A análise da formação e crescimento de fissuras em peças de concreto armado permanece como uma das principais dificuldades no campo da engenharia estrutural. Considerando que as fissuras têm uma influência muito grande no comportamento estrutural global, estudos para prever e controlar a fissuração do concreto são de essencial importância. O objetivo deste trabalho é apresentar um modelo numérico do tipo incorporado para representar as fissuras em peças de concreto armado submetidas aos esforços de flexão e corte, ou seja, um modelo que seja capaz de simular, além das fissuras perpendiculares ao eixo da peça, fissuras inclinadas. Os modelos de fissura incorporada se baseiam no conceito de descontinuidades incorporadas dentro de elementos finitos padrões. No modelo empregado neste trabalho, a fissura é representada através de uma descontinuidade no campo interno de deslocamentos do elemento. O modelo incorporado implementado é uma continuação do trabalho desenvolvido por d’Avila, que baseou-se no modelo de Dvorkin Cuitiño e Gioia que, por sua vez, não inclui a contribuição da armadura no equilíbrio interno de forças do elemento. A interação entre as barras de aço e o concreto é simulada através um modelo de transferência de tensão por aderência entre os dois materiais, conforme Russo, Zingone e Romano e FIB - Bulletin 10. Para representar o comportamento do concreto intacto, utiliza-se o modelo constitutivo de Ottosen. Já para representar as barras de aço da armadura, emprega-se o modelo incorporado desenvolvido por Elwi e Hrudey, que permite uma disposição arbitrária das barras de aço no interior dos elementos de concreto. O modelo constitutivo adotado para a armadura é do tipo elasto-plástico com endurecimento. Foi possível simular a fissuração em flexão e corte em vigas de concreto armado com boa correlação com resultados experimentais. Tais situações não poderiam ser analisadas pelo modelo básico sem as modificações propostas nesta dissertação. / The analysis of the formation and growth of cracks in reinforced concrete members remains as one of the main difficulties in the field of structural engineering. Considering that the crack has a considerable influence in the global structural behavior, studies to predict and to control concrete cracking are of essential importance. The aim of this work is to present a numerical model of the embedded type to represent the cracks in reinforced concrete members under bending and shearing efforts, i. e. , a model that is capable to simulate not only cracks that are perpendicular to the axle of the members but also inclined cracks. The embedded crack models are based on the concept of incorporated discontinuities inside of standard finite elements. In the model used in this work, the crack is represented by a discontinuity in the internal field of the element displacements. The embedded model proposed is a continuation of the work developed by d’Avila, which is based on the model of Dvorkin, Cuitiño e Gioia, that does not consider the inclusion of the reinforced contribution in the internal force equilibrium of the element. A bond stress-transfer approach is used to include this reinforcement contribution. To represent the behavior of the uncracked concrete, the Ottosen constitutive model was used. The embedded model presented by Elwi and Hrudey was employed to represent the reinforcement bars, that allows an arbitrary disposal of the bars of steel inside of the concrete elements. The constitutive model adopted for reinforcement is elasto-plastic with hardening. It was possible to simulate the cracking in bending and shearing in reinforced concrete beams with good agreement with experimental results. These cases could not be analyzed by the basi model without the present proposed modifications.

abstract: Transcranial electrical stimulation (tES) is a non-invasive brain stimulation therapy that has shown potential in improving motor, physiological and cognitive functions in healthy and diseased population. Typical tES procedures involve application of weak current (< 2 mA) to the brain via a pair of large electrodes placed on the scalp. While the therapeutic benefits of tES are promising, the efficacy of tES treatments is limited by the knowledge of how current travels in the brain. It has been assumed that the current density and electric fields are the largest, and thus have the most effect, in brain structures nearby the electrodes. Recent studies using finite element modeling (FEM) have suggested that current patterns in the brain are diffuse and not concentrated in any particular brain structure. Although current flow modeling is useful means of informing tES target optimization, few studies have validated tES FEM models against experimental measurements. MREIT-CDI can be used to recover magnetic flux density caused by current flow in a conducting object. This dissertation reports the first comparisons between experimental data from in-vivo human MREIT-CDI during tES and results from tES FEM using head models derived from the same subjects. First, tES FEM pipelines were verified by confirming FEM predictions agreed with analytic results at the mesh sizes used and that a sufficiently large head extent was modeled to approximate results on human subjects. Second, models were used to predict magnetic flux density, and predicted and MREIT-CDI results were compared to validate and refine modeling outcomes. Finally, models were used to investigate inter-subject variability and biological side effects reported by tES subjects. The study demonstrated good agreements in patterns between magnetic flux distributions from experimental and simulation data. However, the discrepancy in scales between simulation and experimental data suggested that tissue conductivities typically used in tES FEM might be incorrect, and thus performing in-vivo conductivity measurements in humans is desirable. Overall, in-vivo MREIT-CDI in human heads has been established as a validation tool for tES predictions and to study the underlying mechanisms of tES therapies. / Dissertation/Thesis / Doctoral Dissertation Biomedical Engineering 2017

abstract: A cerebral aneurysm is an abnormal ballooning of the blood vessel wall in the brain that occurs in approximately 6% of the general population. When a cerebral aneurysm ruptures, the subsequent damage is lethal damage in nearly 50% of cases. Over the past decade, endovascular treatment has emerged as an effective treatment option for cerebral aneurysms that is far less invasive than conventional surgical options. Nonetheless, the rate of successful treatment is as low as 50% for certain types of aneurysms. Treatment success has been correlated with favorable post-treatment hemodynamics. However, current understanding of the effects of endovascular treatment parameters on post-treatment hemodynamics is limited. This limitation is due in part to current challenges in in vivo flow measurement techniques. Improved understanding of post-treatment hemodynamics can lead to more effective treatments. However, the effects of treatment on hemodynamics may be patient-specific and thus, accurate tools that can predict hemodynamics on a case by case basis are also required for improving outcomes.Accordingly, the main objectives of this work were 1) to develop computational tools for predicting post-treatment hemodynamics and 2) to build a foundation of understanding on the effects of controllable treatment parameters on cerebral aneurysm hemodynamics. Experimental flow measurement techniques, using particle image velocimetry, were first developed for acquiring flow data in cerebral aneurysm models treated with an endovascular device. The experimental data were then used to guide the development of novel computational tools, which consider the physical properties, design specifications, and deployment mechanics of endovascular devices to simulate post-treatment hemodynamics. The effects of different endovascular treatment parameters on cerebral aneurysm hemodynamics were then characterized under controlled conditions. Lastly, application of the computational tools for interventional planning was demonstrated through the evaluation of two patient cases. / Dissertation/Thesis / Ph.D. Bioengineering 2013

The selective laser sintering (SLS) process or the additive manufacturing (AM) enables the construction of a three-dimensional object through melting and solidification of metal powder. The primary advantage of AM over the conventional process is providing the manufacturing flexibility, especially for highly complicated products. The quality of AM products depends upon various processing parameters such as laser power, laser scanning velocity, laser scanning pattern, layer thickness, and hatch spacing. The improper selection of these parameters would lead to parts with defects, severe distortion, and even cracking. I herein perform the numerical and experimental analysis to investigate the interplay between processing parameters and the defect generation. The analysis aims to resolve issues at two different scales, micro-scale and product-scale. At the micro-scale, while the numerical model is developed to investigate the interaction of the laser and materials in the AM process, its advantages and disadvantages compared to an analytical approach (Rosenthal’s equation), which provides a quicker thermal solution, are thoroughly studied. Additionally, numerical results have been verified by series of experiments. Based on the analysis, it is found that the simultaneous consideration of multiple processing parameters could be achieved using the energy density. Moreover, together with existing criteria, a processing window is numerically developed as a guideline for AM users to avoid common defects at this scale including the lack of fusion, balling effect, and over-melting. Thermal results at a micro-scale are extended as an input to determine the residual stress initiation in AM products. The effect of energy density and substrate temperature on a residual stress magnitude is explored. Results show that the stress magnitude within a layer is a strong function of the substrate temperature, where a higher substrate temperature results in a lower stress. Moreover, the stress formation due to a layer’s addition is studied, in which the stress relaxation at locations away from a top surface is observed. Nevertheless, even though the micro-scale analysis can resolve some common defects in AM, it is not capable of predicting product-scale responses such as residual stress development and entire product’s distortion. As a result, the multiscale modeling platform is developed for the numerical investigation at the product level. Three thermal models at various scales are interactively used to yield an effective thermal development calculation at a product-scale. In addition, the influence of the multiple layers, energy densities and scanning patterns on the residual stress formation has been addressed, which leads to the prediction of the residual stress development during the fabrication. The distortion of products due to the residual stress can be described by the product-scale model. Furthermore, among many processing parameters, the energy input and the scanning length are found to be important factors, which could be controlled to achieve the residual stress reduction in AM products. An optimal choice of a scanning length and energy input can reduce an as-built residual stress magnitude by almost half of typically encountered values. Ultimately, the present work aims to illustrate the integration of the computational method as tools to provide manufacturing qualification for part production by the AM process.

In composite materials, transverse shear modulus is a critical moduli parameter for designing complex composite structures. For dependable mathematical modeling of mechanical behavior of composite materials, an accurate estimate of the moduli parameters is critically important as opposed to estimates of strength parameters where underestimation may lead to a non-optimal design but still would give one a safe one. Although there are mechanical and empirical models available to find transverse shear modulus, they are based on many assumptions. In this work, the model is based on a three-dimensional elastic finite element analysis with multiple cells. To find the shear modulus, appropriate boundary conditions are applied to a three-dimensional representative volume element (RVE). To improve the accuracy of the model, multiple cells of the RVE are used and the value of the transverse shear modulus is calculated by an extrapolation technique that represents a large number of cells. Comparing the available analytical and empirical models to the finite element model from this work shows that for polymeric matrix composites, the estimate of the transverse shear modulus by Halpin-Tsai model had high credibility for lower fiber volume fractions; the Mori-Tanaka model was most accurate for the mid-range fiber volume fractions; and the Elasticity Approach model was most accurate for high fiber volume fractions. Since real-life composites have voids, this study investigated the effect of void fraction on the transverse shear modulus through design of experiment (DOE) statistical analysis. Fiber volume fraction and fiber-to-matrix Young’s moduli ratio were the other influencing parameters used. The results indicate that the fiber volume fraction is the most dominating of the three variables, making up to 96% contribution to the transverse shear modulus. The void content and fiber-to-matrix Young’s moduli ratio have negligible effects. To find how voids themselves influence the shear modulus, the transverse shear modulus was normalized with the corresponding shear modulus with a perfect composite with no voids. As expected, the void content has the largest contribution to the normalized shear modulus of 80%. The fiber volume fraction contributed 12%, and the fiber-to-matrix Young’s moduli ratio contribution was again low. Based on the results of this work, the influences and sensitivities of void content have helped in the development of accurate models for transverse shear modulus, and let us confidently study the influence of fiber-to-matrix Young’s moduli ratio, fiber volume fraction and void content on its value.

The technology of haptics rendering has greatly enriched development in Multimedia applications, such as teleoperation, gaming, medical and etc., because it makes the virtual object touchable by the human operator(s) in real world. Human head stiffness rendering is significant in haptic interactive applications as it defines the degree of reality in physical interaction of a human avatar created in virtual environment. In a similar research, the haptic rendering approach has two main types: 1) Haptic Information Integration and 2) Deformation Simulation. However, the complexity in anatomic and geometric structure of a human head makes the rendering procedure challenging because of the issues of accuracy and efficiency. In this work, we propose a hybrid method to render the appropriate stiffness property onto a 3D head polygon mesh of an individual user by firstly studying human head's sophisticated deformation behaviour and then rendering such behaviour as the resultant stiffness property on the polygon mesh. The stiffness property is estimated from a semantically registered and shape-adapted skull template mesh as a reference and modeled from soft tissue's deformation behaviour in a nonlinear Finite Element Method (FEM) framework. To render the stiffness property, our method consists of different procedures, including 3D facial landmark detection, models semantic registration using Iterative Closest Point (ICP) technique, adaptive shape modification processed with a modified Weighted Free-Form Deformation (FFD) and FEM Simulation. After the stiffness property is rendered on a head polygon mesh, we perform a user study by inviting participants to experience the haptic feedback rendered from our results. According to the participants' feedback, the head polygon mesh's stiffness property is properly rendered as it satisfies their expectation.

abstract: Current exosuit technologies utilizing soft inflatable actuators for gait assistance have drawbacks of having slow dynamics and limited portability. The first part of this thesis focuses on addressing the aforementioned issues by using inflatable actuator composites (IAC) and a portable pneumatic source. Design, fabrication and finite element modeling of the IAC are presented. Volume optimization of the IAC is done by varying its internal volume using finite element methods. A portable air source for use in pneumatically actuated wearable devices is also presented. Evaluation of the system is carried out by analyzing its maximum pressure and flow output. Electro-pneumatic setup, design and fabrication of the developed air source are also shown. To provide assistance to the user using the exosuit in appropriate gait phases, a gait detection system is needed. In the second part of this thesis, a gait sensing system utilizing soft fabric based inflatable sensors embedded in a silicone based shoe insole is developed. Design, fabrication and mechanical characterization of the soft gait detection sensors are given. In addition, integration of the sensors, each capable of measuring loads of 700N in a silicone based shoe insole is also shown along with its possible application in detection of various gait phases. Finally, a possible integration of the actuators, air source and gait detection shoes in making of a portable soft exosuit for knee assistance is given. / Dissertation/Thesis / Masters Thesis Mechanical Engineering 2020

Reverse shoulder arthroplasty (RSA) is a common treatment for individuals with arthritis of the glenohumeral joint in the presence of a massive rotator cuff tear. Though this procedure has been effective in restoring function to these individuals, it has also been associated with high early to mid-term complications, such as scapular notching and instability. A finite element (FE) modeling approach has previously been used to study the range of motion an individual with RSA could adduct their arm the polyethylene liner impinged on the inferior scapular bone and the contact stress at the impingement site. This model was then validated in a physical experiment using cadaveric tissue. In this document, I introduce modifications to that FE model to further study instability and scapular notching risk. First, modern RSA implant geometries were introduced into the model, and the effect of polyethylene liner rotation and glenoid version on impingement-free range of motion and instability risk was assessed. Then, a physical material property characterization of rotator cuff tissues present after RSA was performed. Finally, those material properties and continuum elements representative of the rotator cuff tendons were introduced into the FE model. Throughout all of these studies, greater complexity and fidelity was added to improve the ability to model both contact at the impingement site and potential dislocation events through more accurate loadings and boundary conditions.

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