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At least 1,531 records · Page 85

Reduced order models for nonlinear aerodynamics

Reduced order models are needed for reliable, efficient and accurate prediction of aerodynamic forces to analyze fluid structure interaction problems in turbomachinery, including propfans. Here, a finite difference, time marching Navier-Stokes code is validated for unsteady airfoil motion by comparing results with those from classical potential flow. The Navier-Stokes code is then analyzed for calculation of primitive and exact estimates of eigenvalues and eigenvectors associated with fluid-airfoil interaction. A variational formulation for the Euler equations and Navier-Stokes equations will be the basis for reduction of order through an eigenvector transformation.

Mahajan, Aparajit J.↗

Theory Aided Design of Active and Durable Nanoscale Cathode Catalysts (Final Report)

One of the greatest technological hurdles to deployment of fuel cells relates to the sluggish activity, low durability and the high cost of the catalysts that are currently employed. For automotive PEM fuel cells to become commercially viable, the Pt-specific power density would need to be reduced to less than 0.2gPt/kW (at cell voltages >0.65 V). This would require the Pt loadings to be less than 0.15 mg Pt /cm 2 MEA within the membrane electrode assembly. This could be achieved by enhancing the catalytic activity at the cathode, thus lowering its overpotential. Various different Pt-alloys have shown 2-4 times enhanced activities over Pt alone but still suffer some of the same durability issues as that of the pure Pt. There is a general loss of active Pt due to dissolution and sintering. While there have been a number of elegant fundamental experimental and theoretical studies on ideal single crystal Pt and Pt alloy surfaces which have helped to elucidate the factors that control the activity, there have been very few fundamental studies focused on the stability, reactivity and durability of well-defined Pt nanoparticles. We carried out ab initio density functional theory together with a novel double reference method that we developed to simulate constant potential electrochemical systems in order to model the electrocatalytic reduction of oxygen over model Pt alloy surfaces and nanoparticles. These simulations were used to probe the factors that control the electrocatalytic activity, guide the potential selection of new materials and test their stability under reaction conditions. Ab initio calculations were used to determine the reaction energies and activation barriers for a comprehensive array of different elementary adsorption, desorption, surface reaction and diffusion steps over Pt and Pt alloys involved in the electroreduction of oxygen as a function of surface coverage, the electrochemical potential and temperature. The calculations were used to simulate the potential dependent adsorption and surface reaction energies along with activation barriers in order to determine the kinetics for different surface structures and structural features (step edge and corner sites) to provide the necessary input for kinetic Monte Carlo simulations to follow the rates of reaction. More coarse-grained simulated annealing methods were used to help establish the lowest energy structures and morphologies for different Pt and Pt-alloy nanoparticles that form. The results from the DFT calculations were used to establish an ab initio-derived kinetic database that was used in both 2D and 3D kinetic Monte Carlo simulations that were used to follow the electrocatalytic performance over different particle sizes, shapes and compositions. The ab initio calculations together with the kinetic Monte Carlo simulations were used to complete the following objectives: 1) Determine the controlling elementary reaction pathways and intrinsic kinetics involved in ORR and their potential dependent behavior; 2) Establish the influence of the extrinsic reaction environment including surface structure, alloy composition and spatial arrangement and the humidity on ORR kinetics; 3) Elucidate the effects of particle size and morphology as well as the atomic structure and composition of nanoparticles of Pt, Pt 3 Co, Pt 3 Ni, Pt 3 Fe and other Pt-alloys on the electrocatalytic activity and reaction selectivity; 5) Construct surface Pourbaix phase diagrams for different Pt and Pt-alloys in order to map out the most stable surface phases for different material compositions and reaction conditions; 6) Elucidate the mechanisms that control dissolution and re-deposition of Pt.

08 HYDROGEN↗

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

Discrete models of fluids: spatial averaging, closure and model reduction

We consider semidiscrete ODE models of single-phase fluids and two-fluid mixtures. In the presence of multiple fine-scale heterogeneities, the size of these ODE systems can be very large. Spatial averaging is then a useful tool for reducing computational complexity of the problem. The averages satisfy exact balance equations of mass, momentum, and energy. These equations do not form a satisfactory continuum model because evaluation of stress and heat flux requires solving the underlying ODEs. To produce continuum equations that can be simulated without resolving microscale dynamics, we recently proposed a closure method based on the use of regularized deconvolution. Here we continue the investigation of deconvolution closure with the long term objective of developing consistent computational upscaling for multiphase particle methods. The structure of the fine-scale particle solvers is reminiscent of molecular dynamics. For this reason we use nonlinear averaging introduced for atomistic systems by Noll, Hardy, and Murdoch-Bedeaux. We also consider a simpler linear averaging originally developed in large eddy simulation of turbulence. We present several simple but representative examples of spatially averaged ODEs, where the closure error can be analyzed. Based on this analysis we suggest a general strategy for reducing the relative error of approximate closure. For problems with periodic highly oscillatory material parameters we propose a spectral boosting technique that augments the standard deconvolution and helps to correctly account for dispersion effects. We also conduct several numerical experiments, one of which is a complete mesoscale simulation of a stratified two-fluid flow in a channel. In this simulation, the operation count per coarse time step scales sublinearly with the number of particles.

Multiscale modeling, discrete models, fluid flow↗

Evaluation of Lightning Induced Effects in a Graphite Composite Fairing Structure

Defining the electromagnetic environment inside a graphite composite fairing due to near-by lightning strikes is of interest to spacecraft developers. This effort develops a transmission-line-matrix (TLM) model with a CST Microstripes to examine induced voltages. on interior wire loops in a composite fairing due to a simulated near-by lightning strike. A physical vehicle-like composite fairing test fixture is constructed to anchor a TLM model in the time domain and a FEKO method of moments model in the frequency domain. Results show that a typical graphite composite fairing provides adequate shielding resulting in a significant reduction in induced voltages on high impedance circuits despite minimal attenuation of peak magnetic fields propagating through space in near-by lightning strike conditions.

Trout, Dawn H.↗

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗

Towards validation of combined-accelerated stress testing through failure analysis of polyamide-based photovoltaic backsheets

Abstract Novel methods for advancing reliability testing of photovoltaic (PV) modules and materials have recently been developed. Combined-accelerated stress testing (C-AST) is one such method which has demonstrated reliable reproduction of some field-failures which were not reproducible by standard certification tests. To increase confidence and assist in the development of C-AST, and other new testing protocols, it is important to validate that the failure modes observed and mechanisms induced are representative of those observed in the field, and not the product of unrealistic stress conditions. Here we outline a method using appropriate materials characterization and modelling to validate the failure mechanisms induced in C-AST such that we can increase confidence in the test protocol. The method is demonstrated by applying it to a known cracking failure of a specific polyamide (PA)-based backsheet material. We found that the failure of the PA-based backsheet was a result of a combination of stress factors. Photo-oxidation from ultra-violet (UV) radiation exposure caused a reduction in fracture toughness, which ultimately lead to the cracking failure. We show that the chemical and structural changes observed in the backsheet following C-AST aging were also observed in field-aged samples. These results increase confidence that the conditions applied in C-AST are representative of the field and demonstrates our approach to validating the failure mechanisms induced.

14 SOLAR ENERGY↗

Functional Characterization and Structural Insights Into Stereoselectivity of Pulegone Reductase in Menthol Biosynthesis

Monoterpenoids are the main components of plant essential oils and the active components of some traditional Chinese medicinal herbs like Mentha haplocalyx Briq ., Nepeta tenuifolia Briq ., Perilla frutescens (L.) Britt and Pogostemin cablin (Blanco) Benth. Pulegone reductase is the key enzyme in the biosynthesis of menthol and is required for the stereoselective reduction of the Δ 2,8 double bond of pulegone to produce the major intermediate menthone, thus determining the stereochemistry of menthol. However, the structural basis and mechanism underlying the stereoselectivity of pulegone reductase remain poorly understood. In this study, we characterized a novel (-)-pulegone reductase from Nepeta tenuifolia ( Nt PR), which can catalyze (-)-pulegone to (+)-menthone and (-)-isomenthone through our RNA-seq, bioinformatic analysis in combination with in vitro enzyme activity assay, and determined the structure of (+)-pulegone reductase from ( Mp PR) by using X-ray crystallography, molecular modeling and docking, site-directed mutagenesis, molecular dynamics simulations, and biochemical analysis. We identified and validated the critical residues in the crystal structure of Mp PR involved in the binding of the substrate pulegone. We also further identified that residues Leu56, Val282, and Val284 determine the stereoselectivity of the substrate pulegone, and mainly contributes to the product stereoselectivity. This work not only provides a starting point for the understanding of stereoselectivity of pulegone reductases, but also offers a basis for the engineering of menthone/menthol biosynthetic enzymes to achieve high-titer, industrial-scale production of enantiomerically pure products.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Designing Quaternary and Quinary Refractory-Based High-Entropy Alloys: Statistical Analysis of Their Lattice Distortion, Mechanical, and Thermal Properties

The rapid evolution in materials science has resulted in a significant interest in high-entropy alloys (HEAs) for their unique properties. This study focuses on understanding both quaternary and quinary body-centered cubic (BCC) of 12 refractory-based HEAs, and on analysis of their electronic structures, lattice distortions, mechanical, and thermal properties. A comprehensive assessment is undertaken by means of density functional theory (DFT)-based first principles calculations. It is well known that multiple constituents lead to notable lattice distortions, especially in quinary HEAs. This distortion, in turn, has significant implications on the electronic structure that ultimately affect mechanical and thermal behaviors of these alloys such as ductility, lattice thermal conductivity, and toughness. Our in-depth analysis of their electronic structures revealed the role of valence electron concentration and its correlation with bond order and mechanical properties. Local lattice distortion (LD) was investigated for these 12 HEA models. M1 (WTiVZrHf), M7 (TiZrHfW), and M12 (TiZrHfVNb) have the highest LD whereas the models M3 (MoTaTiV), M5 (WTaCrV), M6 (MoNbTaW), and M9 (NbTaTiV) have the less LD. Furthermore, we investigated the thermal properties focusing on Debye temperature (ΘD), thermal conductivity (κ), Grüneisen parameter (γα), and dominant phonon wavelength (λdom). The NbTaTiV(M9) and TiVNbHf(M10) models have significantly reduced lattice thermal conductivities (κL). This reduction is due to the mass increase and strain fluctuations, which in turn signify lattice distortion. The findings not only provide an understanding of these promising materials but also offer guidance for the design of next-generation HEAs with properties tailored for potential specific applications.

Materials Science↗

Aeroelastic Tailoring of the NASA Common Research Model via Novel Material and Structural Configurations

This work explores the use of tow steered composite laminates, functionally graded metals (FGM), thickness distributions, and curvilinear rib/spar/stringer topologies for aeroelastic tailoring. Parameterized models of the Common Research Model (CRM) wing box have been developed for passive aeroelastic tailoring trade studies. Metrics of interest include the wing weight, the onset of dynamic flutter, and the static aeroelastic stresses. Compared to a baseline structure, the lowest aggregate static wing stresses could be obtained with tow steered skins (47% improvement), and many of these designs could reduce weight as well (up to 14%). For these structures, the trade-off between flutter speed and weight is generally strong, although one case showed both a 100% flutter improvement and a 3.5% weight reduction. Material grading showed no benefit in the skins, but moderate flutter speed improvements (with no weight or stress increase) could be obtained by grading the spars (4.8%) or ribs (3.2%), where the best flutter results were obtained by grading both thickness and material. For the topology work, large weight reductions were obtained by removing an inner spar, and performance was maintained by shifting stringers forward and/or using curvilinear ribs: 5.6% weight reduction, a 13.9% improvement in flutter speed, but a 3.0% increase in stress levels. Flutter resistance was also maintained using straightrotated ribs although the design had a 4.2% lower flutter speed than the curved ribs of similar weight and stress levels were higher. These results will guide the development of a future design optimization scheme established to exploit and combine the individual attributes of these technologies.

Jutte, Christine V.↗

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗

Anisotropic Mach Cone Aligned Mesh Adaptation for Low Boom Simulations

An automated off-body Mach cone aligned structured curvilinear grid generation procedure is presented for near-field computational fluid dynamics simulations. This procedure combines output-based indicators and mesh redistribution to perform anisotropic mesh adaptation while maintaining Mach cone alignment. Automation is achieved through a novel direction-based adaptation indicator formulation. The adaptation procedure is demonstrated on the JAXA Wing Body geometry and X-59 C608 demonstrator model from the Second and Third AIAA Sonic Boom Prediction Workshops, respectively. It is demonstrated that anisotropic mesh adaptation may result in a greater than fifty percent reduction in resource usage required to achieve the same level of accuracy as uniform and user constructed Mach cone aligned grids for near-field pressure signatures, ground-level overpressure signatures, and loudness metrics.

CST↗

Cementation of Nuclear Wastes: From Past to Future in a Sustainable Approach - 18266

Cementation of nuclear wastes is a widespread technology due to several factors such as excellent feedback from past experience, simplicity of implementation and versatility. Indeed, as nuclear wastes come in many physical states (bulk wastes, powders, sludges), cementation is the immobilisation process that can easily accommodate this large range of wastes provided the appropriate mixing technology is used: heterogenous cementation (grouting of bulky wastes) or homogenous cementation (intermixing process between the powder or the sludge and the cementitious material). However, nuclear wastes equally present an important chemical variability. This is especially true as New Areva's range of nuclear activities covers the entire fuel cycle: mining, conversion, enrichment and recycling and dismantling and decommissioning. The chemical interactions between the waste and the cement matrix are carefully studied by New Areva's R and D teams in order to provide comprehensive solutions by developing cement formulations which are adapted to wastes characteristics. The aim of the studies is to obtain cement waste-forms that meet the waste acceptance criteria, the final product being thus in perfect adequacy with the disposal requirements. For over 30 years New Areva has been developing cement formulations adapted to the physical and chemical specificities of the wastes accounting for constrains imposed by waste characteristics. The overall approach includes the definition of the appropriate cement composition at laboratory scale, engineering design, equipment manufacturing, testing and commissioning of the cementation facilities. With this strong technical background, a specific methodology has been developed by New Areva teams in order to allow a rapid screening of possible solutions for a given waste (in terms of cement chemistry adapted to the waste) in a learn-fast approach that is based on theoretical analysis and small-scale tests. The methodology was applied for wastes presenting a complex nature (such as reactive metals, ion exchange resins, oils and solvents, mercury, etc), known to interact with Portland cement from a chemical point of view and leading to durability issues of the wasteform (swelling, strength reduction, leaching) and thus reducing the final waste loading. Once the screening process is over, the main drivers for choosing the most appropriate solution to be further developed at pilot scale are: reducing the overall volume and the impact of the final waste package, ensure the waste package performance as defined by the disposal requirements and control the long-term behaviour in final disposal. Moreover, a modelling approach is addressed, aiming to develop a thermo-chemo-mechanical (THM) concrete models that are able to predict the behaviour of the structure (waste form) in time. The aim of the present paper is to describe the main principles within the developed methodology and illustrate it by using a few specific examples. Several distinct cement formulations are developed for complex wastes, limiting the chemical interaction between the cement matrix and the given wastes, obtaining better waste loadings and better overall durability behaviour which facilitates long term behaviour demonstration. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DHIGLS: DRAO H I intermediate galactic latitude survey

Observations of Galactic H i gas for seven targeted regions at intermediate Galactic latitude are presented at 1{sup ′} angular resolution using data from the DRAO Synthesis Telescope (ST) and the Green Bank Telescope (GBT). The DHIGLS data are the most extensive arcminute-resolution measurements of the diffuse atomic interstellar medium beyond those in the Galactic plane. The acquisition, reduction, calibration, and mosaicking of the DRAO ST data and the cross calibration and incorporation of the short-spacing information from the GBT are described. The high quality of the resulting DHIGLS products enables a variety of new studies in directions of low Galactic column density. We analyze the angular power spectra of maps of the integrated H i emission (column density) from the data cubes for several distinct velocity ranges. In fitting power-spectrum models based on a power law, but including the effects of the synthesized beam and noise at high spatial frequencies, we find exponents ranging from −2.5 to −3.0. Power spectra of maps of the centroid velocity for these components give similar results. These exponents are interpreted as being representative of the three-dimensional density and velocity fields of the atomic gas, respectively. We find evidence for dramatic changes in the H i structures in channel maps over even small changes in velocity. This narrow line emission has counterparts in absorption spectra against bright background radio sources, quantifying that the gas is cold and dense and can be identified as the cold neutral medium phase. Fully reduced DHIGLS H i data cubes and other data products are available at www.cita.utoronto.ca/DHIGLS.

79 ASTRONOMY AND ASTROPHYSICS↗

A Computational and Experimental Study of Coflow Laminar Methane/Air Diffusion Flames: Effects of Fuel Dilution, Inlet Velocity, and Gravity

The influences of fuel dilution, inlet velocity, and gravity on the shape and structure of laminar coflow CH4-air diffusion flames were investigated computationally and experimentally. A series of nitrogen-diluted flames measured in the Structure and Liftoff in Combustion Experiment (SLICE) on board the International Space Station was assessed numerically under microgravity (mu g) and normal gravity (1g) conditions with CH4 mole fraction ranging from 0.4 to 1.0 and average inlet velocity ranging from 23 to 90 cm/s. Computationally, the MC-Smooth vorticity-velocity formulation was employed to describe the reactive gaseous mixture, and soot evolution was modeled by sectional aerosol equations. The governing equations and boundary conditions were discretized on a two-dimensional computational domain by finite differences, and the resulting set of fully coupled, strongly nonlinear equations was solved simultaneously at all points using a damped, modified Newton's method. Experimentally, flame shape and soot temperature were determined by flame emission images recorded by a digital color camera. Very good agreement between computation and measurement was obtained, and the conclusions were as follows. (1) Buoyant and nonbuoyant luminous flame lengths are proportional to the mass flow rate of the fuel mixture; computed and measured nonbuoyant flames are noticeably longer than their 1g counterparts; the effect of fuel dilution on flame shape (i.e., flame length and flame radius) is negligible when the flame shape is normalized by the methane flow rate. (2) Buoyancy-induced reduction of the flame radius through radially inward convection near the flame front is demonstrated. (3) Buoyant and nonbuoyant flame structure is mainly controlled by the fuel mass flow rate, and the effects from fuel dilution and inlet velocity are secondary.

flames↗

Uncertainty quantification in multiscale simulation of woven fiber composites

We report woven fiber composites have been increasingly employed as light-weight materials in aerospace, construction, and transportation industries due to their superior properties. These materials possess a hierarchical structure that necessitates the use of multiscale simulations in their modeling. To account for the inherent uncertainty in materials, such simulations must be integrated with statistical uncertainty quantification (UQ) and propagation (UP) methods. However, limited advancement has been made in this regard due to the significant computational costs and complexities in modeling spatially correlated structural variations coupled at different scales. In this work, a non-intrusive approach is proposed for multiscale UQ and UP to address these limitations. We introduce the top-down sampling method that allows to model non-stationary and continuous (but not differentiable) spatial variations of uncertainty sources by creating nested random fields (RFs) where the hyperparameters of an ensemble of RFs is characterized by yet another RF. We employ multi-response Gaussian RFs in top-down sampling and leverage statistical techniques (such as metamodeling and dimensionality reduction) to address the considerable computational costs of multiscale simulations. We apply our approach to quantify the uncertainty in a cured woven composite due to spatial variations of yarn angle, fiber volume fraction, and fiber misalignment angle. Finally, our results indicate that, even in linear analysis, the effect of uncertainty sources on the material’s response could be significant.

42 ENGINEERING↗

Microstructural evolution of NF709 (20Cr–25Ni–1.5MoNbTiN) under neutron irradiation

In this study, because of its superior creep and corrosion resistance as compared with general austenitic stainless steels, NF709 has emerged as a candidate structural material for advanced nuclear reactors. To obtain fundamental information about the radiation resistance of this material, this study examined the microstructural evolution of NF709 subjected to neutron irradiation to 3 displacements per atom at 500 °C. Transmission electron microscopy, scanning electron microscopy, and high-energy x-ray diffraction were employed to characterize radiation-induced segregation, Frank loops, voids, as well as the formation and reduction of precipitates. Radiation hardening of ~76% was estimated by nanoindentation, approximately consistent with the calculation according to the dispersed barrier-hardening model, suggesting Frank loops as the primary hardening source.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗