6 research outputs found

    Nonlinear analysis of composite shells with application to glass structures

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    Laminated glass is a special composite material, which is characterised by an alternating stiff/soft lay-up owing to the significant stiffness mismatch between glass and PVB. This work is motivated by the need for an efficient and accurate nonlinear model for the analysis of laminated glass structures, which describes well the through-thickness variation of displacement fields and the transverse shear strains and enables large displacement analysis. An efficient lamination model is proposed for the analysis of laminated composites with an alternating stiff/soft lay-up, where the zigzag variation of planar displacements is taken into account by adding to the Reissner-Mindlin formulation a specific set of zigzag functions. Furthermore, a piecewise linear through-thickness distribution of the material transverse shear strain is assumed, which agrees well with the real distribution, yet it avoids layer coupling by not imposing continuity constraints on transverse shear stresses. Local formulations of curved multi-layer shell elements are established employing the proposed lamination model, which are framed within local co-rotational systems to allow large displacement analysis for small-strain problems. In order to eliminate the locking phenomenon for the shell elements, an assumed strain method is employed and improved, which readily addresses shear locking, membrane locking, and distortion locking for each constitutive layer. Furthermore, a local shell system is proposed for the direct definition of the additional zigzag displacement fields and associated parameters, which allows the additional displacement variables to be coupled directly between adjacent elements without being subject to the large displacement co-rotational transformations. The developed multi-layer shell elements are employed in this work for typical laminated glass problems, including double glazing systems for which a novel volume-pressure control algorithm is proposed. Several case studies are finally presented to illustrate the effectiveness and efficiency of the proposed modelling approach for the nonlinear analysis of glass structures.Open Acces

    Soft tissue viscoelastic properties: measurements, models and interpretation

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    The quantification of mechanical properties of soft tissues has been of great interest for more than two decades because they have the potential of being used as biomarkers for disease diagnosis. Indentation techniques, the most recognized techniques for characterizing mechanical properties, are widely used for basic science investigations in research labs. The use of elastography techniques coupled with imaging technologies has been growing rapidly in recent years, which is promising for clinical applications. Each technique produces different mechanical behaviors due to the interaction of the stimuli and the structure of the tissue. An appropriate model will parameterize these behaviors to reflect the corresponding tissue microscopic features with high fidelity. The objective of this thesis is to identify combinations of techniques and models that will yield mechanical parameters with diagnostic interpretations about tissue microenvironment. Three techniques for characterizing tissue viscoelastic properties were developed and validated, each offers strengths in a large variety of applications. Indentation based techniques measure low-frequency force-displacement curves under different loading profiles. Ultrasound-based techniques and optical based techniques measure the dispersion behaviors of the propagating wave velocities at mid-to-high frequency ranges. When a material is linear, isotropic, and contains only elastic components, the ā€œintrinsicā€ elastic modulus of the material can be obtained independently of the technique used when corrections are properly made to eliminate the bias from boundary effects. If the material includes time-dependent components, models must be included in the analysis to provide parametric estimates. Classical models for viscoelastic solids such as the Kelvin-Voigt model do not fully represent mechanical measurements in tissues because they are not material continua. Tissue properties are determined in part by fluid movement in the open- and closed-cell compartments found within a viscoelastic collagen matrix that is actively maintained by the embedded cells to meet programmed needs. These biphasic (solid/fluid) media exhibit multifaceted deformation responses that are particularly difficult to model using a concise feature set. The Kelvin-Voigt fractional derivative (KVFD) model introduced in this study represents the measurement data of a broad range in both time and frequency domain with a small number of parameters, and it yields stable estimates for many types of phantoms and tissues. It is superior to the integer derivative models for the materials and techniques we used in this study. Moreover, the KVFD model provides a three-dimensional feature space of mechanical properties that properly characterizes the composition and structure of a material. This was validated through measurements on gelatin-cream emulsion samples exhibiting viscoelastic behavior, as well as ex vivo liver tissue samples. For the elastic property, KVFD parameter E_0 mainly represents the elasticity of the solid matrix and is approximately equal to the shear modulus no matter which technique is used. For the viscous property, when combined with different measurement techniques, KVFD model parameter Ī± and Ļ„ represent different tissue components. The combination of these techniques and the KVFD model have the potential to be able to distinguish between healthy and pathological tissues described by the histological features

    Haptic Enhancement of Sensorimotor Learning for Clinical Training Applications

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    Modern surgical training requires radical change with the advent of increasingly complex procedures, restricted working hours, and reduced ā€˜hands-onā€™ training in the operating theatre. Moreover, an increased focus on patient safety means there is a greater need to objectively measure proficiency in trainee surgeons. Indeed, the existing evidence suggests that surgical sensorimotor skill training is not adequate for modern surgery. This calls for new training methodologies which can increase the acquisition rate of sensorimotor skill. Haptic interventions offer one exciting possible avenue for enhancing surgical skills in a safe environment. Nevertheless, the best approach for implementing novel training methodologies involving haptic intervention within existing clinical training curricula has yet to be determined. This thesis set out to address this issue. In Chapter 2, the development of two novel tools which enable the implementation of bespoke visuohaptic environments within robust experimental protocols is described. Chapters 3 and 4 report the effects of intensive, long-term training on the acquisition of a compliance discrimination skill. The results indicate that active behaviour is intrinsically linked to compliance perception, and that long-term training can help to improve the ability of detecting compliance differences. Chapter 5 explores the effects of error augmentation and parameter space exploration on the learning of a complex novel task. The results indicate that error augmentation can help improve learning rate, and that physical workspace exploration may be a driver for motor learning. This research is a first step towards the design of objective haptic intervention strategies to help support the rapid acquisition of sensorimotor skill. The work has applications in clinical settings such as surgical training, dentistry and physical rehabilitation, as well as other areas such as sport
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