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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

EFFECT OF MODEL-DEPENDENT COVARIANCE MATRIX FOR STUDYING BARYON ACOUSTIC OSCILLATIONS

Large-scale structures in the universe are a powerful tool to test cosmological models and constrain cosmological parameters. A particular feature of interest comes from baryon acoustic oscillations (BAOs), which are sound waves traveling in the hot plasma of the early universe that stopped at the recombination time. This feature can be observed as a localized bump in the correlation function at the scale of the sound horizon r{sub s} . As such, it provides a standard ruler and a lot of constraining power in the correlation function analysis of galaxy surveys. Moreover, the detection of BAOs at the expected scale gives strong support to cosmological models. Both of these studies (BAO detection and parameter constraints) rely on a statistical modeling of the measured correlation function {xi}-circumflex. Usually {xi}-circumflex is assumed to be Gaussian, with a mean {xi}{sub {theta}} depending on the cosmological model and a covariance matrix C generally approximated as a constant (i.e., independent of the model). In this article, we study whether a realistic model-dependent C {sub {theta}} changes the results of cosmological parameter constraints compared to the approximation of a constant covariance matrix C. For this purpose, we use a new procedure to generate lognormal realizations of the luminous red galaxy sample of the Sloan Digital Sky Survey Data Release 7 to obtain a model-dependent C {sub {theta}} in a reasonable time. The approximation of C {sub {theta}} as a constant creates small changes in the cosmological parameter constraints on our sample. We quantify this modeling error using a lot of simulations and find that it only has a marginal influence on cosmological parameter constraints for current and next-generation galaxy surveys. It can be approximately taken into account by extending the 1{sigma} intervals by a factor Almost-Equal-To 1.3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Physics-Informed Machine Learning Model for Ceramic Matrix Composite Creep

A physics-informed recurrent neural network (RNN) based surrogate model is developed to emulate the nonlinear, time-dependent constitutive behavior of ceramic matrix composites (CMCs) driven by matrix damage and constituent creep at the microscale. Physics-informed constraints are introduced into the surrogate model through regularization to ground the prediction in physics and improve its predictive capabilities. Training data is generated using the high-fidelity generalized method of cells (HFGMC) approach which calls appropriate creep and damage models for each of the constituents. This coupling permits simulating the nonlinear behavior of CMCs based on constituent response at the microscale along with microstructural features such as fiber and porosity volume fraction and fiber radius. The microscale repeating unit cell is loaded under creep fatigue conditions to replicate the material loading experienced in a turbine engine. Therefore, the RNN-based surrogate model is tasked with predicting, as a function of variable input stress sequence, temperature, and microstructural features, the resulting strain history response while satisfying physical constraints related to creep rate, isochoric inelastic deformation, and strain energy density. The trained surrogate model is shown to effectively match the strain history over quantified distributions of microstructural features and relevant loading regimes and temperatures. Neural network based surrogate models can offer efficient alternatives to running computationally intensive multiscale material models to simulate the nonlinear response of large structural models. Therefore, the presented work provides evidence towards the feasibility of developing, training, and running such models for CMCs with complex microstructures, nonlinear time-dependent material response, and under non-monotonic loading conditions.

ceramic matrix composites↗
DOE OSTI2020

Multiscale Thermomechanical Damage Model with Internal State Variables for Ceramic Matrix Composites

A length scale-dependent matrix damage model has been developed to simulate the response of ceramic matrix composites (CMCs). This model captures damage initiation and propagation in the brittle matrix material by employing internal state variable (ISV) theory within a multiscale modeling framework to obtain damaged matrix stress-strain constitutive relationships at each length scale. Material degradation due to matrix cracking is captured by a damage variable determined using fracture mechanics and the self-consistent scheme. An additional state variable is introduced to capture the nucleation and growth of matrix porosity, a key mechanism contributing to matrix nonlinearity. Porosity occurs as a result of material diffusion around grain boundaries and the growth of the porosity state variable is related to the material entropy dissipation and the volumetric strain. The nonlinear predictive capabilities of the material model are demonstrated for monolithic silicon carbide, unidirectional (UD) carbon fiber/silicon carbide matrix (C/SiC) CMC, and five-harness satin (5HS) woven C/SiC CMC.

Skinner, Travis D.↗
DOE OSTI2023

Machine Learning Surrogates of a Fuel Matrix Degradation Process Model for Performance Assessment of a Nuclear Waste Repository

Spent nuclear fuel repository simulations are currently not able to incorporate detailed fuel matrix degradation (FMD) process models due to their computational cost, especially when large numbers of waste packages breach. The current paper uses machine learning to develop artificial neural network and k-nearest neighbor regression surrogate models that approximate the detailed FMD process model while being computationally much faster to evaluate. Further, using fuel cask temperature, dose rate, and the environmental concentrations of CO 3 2- , O 2 , Fe 2+ , and H 2 as inputs, these surrogates show good agreement with the FMD process model predictions of the UO 2 degradation rate for conditions within the range of the training data. A demonstration in a full-scale shale repository reference case simulation shows that the incorporation of the surrogate models captures local and temporal environmental effects on fuel degradation rates while retaining good computational efficiency.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1989

A review of failure models for ceramic matrix composite laminates under monotonic loads

Ceramic matrix composites offer significant potential for improving the performance of turbine engines. In order to achieve their potential, however, improvements in design methodology are needed. In the past most components using structural ceramic matrix composites were designed by trial and error since the emphasis of feasibility demonstration minimized the development of mathematical models. To understand the key parameters controlling response and the mechanics of failure, the development of structural failure models is required. A review of short term failure models with potential for ceramic matrix composite laminates under monotonic loads is presented. Phenomenological, semi-empirical, shear-lag, fracture mechanics, damage mechanics, and statistical models for the fast fracture analysis of continuous fiber unidirectional ceramic matrix composites under monotonic loads are surveyed.

Tripp, David E.↗
NASA NTRS2010

Analytical Modelling of Transverse Matrix Cracking of [plus or minus Theta/90(sub n)](sub s) Composite Laminates Under Multiaxial Loading

An analytical model based on the analysis of a cracked unit cell of a composite laminate subjected to multiaxial loads is proposed to predict the onset and accumulation of transverse matrix cracks in the 90(sub n) plies of uniformly stressed [plus or minus Theta/90(sub n)](sub s) laminates. The model predicts the effect of matrix cracks on the stiffness of the laminate, as well as the ultimate failure of the laminate, and it accounts for the effect of the ply thickness on the ply strength. Several examples describing the predictions of laminate response, from damage onset up to final failure under both uniaxial and multiaxial loads, are presented.

Mayugo, J A.↗
NASA NTRS1998

An Investigation of Reliability Models for Ceramic Matrix Composites and their Implementation into Finite Element Codes

The development of modeling approaches for the failure analysis of ceramic-based material systems used in high temperature environments was the primary objective of this research effort. These materials have the potential to support many key engineering technologies related to the design of aeropropulsion systems. Monolithic ceramics exhibit a number of useful properties such as retention of strength at high temperatures, chemical inertness, and low density. However, the use of monolithic ceramics has been limited by their inherent brittleness and a large variation in strength. This behavior has motivated material scientists to reinforce the monolithic material with a ceramic fiber. The addition of a second ceramic phase with an optimized interface increases toughness and marginally increases strength. The primary purpose of the fiber is to arrest crack growth, not to increase strength. The material systems of interest in this research effort were laminated ceramic matrix composites, as well as two- and three- dimensional fabric reinforced ceramic composites. These emerging composite systems can compete with metals in many demanding applications. However, the ongoing metamorphosis of ceramic composite material systems, and the lack of standardized design data has in the past tended to minimize research efforts related to structural analysis. Many structural components fabricated from ceramic matrix composites (CMC) have been designed by "trial and error." The justification for this approach lies in the fact that during the initial developmental phases for a material system fabrication issues are paramount. Emphasis is placed on demonstrating feasibility rather than fully understanding the processes controlling mechanical behavior. This is understandable during periods of rapid improvements in material properties for any composite system. But to avoid the ad hoc approach, the analytical methods developed under this effort can be used to develop rational structural design protocols.

Duffy, Stephen F.↗
DOE OSTI2019

Projected density matrix embedding theory with applications to the two-dimensional Hubbard model

Density matrix embedding theory (DMET) is a quantum embedding theory for strongly correlated systems. From a computational perspective, one bottleneck in DMET is the optimization of the correlation potential to achieve self-consistency, especially for heterogeneous systems of large size. We introduce a new approach, called projected DMET (p-DMET), which achieves self-consistency without needing to optimize the correlation potential. We demonstrate the performance of p-DMET on the two-dimensional Hubbard model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1986

Modeling the curing process of thermosetting resin matrix composites

A model is presented for simulating the curing process of a thermosetting resin matrix composite. The model relates the cure temperature, the cure pressure, and the properties of the prepreg to the thermal, chemical, and rheological processes occurring in the composite during cure. The results calculated with the computer code developed on the basis of the model were compared with the experimental data obtained from autoclave-curved composite laminates. Good agreement between the two sets of results was obtained.

Loos, A. C.↗
DOE OSTI2021

Matrix Graphite Material Models In Pebbles and Compacts For Bison

The cores and reflectors in high-temperature gas-cooled reactors (HTGRs) are made of graphite materials, with the graphite acting as a moderator, a fuel host matrix, or the foundation for various structural components. This study aims to survey the models in the literature for graphite materials being used as host matrices in pebble/fuel compacts and to implement those surveyed models into Bison to conduct an early assessment of graphite's thermo-mechanical response under various reactor conditions. In this study, thermal (e.g., thermal conductivity, and specific heat capacity) and mechanical (e.g., elastic properties, thermal expansion, irradiation-induced dimensional changes, and irradiation-induced creep) material models for various graphite grades (e.g., H-451, IG-110, G-348, 2020, A3-3, and A3-27) are incorporated into Bison. Two benchmark problems are then exercised utilizing these new graphite-related capabilities: (1) modeling an Advanced Gas Reactor (AGR)-2 fuel compact, and (2) modeling the debonding of a particle-matrix interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1985

Thermoplastic matrix composite processing model

The effects the processing parameters pressure, temperature, and time have on the quality of continuous graphite fiber reinforced thermoplastic matrix composites were quantitatively accessed by defining the extent to which intimate contact and bond formation has occurred at successive ply interfaces. Two models are presented predicting the extents to which the ply interfaces have achieved intimate contact and cohesive strength. The models are based on experimental observation of compression molded laminates and neat resin conditions, respectively. Identified as the mechanism explaining the phenomenon by which the plies bond to themselves is the theory of autohesion (or self diffusion). Theoretical predictions from the Reptation Theory between autohesive strength and contact time are used to explain the effects of the processing parameters on the observed experimental strengths. The application of a time-temperature relationship for autohesive strength predictions is evaluated. A viscoelastic compression molding model of a tow was developed to explain the phenomenon by which the prepreg ply interfaces develop intimate contact.

Dara, P. H.↗
NASA NTRS1997

Micromechanical Modeling of Woven Metal Matrix Composites

This report presents the results of an extensive micromechanical modeling effort for woven metal matrix composites. The model is employed to predict the mechanical response of 8-harness (8H) satin weave carbon/copper (C/Cu) composites. Experimental mechanical results for this novel high thermal conductivity material were recently reported by Bednarcyk et al. along with preliminary model results. The micromechanics model developed herein is based on an embedded approach. A micromechanics model for the local (micro-scale) behavior of the woven composite, the original method of cells (Aboudi), is embedded in a global (macro-scale) micromechanics model (the three-dimensional generalized method of cells (GMC-3D) (Aboudi). This approach allows representation of true repeating unit cells for woven metal matrix composites via GMC-3D, and representation of local effects, such as matrix plasticity, yarn porosity, and imperfect fiber-matrix bonding. In addition, the equations of GMC-3D were reformulated to significantly reduce the number of unknown quantities that characterize the deformation fields at the microlevel in order to make possible the analysis of actual microstructures of woven composites. The resulting micromechanical model (WCGMC) provides an intermediate level of geometric representation, versatility, and computational efficiency with respect to previous analytical and numerical models for woven composites, but surpasses all previous modeling work by allowing the mechanical response of a woven metal matrix composite, with an elastoplastic matrix, to be examined for the first time. WCGMC is employed to examine the effects of composite microstructure, porosity, residual stresses, and imperfect fiber-matrix bonding on the predicted mechanical response of 8H satin C/Cu. The previously reported experimental results are summarized, and the model predictions are compared to monotonic and cyclic tensile and shear test data. By considering appropriate levels of porosity, residual stresses, and imperfect fiber-matrix debonding, reasonably good qualitative and quantitative correlation is achieved between model and experiment.

Bednarcyk, Brett A.↗
NASA NTRS1998

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Belcastro, Christine M.↗
DOE OSTI2014

Low-lying excited states in armchair polyacene within Pariser-Parr-Pople model: A density matrix renormalization group study

We studied the nature of the ground state and low-lying excited states of armchair polyacene oligomers (Polyphenanthrene) within long-range Pariser-Parr-Pople model Hamiltonian with up to 14 monomers using symmetrized density matrix renormalization group technique. The ground state of all armchair polyacenes studied is found to be singlet. The results show that lowest singlet dipole allowed excited state has higher energy for armchair polyacenes as compared to linear fused polyacenes. Moreover, unlike linear fused polyacenes, the lowest singlet excited state of these oligomers is always found to lie below the lowest dipole forbidden two-photon state indicating that these armchair polyacene oligomers strongly fluoresce. The calculations of low-lying excitations on singly and triply electron doped armchair polyacene oligomers show a low energy band with strong transition dipole moment that coupled to charge conductivity. This implies armchair polyacene posses novel field-effect transistor properties.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

ezECM

Allows the user to fit a classical event categorization matrix (ECM) model, and a novel Bayesian event categorization matrix model, both of which are used for nuclear detonation detection.

Koermer, Scott↗
DOE OSTI2015

On implementation of EM-type algorithms in the stochastic models for a matrix computing on GPU

The paper discusses the main ideas of an implementation of EM-type algorithms for computing on the graphics processors and the application for the probabilistic models based on the Cox processes. An example of the GPU’s adapted MATLAB source code for the finite normal mixtures with the expectation-maximization matrix formulas is given. The testing of computational efficiency for GPU vs CPU is illustrated for the different sample sizes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗