132 resultados para Defect Prediction
Resumo:
The prediction of cracking direction in composite materials is of significance to the design of composite structures. This paper presents several methods for predicting the cracking direction in the double grooved tension-shear specimen which gives mixed-mode cracking. Five different criteria are used in this analysis: two of them have been used by other investigators and the others are proposed by the present authors. The strain energy density criterion proposed by G.C. Sih is modified to take account of the influence of the anisotropy of the strength on the direction of crack. The two failure criteria of Tsai-Hill and Norris are extended to predict the crack orientation. The stress distributions in the near-notch zone are calculated by using the 8-node quadrilateral isoparametric finite element method. The predictions of all the criteria except one are in good agreement with the experimental measurement. In addition, on the basis of the FEM results, the size of the zone in which the singular term is dominant is estimated.
Resumo:
The recent application of large-eddy simulation (LES) to particle-laden turbulence requires that the LES with a subgrid scale (SGS) model could accurately predict particle distributions. Usually, a SGS particle model is used to recover the small-scale structures of velocity fields. In this study, we propose a rescaling technique to recover the effects of small-scale motions on the preferential concentration of inertial particles. The technique is used to simulate particle distribution in isotropic turbulence by LES and produce consistent results with direct numerical simulation (DNS). Key words: particle distribution, particle-laden turbulence, large-eddy simulation, subgrid scale model.
Resumo:
We derive an explicit expression for predicting the thicknesses of shear bands in metallic glasses. The model demonstrates that the shear-band thickness is mainly dominated by the activation size of the shear transformation zone (STZ) and its activation free volume concentration. The predicted thicknesses agree well with the results of measurements and simulations. The underlying physics is attributed to the local topological instability of the activated STZ. The result is of significance in understanding the origin of inhomogeneous flow in metallic glasses. (C) 2009 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Resumo:
Carbon nanotubes (CNTs) have been regarded as ideal reinforcements of high-performance composites with enormous applications. However, the waviness of the CNTs and the interfacial bonding condition between them and the matrix are two key factors that influence the reinforcing efficiency. In this paper, the effects of the waviness of the CNTs and the interfacial debonding between them and the matrix on the effective moduli of CNT-reinforced composites are studied. A simple analytical model is presented to investigate the influence of the waviness on the effective moduli. Then, two methods are proposed to examine the influence of the debonding. It is shown that both the waviness and debonding can significantly reduce the stiffening effect of the CNTs. The effective moduli are very sensitive to the waviness when the latter is small, and this sensitivity decreases with the increase of the waviness. (C) 2008 Elsevier Ltd. All rights reserved.
Resumo:
Many diseases are believed to be related to abnormal protein folding. In the first step of such pathogenic structural changes, misfolding occurs in regions important for the stability of the native structure. This destabilizes the normal protein conformation, while exposing the previously hidden aggregation-prone regions, leading to subsequent errors in the folding pathway. Sites involved in this first stage can be deemed switch regions of the protein, and can represent perfect binding targets for drugs to block the abnormal folding pathway and prevent pathogenic conformational changes. In this study, a prediction algorithm for the switch regions responsible for the start of pathogenic structural changes is introduced. With an accuracy of 94%, this algorithm can successfully find short segments covering sites significant in triggering conformational diseases (CDs) and is the first that can predict switch regions for various CDs. To illustrate its effectiveness in dealing with urgent public health problems, the reason of the increased pathogenicity of H5N1 influenza virus is analyzed; the mechanisms of the pandemic swine-origin 2009 A(H1N1) influenza virus in overcoming species barriers and in infecting large number of potential patients are also suggested. It is shown that the algorithm is a potential tool useful in the study of the pathology of CDs because: (1) it can identify the origin of pathogenic structural conversion with high sensitivity and specificity, and (2) it provides an ideal target for clinical treatment.
Resumo:
A new transition prediction model is introduced, which couples the intermittency effect into the turbulence transport equations and takes the characteristics of fluid transition into consideration to mimic the exact process of transition. Test cases include a two-dimensional incompressible plate and a two-dimensional NACA0012 airfoil. Performance of this transition model for incompressible flows is studied, with numerical results consistent to experimental data. The requirement of grid resolution for this transition model is also studied.
Resumo:
Growth-induced defects in Yb:FAP crystals grown by the Czochralski method have been investigated by optical microscopy, chemical etching, scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). Anisotropic etching features have been observed on two FAP crystal planes: (0001) and (1010). The shape of etch pits on the (0001) plane is hexagonal, while the etch pits on the (1010) plane have a variety of irregular shapes. It is also found that the density of etch pit varies along the boule. Based on the experimental observations, the formation mechanisnis of growth defects are discussed, and methods for reducing the growth-induced defect concentration is proposed. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
A simple and practical model is used to analyse the influence of substrate surface defect on the optical characteristics of a single-layer coating. A single-layer coating is prepared and its optical properties are fitted. Some explanations for the origin of the transition layer are presented. It is concluded that there is a transition layer forming between the substrate and coating, which is attributed to substrate surface defects, and its refractive index change is nearly of linearity.
Resumo:
Optical filters composed of Ag, Al2O3, and ZnSe films were prepared on BK7 substrates by evaporation. By employing spectrophotometer, microscope, scanning electron microscope (SEM), and energy dispersive spectrum (EDS) analysis, the moisture-dependent stability of the samples was tested. The experimental results revealed that filter failure often occurs initially at defect sites. Small sputtering particles and pinhole are found to be two types of defects that induced the optical coating filter failure. The mechanisms of the defect-induced failure of the filters also are discussed in the article. (C) 2005 Elsevier Ltd. All rights reserved.
Resumo:
The initiation of laser damage within optical coatings can be better understood by thermal-mechanical modeling of coating defects. The result of this modeling shows that a high-temperature rise and thermal stress can be seen just inside the nodular defect compared to surrounding coating layers. The temperature rise and thermal stress tend to increase with seed diameter. Shallower seed tend to cause higher temperature rise and greater thermal stress. There is a critical seed depth at which thermal stress is largest. The composition of the seed resulting from different coating-material emission during evaporation can affect the temperature rise and thermal stress distribution.
Resumo:
In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.