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At least 1,459 records · Page 81

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NASA NTRS2018

A Higher-Order Space-Time Finite-Element Method for Moving-Body and Fluid-Structure Interaction Problems

We present a high-order finite-element method for moving body and fluid/structure interaction problems. Our solution strategy is based on a space-time discontinuous Galerkin (DG) spectral-element discretization which extends to arbitrary order of accuracy. The space-time DG discretization is a natural choice for moving body and fluid-structure interaction problems as moving surfaces are incorporated simply by considering curved space-time elements whose space-time faces align with the moving body. We present a discontinuous-Galerkin in time discretization for six-degree of motion modeling of rigid bodies, and a continuous-Galerkin discretization for equations of linear elasticity to generate curved space-time meshes. Numerical results for several simple 2D test cases are presented in order to verify the implementation of the different models. Finally we present a preliminary dynamic simulation of a parachute.

High-Order↗

NASA NTRS2021

Comparing Commercial and Research Computational Fluid Dynamic Codes Using High-Order Workshop Benchmark Problems

The commercial computational fluid dynamic (CFD) code ANSYS Fluent and multiple research CFD codes (ez4d with uses the conservation element and solution element (CESE) method and codes that use the flux reconstruction (FR) method) were tested using three different benchmark problems from the International Workshop for High-Order CFD Methods. The benchmark problems included the transonic Ringleb flow, vortex transport by uniform flow, and laminar boundary layer on a flat plate. Simulation results from all three benchmark problems showed that the Fluent solutions had less error than the ez4d solutions for a given degree of freedom. As expected, both the Fluent and ez4d solutions had larger errors for a given degree of freedom than the simulations that used the FR method because both Fluent and ez4d utilized a second-order scheme whereas the FR codes utilized a fourth-order scheme.

CFD↗

NASA NTRSDate not supplied

Extending Explicit Guidance Methods to Higher Dimensions, Additional Conditions, and Higher Order Integration

Guidance functions play critical roles in autonomy to steer vehicles and aircraft to the intended target or destination. Explicit guidance (E Guidance) solves the two-point boundary value problem with initial and final conditions for position and velocity. The original formulation of E Guidance involves translational acceleration commands with a direct relationship to time, and it is possible to modify E Guidance for rotational acceleration. Other extensions for E Guidance include higher dimensions, additional conditions, and higher-order integration of the linearly independent E Guidance functions. The most promising extension involves higher-order integration of the E Guidance functions, but it may be physically impractical by initially moving away from the target. This paper provides a brief overview of some methods that extend E Guidance to higher dimensions, utilize additional conditions, or perform higher-order integration, and if they satisfy the two-point boundary value problem.

explicit guidance↗

NASA NTRSDate not supplied

Extending Explicit Guidance Methods to Higher Dimensions, Additional Conditions, and Higher Order Integration

Guidance functions play critical roles in autonomy to steer vehicles and aircraft to the intended target or destination. Explicit guidance (E Guidance) solves the two-point boundary value problem with initial and final conditions for position and velocity. The original formulation of explicit guidance involves translational acceleration commands with a direct relationship to time, and it is possible to modify E Guidance for rotational acceleration. Other extensions for E Guidance include higher dimensions, additional conditions, and higher-order integration of the linearly independent E Guidance functions. The most promising extension involves higher-order integration of the E Guidance functions, but it may be physically impractical by initially moving away from the target. This paper provides a brief overview of some methods that extend E Guidance to higher dimensions, utilize additional conditions, or perform higher-order integration, and if they satisfy the two-point boundary value problem.

explicit guidance↗

NASA NTRSDate not supplied

New Capabilities and Improvements to the High-Order Glenn Flux Reconstruction Code

The Glenn Flux Reconstruction (GFR) code is a computational fluid dynamics (CFD) code under development at NASA Glenn Research Center. GFR is based on the high-order flux reconstruction (FR) method and provides a large-eddy simulation (LES) capability that is both accurate and efficient for complex aeropropulsion flows. Three significant new capabilities have been added to the code that improve its performance and functionality. First, a variety of explicit Runge-Kutta methods, including some with adaptive time stepping, were added to GFR with two methods offering a 33% improvement in time-to-solution. Second, GFR can now utilize fully unstructured, mixed-element meshes to more easily facilitate the grid generation process for complex geometries. Finally, a rotating reference frame capability has been added to GFR for solving rotating turbomachinery problems. A selection of results demonstrating these new capabilities are presented in this work. The Taylor-Green vortex problem is used to verify the new unstructured capability by showing similar accuracy and resolution for all element types. LES of the Turbulent Heat Flux Phase III (THX3) experiment with comparison to another high-order LES code and a popular Reynolds-averaged Navier-Stokes (RANS) code demonstrates the accuracy of the code for complex aeropropulsion flows. Finally, LES of a spacecraft cabin ventilation fan shows the ability of GFR to efficiently establish a fan performance map and identify operating points for further analysis at high orders of accuracy.

High-Order Methods↗

NASA NTRSDate not supplied

New Capabilities and Improvements to the High-Order Glenn Flux Reconstruction Code

Direct Numerical Simulations↗

DOE OSTI2016

Update on the Comparison of Second-Order Loads on a Tension Leg Platform for Wind Turbines: Preprint

In comparison to other kinds of floaters (like a spar or a semisubmersible), the tension leg platform has several notable advantages: its vertical motions are negligible, its weight is lighter, and its mooring system's footprint is smaller. Although a tension leg platform has a negligible response to first-order vertical wave loads, the second-order wave loads need to be addressed. This paper follows up on a verification study of second-order wave loads on a tension leg platform for wind turbines done by the Maritime Research Institute of The Netherlands and National Renewable Energy Laboratory and it brings some corrections to its conclusions.

17 WIND ENERGY↗

DOE OSTI2016

Update on the Comparison of Second-Order Loads on a Tension Leg Platform for Wind Turbines

17 WIND ENERGY↗

DOE OSTI2024

Reduced-Order Modeling of Multigroup Neutron Cross Sections for High-Temperature Gas-cooled Reactors

Abstract – Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗

DOE OSTI2024

Advanced Cross Section Library Generation using Reduced Order Models

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗

DOE OSTI2018

Impact of Physics Parameterization Ordering in a Global Atmosphere Model

Abstract Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid‐scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k ‐means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Engineering of Ferroic Orders in Thin Films by Anionic Substitution

Multiferroics are a unique class of materials where magnetic and ferroelectric orders coexist. The research on multiferroics contributes significantly to the fundamental understanding of the strong correlations between different material degrees of freedom and provides an energy-efficient route toward the electrical control of magnetism. While multiple ABO 3 oxide perovskites are identified as being multiferroic, their magnetoelectric coupling strength is often weak, necessitating the material search in different compounds. Here, the observation of room-temperature multiferroic orders in multi-anion SrNbO 3-x N x thin films is reported. In these samples, the multi-anion state enables the room-temperature ferromagnetic ordering of the Nb d-electrons. Simultaneously, ferroelectric responses that originate from the structural symmetry breaking associated are found with both the off-center displacements of Nb and the geometric displacements of Sr, depending on the relative O-N arrangements within the Nb-centered octahedra. So findings not only diversify the available multiferroic material pool but also demonstrate a new multiferroism design strategy via multi-anion engineering.

thin-films↗

DOE OSTI2019

An Ordered Ni 6 ‐Ring Superstructure Enables a Highly Stable Sodium Oxide Cathode

Abstract Sodium‐based layered oxides are among the leading cathode candidates for sodium‐ion batteries, toward potential grid energy storage, having large specific capacity, good ionic conductivity, and feasible synthesis. Despite their excellent prospects, the performance of layered intercalation materials is affected by both a phase transition induced by the gliding of the transition metal slabs and air‐exposure degradation within the Na layers. Here, this problem is significantly mitigated by selecting two ions with very different MO bond energies to construct a highly ordered Ni 6 ‐ring superstructure within the transition metal layers in a model compound (NaNi 2/3 Sb 1/3 O 2 ). By virtue of substitution of 1/3 nickel with antimony in NaNiO 2 , the existence of these ordered Ni 6 ‐rings with super‐exchange interaction to form a symmetric atomic configuration and degenerate electronic orbital in layered oxides can not only largely enhance their air stability and thermal stability, but also increase the redox potential and simplify the phase‐transition process during battery cycling. The findings reveal that the ordered Ni 6 ‐ring superstructure is beneficial for constructing highly stable layered cathodes and calls for new paradigms for better design of layered materials.

Wang, Peng‐Fei↗

DOE OSTI2023

Charge Density Wave Order and Electronic Phase Transitions in a Dilute d ‐Band Semiconductor

Abstract As one of the most fundamental physical phenomena, charge density wave (CDW) order predominantly occurs in metallic systems such as quasi‐1D metals, doped cuprates, and transition metal dichalcogenides, where it is well understood in terms of Fermi surface nesting and electron–phonon coupling mechanisms. On the other hand, CDW phenomena in semiconducting systems, particularly at the low carrier concentration limit, are less common and feature intricate characteristics, which often necessitate the exploration of novel mechanisms, such as electron–hole coupling or Mott physics, to explain. In this study, an approach combining electrical transport, synchrotron X‐ray diffraction, and density‐functional theory calculations is used to investigate CDW order and a series of hysteretic phase transitions in a dilute d ‐band semiconductor, BaTiS 3 . These experimental and theoretical findings suggest that the observed CDW order and phase transitions in BaTiS 3 may be attributed to both electron–phonon coupling and non‐negligible electron–electron interactions in the system. This work highlights BaTiS 3 as a unique platform to explore CDW physics and novel electronic phases in the dilute filling limit and opens new opportunities for developing novel electronic devices.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Minimizing Inter‐Lattice Strain to Stabilize Li‐Rich Cathode by Order–Disorder Control

Li-rich Mn-based layered (LMR) cathodes with anionic redox chemistry show great potential for next-generation sustainable Li-ion battery (LIB) applications due to the low cost and high energy density. However, the asynchronous structural evolutions with cycling in the heterogeneous composite structure of LMR lead to serious lattice strain and thus fast electrochemical decay, which hinders the commercialization of LMR cathodes. Here, in this study, an order–disorder coherent LMR cathode is demonstrated that exhibits a higher average voltage (by 0.25 V), negligible voltage decay (97.6% voltage retention after 100 cycles at 100 mA g −1 ), and enhanced cycling stability (98% capacity retention after 200 cycles at 100 mA g −1 ) compared to its layered oxide counterparts. It is proposed that this order–disorder coherent structure design can promote a more synchronous and homogeneous structure evolution during charge and discharge, thus minimizing lattice strain, which significantly prevents layer collapse and collective degradation at high voltage, improving the electrochemical stability. The study displays the feasibility of optimizing the performance of Li-rich cathode materials through a dedicated order–disorder structure control for sustainable energy storage.

Xu, Shenyang [Peking University, Shenzhen (China)]↗

DOE OSTI2018

Ordering and Grain Growth in Charged Block Copolymer Bulk Films: A Comparison of Solvent-Related Processes

While prior efforts have demonstrated that the morphologies of block copolymer (BC) bulk films can be controlled through judicious chemical design and thermal annealing, recent interest has focused on regulating the orientation of BC nanostructures and minimizing defects. Thermal processes developed to achieve this purpose for nonpolar BCs are not, however, suitable for orienting microphase-ordered BCs composed of at least one block with charged moieties that can form thermally stable ionic clusters. To overcome this challenge, we have previously applied solvent-vapor (SV) annealing to block ionomer (BI) bulk films composed of midblock-sulfonated pentablock copolymers and established that this approach yields highly ordered morphologies that display evidence of improved in-plane orientation. Here, we employ small-angle X-ray scattering to compare the effectiveness of three solvent-related processes-SV annealing, SV permeation, and SV sorption-on BI ordering and grain growth, and offer explanations for observed differences on the basis of thermodynamic- and transport-related considerations. As a result, differences in the experimental design of these solvent-related processes are found to affect nanostructural development, as evidenced by the extent of in-plane grain growth.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Liquid Crystalline Order and Electric Switching of Upconversion Luminescence in Colloidal Nanorod Suspensions

The polarization-dependent photon upconversion luminescence properties of large-scale orientationally ordered soft matter systems formed by colloidal nanorods dispersed in an isotropic solvent are studied. The electrostatically charged photon-upconverting nanorods form an isotropic dispersion at low concentrations, whereas orientational order and a nematic phase emerge at high concentrations. When an alternating electric field is applied, particles align in the direction of the electric field in both nematic and isotropic phases, though the nature of this electric switching is different in these two phases. Owing to the long-range orientational order in the nematic phase, the upconversion luminescence from the particles is polarized without an external field. Polarization dependence of these properties can also be electrically induced in an isotropic phase of the colloidal nanorods. Further, the dynamics of switching of photon upconversion luminescence in both nematic and isotropic dispersions are explored and their potential technological uses are discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2019

The Role of Ordering on the Thermoelectric Properties of Blends of Regioregular and Regiorandom Poly(3‐hexylthiophene)

Abstract The thermoelectric properties of semiconducting polymers are influenced by both the carrier concentration and the morphology that sets the pathways for charge transport. A combination of optical, morphological, and electrical characterization is used to assess the effect of the role of disorder on the thermoelectric properties of thin films of poly(3‐hexylthiophene) (P3HT) doped with 2,3,5,6‐tetrafluoro‐7,7,8,8‐tetracyanoquinodimethane (F 4 TCNQ). Controlled morphologies are formed by casting blends of regioregular (RR‐P3HT) and regiorandom (RRa‐P3HT) and then subsequently doped with F 4 TCNQ from the vapor phase. Optical spectroscopy and X‐ray scattering show that vapor phase doping induces order in the disordered regions of thin films and increases the long‐range connectivity of the film. The thermoelectric properties are assessed as a function of composition and it is shown that while the Seebeck coefficient is affected by structural ordering, the electrical conductivity and power factor are more strongly correlated with the long‐range connectivity of ordered domains.

Lim, Eunhee↗