396 resultados para Structural mechanics.

em Queensland University of Technology - ePrints Archive


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This contribution outlines Synchrotron-based X-ray micro-tomography and its potential use in structural geology and rock mechanics. The paper complements several recent reviews of X-ray microtomography. We summarize the general approach to data acquisition, post-processing as well as analysis and thereby aim to provide an entry point for the interested reader. The paper includes tables listing relevant beamlines, a list of all available imaging techniques, and available free and commercial software packages for data visualization and quantification. We highlight potential applications in a review of relevant literature including time-resolved experiments and digital rock physics. The paper concludes with a report on ongoing developments and upgrades at synchrotron facilities to frame the future possibilities for imaging sub-second processes in centimetre-sized samples.

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Osteoporotic spinal fractures are a major concern in ageing Western societies. This study develops a multi-scale finite element (FE) model of the osteoporotic lumbar vertebral body to study the mechanics of vertebral compression fracture at both the apparent (whole vertebral body) and micro-structural (internal trabecular bone core)levels. Model predictions were verified against experimental data, and found to provide a reasonably good representation of the mechanics of the osteoporotic vertebral body. This novel modelling methodology will allow detailed investigation of how trabecular bone loss in osteoporosis affects vertebral stiffness and strength in the lumbar spine.

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Acoustic emission (AE) is the phenomenon where high frequency stress waves are generated by rapid release of energy within a material by sources such as crack initiation or growth. AE technique involves recording these stress waves by means of sensors placed on the surface and subsequent analysis of the recorded signals to gather information such as the nature and location of the source. It is one of the several diagnostic techniques currently used for structural health monitoring (SHM) of civil infrastructure such as bridges. Some of its advantages include ability to provide continuous in-situ monitoring and high sensitivity to crack activity. But several challenges still exist. Due to high sampling rate required for data capture, large amount of data is generated during AE testing. This is further complicated by the presence of a number of spurious sources that can produce AE signals which can then mask desired signals. Hence, an effective data analysis strategy is needed to achieve source discrimination. This also becomes important for long term monitoring applications in order to avoid massive date overload. Analysis of frequency contents of recorded AE signals together with the use of pattern recognition algorithms are some of the advanced and promising data analysis approaches for source discrimination. This paper explores the use of various signal processing tools for analysis of experimental data, with an overall aim of finding an improved method for source identification and discrimination, with particular focus on monitoring of steel bridges.

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Research in structural dynamics has received considerable attention due to problems associated with emerging slender structures, increased vulnerability of structures to random loads and aging infrastructure. This paper briefly describes some such research carried out on i) dynamics of composite floor structure, ii) dynamics of cable supported footbridge, iii) seismic mitigation of frame-shear wall structure using passive dampers and iv) development of a damage assessment model for use in structural health modelling.

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This paper is concerned with applying a particle-based approach to simulate the micro-level cellular structural changes of plant cells during drying. The objective of the investigation was to relate the micro-level structural properties such as cell area, diameter and perimeter to the change of moisture content of the cell. Model assumes a simplified cell which consists of two basic components, cell wall and cell fluid. The cell fluid is assumed to be a Newtonian fluid with higher viscosity compared to water and cell wall is assumed to be a visco-elastic solid boundary located around the cell fluid. Cell fluid is modelled with Smoothed Particle Hydrodynamics (SPH) technique and for the cell wall; a Discrete Element Method (DEM) is used. The developed model is two-dimensional, but accounts for three-dimensional physical properties of real plant cells. Drying phenomena is simulated as fluid mass reductions and the model is used to predict the above mentioned structural properties as a function of cell fluid mass. Model predictions are found to be in fairly good agreement with experimental data in literature and the particle-based approach is demonstrated to be suitable for numerical studies of drying related structural deformations. Also a sensitivity analysis is included to demonstrate the influence of key model parameters to model predictions.

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The actin microfilament plays a critical role in many cellular processes including embryonic development, wound healing, immune response, and tissue development. It is commonly organized in the form of networks whose mechanical properties change with changes in their architecture due to cell evolution processes. This paper presents a new nonlinear continuum mechanics model of single filamentous actin (F-actin) that is based on nanoscale molecular simulations. Following this continuum model of the single F-actin, mechanical properties of differently architected lamellipodia are studied. The results provide insight that can contribute to the understanding of the cell edge motions of living cells.

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The texture of agricultural crops changes during harvesting, post harvesting and processing stages due to different loading processes. There are different source of loading that deform agricultural crop tissues and these include impact, compression, and tension. Scanning Electron Microscope (SEM) method is a common way of analysing cellular changes of materials before and after these loading operations. This paper examines the structural changes of pumpkin peel and flesh tissues under mechanical loading. Compression and indentation tests were performed on peel and flesh samples. Samples structure were then fixed and dehydrated in order to capture the cellular changes under SEM. The results were compared with the images of normal peel and flesh tissues. The findings suggest that normal flesh tissue had bigger size cells, while the cellular arrangement of peel was smaller. Structural damage was clearly observed in tissue structure after compression and indentation. However, the damages that resulted from the flat end indenter was much more severe than that from the spherical end indenter and compression test. An integrated deformed tissue layer was observed in compressed tissue, while the indentation tests shaped a deformed area under the indenter and left the rest of the tissue unharmed. There was an obvious broken layer of cells on the walls of the hole after the flat end indentations, whereas the spherical indenter created a squashed layer all around the hole. Furthermore, the influence of loading was lower on peel samples in comparison with the flesh samples. The experiments have shown that the rate of damage on tissue under constant rate of loading is highly dependent on the shape of equipment. This fact and observed structural changes after loading underline the significance of deigning post harvesting equipments to reduce the rate of damage on agricultural crop tissues.

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The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

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Steady and pulsed flow stationary impinging jets have been employed to simulate the wind field produced by a thunderstorm microburst. The effect on the low level wind field due to jet inclination with respect to the impingement surface has been studied. A single point velocity time history has been compared to the full-scale Andrews AFB microburst for model validation. It was found that for steady flow, jet inclination increased the radial extent of high winds but did not increase the magnitude of these winds when compared to the perpendicular impingement case. It was found that for inclined pulsed flow the design wind conditions could increase compared to perpendicular impingement. It was found that the location of peak winds was affected by varying the outlet conditions.

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Structural damage detection using modal strain energy (MSE) is one of the most efficient and reliable structural health monitoring techniques. However, some of the existing MSE methods have been validated for special types of structures such as beams or steel truss bridges which demands improving the available methods. The purpose of this study is to improve an efficient modal strain energy method to detect and quantify the damage in complex structures at early stage of formation. In this paper, a modal strain energy method was mathematically developed and then numerically applied to a fixed-end beam and a three-story frame including single and multiple damage scenarios in absence and presence of up to five per cent noise. For each damage scenario, all mode shapes and natural frequencies of intact structures and the first five mode shapes of assumed damaged structures were obtained using STRAND7. The derived mode shapes of each intact and damaged structure at any damage scenario were then separately used in the improved formulation using MATLAB to detect the location and quantify the severity of damage as compared to those obtained from previous method. It was found that the improved method is more accurate, efficient and convergent than its predecessors. The outcomes of this study can be safely and inexpensively used for structural health monitoring to minimize the loss of lives and property by identifying the unforeseen structural damages.

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This paper presents a feasibility study on structural damage alarming and localization of long-span cable-supported bridges using multi-novelty indices formulated by monitoring-derived modal parameters. The proposed method which requires neither structural model nor damage model is applicable to structures of arbitrary complexity. With the intention to enhance the tolerance to measurement noise/uncertainty and the sensitivity to structural damage, an improved novelty index is formulated in terms of auto-associative neural networks (ANNs) where the output vector is designated to differ from the input vector while the training of the ANNs needs only the measured modal properties of the intact structure under in-service conditions. After validating the enhanced capability of the improved novelty index for structural damage alarming over the commonly configured novelty index, the performance of the improved novelty index for damage occurrence detection of large-scale bridges is examined through numerical simulation studies of the suspension Tsing Ma Bridge (TMB) and the cable-stayed Ting Kau Bridge (TKB) incurred with different types of structural damage. Then the improved novelty index is extended to formulate multi-novelty indices in terms of the measured modal frequencies and incomplete modeshape components for damage region identification. The capability of the formulated multi-novelty indices for damage region identification is also examined through numerical simulations of the TMB and TKB.

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The purpose of this research was to develop and test a multicausal model of the individual characteristics associated with academic success in first-year Australian university students. This model comprised the constructs of: previous academic performance, achievement motivation, self-regulatory learning strategies, and personality traits, with end-of-semester grades the dependent variable of interest. The study involved the distribution of a questionnaire, which assessed motivation, self-regulatory learning strategies and personality traits, to 1193 students at the start of their first year at university. Students' academic records were accessed at the end of their first year of study to ascertain their first and second semester grades. This study established that previous high academic performance, use of self-regulatory learning strategies, and being introverted and agreeable, were indicators of academic success in the first semester of university study. Achievement motivation and the personality trait of conscientiousness were indirectly related to first semester grades, through the influence they had on the students' use of self-regulatory learning strategies. First semester grades were predictive of second semester grades. This research provides valuable information for both educators and students about the factors intrinsic to the individual that are associated with successful performance in the first year at university.