Learning Abaqus for Master\u27s thesis project

I am writing to notify the results of the independent study that I have been performing over the semester of Fall 2016. The objective of this study was to lay a foundation of a Master’s thesis project at which the end goal would be to improve the repair rate of the human rotator cuff tear repairs. The experimental plots of the most recent models will be further attached

Image Analysis to Quantitatively Estimate Catheter Bending Stiffness

The performance of endovascular surgery is highly dependent on catheter stiffness, especially when navigating past tortuous anatomy. Stiff catheters lack the maneuverability of compliant catheters, but they provide necessary support for medical device delivery and intervention. Conversely, compliant catheters can easily navigate through the vasculature, but they are not stable enough for device delivery and intervention. Catheters vary in length, diameter, shape, and stiffness to accommodate various surgical situations. Although stiffness is of critical importance when considering catheter properties, biomedical companies offer no quantitative measure of a catheter’s bending rigidity. A method for determining bending rigidity would therefore allow surgeons to compare products and make informed decisions on which catheters to use in surgery. Linear beam theory, also known as small deformation beam theory, is often used to determine beam stiffness. However, since catheters are made from soft, composite materials, they undergo large deformations when subject to relatively small loads, and the linear beam theory loses accuracy. A nonlinear formulation of Euler-Bernoulli beam theory was used to derive a nonlinear flexural rigidity equation. The nonlinear flexural rigidity equation was validated using finite element analysis. The analysis showed that nonlinear beam theory could accurately predict beam stiffness, even at very large strains, compared to linear beam theory which loses accuracy as strain increases. A simple image analysis experiment was devised to obtain the necessary parameters to calculate catheter stiffness. Expired and used catheters, donated by Drs. Joshua Osbun and Mohammed Zayed, were used for experimentation. Each catheter sample was subject to two experimental treatments: one smaller applied external moment and one larger applied external moment. For each treatment, flexural rigidity was calculated from the linear and nonlinear theories. The consistency of both theories was measured as the percent difference between experimental treatments. Statistical testing was performed using a paired data T-test for difference between means. For catheter samples with high variation in angular deflection between treatments (\u3e 30°), the nonlinear beam theory was much more consistent than the linear beam theory for quantifying catheter stiffness (p \u3c 0.01). Across all experimental data, there was not significant evidence to indicate that the nonlinear theory was more consistent at measuring flexural rigidity than the linear theory (p = 0.073 \u3e 0.05). Finite element analysis shows that nonlinear beam theory predicts beam stiffness more accurately than linear beam theory across varying angular deflections. Since the data does not suggest statistical significance, the experimental procedure must be further refined before using nonlinear beam theory to quantify catheter stiffness. Possible sources of error and suggestions for future experimentation are discussed at the end of this paper

Analysis, Design, and Simulation of Clamp System

Modeling and modifications made to clamping system

Skull Shape Affects Susceptibility to Traumatic Brain Injury

Rapid deformation of brain matter caused by skull acceleration is one of the most significant causes of concussion and severe traumatic brain injury (TBI). Despite substantial research being conducted in this area of study, very little is understood regarding the mechanics of the brain when exposed to rapid acceleration. As a result, the biomechanics of TBI remain ambiguous. In the present study, we apply a new strain estimation algorithm that enables the tracking of strains on the periphery of an image onto data obtained from tagged gel phantom and human MR-images. We use this new method to quantify strain concentrations at the brain-skull interface, and observe the interactions between the brain and the connective tissue that anchors it inside the skull. Our results allow us to noninvasively observe and quantify the biomechanical response of the brain to rapid skull movement. We find that the sub-arachnoid space creates regions of high strain magnitudes due to its anatomical makeup, and that the falx cerebri creates regions of high strain due to its inhibition of brain motion. Additionally, we see that skull shape significantly affects the transmission of strains at the brain-skull interface, and that certain skull shapes create localized concentrations of high strains. Our results imply that skull shape plays an important role in affecting sensitivity to acceleration among individuals, and may increase the likelihood of TBI in the event of an accident

An advanced course on finite element analysis, with application to the stress distribution in teeth

The overall goal of my work is to gain insight into how tooth shape relates to its function. As a step towards this, I undertook an independent study project to further improve my skills on finite element analysis (FEA) this semester, and to combine this into my Master’s thesis project work. Continuing from the previous independent study course, the tooth model was improved to eliminate singularities and a contact surface model was included to simulate contact stress problems. I believe that these series of problems will be useful to my research. This report contains an overview of some literature that I studied, and a summary of several finite element output plots that I found to be particularly instructive

Kinematics-based tracking of cells and fluorescent beads using feature vectors

Tracking of cells or fluorescent beads from images of deforming or developing biological systems is a central challenge in biomechanics. In the former case, the objective is often to find the same cell in a tissue or on a Petri dish that has been imaged before and after time in an incubator. In the latter case, the objective is often to estimate mechanical tractions based upon displacement of fluorescent beads embedded in a defined extracellular matrix. A great number of techniques exist for this purpose, and all face challenges in matching cells and beads from one image to the next and in identifying mismatches. Here, we present a simple, fast, and effective technique for matching cells and beads using “feature vectors” that connect a cell or bead to a set of its nearest neighbors. A generalized feature vector deformation gradient tensor is defined that enables the use of standard kinematics to estimate the maximum likelihood matches between cells or beads in image pairs. We describe the strengths and limitations of the approach and present examples of its application

Programmable and reversible integrin-mediated cell adhesion reveals hysteresis in actin kinetics that alters subsequent mechanotransduction

Dynamically evolving adhesions between cells and extracellular matrix (ECM) transmit time-varying signals that control cytoskeletal dynamics and cell fate. Dynamic cell adhesion and ECM stiffness regulate cellular mechanosensing cooperatively, but it has not previously been possible to characterize their individual effects because of challenges with controlling these factors independently. Therefore, a DNA-driven molecular system is developed wherein the integrin-binding ligand RGD can be reversibly presented and removed to achieve cyclic cell attachment/detachment on substrates of defined stiffness. Using this culture system, it is discovered that cyclic adhesion accelerates F-actin kinetics and nuclear mechanosensing in human mesenchymal stem cells (hMSCs), with the result that hysteresis can completely change how hMSCs transduce ECM stiffness. Results are dramatically different from well-known results for mechanotransduction on static substrates, but are consistent with a mathematical model of F-actin fragments retaining structure following loss of integrin ligation and participating in subsequent repolymerization. These findings suggest that cyclic integrin-mediated adhesion alters the mechanosensing of ECM stiffness by hMSCs through transient, hysteretic memory that is stored in F-actin

Multiphase elastic homogenization, and the mechanics of tendon-to-bone attachment

Estimates of the effective stiffness of a composite containing multiple types of inclusions are needed for the design and study of functionally graded systems in engineering and biologic materials. One important stiffening mechanism in biologic systems is the accumulation of a high volume fraction of mineral inclusions within and upon collagen fibers. Modeling of this mechanism is critical for understanding how stresses are transmitted from tendon to bone and for designing improvements to surgical procedures for reattaching tendon to bone. The latter is a critical need because failure rates following surgical reattachment are as high as 94% in some populations. Modeling of such material remains difficult Because of a number of physiological and mathematical challenges. A range of methods have been described in the literature for estimating the effective elastic properties of composites containing low volume fractions of different inclusion types. Here, we provide an estimate of the effective elastic responses of composites containing high volume fractions of different, ellipsoidal and anisotropic inclusion types. The homogenization estimate compared well against numerical simulation and available experimental data. The method out-performed all methods of which we are aware for modeling of numerical simulations of the mechanical response of the graded attachment of tendon to bone. The method is a good candidate for the characterization of composites with multiple types of anisotropic inclusions, even if these inclusions have moderate volume fractions and a variety of aspect ratios

Tailoring of arteriovenous graft‑to‑vein anastomosis angle to attenuate pathological flow fields

Abstract Arteriovenous grafts are routinely placed to facilitate hemodialysis in patients with end stage renal disease. These grafts are conduits between higher pressure arteries and lower pressure veins. The connection on the vein end of the graft, known as the graft-to-vein anastomosis, fails frequently and chronically due to high rates of stenosis and thrombosis. These failures are widely believed to be associated with pathologically high and low flow shear strain rates at the graft-to-vein anastomosis. We hypothesized that consistent with pipe flow dynamics and prior work exploring vein-to-artery anastomosis angles in arteriovenous fistulas, altering the graft-to-vein anastomosis angle can reduce the incidence of pathological shear rate fields. We tested this via computational fluid dynamic simulations of idealized arteriovenous grafts, using the Bird-Carreau constitutive law for blood. We observed that low graft-to-vein anastomosis angles ( $$40^{\circ }$$ > 40 ∘ ) led to increased incidence of pathologically high shear rates. Optimizations predicted that an intermediate  ( $$\sim 30^\circ$$ ∼ 30 ∘ ) graft-to-anastomosis angle was optimal. Our study demonstrates that graft-to-vein anastomosis angles can significantly impact pathological flow fields, and can be optimized to substantially improve arteriovenous graft patency rates