18 resultados para damage evolution process

em Cambridge University Engineering Department Publications Database


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In the field of vibration-based damage detection of concrete structures efficient damage models are needed to better understand changes in the vibration properties of cracked structures. These models should quantitatively replicate the damage mechanisms in concrete and easily be used as damage detection tools. In this paper, the flexural cracking behaviour of plain concrete prisms subject to monotonic and cyclic loading regimes under displacement control is tested experimentally and modelled numerically. Four-point bending tests on simply supported un-notched prisms are conducted, where the cracking process is monitored using a digital image correlation system. A numerical model, with a single crack at midspan, is presented where the cracked zone is modelled using the fictitious crack approach and parts outside that zone are treated in a linear-elastic manner. The model considers crack initiation, growth and closure by adopting cyclic constitutive laws. A multi-variate Newton-Raphson iterative solver is used to solve the non-linear equations to ensure equilibrium and compatibility at the interface of the cracked zone. The numerical results agree well with the experiments for both loading scenarios. The model shows good predictions of the degradation of stiffness with increasing load. It also approximates the crack-mouth-opening-displacement when compared with the experimental data of the digital image correlation system. The model is found to be computationally efficient as it runs full analysis for cyclic loading in less than 2. min, and it can therefore be used within the damage detection process. © 2013 Elsevier Ltd.

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Bone as most of living tissues is able, during its entire lifetime, to adapt its internal microstructure and subsequently its associated mechanical properties to its specific mechanical and physiological environment in a process commonly known as bone remodelling. Bone is therefore continuously renewed and micro-damage, accumulated by fatigue or creep, is removed minimizing the risk of fracture. Nevertheless, bone is not always able to repair itself completely. Actually, if bone repairing function is slower than micro-damage accumulation, a type of bone fracture, usually known as "stress fracture", can finally evolve. In this paper, we propose a bone remodelling continuous model able to simulate micro-damage growth and repair in a coupled way and able therefore to predict the occurrence of "stress fractures". The biological bone remodelling process is modelled in terms of equations that describe the activity of basic multicellular units. The predicted results show a good correspondence with experimental and clinical data. For example, in disuse, bone porosity increases until an equilibrium situation is achieved. In overloading, bone porosity decreases unless the damage rate is so high that causes resorption or "stress fracture".

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We investigate the evolution of localized blobs of swirling or buoyant fluid in an infinite, inviscid, electrically conducting fluid. We consider the three cases of a strong imposed magnetic field, a weak imposed magnetic field, and no magnetic field. For a swirling blob in the absence of a magnetic field, we find, in line with others, that the blob bursts radially outward under the action of the centrifugal force, forming a thin annular vortex sheet. A simple model of this process predicts that the vortex sheet thins exponentially fast and that it moves radially outward with constant velocity. These predictions are verified by high-resolution numerical simulations. When an intense magnetic field is applied, this phenomenon is suppressed, with the energy and angular momentum of the blob now diffusing axially along the magnetic field lines, converting the blob into a columnar structure. For modest or weak magnetic fields, there are elements of both types of behavior, with the radial bursting dominating over axial diffusion for weak fields. However, even when the magnetic field is very weak, the flow structure is quite distinct to that of the nonmagnetic case. In particular, a small but finite magnetic field places a lower bound on the thickness of the annular vortex sheet and produces an annulus of counter-rotating fluid that surrounds the vortex core. The behavior of the buoyant blob is similar. In the absence of a magnetic field, it rapidly develops the mushroomlike shape of a thermal, with a thin vortex sheet at the top and sides of the mushroom. Again, a simple model of this process predicts that the vortex sheet at the top of the thermal thins exponentially fast and rises with constant velocity. These predictions are consistent with earlier numerical simulations. Curiously, however, it is shown that the net vertical momentum associated with the blob increases linearly in time, despite the fact that the vertical velocity at the front of the thermal is constant. As with the swirling blob, an imposed magnetic field inhibits the formation of a vortex sheet. A strong magnetic field completely suppresses the phenomenon, replacing it with an axial diffusion of momentum, while a weak magnetic field allows the sheet to form, but places a lower bound on its thickness. The magnetic field does not, however, change the net vertical momentum of the blob, which always increases linearly with time.

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Design work involves uncertainty that arises from, and influences, the progressive development of solutions. This paper analyses the influences of evolving uncertainty levels on the design process. We focus on uncertainties associated with choosing the values of design parameters, and do not consider in detail the issues that arise when parameters must first be identified. Aspects of uncertainty and its evolution are discussed, and a new task-based model is introduced to describe process behaviour in terms of changing uncertainty levels. The model is applied to study two process configuration problems based on aircraft wing design: one using an analytical solution and one using Monte-Carlo simulation. The applications show that modelling uncertainty levels during design can help assess management policies, such as how many concepts should be considered during design and to what level of accuracy. © 2011 Springer-Verlag.

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Breather stability and longevity in thermally relaxing nonlinear arrays is investigated under the scrutiny of the analysis and tools employed for time series and state reconstruction of a dynamical system. We briefly review the methods used in the analysis and characterize a breather in terms of the results obtained with such methods. Our present work focuses on spontaneously appearing breathers in thermal Fermi-Pasta-Ulam arrays but we believe that the conclusions are general enough to describe many other related situations; the particular case described in detail is presented as another example of systems where three incommensurable frequencies dominate their chaotic dynamics (reminiscent of the Ruelle-Takens scenario for the appearance of chaotic behavior in nonlinear systems). This characterization may also be of great help for the discovery of breathers in experimental situations where the temporal evolution of a local variable (like the site energy) is the only available/measured data. © 2005 American Institute of Physics.

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In FEA of ring rolling processes the tools' motions usually are defined prior to simulation. This procedure neglects the closed-loop control, which is used in industrial processes to control up to eight degrees of freedom (rotations, feed rates, guide rolls) in real time, taking into account the machine's performance limits as well as the process evolution. In order to close this gap in the new simulation approach all motions of the tools are controlled according to sensor values which are calculated within the FE simulation. This procedure leads to more realistic simulation results in comparison to the machine behaviour. © 2012 CIRP.

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The prediction of time-changing variances is an important task in the modeling of financial data. Standard econometric models are often limited as they assume rigid functional relationships for the evolution of the variance. Moreover, functional parameters are usually learned by maximum likelihood, which can lead to over-fitting. To address these problems we introduce GP-Vol, a novel non-parametric model for time-changing variances based on Gaussian Processes. This new model can capture highly flexible functional relationships for the variances. Furthermore, we introduce a new online algorithm for fast inference in GP-Vol. This method is much faster than current offline inference procedures and it avoids overfitting problems by following a fully Bayesian approach. Experiments with financial data show that GP-Vol performs significantly better than current standard alternatives.

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The achievement of the desirable morphology at the nanometer scale of bulk heterojunctions consisting of a conjugated polymer with fullerene derivatives is a prerequisite in order to optimize the power conversion efficiency of organic solar cells. The various experimental conditions such as the choice of solvent, drying rates and annealing have been found to significantly affect the blend morphology and the final performance of the photovoltaic device. In this work, we focus on the effects of post deposition thermal annealing at 140 °C on the blend morphology, the optical and structural properties of bulk heterojunctions that consist of poly(3-hexylthiophene) (P3HT) and a methanofullerene derivative (PCBM). The post thermal annealing modifies the distribution of the P3HT and the PCBM inside the blend films, as it has been found by Spectroscopic Ellipsometry studies in the visible to far-ultraviolet spectral range. Phase separation was identified by AFM and GIXRD as a result of a slow drying process which took place after the spin coating process. The increase of the annealing time resulted to a significant increase of the P3HT crystallinity at the top regions of the blend films. © 2011 Elsevier B.V. All rights reserved.