by a complex relationship of fluid dynamics, heat and mass transfer, contactor geometry, and chemical properties. The efficiency of the contactor must be balanced with other factors, primarily pressure drop through the system. Triply periodic minimal surfaces (TPMS) are a class of differential surfaces that have been explored in multiple engineering applications and have been shown to exhibit excellent performance when used in heat exchangers. Their tortuous path provides a high surface-to-volume ratio and favorable trade-off between contact area and pressure drop. In this work, a gyroid-type TPMS contactor was evaluated using computational fluid dynamics for a variety of geometric parameters to explore the potential benefit of TPMS shapes for DAC applications. A thin-film model was employed to model the flow and distribution of the capture solvent, allowing efficient simulations of TPMS structures at scale by eliminating the need for a computationally intensive interface capturing method. A liquid-gas mass transfer model was implemented in the commercial software STAR-CCM+ and used to predict the CO 2 capture efficiency and study the trade-off between capture performance and pressure drop through analysis of capture rates, mass transfer coefficients, and other relevant variables. TPMS contactors with a variety of geometric parameters and two capture solvent options were investigated to determine the effect of design choices on the operational performance of DAC systems. In conclusion, results showed that while contactor geometry is the dominant factor in efficiency and pressure drop, the physiochemical properties of the solvent are an important secondary influence on the contactor performance.

CFD↗
DOE OSTI2024

Medial axis and local thickness computation using the Fast Sweeping Method

This report describes an efficient and robust voxel-based methodology for computing the medial axis, local thickness, and distance-to-skeleton of arbitrary three-dimensional geometries. It is assumed that the object can be represented by an exact or approximate signed distance function on a discrete grid. The gradient of such function is used to formulate a hyperbolic partial differential equation (PDE) that models the collapse of the position vector in space. By exploiting the causality property of the PDE, the Fast Sweeping Method is able to obtain the solution in a finite number of sweeps independent of the mesh resolution. The intersection of characteristic lines leads to the formation of shocks and a discrete bisector function is used to identify the medial axis. The same PDE approach is used to compute the local thickness inside the object and obtain the distance-to-skeleton field. Multiple examples are given in two and three dimensions along with a resolution study. The methodology has optimal complexity and yields subsecond computational times for geometries with over a million zones on a single core. The methodology is also capable of parallelization across shared and distributed memory architectures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

LivermorE Al Projector for Computed Tomography Tasks

With recent computed tomography (CT) efforts using Artificial Intelligence (AI) and Deep Learning (DL)techniques, there is a strong need for differentiable forward projection models that can be integrated into existing DL frameworks. We developed a pytorch-based package library providing differentiable forward and back projection functions and classes to facilitate forward and back propagation of CT operations in the training procedure. This forward projectors support three CT projection geometries: cone, parallel and modular beams. This package can be used with both CPU and GPU with CUDA.

Kim, Hyojin↗
DOE OSTI2020

Monitoring the Possible Effects of Corroding Fuel Cladding in Nuclear Ponds: a Modified ROV for Storage Ponds - 20144

Nuclear ponds are used worldwide to store radioactive nuclear material, often for extended periods of time. The pond water conditions need to be closely monitored so that mitigation strategies can be put in place should any leakage of radioactive material occur. This paper describes the selection, development and on-site deployment of a bespoke system whose design was based on of-the-shelf components. The system is able to identify, locate and differentiate the leakage of radioactive material stored in nuclear ponds from the background activity of the water in the pond. The selection of an appropriate detector and monitoring geometry was supported by MCNP modelling which allowed a high degree of confidence in the proposed design. The development of the system allowed a real-time indication of the canister integrity, without incurring the increased operator doses from manual sampling operations that were previously used on site. The benefits of the developed system include the fact that the system is lightweight, easily deployable, retrievable, decontaminable and results in negligible waste products. Moreover, it is able to analyse the samples in-situ, in this way reducing the time needed to manually collect and send the samples to a laboratory for lengthy analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Sparse-grid discontinuous Galerkin methods for the Vlasov–Poisson–Lenard–Bernstein model

Sparse-grid methods have recently gained interest in reducing the computational cost of solving high-dimensional kinetic equations. In this paper, we construct adaptive and hybrid sparse-grid methods for the Vlasov–Poisson–Lenard–Bernstein (VPLB) model. This model has applications to plasma physics and is simulated in two reduced geometries: a 0x3v space homogeneous geometry and a 1x3v slab geometry. Here we use the discontinuous Galerkin (DG) method as a base discretization due to its high-order accuracy and ability to preserve important structural properties of partial differential equations. We utilize a multiwavelet basis expansion to determine the sparse-grid basis and the adaptive mesh criteria. We analyze the proposed sparse-grid methods on a suite of three test problems by computing the savings afforded by sparse-grids in comparison to standard solutions of the DG method. The results are obtained using the adaptive sparse-grid discretization library ASGarD.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Thermal Effects on Far-Field Distributed Acoustic Strain-Rate Sensors

Summary Fiber-optic cables cemented outside of the casing of an unconventional well measure crosswell strain changes during fracturing of neighboring wells with low-frequency distributed acoustic sensing (LF-DAS). As a hydraulic fracture intersects an observation well instrumented with fiber-optic cables, the fracture fluid injected at ambient temperatures can cool a section of the sensing fiber. Often, LF-DAS and distributed temperature sensing (DTS) cables are run in tandem, enabling the detection of such cooling events. The increasing use of LF-DAS for characterizing unconventional hydraulic fracture completions demands an investigation of the effects of temperature on the measured strain response by LF-DAS. Researchers have demonstrated that LF-DAS can be used to extract the temporal derivative of temperature for use as a differential-temperature-gradient sensor. However, differential-temperature-gradient sensing is predicated on the ability to filter strain components out of the optical signal. In this work, beginning with an equation for optical phase shift of LF-DAS signals, a model relating strain, temperature, and optical phase shift is explicitly developed. The formula provides insights into the relative strength of strain and temperature effects on the phase shift. The uncertainty in the strain-rate measurements due to thermal effects is estimated. The relationship can also be used to quantify uncertainties in differential-temperature-gradient sensors due to strain perturbations. Additionally, a workflow is presented to simulate the LF-DAS response accounting for both strain and temperature effects. Hydraulic fracture geometries are generated with a 3D fracture simulator for a multistage unconventional completion. The fracture width distributions are imported by a displacement discontinuity method (DDM) program to compute the strain rates along an observation well. An analytic model is used to approximate the temperature in the fracture. Using the derived formulae for optical phase shift, the model outputs are then used to compute the LF-DAS response at a fiber-optic cable, enabling the generation of waterfall plots including both strain and thermal effects. The model results suggest that before, during, and immediately following a fracture intersecting a well instrumented with fiber, the strain on the fiber drives the LF-DAS signal. However, at later times, as completion fluid cools the observation well, the temperature component of the LF-DAS signal can be equal to or exceed the strain component. The modeled results are compared to a published field case in an attempt to enhance the interpretation of LF-DAS waterfall plots. Finally, we propose a sensing configuration to identify the events when “wet fractures” (fractures with fluids) intersect the observation well.

Engineering↗
DOE OSTI2021

M3 milestone: Advanced contact 2021

This report describes advanced contact approaches and implementations in FY21 for use in emerging reactors with geometries that differ from LWR/EBR-II cylindrical fuel. Contact remains a challenging and crucially important component of our modeling toolkit. While significant improvements have been made through mortar and automatic differentiation, we explored advanced approaches (i.e., dual mortar) that yields better conditioned systems and will improve the robustness and performance of BISON contact problems. This effort is relevant to emerging reactor types, such as micro reactors and the corresponding complex and numerous contact surfaces. In this report, improvements of the mortar-based contact formulation are described. Benchmark problems and BISON assessment cases are included to demonstrate the improvements and advantages that are brought by the recent capability. Remaining issues are discussed and corresponding development plans are outlined.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Modulating Transition Metal Reactivity with Force

The reactivity and selectivity of a transition metal catalyst is intimately related to its ligand-sphere geometry, and, in many cases, the ideal ligand geometry for one step of a catalytic cycle is poorly matched to the ideal ligand geometry for another. For this reason, methods for reversibly modulating ligand geometry on the time scale of catalytic turnover or monomer enchainment are highly desirable. Mechanical force represents a heretofore untapped approach to modulate catalyst geometry and/or reactivity, with the potential to do so on the timescale of catalytic turnover or monomer enchainment. Macroscopic mechanical forces are large, directional and localized to an extent that differentiates them from other forms of energy input such as heat or light. Here, in this Concept, we describe our efforts to address the fundamental challenges associated with force-modulated transition metal catalysis by employing molecular force probe ligands comprising a stiff stilbene photoswitch tethered to rotationally flexible biaryl bisphosphine ligand. Our efforts to date include the modulation of catalytic activity through force-mediated ligand perturbations, quantification of the force-coupled ligand effects on the energetics of elementary organometallic transformations, and evaluation of the mechanisms of force transduction in these systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Nanostructural and rheological transitions of pH-responsive supramolecular systems involving a zwitterionic amphiphile and a triamine

Supramolecular aqueous complexes of a synthesized zwitterionic surfactant, 2-(dimethyl(octadecyl)ammonio)acetate (stearyl betaine) and diethylenetriamine, have been found to display pH-tunable rheological properties without the need for a co-surfactant. For this supramolecular system, the dynamically changing interplay among the constituents is responsible for the rich phase behavior including hollow nanotubules, bilayers, and vesicles. A further hypothesis is that hollow nanotubular structure is highly desirable for achieving chain entanglement geometries with reduced mesh size. The rheological properties of the suspension were measured using a rotational rheometer. An analysis using zero-shear viscosities at various temperatures as well as differential scanning calorimetry(DSC) helped shed light on thermodynamic and phase transitions taking place. The morphology of the suspension was analyzed by using a combination of small angle x-ray scattering(SAXS) and atomic force microscopy(AFM). Large steady-shear viscosities (up to ~160 Pa.s) and viscoelastic behavior was observed in acidic conditions which diminished upon increasing the pH. A novel analysis consisting of measured thermodynamic quantities such as activation energy(E a ) and enthalpy of transition(ΔH T ) further allude to the rich pH-sensitive nanoarchitecture of the system. Rather than commonly observed wormlike micelles, hollow nanotubules, as long as 1.6 µm were observed at pH 4 which disintegrated to bilayer sheets and vesicles upon increasing pH. Finally, gaining a comprehensive understanding from all the results, a transition mechanism between different suspension architectures was proposed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimization using pathwise algorithmic derivatives of electromagnetic shower simulations

Among the well-known methods to approximate derivatives of expectancies computed by Monte-Carlo simulations, averages of pathwise derivatives are often the easiest one to apply. Computing them via algorithmic differentiation typically does not require major manual analysis and rewriting of the code, even for very complex programs like simulations of particle-detector interactions in high-energy physics. However, the pathwise derivative estimator can be biased if there are discontinuities in the program, which may diminish its value for applications. This work integrates algorithmic differentiation into the electromagnetic shower simulation code HepEmShow based on G4HepEm, allowing us to study how well pathwise derivatives approximate derivatives of energy depositions in a sampling calorimeter with respect to parameters of the beam and geometry. We found that when multiple scattering is disabled in the simulation, means of pathwise derivatives converge quickly to their expected values, and these are close to the actual derivatives of the energy deposition. Additionally, we demonstrate the applicability of this novel gradient estimator for stochastic gradient-based optimization in a model example.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Picosecond magneto-optic thermometry measurements of nanoscale thermal transport in AlN thin films

The thermal conductivity Λ of wide bandgap semiconductor thin films, such as AlN, affects the performance of high-frequency devices, power devices, and optoelectronics. However, accurate measurements of Λ in thin films with sub-micrometer thicknesses and Λ > 100 W m -1 K -1 is challenging. Widely used pump/probe metrologies, such as time–domain thermoreflectance (TDTR) and frequency–domain thermoreflectance, lack the spatiotemporal resolution necessary to accurately quantify thermal properties of sub-micrometer thin films with high Λ. In this work, we use a combination of magneto-optic thermometry and TiN interfacial layers to significantly enhance the spatiotemporal resolution of pump/probe thermal transport measurements. We use our approach to measure Λ of 100, 400, and 1000 nm AlN thin films. We coat AlN thin films with a ferromagnetic thin-film transducer with the geometry of (1 nm-Pt/0.4 nm-Co) x3 /(2 nm-TiN). This PtCo/TiN transducer has a fast thermal response time of <50 ps, which allows us to differentiate between the thermal response of the transducer, AlN thin film, and substrate. For the 100, 400, and 1000 nm thick AlN films, we determine Λ to be 200 ± 80, 165 ± 35, and 300 ± 70 W m -1 K -1 , respectively. We conclude with an uncertainty analysis that quantifies the errors associated with pump/probe measurements of thermal conductivity, as a function of transducer type, thin-film thermal conductivity, and thin-film thickness. Time resolved magneto-optic Kerr effect experiments can measure films that are three to five times thinner than is possible with standard pump/probe metrologies, such as TDTR. This advance in metrology will enable better characterization of nanoscale heat transfer in high thermal conductivity material systems like wide bandgap semiconductor heterostructures and devices.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strongly nonlinear wave propagation in elasto-plastic metamaterials: Low-order dynamic modeling

Nonlinear elastic metamaterials are known to support a variety of dynamic phenomena that enhance our capacity to manipulate elastic waves. Since these properties stem from complex, subwavelength geometry, full-scale dynamic simulations are often prohibitively expensive at scales of interest. Prior studies have therefore utilized low-order effective medium models, such as discrete mass-spring lattices, to capture essential properties in the long-wavelength limit. While models of this type have been successfully implemented for a wide variety of nonlinear elastic systems, they have predominantly considered dynamics depending only on the instantaneous kinematics of the lattice, neglecting history-dependent effects, such as wear and plasticity. Here, to address this limitation, the present study develops a lattice-based modeling framework for nonlinear elastic metamaterials undergoing plastic deformation. Due to the history- and rate-dependent nature of plasticity, the framework generally yields a system of differential-algebraic equations whose computational cost is significantly greater than an elastic system of comparable size. We demonstrate the method using several models inspired by classical lattice dynamics and continuum plasticity theory and explore means to obtain empirical plasticity models for general geometries, thereby gaining insight into the influence of microstructural plasticity on effective material performance, which can be used to improve the design of nonlinear mechanical metamaterials.

Dynamic simulation↗
DOE OSTI2025

Inferring fracture dilation and shear slip from surface deformation utilising trained surrogate models

An important task in energy and CO 2 storage (sequestration) in the subsurface is to verify that the surrounding fractures and faults are not activated, acting as leakage pathways. This is achievable through effective and efficient Measurement, Monitoring and Verification (MMV) plans. In this work, two surrogate models are trained to captures dilation (opening) and shear deformation of fractures, and the associated surface deformation. The trained surrogate model, based on conditional Generative-Adversarial Networks (cGAN) receives fracture apertures from dilational fractures together with fracture slips from shear fractures and predicts the combined surface deformation. An inversion algorithm based on Bayesian framework is proposed to identify the geometry of both types of fractures, as well as volume of dilational fractures and deformation moment induced by shear fractures, all from the measured surface deformation data. The inversion algorithm utilises the Differential Evolution (DE) optimisation technique that has the superior performance in finding the global minimum of cost function. The proposed surrogate-assisted inversion successfully inferred the unknown dip, dip direction and the volume of the dilational fractures as well as the induced deformation moment in shear fractures. The model was further tested for the inversion of a field hydraulic fracturing tilt dataset applying different scenarios with varying unknowns to show the model's performance, as well as incorporating shear deformation for better match with the observed data.

Dilation and shear↗
DOE OSTI2024

The Computational Analysis of a Generic Hypersonic Store Separation

Many current hypersonic vehicles involve a main vehicle from which components separate during flight and presents simulation challenges such as shock-shock interactions, highly nonlinear interactions, and shock wave boundary layer interactions. These aerodynamic phenomena influence the attitude and trajectory of each object, which needs to be understood before large-scale experiments can be run. To gain a generic understanding of the process, high-fidelity Reynolds-averaged Navier-Stokes solutions are performed on a conical vehicle geometry passing through an oblique shock wave that is representative of different configurations and scenarios. Trajectory and applied forces are tracked and show the vehicle’s dynamics are predominantly the result of differential flow incidence angles causing a strong shock; this leads to a large pressure increase over a fraction of the vehicle, which influences pitch. The vehicle appears to follow conventional stability theory with detached eddy simulation and small disturbances in initial attitude shown to have minimal influence on the scenario.

Savery, Ryan↗
DOE OSTI2023

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗
DOE OSTI2023

Solution–Doped Donor–Acceptor Copolymers Based on Diketopyrrolopyrrole and 3, 3'–Bis (2–(2–(2–Methoxyethoxy) Ethoxy) ethoxy)–2, 2'–Bithiophene Exhibiting Outstanding Thermoelectric Power Factors with p –Dopants

The design of polymeric semiconductors exhibiting high electrical conductivity (σ) and thermoelectric power factor (PF) will be vital for flexible large-area electronics. In this work, four polymers based on diketopyrrolopyrrole (DPP), 2,3-dihydrothieno[3,4-b][1,4]dioxine (EDOT), thieno[3,2-b]thiophene (TT), and 3, 3'-bis (2-(2-(2-methoxyethoxy) ethoxy) ethoxy)-2, 2'-bithiophene (MEET) are investigated as side-chains, with the MEET polymers newly synthesized for this study. These polymers are systematically doped with tetrafluorotetracyanoquinodimethane ( F 4 TCNQ), CF3SO3H, and the synthesized dopant Cp(CN) 3 -(COOMe) 3 , differing in geometry and electron affinity. The DPP-EDOT-based polymer containing MEET as side-chains exhibits the highest conductivity (σ) ≈700 S cm–1 in this series with the acidic dopant (CF 3 SO 3 H). This polymer also shows the lowest oxidation potential by cyclic voltammetry (CV), the strongest intermolecular interactions evidenced by differential scanning calorimetry (DSC), and has the most oxygen-based functionality for possible hydrogen bonding and ionic screening. Other polymers exhibit high σ ≈300–500 S cm–1 and power factor up to 300 µW m –1 K –2 . The mechanism of conductivity is predominantly electronic, as validated by time-dependent conductance studies and transient thermo voltage monitoring over time, including for those doped with the acid. Furthermore, these materials maintain significant thermal stability and air stability over ≈6 weeks. Density functional theory calculations reveal molecular geometries and inform about frontier energy levels. Raman spectroscopy, in conjunction with scanning electron microscopy (SEM-EDS) and x-ray diffraction, provides insight into the solid-state microstructure and degree of phase separation of the doped polymer films. Infrared spectroscopy enables this study to further quantify the degree of charge transfer from polymer to dopant.

36 MATERIALS SCIENCE↗