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At least 1,045 records · Page 58

First-principles and cluster expansion study of the effect of magnetism on short-range order in Fe–Ni–Cr austenitic stainless steels

Short-range order (SRO), the regular and predictable arrangement of atoms over short distances, alters the mechanical properties of technologically relevant structural materials such as medium/high entropy alloys and austenitic stainless steels. In this study, we present a generalized spin cluster expansion (CE) model and show that magnetism is a primary factor influencing the level of SRO present in austenitic Fe-Ni-Cr alloys. The spin CE consists of a chemical cluster expansion combined with an Ising model for Fe-Ni-Cr austenitic alloys. It explicitly accounts for local magnetic exchange interactions, thereby capturing the effects of finite temperature magnetism on SRO. Model parameters are obtained by fitting to a first-principles data set comprising both chemically and magnetically diverse FCC configurations. The magnitude of the magnetic exchange interactions are found to be comparable to the chemical interactions. Compared to a conventional implicit magnetism CE built from only magnetic ground state configurations, the spin CE shows improved performance on several experimental benchmarks over a broad spectrum of compositions, particularly at higher temperatures due to the explicit treatment of magnetic disorder. We find that SRO is strongly influenced by alloy Cr content, since Cr atoms prefer to align antiferromagnetically with nearest neighbors but become magnetically frustrated with increasing Cr concentration. Using the spin CE, we predict that increasing the Cr concentration in typical austenitic stainless steels promotes the formation of SRO and increases order-disorder transition temperatures. Furthermore, this study underscores the significance of considering magnetic interactions explicitly when exploring the thermodynamic properties of complex transition metal alloys. It also highlights guidelines for customizing SRO through adjustments of alloy composition.

36 MATERIALS SCIENCE↗

Morphological traits for allometric scaling of the European Sea Bass Dicentrarchus labrax (Linnaeus, 1758) from Southern Portugal population

Abstract The present study aimed to determine the allometric scaling among a selection of morphological traits in European sea bass ( Dicentrarchus labrax ) to estimate fish body weight. A set of morphological traits (fish body weight, length, height, and width) were directly measured in 146 fish of a recirculating aquaculture system, with body weights ranging from 17.11 to 652.21 g. In addition, a collection of digital imagery of each anesthetized fish from the side and top views were used to estimate other traits (indirect measures). Multiple regression analysis and regression coefficients were calculated using all possible combinations of biometric data (predictors) to estimate fish body weight, applying different numerical fitting models (linear, log‐linear, quadratic, exponential). The results showed that the best combination of traits for estimating fish body weight were fish body width, length and height, collected from direct measure ( R 2 = 0.995), for a log‐linear model fitting, which revealed more accurate determinations than the most commonly used length–weight relationship. Nevertheless, other combinations of morphological traits and fitting models were also found to be suitable in successfully predict fish body weight, with variability ranging between 92.5% and 98.5%. For indirect measures, the best predictor was a combination of traits from top view (width, eye distance and area without fins) fitted with a log‐linear function. These results comprise a relevant baseline in supporting the high potential of noninvasive methods to accurately follow the growth of European sea bass juveniles, recurring to imagery analysis of anesthetized fish. It has major potential applications in feeding consumption trials and fish growth models, as it allows for continuously following up fish growth under different experimental conditions without therein distress derived from manipulation.

Azevedo, Ana↗

Size- and temperature-dependent magnetization of iron nanoclusters

In this paper, the magnetic behavior of bcc iron nanoclusters, with diameters between 2 and 8 nm, is investigated by means of spin dynamics simulations coupled to molecular dynamics, using a distance-dependent exchange interaction. Finite-size effects in the total magnetization as well as the influence of the free surface and the surface/core proportion of the nanoclusters are analyzed in detail for a wide temperature range, going beyond the cluster and bulk Curie temperatures. Comparison is made with experimental data and with theoretical models based on the mean-field Ising model adapted to small clusters, and taking into account the influence of low coordinated spins at free surfaces. Our results for the temperature dependence of the average magnetization per atom M (T), including the thermalization of the transnational lattice degrees of freedom, are in very good agreement with available experimental measurements on small Fe nanoclusters. In contrast, significant discrepancies with experiment are observed if the translational degrees of freedom are artificially frozen. The finite-size effects on M (T) are found to be particularly important near the cluster Curie temperature. Simulated magnetization above the Curie temperature scales with cluster size as predicted by models assuming short-range magnetic ordering. Analytical approximations to the magnetization as a function of temperature and size are proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Intrinsic kinetics of water-inhibited ultra-lean methane oxidation over PtPd-Mg/ θ -Al 2 O 3 catalyst

Here, this study develops intrinsic methane oxidation kinetics for ultra-lean methane conditions in the presence of water over a highly active and stable PtPd–Mg/θ-Al 2 O 3 catalyst. Comprehensive laboratory experiments were conducted over a wide range of methane concentrations (150–1200 ppm CH 4 ), water contents (1–5% H 2 O), and industrially relevant space velocities (80,000 ≤ GHSV ≤ 160,000 h -1 ). These systematic experiments informed a two-dimensional, axisymmetric, multiscale reactor model that was used to develop and validate methane oxidation kinetics under practically relevant conditions, including non-isothermal operation and high conversion regimes. Combined experimental and modeling results revealed significant intraparticle diffusion resistance and transport-induced reaction exotherm at elevated temperatures, which limited catalyst utilization despite high intrinsic activity. These transport effects were explicitly incorporated into the reactor model, enabling accurate estimation of intrinsic kinetic parameters without reliance on conventional effectiveness-factor corrections. The resulting kinetic model successfully captured both kinetically controlled and mass-transfer-limited regimes and reliably predicted CH 4 conversion across broad ranges of temperature, methane concentration, and water content

Heat and mass transfer limitations↗

Measurements and Prediction of Ash Deposition in a Cyclone-Fired Boiler Operating under Variable Load Conditions

Measurements of ash deposition rates were made between the secondary superheater and reheater sections of a 450 MW cyclone-fired lignite boiler as the operational load varied from 33 to 100%. Significant reductions in deposition rates with a decrease in operational load were observed. To uncover the causative mechanisms behind these observations, operational data from the power plant were used to carry out computational fluid dynamic (CFD) simulations of the boiler. After ascertaining that the gas temperatures and velocities at various sections within the boiler were being represented adequately, decoupled simulations of the ash deposition process on the deposit probe were carried out using a finely resolved boundary layer mesh. Fly ash particle size distribution (PSD) and its concentration for the decoupled calculations were determined from stand-alone cyclone barrel simulations. The ash partitioning (mass %) between the fly ash and slag was found to be ~50:50, which was in line with previous field observations, and it did not vary significantly across different cyclone loads. The predicted PSD of the deposit ash was concentrated in the size range 10–30 microns, which was in agreement with cross-sectional images of the deposit obtained from the measurements. At lower loads, sharp variations in the deposition rates were predicted in the gas temperature range 950–1150 K. The particle kinetic energy—particle viscosity-based capture methodology utilized in this study in conjunction with appropriate ash compositions, ash viscosity models and gas temperature estimates can help estimate slagging propensities at different loads reasonably well in these systems.

Krishnamoorthy, Gautham (ORCID:0000000255205092)↗

Workshop on Jet Exhaust Noise Reduction for Tactical Aircraft - NASA Perspective

Jet noise from supersonic, high performance aircraft is a significant problem for takeoff and landing operations near air bases and aircraft carriers. As newer aircraft with higher thrust and performance are introduced, the noise tends to increase due to higher jet exhaust velocities. Jet noise has been a subject of research for over 55 years. Commercial subsonic aircraft benefit from changes to the engine cycle that reduce the exhaust velocities and result in significant noise reduction. Most of the research programs over the past few decades have concentrated on commercial aircraft. Progress has been made by introducing new engines with design features that reduce the noise. NASA has recently started a new program called "Fundamental Aeronautics" where three projects (subsonic fixed wing, subsonic rotary wing, and supersonics) address aircraft noise. For the supersonics project, a primary goal is to understand the underlying physics associated with jet noise so that improved noise prediction tools and noise reduction methods can be developed for a wide range of applications. Highlights from the supersonics project are presented including prediction methods for broadband shock noise, flow measurement methods, and noise reduction methods. Realistic expectations are presented based on past history that indicates significant jet noise reduction cannot be achieved without major changes to the engine cycle. NASA s past experience shows a few EPNdB (effective perceived noise level in decibels) can be achieved using low noise design features such as chevron nozzles. Minimal thrust loss can be expected with these nozzles (< 0.5%) and they may be retrofitted on existing engines. In the long term, it is desirable to use variable cycle engines that can be optimized for lower jet noise during takeoff operations and higher thrust for operational performance. It is also suggested that noise experts be included early in the design process for engine nozzle systems to participate in decisions that may impact the jet noise.

Huff, Dennis L.↗

Gas side heat transfer: 2-D flow

Significant progress was made in advancing the idea of establishing a unified approach for predicting airfoil heat transfer for a wide range of operating conditions and geometries. Preliminary results are encouraging and further mixing length (ml) turbulence modeling ideas will be explored, concentrating on transition behavior. The capability of available modeling techniques to predict airfoil surface heat transfer distributions in a two-dimensional flow field was assessed, experimental data as required for model verification were acquired, and improvements in the analytic models was made and verified.

York, R.↗

Accelerating defect predictions in semiconductors using graph neural networks

First-principles computations reliably predict the energetics of point defects in semiconductors but are constrained by the expense of using large supercells and advanced levels of theory. Machine learning models trained on computational data, especially ones that sufficiently encode defect coordination environments, can be used to accelerate defect predictions. Here, we develop a framework for the prediction and screening of native defects and functional impurities in a chemical space of group IV, III–V, and II–VI zinc blende semiconductors, powered by crystal Graph-based Neural Networks (GNNs) trained on high-throughput density functional theory (DFT) data. Using an innovative approach of sampling partially optimized defect configurations from DFT calculations, we generate one of the largest computational defect datasets to date, containing many types of vacancies, self-interstitials, anti-site substitutions, impurity interstitials and substitutions, as well as some defect complexes. We applied three types of established GNN techniques, namely crystal graph convolutional neural network, materials graph network, and Atomistic Line Graph Neural Network (ALIGNN), to rigorously train models for predicting defect formation energy (DFE) in multiple charge states and chemical potential conditions. We find that ALIGNN yields the best DFE predictions with root mean square errors around 0.3 eV, which represents a prediction accuracy of 98% given the range of values within the dataset, improving significantly on the state-of-the-art. We further show that GNN-based defective structure optimization can take us close to DFT-optimized geometries at a fraction of the cost of full DFT. The current models are based on the semi-local generalized gradient approximation-Perdew–Burke–Ernzerhof (PBE) functional but are highly promising because of the correlation of computed energetics and defect levels with higher levels of theory and experimental data, the accuracy and necessity of discovering novel metastable and low energy defect structures at the PBE level of theory before advanced methods could be applied, and the ability to train multi-fidelity models in the future with new data from non-local functionals. The DFT-GNN models enable prediction and screening across thousands of hypothetical defects based on both unoptimized and partially optimized defective structures, helping identify electronically active defects in technologically important semiconductors.

Rahman, Md Habibur (ORCID:000000027705984X)↗

Verification and Validation Activities for the Multi-Fidelity Toolkit

The Multi-Fidelity Toolkit (MFTK) is a simulation tool being developed at Sandia National Laboratories for aerodynamic predictions of compressible flows over a range of physics fidelities and computational speeds. These models include the Reynolds-Averaged-Navier-Stokes (RANS) equations, the Euler equations, and modified Newtonian aerodynamics (MNA) equations, and they can be invoked independently or coupled with hierarchical Kriging to interpolate between high-fidelity simulations using lower-fidelity data. However, as with any new simulation capability, verification and validation are necessary to gather credibility evidence. This work describes formal code- and solution-verification activities as well as model validation with uncertainty considerations. Code verification is performed on the MNA model by comparing with an analytical solution for flat-plate and inclined-plate geometries. Solution-verification activities include grid-refinement studies of HIFiRE-1 wind tunnel measurements, which are used for validation, for all model fidelities. A thorough treatment of the validation comparison with prediction error and validation uncertainty is also presented.

42 ENGINEERING↗

The HEAO-1 soft X-ray survey of cataclysmic variable stars

A survey of the soft X-ray emission from 206 cataclysmic variable stars, including dwarf novae in optically quiescent states, classical novae, recurrent novae, nova-like objects and polars, is reported. This is an extension of a previous survey of dwarf novae in outbursts by Cordova et al. (1980). The number of surveyed stars that correspond to features greater than 2 sigma is not in excess of the number of chance coincidences expected on the basis of a random sample of positions distributed over the entire sky. While a few cataclysmic variables have been previously identified as X-ray sources, the results of this survey imply that cataclysmic variables as a class must be, at best, low-luminosity X-ray sources with fluxes below the HEAO-1 A2 detector's sensitivity limit of a few times 10 to the -11th erg/sq cm-s in the energy range 0.1-3 keV. The X-ray luminosities of the cataclysmic variables are consistent with predictions from disk accretion models, provided that a wide range of accretion rates apply.

Cordova, F. A.↗

Structure and Dynamics of Domains in Ferroelectric Nanostructures – Phase-Field Modeling (Final Technical Report)

Domain pattern formation is one of the most common phenomena in nature and is a topic of immense interest in many fields ranging from materials science and physics to chemistry and biology. This DOE sponsored research project explored the basic science concerning the thermodynamic stability of mesoscale polarization domain patterns and their temporal evolution mechanisms during formation and subsequent switching in ferroelectric nanostructures and heterostructures. The project employed the computational phase-field method in combination of microelasticity and electrostatic theories. The research was carried out in close collaboration with a number of experimental groups who used High Resolution Transmission Electron Microscopy (HRTEM), in situ TEM with Scanning Probe Microscopy (SPM), or Piezoresponse Force Microscopy (PFM) to characterize the domain structures and dynamics of ferroelectric thin films and heterostructures and who grow high-quality ferroelectric and multiferroic thin films using advanced growth techniques such as Molecular Beam Epitaxy (MBE), Pulsed Laser Deposition (PLLD), and sputtering. The research efforts of the project help establish the phase-field method as the most powerful method for understanding and predicting domain structures in ferroelectric thin films and nanostructures. The findings of the project led to the basic understanding of stability and switching mechanisms of ferroelectric domains under different mechanical boundary conditions and under either homogeneous capacitor configurations or local fields using metallic probes as electrodes and the emergence of charged domain walls during domain switching. The project predicted the spatial length scales, temperature ranges, and electromechanical conditions for different polar states in heterostructures and guided the discovery of both transient and stable novel polarization states containing vortex lattices in oxide superlattices. The project resulted in 134 journal publications and 6 PhD theses with all the PhD graduates currently working in either academia or industry within the United States. The basic understanding on the stability of mesoscale polar states and pattern evolution achieved by the project improved our ability to control and engineer properties of ferroelectric thin films and heterostructures for potential applications in nanoscale electronic devices.

36 MATERIALS SCIENCE↗

Influence of Mean-Density Gradient on Small-Scale Turbulence Noise

A physics-based methodology is described to predict jet-mixing noise due to small-scale turbulence. Both self- and shear-noise source teens of Lilley's equation are modeled and the far-field aerodynamic noise is expressed as an integral over the jet volume of the source multiplied by an appropriate Green's function which accounts for source convection and mean-flow refraction. Our primary interest here is to include transverse gradients of the mean density in the source modeling. It is shown that, in addition to the usual quadrupole type sources which scale to the fourth-power of the acoustic wave number, additional dipole and monopole sources are present that scale to lower powers of wave number. Various two-point correlations are modeled and an approximate solution to noise spectra due to multipole sources of various orders is developed. Mean flow and turbulence information is provided through RANS-k(epsilon) solution. Numerical results are presented for a subsonic jet at a range of temperatures and Mach numbers. Predictions indicated a decrease in high frequency noise with added heat, while changes in the low frequency noise depend on jet velocity and observer angle.

Khavaran, Abbas↗

Viscous effects on the instability of an axisymmetric jet

The stability characteristics of a laminar, axisymmetric jet, issuing from fully developed Poiseuille flow, are investigated. The jet preferred frequency, as inferred from surveys of u'-spectra, is found to yield a Strouhal number (St) that depends on the Reynolds number (R); St and R are based on the jet diameter (D) and the average velocity (U sub av) at the jet origin. The value of St increases with increasing R in the range 400 less than approximately R less than approximately 4000, attaining an asymptotic value of about 0.45. Flow visualization confirms that the instability is primarily in a helical mode, as predicted by stability analyses. Analyses do predict a similar St versus R variation in approximately the correct St-range. However, the R-range where this is predicted is lower than that found experimentally.

Zaman, K. B. M. Q.↗

Thermodynamics of clathrate hydrate at low and high pressures with application to the outer solar system

The thermodynamic stability of clathrate hydrate is calculated to predict the formation conditions corresponding to a range of solar system parameters. The calculations were performed using the statistical mechanical theory developed by van der Waals and Platteeuw (1959) and existing experimental data concerning clathrate hydrate and its components. Dissociation pressures and partition functions (Langmuir constants) are predicted at low pressure for CO clathrate (hydrate) using the properties of chemicals similar to CO. It is argued that nonsolar but well constrained noble gas abundances may be measurable by the Galileo spacecraft in the Jovian atmosphere if the observed carbon enhancement is due to bombardment of the atmosphere by clathrate-bearing planetesimals sometime after planetary formation. The noble gas abundances of the Jovian satellite Titan are predicted, assuming that most of the methane in Titan is accreted as clathrate. It is suggested that under thermodynamically appropriate conditions, complete clathration of water ice could have occurred in high-pressure nebulas around giant planets, but probably not in the outer solar nebula. The stability of clathrate in other pressure ranges is also discussed.

Lunine, J. I.↗

Non-solar noble gas abundances in the atmosphere of Jupiter

The thermodynamic stability of clathrate hydrate is calculated to predict the formation conditions corresponding to a range of solar system parameters. The calculations were performed using the statistical mechanical theory developed by van der Waals and Platteeuw (1959) and existing experimental data concerning clathrate hydrate and its components. Dissociation pressures and partition functions (Langmuir constants) are predicted at low pressure for CO clathrate (hydrate) using the properties of chemicals similar to CO. It is argued that nonsolar but well constrained noble gas abundances may be measurable by the Galileo spacecraft in the Jovian atmosphere if the observed carbon enhancement is due to bombardment of the atmosphere by clathrate-bearing planetesimals sometime after planetary formation. The noble gas abundances of the Jovian satellite Titan are predicted, assuming that most of the methane in Titan is accreted as clathrate. It is suggested that under thermodynamically appropriate conditions, complete clathration of water ice could have occurred in high-pressure nebulas around giant planets, but probably not in the outer solar nebula. The stability of clathrate in other pressure ranges is also discussed.

Lunine, Jonathan I.↗

Testing the thermal Sunyaev-Zel’dovich power spectrum of a halo model using hydrodynamical simulations

Statistical properties of large-scale cosmological structures serve as powerful tools for constraining the cosmological properties of our Universe. Tracing the gas pressure, the thermal Sunyaev-Zel’dovich (tSZ) effect is a biased probe of mass distribution and, hence, can be used to test the physics of feedback or cosmological models. Therefore, it is crucial to develop robust modelling of hot gas pressure for applications to tSZ surveys. Since gas collapses into bound structures, it is expected that most of the tSZ signal is within halos produced by cosmic accretion shocks. Hence, simple empirical halo models can be used to predict the tSZ power spectra. In this study, we employed the HMx halo model to compare the tSZ power spectra with those of several hydrodynamical simulations: the Horizon suite and the Magneticum simulation. We examine various contributions to the tSZ power spectrum across different redshifts, including the one- and two-halo term decomposition, the amount of bound gas, the importance of different masses, and the electron pressure profiles. Our comparison of the tSZ power spectrum reveals discrepancies between the halo model and cosmological simulations that increase with redshift. We find a 20% to 50% difference between the measured and predicted tSZ angular power spectrum over the multipole range ℓ = 10 3 − 10 4 . Our analysis reveals that these differences are driven by the excess of power in the predicted two-halo term at low k and in the one-halo term at high k . At higher redshifts ( z ∼ 3), simulations indicate that more power comes from outside the virial radius than from inside, suggesting a limitation in the applicability of the halo model. We also observe differences in the pressure profiles, despite the fair level of agreement on the tSZ power spectrum at low redshift with the default calibration of the halo model. In conclusion, our study suggests that the properties of the halo model need to be carefully controlled against real or mock data to be proven useful for cosmological purposes.

Ayçoberry, Emma (ORCID:0000000292351195)↗

Engineering prediction of turbulent skin friction and heat transfer in high-speed flow

A large collection of experimental turbulent-skin-friction and heat-transfer data for flat plates and cones was used to determine the most accurate of six of the most popular engineering-prediction methods; the data represent a Mach number range from 4 to 13 and ratio of wall to total temperature ranging from 0.1 to 0.7. The Spalding and Chi method incorporating virtual-origin concepts was found to be the best prediction method for Mach numbers less than 10; the limited experimental data for Mach numbers greater than 10 were not well predicted by any of the engineering methods except the Coles method.

Cary, A. M., Jr.↗

Finite Element Model Development For Aircraft Fuselage Structures

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results.

Buehrle, Ralph D.↗