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At least 1,405 records · Page 78

Influence of Constituents on Creep Properties of SiC/SiC Composites

SiC-SiC composites are being considered as potential candidate materials for next generation turbine components such as combustor liners, nozzle vanes and blades because of their low density, high temperature capability, and tailorable mechanical properties. These composites are essentially fabricated by infiltrating matrix into a stacked array of fibers or fiber preform by one or a combination of manufacturing methods such as, Melt Infiltration (MI) of molten silicon metal, Chemical Vapor Infiltration (CVI), Polymer Infiltration and Pyrolysis (PIP). To understand the influence of constituents, the SiC-SiC composites fabricated by MI, CVI, and PIP methods were creep tested in air between 12000 and 14500 degrees Centigrade for up to 500 hours. The failed specimens were analyzed under a scanning electron microscope to assess damage mechanisms. Also, knowing the creep deformation parameters of the fiber and the matrix under the testing conditions, the creep behavior of the composites was modeled and compared with the measured data. The implications of the results on the long term durability of these composites will be discussed.

modeling↗

Dynamic modeling of gene expression data

We describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.

NASA Discipline Plant Biology↗

Prediction of Stiffness and Fatigue Lives of Polymer Matrix Composite Laminates Using Artificial Neural Networks

Machine learning (ML) models are increasingly being used in many engineering fields due to the advancements in ML algorithms and availability of high-speed computing power. One of the most popular ML class of models is artificial neural networks (ANN). ML is increasingly being used in the design and analysis of composite materials and structures, specifically in the constitutive modeling of composite materials with the focus on greatly accelerating multiscale analyses of composite materials and structures through development of surrogate models. Towards that end, both Python and MATLAB-based neural nets have been developed to predict initial stiffness and fatigue life of an eight-ply symmetric polymer matrix composite laminate. Two types of neural networks, a Multilayer Perceptron (MLP) and a Recurrent Neural Network (RNN), have been developed for both platforms. Results show that the both neural net types can provide an excellent estimate of initial stiffness as well as fatigue life of eight-ply symmetric polymer matrix composite laminate. RNNs are better able to capture the shape of the fatigue curve of a laminate. This tool can be very useful for system level studies to obtain an estimate of desired properties and life of PMC composite laminates. The associated surrogate models could also be used in composite multiscale analyses to replace the actual physics-based calculations at lower scales and thereby significantly increase the computational efficiency of such analyses and thus make multiscale analyses a viable industrial tool for large scale structural problems.

Composite↗

How does a probe inserted into the discharge influence the plasma structure?

Shielding the bias applied to the probe by the sheath formed around it and determination of parameters of unperturbed plasmas are in the basis of the probe diagnostics. The results from a two-dimensional model of a discharge with a probe inserted in it show that the probe influences the spatial distribution of the plasma parameters in the entire discharge. The increase (although slight) in the electron temperature, due to the increased losses of charged particles on the additional wall in the discharge (mainly the probe holder), leads to redistribution of the plasma density and plasma potential, as shown by the results obtained at the floating potential of the probe. The deviations due to the bias applied to the probe tip are stronger in the ion saturation region of the probe characteristics. The pattern of the spatial redistribution of the plasma parameters advances together with the movement of the probe deeper in the discharge. Although probe sheaths and probe characteristics resulting from the model are shown, the study does not aim at discussions on the theories for determination of the plasma density from the ion saturation current. Regardless of the modifications in the plasma behavior in the entire discharge, the deviations of the plasma parameters at the position of the probe tip and, respectively, the uncertainty which should be added as an error when the accuracy of the probe diagnostics is estimated do not exceed 10%. Consequently, the electron density and temperature obtained, respectively, at the position of the plasma potential on the probe characteristics and from its transition region are in reasonable agreement with the results from the model of the discharge without a probe. Being in the scope of research on a source of negative hydrogen ions with the design of a matrix of small radius inductive discharges, the model is specified for a low-pressure hydrogen discharge sustained in a small-radius tube.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cosmology at high redshift — a probe of fundamental physics

An observational program focused on the high redshift (2<z<6) Universe has the opportunity to dramatically improve over upcoming LSS and CMB surveys on measurements of both the standard cosmological model and its extensions. Using a Fisher matrix formalism that builds upon recent advances in Lagrangian perturbation theory, we forecast constraints for future spectroscopic and 21-cm surveys on the standard cosmological model, curvature, neutrino mass, relativistic species, primordial features, primordial non-Gaussianity, dynamical dark energy, and gravitational slip. We compare these constraints with those achievable by current or near-future surveys such as DESI and Euclid, all under the same forecasting formalism, and compare our formalism with traditional linear methods. Here, our Python code FishLSS — used to calculate the Fisher information of the full shape power spectrum, CMB lensing, the cross-correlation of CMB lensing with galaxies, and combinations thereof — is publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

Emergent Superconductivity and Competing Charge Orders in Hole-Doped Square-Lattice t – J Model

The square-lattice Hubbard and closely related t-J models are considered as basic paradigms for understanding strong correlation effects and unconventional superconductivity (SC). Recent large-scale density matrix renormalization group simulations on the extended t-J model have identified d-wave SC on the electron-doped side (with the next-nearest-neighbor hopping t 2 > 0) but a dominant charge density wave (CDW) order on the hole-doped side (t 2 < 0), which is inconsistent with the SC of hole-doped cuprate compounds. We re-examine the ground-state phase diagram of the extended t-J model by employing the state-of-the-art density matrix renormalization group calculations with much enhanced bond dimensions, allowing more accurate determination of the ground state. On six-leg cylinders, while different CDW phases are identified on the hole-doped side for the doping range δ = 1/16 – 1/8, a SC phase emerges at a lower doping regime, with algebraically decaying pairing correlations and d-wave symmetry. On the wider eight-leg systems, the d-wave SC also emerges on the hole-doped side at the optimal 1=8 doping, demonstrating the winning of SC over CDW by increasing the system width. Furthermore, our results not only suggest a new path to SC in general t-J model through weakening the competing charge orders, but also provide a unified understanding on the SC of both hole- and electron-doped cuprate superconductors.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

How Bayesian methods can improve R -matrix analyses of data: The example of the d t reaction

The 3 H(d, n) 4 He reaction is of significant interest in nuclear astrophysics and nuclear applications. It is an important, early step in big-bang nucleosynthesis and a key process in nuclear fusion reactors. We use one- and two-level R-matrix approximations to analyze data on the cross section for this reaction at center-of-mass energies below 215 keV. We critically examine the data sets using a Bayesian statistical model that allows for both common-mode and additional point-to-point un- certainties. We use Markov Chain Monte Carlo sampling to evaluate this R-matrix-plus-statistical model and find two-level R-matrix results that are stable with respect to variations in the channel radii. The S factor at 40 keV evaluates to 25.36(19) MeV b (68% credibility interval). We discuss our Bayesian analysis in detail and provide guidance for future applications of Bayesian methods to R-matrix analyses. We also discuss possible paths to further reduction of the S-factor uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An approximate Kalman filter for ocean data assimilation: An example with an idealized Gulf Stream model

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter based on approximation of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudomeasurements are examined, including velocity, density, and volume transport at localized arrays and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform an empirical nudging scheme used in a previous study. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

Fukumori, Ichiro↗

An Approximate Kalman Filter for Ocean Data Assimilation; An Example with an Idealized Gulf Stream Model

A practical method of data assimilation for use with large, nonlinear, ocean general circulation models is explored. A Kalman filter based on approximations of the state error covariance matrix is presented, employing a reduction of the effective model dimension, the error's asymptotic steady-state limit, and a time-invariant linearization of the dynamic model for the error integration. The approximations lead to dramatic computational savings in applying estimation theory to large complex systems. We examine the utility of the approximate filter in assimilating different measurement types using a twin experiment of an idealized Gulf Stream. A nonlinear primitive equation model of an unstable east-west jet is studied with a state dimension exceeding 170,000 elements. Assimilation of various pseudo measurements is examined, including velocity, density, and volume transport at localized arrays, and realistic distributions of satellite altimetry and acoustic tomography observations. Results are compared in terms of their effects on the accuracies of the estimation. The approximate filter is shown to outperform a previous study that used an empirical nudging scheme. The examples demonstrate that useful approximate estimation errors can be computed in a practical manner for general circulation models.

['Kalman↗

Modeling of Hydraulic Fracture Propagation at the kISMET Site Using a Fully Coupled 3D Network-Flow and Quasi- Static Discrete Element Model

Aimed at supporting the design of hydraulic fracturing experiments at the kISMET site, ~1500 m below ground in a deep mine, we performed pre-experimental hydraulic fracturing simulations in order to estimate the breakdown pressure, propagation pressure, fracture geometry, and the magnitude of induced seismicity using a newly developed fully coupled three-dimensional (3D) network flow and quasi-static discrete element model (DEM). The quasi-static DEM model, which is constructed by Delaunay tessellation of the rock volume, considers rock fabric heterogeneities by using the “disordered” DEM mesh and adding random perturbations to the stiffness and tensile/shear strengths of individual DEM elements and the elastic beams between them. A conjugate 3D flow network based on the DEM lattice is constructed to calculate the fluid flow in both the fracture and porous matrix. One distinctive advantage of the model is that fracturing is naturally described by the breakage of elastic beams between DEM elements. It is also extremely convenient to introduce mechanical anisotropy into the model by simply assigning orientation-dependent tensile/shear strengths to the elastic beams. In this paper, the 3D hydraulic fracturing model was verified against the analytic solution for a penny-shaped crack model. We applied the model to simulate fracture propagation from a vertical open borehole based on initial estimates of rock mechanical properties and in-situ stress conditions. The breakdown pressure and propagation pressure are directly obtained from the simulation. In addition, the released elastic strain energies of individual fracturing events were calculated and used as a conservative estimate for the magnitudes of the potential induced seismic activities associated with fracturing. The comparisons between model predictions and experimental results are still ongoing.

15 GEOTHERMAL ENERGY↗

Reflectance properties of one-dimensional metal-dielectric ternary photonic crystal

Metallic photonic crystal has a very important application in absorption enhancement in solar cells. It has been found that an ultra-thin metallic layer becomes transparent due to internal scattering of light through the each interface of the dielectric and metal surfaces. The metal has absorption due to their surface plasmon and the plasmon has important parameters for changing optical properties of the metal. We consider ternary metallic-dielectric photonic crystal (MDPC) for having large probabilities to change the optical properties of the MDPC and the photonic crystals may be changed by changing dimensionality, symmetry, lattice parameters, Filling fraction and effective refractive index refractive index contrast. In this present communication, we try to show that the photonic band gap in ternary metal-dielectric photonic crystal can be significantly enlarged when air dielectric constant is considered. All the theoretical analyses are made based on the transfer matrix method together with the Drude model of metal.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Draft Experimental Plan for Commercial SNF Degradation in Repository Environments with a Focus on Fracture Matrix Degradation

This report documents work performed supporting US Department of Energy (DOE) Nuclear Energy Spent Fuel and Waste Disposition, Spent Fuel and Waste Science and Technology, under work breakdown structure element 1.08.01.03.04, “Inventory and Waste Form Characteristics and Performance.” In particular, this report fulfills the M3 milestone, M3SF-21OR010309072 "Draft Experimental Plan for Commercial SNF Degradation in Repository Environments” as described in work package SF-21OR01030907 "SNF Degradation Testing-ORNL".This experimental plan is a collaboration between ORNL, SNL, ANL, and PNNL. It is intended to support source term model development and spent fuel degradation testing in a range of generic repository conditions. Potential testing and experiments to support validation of the Fuel Matrix Dissolution Model (FMDM) and the overall development/validation of repository source term modeling are discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Analysis of delamination in cross ply laminates initiating from impact induced matrix cracking

Several two dimensional finite element analyses of (0 sub 2/90 sub 8/0 sub 2) glass/epoxy and graphite-epoxy composite laminates were performed to study some of the characteristics of damage development due to an impact load. A cross section through the thickness of the laminate with fixed ends, and carrying a transverse load in the center was analyzed. Inclined matrix cracks such as those produced by low velocity impact were modeled in the 90 deg ply group. The introduction of the matrix cracks caused large interlaminar tension and shear stresses in the vicinity of both crack tips in the 0/90 and 90/0 interfaces. The large interlaminar stresses at the ends of the matrix cracks indicate that matrix cracking may give rise to delamination. The ratio of mode I to total strain energy release rate at the beginning of delamination calculated at the two matrix crack tips was 60 and 28 pct., respectively, in the glass/epoxy laminate. The corresponding ratio was 97 and 77 pct. in the graphite-epoxy laminate. Thus, a significant mode I component of strain energy release rate may be present at the delamination initiation due to an impact load.

Salpekar, S. A.↗

Fully Coupled Micro/Macro Deformation, Damage, and Failure Prediction for SiC/Ti-15-3 Laminates

The deformation, failure, and low cycle fatigue life of SCS-6/Ti-15-3 composites are predicted using a coupled deformation and damage approach in the context of the analytical generalized method of cells (GMC) micromechanics model. The local effects of inelastic deformation, fiber breakage, fiber-matrix interfacial debonding, and fatigue damage are included as sub-models that operate on the micro scale for the individual composite phases. For the laminate analysis, lamination theory is employed as the global or structural scale model, while GMC is embedded to operate on the meso scale to simulate the behavior of the composite material within each laminate layer. While the analysis approach is quite complex and multifaceted, it is shown, through comparison with experimental data, to be quite accurate and realistic while remaining extremely efficient.

Bednarcyk, Brett A.↗

The matrix exponential in transient structural analysis

The primary usefulness of the presented theory is in the ability to represent the effects of high frequency linear response with accuracy, without requiring very small time steps in the analysis of dynamic response. The matrix exponential contains a series approximation to the dynamic model. However, unlike the usual analysis procedure which truncates the high frequency response, the approximation in the exponential matrix solution is in the time domain. By truncating the series solution to the matrix exponential short, the solution is made inaccurate after a certain time. Yet, up to that time the solution is extremely accurate, including all high frequency effects. By taking finite time increments, the exponential matrix solution can compute the response very accurately. Use of the exponential matrix in structural dynamics is demonstrated by simulating the free vibration response of multi degree of freedom models of cantilever beams.

Minnetyan, Levon↗

Matrix Multiply Performance of GPUs on Exascale-class HPE/Cray Systems

The computation of dense matrix-matrix products (GEMMs) is central to many modeling and simulation workloads as well as AI/ML deep learning campaigns. In fact, millions of dollars are spent annually on computing GEMMs, and large model training demands are increasing exponentially. Specialized processors such as GPUs are designed to perform well for these operations. However, the performance of GEMMs on GPUs can exhibit complex behaviors depending on many factors, making it challenging to optimize the performance of GEMMs on these processors. In this study we undertake an examination of GEMM performance on several leading GPU models taken from product lines of GPUs to be deployed in forthcoming exascale computing systems. We show results to illustrate the many factors that can affect performance of GEMMs on GPUs. We then present data collected from a large number of test runs for an example GEMM operation to show the dependence behaviors of GEMM rate on matrix dimensions. Finally, we show results from machine learning-based performance models using novel feature engineering methods to fit the measured performance, providing a potential basis for GEMM performance tuning and autotuning methods for GPUs. Recommendations are also given for how to achieve high GEMM performance on modern GPUs.

Melesse Vergara, Veronica↗

Atomistic model of xenon gas bubble re-solution rate due to thermal spike in uranium oxide

Atomistic simulations are performed to study the response of Xe gas bubbles in UO 2 to ionizing fission products through the thermal spike approximation. A portion of the total electronic stopping power (S e ) is taken as the thermal spike energy through a ratio variable ζ. The thermal spike energy causes extreme melting within the fission track cylindrical region. Molecular dynamics is employed to quantify the probability of a Xe gas atom to be re-solved (re-dissolved) back into the UO 2 matrix. Subsequently, a re-solution model is developed and parametrized as a function of bubble radius (R), off-centered distance (r), and thermal spike energy (ζS e ). The off-centered distance measures the shift of the thermal spike axis from the bubble center. To evaluate the re-solution model, independent fission product yield of U-235 fission due to thermal neutrons (0.0253 eV), taken from the JEFF-3.3 database, is used. The kinetic energy of the fission products is taken from the EXFOR database. Subsequently, the decay of Se over distance for each fission product is simulated. Finally, the evaluated re-solution rate (re-solution probability per second) is presented as a function of bubble radius for a range of ζ.

74 ATOMIC AND MOLECULAR PHYSICS↗