3 resultados para Fatigue Behavior

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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This thesis proposes an integrated holistic approach to the study of neuromuscular fatigue in order to encompass all the causes and all the consequences underlying the phenomenon. Starting from the metabolic processes occurring at the cellular level, the reader is guided toward the physiological changes at the motorneuron and motor unit level and from this to the more general biomechanical alterations. In Chapter 1 a list of the various definitions for fatigue spanning several contexts has been reported. In Chapter 2, the electrophysiological changes in terms of motor unit behavior and descending neural drive to the muscle have been studied extensively as well as the biomechanical adaptations induced. In Chapter 3 a study based on the observation of temporal features extracted from sEMG signals has been reported leading to the need of a more robust and reliable indicator during fatiguing tasks. Therefore, in Chapter 4, a novel bi-dimensional parameter is proposed. The study on sEMG-based indicators opened a scenario also on neurophysiological mechanisms underlying fatigue. For this purpose, in Chapter 5, a protocol designed for the analysis of motor unit-related parameters during prolonged fatiguing contractions is presented. In particular, two methodologies have been applied to multichannel sEMG recordings of isometric contractions of the Tibialis Anterior muscle: the state-of-the-art technique for sEMG decomposition and a coherence analysis on MU spike trains. The importance of a multi-scale approach has been finally highlighted in the context of the evaluation of cycling performance, where fatigue is one of the limiting factors. In particular, the last chapter of this thesis can be considered as a paradigm: physiological, metabolic, environmental, psychological and biomechanical factors influence the performance of a cyclist and only when all of these are kept together in a novel integrative way it is possible to derive a clear model and make correct assessments.

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Shape memory materials (SMMs) represent an important class of smart materials that have the ability to return from a deformed state to their original shape. Thanks to such a property, SMMs are utilized in a wide range of innovative applications. The increasing number of applications and the consequent involvement of industrial players in the field have motivated researchers to formulate constitutive models able to catch the complex behavior of these materials and to develop robust computational tools for design purposes. Such a research field is still under progress, especially in the prediction of shape memory polymer (SMP) behavior and of important effects characterizing shape memory alloy (SMA) applications. Moreover, the frequent use of shape memory and metallic materials in biomedical devices, particularly in cardiovascular stents, implanted in the human body and experiencing millions of in-vivo cycles by the blood pressure, clearly indicates the need for a deeper understanding of fatigue/fracture failure in microsize components. The development of reliable stent designs against fatigue is still an open subject in scientific literature. Motivated by the described framework, the thesis focuses on several research issues involving the advanced constitutive, numerical and fatigue modeling of elastoplastic and shape memory materials. Starting from the constitutive modeling, the thesis proposes to develop refined phenomenological models for reliable SMA and SMP behavior descriptions. Then, concerning the numerical modeling, the thesis proposes to implement the models into numerical software by developing implicit/explicit time-integration algorithms, to guarantee robust computational tools for practical purposes. The described modeling activities are completed by experimental investigations on SMA actuator springs and polyethylene polymers. Finally, regarding the fatigue modeling, the thesis proposes the introduction of a general computational approach for the fatigue-life assessment of a classical stent design, in order to exploit computer-based simulations to prevent failures and modify design, without testing numerous devices.

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Laser Shock Peening (LSP) is a surface enhancement treatment which induces a significant layer of beneficial compressive residual stresses up to several mm underneath the surface of metal components in order to improve the detrimental effects of crack growth behavior rate in it. The aim of this thesis is to predict the crack growth behavior of thin Aluminum specimens with one or more LSP stripes defining a compressive residual stress area. The LSP treatment has been applied as crack retardation stripes perpendicular to the crack growing direction, with the objective of slowing down the crack when approaching the LSP patterns. Different finite element approaches have been implemented to predict the residual stress field left by the laser treatment, mostly by means of the commercial software Abaqus/Explicit. The Afgrow software has been used to predict the crack growth behavior of the component following the laser peening treatment and to detect the improvement in fatigue life comparing to the specimen baseline. Furthermore, an analytical model has been implemented on the Matlab software to make more accurate predictions on fatigue life of the treated components. An educational internship at the Research and Technologies Germany- Hamburg department of Airbus helped to achieve knowledge and experience to write this thesis. The main tasks of the thesis are the following: -To up to date Literature Survey related to laser shock peening in metallic structures -To validate the FE models developed against experimental measurements at coupon level -To develop design of crack growth slow down in centered and edge cracked tension specimens based on residual stress engineering approach using laser peened patterns transversal to the crack path -To predict crack growth behavior of thin aluminum panels -To validate numerical and analytical results by means of experimental tests.