The Effect of Stochastically Varying Creep Parameters on Residual Stresses in Ceramic Matrix Composites

Constituent properties, along with volume fraction, have a first order effect on the microscale fields within a composite material and influence the macroscopic response. Therefore, there is a need to assess the significance of stochastic variation in the constituent properties of composites at the higher scales. The effect of variability in the parameters controlling the time-dependent behavior, in a unidirectional SCS-6 SiC fiber-reinforced RBSN matrix composite lamina, on the residual stresses induced during processing is investigated numerically. The generalized method of cells micromechanics theory is utilized to model the ceramic matrix composite lamina using a repeating unit cell. The primary creep phases of the constituents are approximated using a Norton-Bailey, steady state, power law creep model. The effect of residual stresses on the proportional limit stress and strain to failure of the composite is demonstrated. Monte Carlo simulations were conducted using a normal distribution for the power law parameters and the resulting residual stress distributions were predicted

Multiscale Modeling of Ceramic Matrix Composites

Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured

A Compilation of MATLAB Scripts and Functions for MACGMC Analyses

The primary aim of the current effort is to provide scripts that automate many of the repetitive pre- and post-processing tasks associated with composite materials analyses using the Micromechanics Analysis Code with the Generalized Method of Cells. This document consists of a compilation of hundreds of scripts that were developed in MATLAB (The Mathworks, Inc., Natick, MA) programming language and consolidated into 16 MATLAB functions. (MACGMC). MACGMC is a composite material and laminate analysis software code developed at NASA Glenn Research Center. The software package has been built around the generalized method of cells (GMC) family of micromechanics theories. The computer code is developed with a user-friendly framework, along with a library of local inelastic, damage, and failure models. Further, application of simulated thermo-mechanical loading, generation of output results, and selection of architectures to represent the composite material have been automated to increase the user friendliness, as well as to make it more robust in terms of input preparation and code execution. Finally, classical lamination theory has been implemented within the software, wherein GMC is used to model the composite material response of each ply. Thus, the full range of GMC composite material capabilities is available for analysis of arbitrary laminate configurations as well. The pre-processing tasks include generation of a multitude of different repeating unit cells (RUCs) for CMCs and PMCs, visualization of RUCs from MACGMC input and output files and generation of the RUC section of a MACGMC input file. The post-processing tasks include visualization of the predicted composite response, such as local stress and strain contours, damage initiation and progression, stress-strain behavior, and fatigue response. In addition to the above, several miscellaneous scripts have been developed that can be used to perform repeated Monte-Carlo simulations to enable probabilistic simulations with minimal manual intervention. This document is formatted to provide MATLAB source files and descriptions of how to utilize them. It is assumed that the user has a basic understanding of how MATLAB scripts work and some MATLAB programming experience

Modeling of Melt-Infiltrated SiC/SiC Composite Properties

The elastic properties of a two-dimensional five-harness melt-infiltrated silicon carbide fiber reinforced silicon carbide matrix (MI SiC/SiC) ceramic matrix composite (CMC) were predicted using several methods. Methods used in this analysis are multiscale laminate analysis, micromechanics-based woven composite analysis, a hybrid woven composite analysis, and two- and three-dimensional finite element analyses. The elastic properties predicted are in good agreement with each other as well as with the available measured data. However, the various methods differ from each other in three key areas: (1) the fidelity provided, (2) the efforts required for input data preparation, and (3) the computational resources required. Results also indicate that efficient methods are also able to provide a reasonable estimate of local stress fields

Stochastic Simulation of Mudcrack Damage Formation in an Environmental Barrier Coating

The FEAMAC/CARES program, which integrates finite element analysis (FEA) with the MAC/GMC (Micromechanics Analysis Code with Generalized Method of Cells) and the CARES/Life (Ceramics Analysis and Reliability Evaluation of Structures / Life Prediction) programs, was used to simulate the formation of mudcracks during the cooling of a multilayered environmental barrier coating (EBC) deposited on a silicon carbide substrate. FEAMAC/CARES combines the MAC/GMC multiscale micromechanics analysis capability (primarily developed for composite materials) with the CARES/Life probabilistic multiaxial failure criteria (developed for brittle ceramic materials) and Abaqus (Dassault Systmes) FEA. In this report, elastic modulus reduction of randomly damaged finite elements was used to represent discrete cracking events. The use of many small-sized low-aspect-ratio elements enabled the formation of crack boundaries, leading to development of mudcrack-patterned damage. Finite element models of a disk-shaped three-dimensional specimen and a twodimensional model of a through-the-thickness cross section subjected to progressive cooling from 1,300 C to an ambient temperature of 23 C were made. Mudcrack damage in the coating resulted from the buildup of residual tensile stresses between the individual material constituents because of thermal expansion mismatches between coating layers and the substrate. A two-parameter Weibull distribution characterized the coating layer stochastic strength response and allowed the effect of the Weibull modulus on the formation of damage and crack segmentation lengths to be studied. The spontaneous initiation of cracking and crack coalescence resulted in progressively smaller mudcrack cells as cooling progressed, consistent with a fractal-behaved fracture pattern. Other failure modes such as delamination, and possibly spallation, could also be reproduced. The physical basis assumed and the heuristic approach employed, which involves a simple stochastic cellular automaton methodology to approximate the crack growth process, are described. The results ultimately show that a selforganizing mudcrack formation can derive from a Weibull distribution that is used to describe the stochastic strength response of the bulk brittle ceramic material layers of an EBC

Advanced Manifolds for Improved Solid Oxide Electrolyzer Performance

An investigation was conducted to see if additive manufacturing could be used to fabricate more efficient manifold designs for improved flow, reduced stresses, and decreased number of joints to be sealed for a solid oxide electrolyzer used to convert carbon dioxide to oxygen. Computational flow and mechanical modeling were conducted on a NASA Glenn Research Center patented cell and stack design with the potential to achieve a 3-4 times mass reduction. Various manifold designs were modeled, and two were downselected to be fabricated and tested. Some benefit was seen in a baffled manifold design, which directed incoming flow more effectively into the flow channels, compared to the original design, where the flow spent more time within the manifold itself. Flow measurements indicated some non-uniformity of flow across the channels at higher flow rates, which were not predicted by the model. Some possible explanations for the differences are discussed

Modeling of Time-Dependent Strength Degradation of SiC/SiC Ceramic Matrix Composites via MAC/GMC Computer Code

Silicon carbide fiber reinforced silicon carbide (SiC/SiC) ceramic matrix composites (CMCs) display time-dependent strength degradation at intermediate temperatures (600 to 900 degrees Centigrade). This is generally believed to be an oxidation induced phenomenon. The understanding of the effect of temperature with environment (oxidation) is key towards development of SiC/SiC CMCs with a reliable load carrying capacity. Various theories have been proposed to explain the strength degradation. One suggests that the boron nitride (BN) coating deposited on the fibers oxidizes causing fusion of fibers. Another theory proposes that the SiC fibers are oxidized forming a silica scale leading to premature fiber failure. A more recent theory suggests that SiC fiber strength is intrinsically time-dependent due to slow crack growth of flaws in the fibers. An empirical model, termed as a "fiber classic model," which is based on a standard slow crack growth type power-law, has been implemented within NASA's micromechanics-based MAC/GMC computer code as a user routine. Model parameters for this "classic model" were calibrated from stress-rupture data of Hi-Nicalon (TM) monofilaments using the maximum likelihood estimation (MLE) technique. This new capability in the MAC/GMC computer code was then used to predict the stress-rupture behavior of Hi-Nicalon (TM) tows as well as 2-D SiC/SiC composites reinforced with Hi-Nicalon (TM) fibers. Results demonstrate that the MAC/GMC with this new capability successfully predicts the time-to-failure vs. applied stress within the intermediate temperature range at various scales as well as laminated composites in an oxidizing environment

Common variation in ISL1 confers genetic susceptibility for human congenital heart disease

Congenital heart disease (CHD) is the most common birth abnormality and the etiology is unknown in the overwhelming majority of cases. ISLET1 (ISL1) is a transcription factor that marks cardiac progenitor cells and generates diverse multipotent cardiovascular cell lineages. The fundamental role of ISL1 in cardiac morphogenesis makes this an exceptional candidate gene to consider as a cause of complex congenital heart disease. We evaluated whether genetic variation in ISL1 fits the common variant-common disease hypothesis. A 2-stage case-control study examined 27 polymorphisms mapping to the ISL1 locus in 300 patients with complex congenital heart disease and 2,201 healthy pediatric controls. Eight genic and flanking ISL1 SNPs were significantly associated with complex congenital heart disease. A replication study analyzed these candidate SNPs in 1,044 new cases and 3,934 independent controls and confirmed that genetic variation in ISL1 is associated with risk of non-syndromic congenital heart disease. Our results demonstrate that two different ISL1 haplotypes contribute to risk of CHD in white and black/African American populations

Stochastic-Strength-Based Damage Simulation of Ceramic Matrix Composite Laminates

The Finite Element Analysis-Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program was used to characterize and predict the progressive damage response of silicon-carbide-fiber-reinforced reaction-bonded silicon nitride matrix (SiC/RBSN) composite laminate tensile specimens. Studied were unidirectional laminates [0] (sub 8), [10] (sub 8), [45] (sub 8), and [90] (sub 8); cross-ply laminates [0 (sub 2) divided by 90 (sub 2),]s; angled-ply laminates [plus 45 (sub 2) divided by -45 (sub 2), ]s; doubled-edge-notched [0] (sub 8), laminates; and central-hole laminates. Results correlated well with the experimental data. This work was performed as a validation and benchmarking exercise of the FEAMAC/CARES program. FEAMAC/CARES simulates stochastic-based discrete-event progressive damage of ceramic matrix composite and polymer matrix composite material structures. It couples three software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/Life), and (3) the Abaqus finite element analysis program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating-unit-cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC, and Abaqus is used to model the overall composite structure. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events that incrementally progress until ultimate structural failure

Contribution of Color Information in Visual Saliency Model for Videos

International audienceMuch research has been concerned with the contribution of the low level features of a visual scene to the deployment of visual attention. Bottom-up saliency models have been developed to predict the location of gaze according to these features. So far, color besides to brightness, contrast and motion is considered as one of the primary features in computing bottom-up saliency. However, its contribution in guiding eye movements when viewing natural scenes has been debated. We investigated the contribution of color information in a bottom-up visual saliency model. The model efficiency was tested using the experimental data obtained on 45 observers who were eye tracked while freely exploring a large data set of color and grayscale videos. The two datasets of recorded eye positions, for grayscale and color videos, were compared with a luminance-based saliency model. We incorporated chrominance information to the model. Results show that color information improves the performance of the saliency model in predicting eye positions