948 resultados para Composite particle models


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In this paper, a methodology to reduce composite structure maintenance operational cost using SHM systems is adressed. Based on SHM real-time data, in-service structure lifetime prognostic and remaining useful lifetime (RUL) can be performed. Maintenance timetable can be therefore predicted by optimizing inspection times. A probabilistic ap-proach is combined with phenomenological fatigue damage models for composite mate-rials to perform maintenance cost-effectiveness of composite structure. A Monte Carlo method is used to estimate the probability of failure of composite structures and com-pute the average number of composite structure components to be replaced over the component lifetime. The replacement frequency of a given structure component over the aircraft lifetime is assessed. A first application of aeronautical composite structure maintenance is considered. Two composite models to predict the fatigue life and several laminates have been used. Our study shows that maintenance cost-effectiveness depends on material and fatigue loading applied.

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Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problein in damage assessment. A recently developed C-0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data. (C) 2016 Elsevier Ltd. All rights reserved.

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In this paper, the effect of particle size on the formation of adiabatic shear band in 2024 All matrix composites reinforced with 15% volume fraction of 3.5, 10 and 20 mum SiC particles was investigated by making use of split Hopkinson pressure bar (SHPB). The results have demonstrated that the onset of adiabatic shear banding in the composites strongly depends on the particle size and adiabatic shear banding is more readily observed in the composite reinforced with small particles than that in the composite with large particles. This size dependency phenomenon can be characterized by the strain gradient effect. Instability analysis reveals that high strain gradient is a strong driving force for the formation of adiabatic shear banding in particle reinforced metal matrix composites (MMCp).

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针对高体积份数、随机分布、等轴状颗粒增强复合材料 ,研究了材料的应变分布规律 ,给出了基体和增强体应变平均值与材料微观结构参数之间的定量关系。结果表明 ,除应变平均值外 ,应变涨落是影响刚度张量的另一个重要因素 ,研究了应变涨落与材料微观结构参数之间的关系 ,并推导出了复合材料的刚度张量。与实验结果和以往的理论比较 ,预测结果与实验结果吻合良好

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Dislocation models with considering the mismatch of elastic modulus between matrix and reinforcing particles are used to determine the effective strain gradient \ita for particle reinforced metal matrix composites (MMCp) in the present research. Based on Taylor relation and the kinetics of dislocation multiplication, glide and annihilation, a strain gradient dependent constitutive equation is developed. By using this strain gradient-dependent constitutive equation, size-dependent deformation strengthening behavior is characterized. The results demonstrate that the smaller the particle size, the more excellent in the reinforcing effect. Some comparisons with the available experimental results demonstrate that the present approach is satisfactory.

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Vertically aligned carbon nanotubes were synthesized by plasma enhanced chemical vapor deposition using nickel as a metal catalyst. High resolution transmission electron microscopy analysis of the particle found at the tip of the tubes reveals the presence of a metastable carbide Ni3C. Since the carbide is found to decompose upon annealing at 600 degreesC, we suggest that Ni3C is formed after the growth is stopped due to the rapid cooling of the Ni-C interstitial solid solution. A detailed description of the tip growth mechanism is given, that accounts for the composite structure of the tube walls. The shape and size of the catalytic particle determine the concentration gradient that drives the diffusion of C atoms across and though the metal. (C) 2004 American Institute of Physics.

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A cylindrical cell model based on continuum theory for plastic constitutive behavior of short-fiber/particle reinforced composites is proposed. The composite is idealized as uniformly distributed periodic arrays of aligned cells, and each cell consists of a cylindrical inclusion surrounded by a plastically deforming matrix. In the analysis, the non-uniform deformation field of the cell is decomposed into the sum of the first order approximate field and the trial additional deformation field. The precise deformation field are determined based on the minimum strain energy principle. Systematic calculation results are presented for the influence of reinforcement volume fraction and shape on the overall mechanical behavior of the composites. The results are in good agreement with the existing finite element analyses and the experimental results. This paper attempts to stimulate the work to get the analytical constitutive relation of short-fiber/particle reinforced composites.

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A study has been performed of the erosion of aluminium by silica sand particles at a velocity of 4.5 m s-1, both air-borne and in the form of a water-borne slurry. Measurements made under similar experimental conditions show that slurry erosion proceeds at a rate several times that of air-borne erosion, the ratio of the two rates depending strongly on the angle of impact. Sand particles become embedded into the metal surface during air-borne particle erosion, forming a composite layer of metal and silica, and provide the major cause of the difference in wear rate. The embedded particles giving rise to surface hardening and a significant reduction in the erosion rate. Embedment of erodent particles was not observed during slurry erosion. Lubrication of the impacting interfaces by water appears to have minimal effect on the wear of aluminium by slurry erosion.

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Dynamic compression tests were performed by means of a Split Hopkinson Pressure Bar (SHPB). Test materials were 2124Al alloys reinforced with 17% volume fraction of 3, 13 and 37 μm SiC particles, respectively. Under strain rate ε = 2100 l/s, SiC particles have a strong effect on σ0.2 of the composites and the σ0.2 increases with different SiC particle size in the following order: 2124Al-alloy → 124Al/SiCp (37 μm) → 2124Al/SiCp (13 μm) → 2124Al/SiCp (3 μm), and the strain hardening of the composites depends mainly on the strain hardening of matrix, 2124A1 alloy. The results of dimensional analysis present that the flow stress of these composites not only depends on the property of reinforcement and matrix but also relates to the microstructure scale, matrix grain size, reinforcement size, the distance between reinforcements and dislocations in matrix. The normalized flow stress here is a function of inverse power of the edge-edge particle spacing, dislocation density and matrix grain size. Close-up observation shows that, in the composite containing SiC particles (3 μm), localized deformation formed readily comparing with other materials under the same loading condition. Microscopic observations indicate that different plastic flow patterns occur within the matrix due to the presence of hard particles with different sizes.

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The influences of I,article size on the mechanical properties of the particulate metal matrix composite;are obviously displayed in the experimental observations. However, the phenomenon can not be predicted directly using the conventional elastic-plastic theory. It is because that no length scale parameters are involved in the conventional theory. In the present research, using the strain gradient plasticity theory, a systematic research of the particle size effect in the particulate metal matrix composite is carried out. The roles of many composite factors, such as: the particle size, the Young's modulus of the particle, the particle aspect ratio and volume fraction, as well as the plastic strain hardening exponent of the matrix material, are studied in detail. In order to obtain a general understanding for the composite behavior, two kinds of particle shapes, ellipsoid and cylinder, are considered to check the strength dependence of the smooth or non-smooth particle surface. Finally, the prediction results will be applied to the several experiments about the ceramic particle-reinforced metal-matrix composites. The material length scale parameter is predicted.

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Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many applications it may be necessary to compute the sensitivity, or derivative, of the optimal filter with respect to the static parameters of the state-space model; for instance, in order to obtain maximum likelihood model parameters of interest, or to compute the optimal controller in an optimal control problem. In Poyiadjis et al. [2011] an original particle algorithm to compute the filter derivative was proposed and it was shown using numerical examples that the particle estimate was numerically stable in the sense that it did not deteriorate over time. In this paper we substantiate this claim with a detailed theoretical study. Lp bounds and a central limit theorem for this particle approximation of the filter derivative are presented. It is further shown that under mixing conditions these Lp bounds and the asymptotic variance characterized by the central limit theorem are uniformly bounded with respect to the time index. We demon- strate the performance predicted by theory with several numerical examples. We also use the particle approximation of the filter derivative to perform online maximum likelihood parameter estimation for a stochastic volatility model.

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Lattice-type model can simulate in a straightforward manner heterogeneous brittle media. Mohr-Coulomb failure criterion has recently been involved into the generalized beam (GB) lattice model, and as a result, numerical experiments on concrete under various loading conditions can be conducted. The GB lattice model is further used to investigate the reinforced fiber/particle composites instead of only particle composites as the model did before. Numerical examples are given to show the effectiveness of the modeling procedure, and influences of inclusions (particle, fiber and rebar) on the fracture processes are also discussed. (c) 2008 Elsevier Ltd. All rights reserved.

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We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals "on-the-fly" as well as their limiting occupation measures with a given precision degree that does not depend on the final time horizon. We provide uniform convergence results with respect to the time horizon parameter as well as functional central limit theorems and exponential concentration estimates. Our results have important consequences for online parameter estimation for non-linear non-Gaussian state-space models. We show how the forward filtering backward smoothing estimates of additive functionals can be computed using a forward only recursion.

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The influence of the thermal residual stress on the deformation behavior of a composite has been analyzed with a new micromechanical method. The method is based on secant moduli approximation and a new homogenized effective stress to characterize the plastic state of the matrix. It is found that the generated thermal residual stresses after cooling and their influence on the subsequent deformation behavior depends significantly on the aspect ratio of the inclusions. With prolate inclusions, the presence of thermal residual stresses generate a higher compressive hardening curves of the composite, but it is reversed with oblate inclusions. For particle reinforced composite, thermal residual stresses induce a tensile hardening curve higher than the compressive one and this is in agreement with experimental observations. (C) 1998 Elsevier Science Ltd.

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A general analytical model for a composite with an isotropic matrix and two populations of spherical inclusions is proposed. The method is based on the second order moment of stress for evaluating the homogenised effective stress in the matrix and on the secant moduli concept for the plastic deformation. With Webull's statistical law for the strength of SiCp particles, the model can quantitatively predict the influence of particle fracture on the mechanical properties of PMMCs. Application of the proposed model to the particle cluster shows that the particle cluster has neglected influence on the strain and stress curves of the composite. (C) 1998 Elsevier Science B.V.