874 resultados para surface crack fracture stress-strain field
Guided propagation of surface acoustic waves and piezoelectric field enhancement in ZnO/GaAs systems
Resumo:
The characteristics and dispersion of the distinct surface acoustic waves (SAWs) propagating in ZnO/GaAs heterostructures have been studied experimentally and theoretically. Besides the Rayleigh mode, strong Sezawa modes, which propagate confined in the overlayer, arise due to the smaller sound velocity in ZnO than in the substrate. The design parameters of the structure providing the strongest piezoelectric field at a given depth within the layered system for the different modes have been determined. The piezoelectric field of the Rayleigh mode is shown to be more than 10 times stronger at the interface region of the tailored ZnO/GaAs structure than at the surface region of the bulk GaAs, whereas the same comparison for the first Sezawa mode yields a factor of 2. This enhancement, together with the capacity of selecting waves with different piezoelectric and strain field depth profiles, will facilitate the development of SAW-modulated optoelectronic applications in GaAs-based systems. 2011 American Institute of Physics.
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The stress and strain fields in self-organized growth coherent quantum dots (QD) structures are investigated in detail by two-dimension and three-dimension finite element analyses for lensed-shaped QDs. The nonobjective isolate quantum dot system is used. The calculated results can be directly used to evaluate the conductive band and valence band confinement potential and strain introduced by the effective mass of the charge carriers in strain QD.
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A point interpolation method with locally smoothed strain field (PIM-LS2) is developed for mechanics problems using a triangular background mesh. In the PIM-LS2, the strain within each sub-cell of a nodal domain is assumed to be the average strain over the adjacent sub-cells of the neighboring element sharing the same field node. We prove theoretically that the energy norm of the smoothed strain field in PIM-LS2 is equivalent to that of the compatible strain field, and then prove that the solution of the PIM- LS2 converges to the exact solution of the original strong form. Furthermore, the softening effects of PIM-LS2 to system and the effects of the number of sub-cells that participated in the smoothing operation on the convergence of PIM-LS2 are investigated. Intensive numerical studies verify the convergence, softening effects and bound properties of the PIM-LS2, and show that the very tight lower and upper bound solutions can be obtained using PIM-LS2.
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Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.
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Stereotactic radiosurgery treatments involve the delivery of very high doses for a small number of fractions. To date, there is limited data in terms of the skin dose for the very small field sizes used in these treatments. In this work, we determine relative surface doses for small size circular collimators as used in stereotactic radiosurgery treatments. Monte Carlo calculations were performed using the BEAMnrc code with a model of the Novalis 15 Trilogy linear accelerator and the BrainLab circular collimators. The surface doses were calculated at the ICRU skin dose depth of 70 m all using the 6 MV SRS x-ray beam. The calculated surface doses varied between 15 12% with decreasing values as the field size increased from 4 to 30 mm. In comparison, surface doses were measured using Gafchromic EBT3 film positioned at the surface of a Virtual Water phantom. The absolute agreement between calculated and measured surface doses was better than 2.5% which is well within the 20 uncertainties of the Monte Carlo calculations and the film measurements. Based on these results, we have shown that the Gafchromic EBT3 film is suitable for surface dose estimates in very small size fields as used in SRS.
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The effect of injection and suction on the generalised vortex flow of a steady laminar incompressible fluid over a stationary infinite disc with or without magnetic field under boundary-layer approximations has been studied. The coupled nonlinear ordinary differential equations governing the self-similar flow have been numerically solved using the finite-difference scheme. The results indicate that the injection produces a deeper inflow layer and de-stabilises the motion while suction or magnetic field suppresses the inflow layer and produces stability. The effect of decreasingn, the parameter characterising the nature of vortex flow, is similar to that of increasing the injection rate.
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An experimental investigation into the ambient temperature, load-controlled tensiontension fatigue behavior of a martensitic Nitinol shape memory alloy (SMA) was conducted. Fatigue life for several stress levels spanning the critical stress for detwinning was determined and compared with that obtained on an alloy similar in composition but in the austenitic state at room temperature. Results show that the fatigue life of the pseudo-plastic alloy is superior to superelastic shape memory alloy. The stressstrain hysteretic response, monitored throughout the fatigue loading, reveals progressive strain accumulation with the cyclic loading. In addition, the area of hysteresis and recoverable and frictional energies were found to decrease with increasing number of fatigue cycles. Post-mortem characterization of the fatigued specimens through calorimetry and fractography was conducted in order to get further insight into the fatigue micromechanisms. These results are discussed in terms of reversible and irreversible microstructural changes that take place during cyclic loading. Aspects associated with self-heating of martensitic alloy undergoing high frequency stress cycling are discussed.
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An application of Artificial Neural Networks for predicting the stress-strain response of jointed rocks under different confining pressures is presented in this paper. Rocks of different compressive strength with different joint properties (frequency, orientation and strength of joints) are considered in this study. The database for training the neural network is formed from the results of triaxial compression tests on different intact and jointed rocks with different joint properties tested at different confining pressures reported by various researchers in the literature. The network was trained using a three-layered network with the feed-forward back propagation algorithm.About 85% of the data was used for training and the remaining 15% was used for testing the network. Results from the analyses demonstrated that the neural network approach is effective in capturing the stress-strain behaviour of intact rocks and the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different jointed rocks, whose intact strength varies from 11.32 MPa to 123 MPa, spacing of joints varies from 10 cm to 100 cm. and confining pressures range from 0 to 13.8 MPa. (C) 2010 Elsevier Ltd. All rights reserved.
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This paper presents test results for 22 high strength deformed bars and nine mild steel bars subjected to monotonic repeated and reversed axial loading to determine the stress-strain behavior. Equations have been proposed for the stress-strain curves and have been compared with test results. Satisfactory agreement was obtained.
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This paper presents test results for 22 high strength deformed bars and nine mild steel bars subjected to monotonic repeated and reversed axial loading to determine the stress-strain behavior. Equations have been proposed for the stress-strain curves and have been compared with test results. Satisfactory agreement was obtained.
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Strength and behaviour of cement stabilised rammed earth (CSRE) is a scantily explored area. The present study is focused on the strength and elastic properties of CSRE. Characteristics of CSRE are influenced by soil composition, density of rammed earth, cement and moisture content. The study is focused on examining (a) role of clay content of the soil on strength of CSRE and arriving at optimum clay fraction of the soil mix, (b) influence of moisture content, cement content and density on strength and (c) stress-strain relationships and elastic properties for CSRE. Major conclusions are (a) there is considerable difference between dry and wet compressive strength of CSRE and the wet to dry strength ratio depends upon the clay fraction of soil mix and cement content, (b) optimum clay fraction yielding maximum compressive strength for CSRE is about 16%, (c) strength of CSRE is highly sensitive to density and for a 20% increase in density the strength increases by 300-500% and (d) in dry state the ultimate strain at failure for CSRE is as high as 1.5%, which is unusual for brittle materials.
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Recycling plastic waste from water bottles has become one of the major challenges worldwide. The present study provides an approach for the use plastic waste as reinforcement material in soil. The experimental results in the form of stress-strain-pore water pressure response are presented. Based on experimental test results, it is observed that the strength of soil is improved and compressibility reduced significantly with addition of a small percentage of plastic waste to the soil. The use of the improvement in strength and compressibility response due to inclusion of plastic waste can be advantageously used in bearing capacity improvement and settlement reduction in the design of shallow foundations. (C) 2010 Elsevier Ltd. All rights reserved.
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Mulberry fiber (Bivoltine) and non-mulberry fiber (Tassar) were subjected to stress-strain studies and the corresponding samples were examined using wide angle X-ray scattering studies. Here we have two different characteristic stress-strain curves and this has been correlated with changes in crystallite shape ellipsoids in all the fibers. Exclusive crystal structure studies of Tassar fibers show interesting feature of transformation from antiparallel chains to parallel chains.
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The applicability of Artificial Neural Networks for predicting the stress-strain response of jointed rocks at varied confining pressures, strength properties and joint properties (frequency, orientation and strength of joints) has been studied in the present paper. The database is formed from the triaxial compression tests on different jointed rocks with different confining pressures and different joint properties reported by various researchers. This input data covers a wide range of rock strengths, varying from very soft to very hard. The network was trained using a 3 layered network with feed forward back propagation algorithm. About 85% of the data was used for training and remaining15% for testing the predicting capabilities of the network. Results from the analyses were very encouraging and demonstrated that the neural network approach is efficient in capturing the complex stress-strain behaviour of jointed rocks. A single neural network is demonstrated to be capable of predicting the stress-strain response of different rocks, whose intact strength vary from 11.32 MPa to 123 MPa and spacing of joints vary from 10 cm to 100 cm for confining pressures ranging from 0 to 13.8 MPa.