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<p>Research in the field of human injury biomechanics with respect to athletes has indicated that head acceleration events (HAEs) suffered during participation in a contact sport can cause long-term neurological changes that present asymptomatically. This concept has been referred to as “mild” traumatic brain injury (mTBI). This mirrors results found in soldiers, where it is also now thought that traumatic brain injury, coupled with psychological trauma can lead to posttraumatic stress disorder (PTSD). Current consensus amongst the neurotrauma research community is that all HAEs matter, whether caused by blast, blunt force, or directed energy weapons.</p> <p><br></p> <p>Previous research has focused on the long-term changes that have been demonstrated and quantified, however very little research has been done to quantify the effects of a single insult to the brain. Several studies have had participants perform head motions while in a magnetic resonance imaging (MRI) scanner. Digital twins may be used to simulate the effects of an insult, be it blast, blunt force, or directed energy to an object. Finite element models of the human head and brain have a long history of development from the earliest models in the 1970s to today. Currently, numerous software packages allow for the regularization and comparison of MRI datasets. Some software packages offer additionally the ability to create subject specific finite element meshes interactively from a single MRI image. Previous research in the HIRRT Lab reduced the time to generate simulation geometry to approximately 48 hours to generate a patient specific finite element mesh. This represented a substantial reduction in the processing time for a single scan, which to the knowledge of the authors required on the time scale of weeks to process a single geometry including the skull robustly or required costly software licenses, and still required user interactive processes. The architecture and deployment of the HIRRT Lab Cluster, a high-performance computing system that is a cost-optimized research tool to enable rapid processing of scans to simulation geometry using batch processes on a Slurm cluster. There are software optimizations, operating system optimizations, and Linux kernel-level optimization (and selections) utilized that enable the hardware selected to perform optimally. </p> <p><br></p> <p>To the knowledge of the author, no single pipeline enables the automated generation of robust, patient specific finite element meshes from raw datasets fresh from an MRI. This package addresses those limitations with a design heavily tilted towards Linux cluster implementations. The author has created a pipeline of code designed to run on a Linux-based compute cluster that is capable of processing 1700 scans from raw T1-weighted MRI scans to a finite element mesh with regions of interest (ROIs) identified as element sets, and white matter fiber orientation determined from diffusion tensor imaging (DTI) scans in under 7 days using the current hardware available in the HIRRT Lab Cluster with appropriate software licensing. This represents a speed up of over 1200x compared to the original program overall at just mesh processing, and a speed up of 22x for a single scan being processed, with additional features and detail not captured by the original code. </p> <p><br></p> <p>Accurate representative models for subpopulations via their immutable traits (e.g. size, biological sex, ethnicity/ancestry, or age) can further reduce the number of simulations that are required to accurately assist in the improvement of finite element models that may be used to improve the design of personal protective equipment, create new techniques, or aid in the design of new vehicles capable of reducing the exposure of individuals to potentially traumatic damage. The use of subpopulation groupings rather than the simulation of each unique individual, even models consisting of bounding cases, such as the largest or smallest representative members of a subpopulation can reduce the amount of data that needs to be processed to generate useful design feedback for engineers. </p> <p><br></p> <p>Subject-specific models allow for greater variation in strain due to geometric differences between individuals brains and should be used where possible to describe a given individual’s strain history more accurately, which can be used to assess the formation of damage as indicated by biomarkers. To understand the long-term effects of blast overpressures on brain structure, function, and chemistry, and subsequently develop appropriate mitigation strategies, computational models of individual soldiers must be developed. These models must integrate blast physics and neuroimaging of actual tissue damage to the brain. There is a need to develop constitutive equations capable of being used in multi-scale models to relate various insults directly to damage in the brain. These equations should be linked to damage as indicated through various MRI scan types and used to robustly assess individuals over the course of their unique impact histories. Through the development of a digital twin in this manner, unique predictive medicine may be used to proactively identify those athletes and warfighters who may be at higher risk for long term detrimental effects from further exposure to HAEs.</p>

The aim of this work is to evaluate the mechanical strength of a co-polymer of 2-hydroxyethylmethacrylate (HEMA) and methylmethacrylate (MMA), so that it can be applied as an interfacial layer between bone cement and steel implants to improve their performance and life. Finite element (FE) analysis techniques are used to assess the behavior of the interface layer under static and dynamic loading conditions. The material property of the co-polymer is a function of its composition and water saturation. The factors affecting the strength of the bone-implant interface are many. Implant interfacial fracture can lead to decreased stability. Fatigue life is a very important process in failure. The results obtained from static and dynamic analyses show that increasing the percentage of HEMA improves the strength of the interface by reducing the stiffness of the implant, absorbing more energy and by reducing the interfacial stress peaks and making the stress distribution more nearly uniform.

Gear transmission systems are considered one of the critical aspects of vibration analysis, and it contains various potential faults such as misalignment, cracks, and noise. Therefore, it requires vibration monitoring to ensure the system is operating properly. Case mounted accelerometers are frequently used to monitor frequencies in a system. However, it is not a simple task to identify and interpret the acceleration data since there are many gear mesh frequencies present. One of the approaches utilized by researchers to perform gear diagnostic is Finite Element Modeling. This study focuses on stiffness cycle and meshing stiffness of non-linear quasi-static finite element modeling. The comparisons of meshing stiffness will concentrate on the type of elements, the integration methods, the meshing quality, plane stress and plane strain analysis, sensitivity of model tolerance, and crack modeling. The results show that the FEA approach is extremely sensitive to tolerance, mesh density, and element choice. Also, the results indicate that a complete sensitivity and convergence studies should be carried out for a satisfactory stiffness match.

Studies are currently being performed to determine the effects of bisphosphonate treatments on the structure and density of bone tissue. One of the pathways for gaining a better understanding of the effects of this and other treatments involves creating a computer simulation. Theory suggests that bone tissue structure and density are directly related to the manner in which the tissue is loaded. Remodeling is the process in which bone tissue is resorbed in areas of low stress distributions, and generated in areas of high stress distributions. Previous studies have utilized numerical methods and finite element methods to predict bone structure as a result of stress distributions within the tissues. The Finite Element method was chosen for this study. This study was done on a canine (beagle) rib. The goal of this study was to develop an FEA model of the rib that would be used in conjunction with a bone remodeling algorithm, to model the behavior of the bone tissue. Appropriate boundary conditions, loads, and loading cycles were determined from literature, and applied. Respiration was assumed as the dominating activity; therefore the muscles involved in respiration were the primary source of the rib loading. The model also included an integrated UMAT sub-routine, which utilized data from the FEA model to iterate bone tissue densities and structures. The model closely predicted the porosities of the bone tissue, when compared to actual tissue samples, as well as what literature describes.

Geckos can freely climb on walls and ceilings against their body weight at speed of over 1ms-1. Switching between attachment and detachment seem simple and easy for geckos, without considering the surface to be dry or wet, smooth or rough, dirty or clean. In addition, gecko can shed dirt particles during use, keeping the adhesive pads clean. Mimicking this biological system can lead to a new class of dry adhesives for various applications. However, gecko’s unique dry self-cleaning mechanism remains unknown, which impedes the development of self-cleaning dry adhesives. In this dissertation we provide new evidence and self-cleaning mechanism to explain how gecko shed particles and keep its sticky feet clean. First we studied the dynamic enhancement observed between micro-sized particles and substrate under dry and wet conditions. The adhesion force of soft (polystyrene) and hard (SiO2 and Al2O3) micro-particles on soft (polystyrene) and hard (fused silica and sapphire) substrates was measured using an atomic force microscope (AFM) with retraction (z-piezo) speed ranging over 4 orders of magnitude. The adhesion is strongly enhanced by the dynamic effect. When the retraction speeds varies from 0.02 µm/s to 156 µm/s, the adhesion force increases by 10% ~ 50% in dry nitrogen while it increases by 15%~70% in humid air. A dynamic model was developed to explain this dynamic effect, which agrees well with the experimental results. Similar dynamic enhancement was also observed in aqueous solution. The influence of dynamic factors related to the adhesion enhancement, such as particle inertia, viscoelastic deformations and crack propagation, was discussed to understand the dynamic enhancement mechanisms. Although particles show dynamic enhancement, Gecko fabrillar hair shows a totally different trend. The pull off forces of a single gecko seta and spatula was tested by AFM under different pull-off velocities. The result shows that both the spatula and the seta have a rate independent adhesion response in normal retraction, which is quite different from micro-particles. Further research indicated the shape of the contact area was a key factor to the dynamic effect. In order to verify this hypothesis, artificial gecko spatula made of glass fibers was nanofabricated by a focus ion beam (FIB) and tested by AFM. These manmade spatulae also show a rate independent adhesion response. The dynamic adhesion of a single gecko seta and spatula were simulated with finite element analysis and the results also confirm the rate independent phenomena.. In conclusion, self-cleaning is induced by dynamic effect during gecko locomotion. The relative dynamic adhesion change between particles and seta makes it possible for gecko to shed the dirt particles while walking.Finally, the fatigue property of gecko seta was examined with the atomic force microscope under cyclic attachment/detachment process, mimicking gecko running. The adhesion force versus cycles has been tested and evaluated. Fatigue mechanism of gecko seta was also analyzed based on the experimental findings.

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found that most of these factors are directly or indirectly linked to subjects’ BMI (body mass index). Thus, from a statistical perspective, BMI could be an overall indicator of the probability of femur fracture from a sideways fall. Using a biomechanics approach coupled with statistical data we investigate this relationship with a large cohort of postmenopausal women aged 50-79 from WHI-OS (Women’s Health Initiative Observational Cohort). The cohort is divided into six sub-cohorts by BMI where each fall-related factor is examined and compared with each other. Significant differences are discovered among cohorts in terms of femur size, aBMD (areal bone mineral density), peak fall force based on kinematics, and maximum von Mises stresses induced in the proximal femur. Through a probabilistic margin of safety approach which has been recently applied to orthopedic application, we found the margin of safety predicted probability to be decreasing faster with increasing BMI and better v fitted with medical record of the identical cohort compared to that found using a deterministic risk factor approach. To promote the application in other situations, tumor damaged femur bones are examined and tested for possible stress concentration effect in terms of probability of failure. The influence of tumor lesion turned out to be size and location sensitive. The superior side of the femoral neck has the highest stress concentration effect from tumor lesion where a 4mm diameter lesion could result in a 1.7 times greater maximum von Mises stress and 2.95 times greater probability of failure.

Tool wear is a significant problem for manufacturing companies and represents a major challenge in their operations, but it is also a way they can gain a competitive advantage. To do this it is important to set up a standard procedure to develop high performing tooling. This thesis outlines how the Finite Element (FE) method can be used to understand and develop tool geometry. FE based simulation, as a numerical method, is a reliable method to assess the performance of a cutting tool before conducting machining tests based on the force and temperature profile predicted by the FE model. Defining a mathematical model which can be used as a built-in algorithm for tool wear prediction is very challenging and time consuming. Instead there is a possibility of using other factors such as stress distribution and temperature profile and correlate them to tool wear. In this research, the performance of different tool edge radius in cutting has been studied through experiments and in parallel Updated Lagrangian Models have been developed through ABAQUS/EXPLICIT for various cutting conditions, and experimental data was used to validate the data that has been generated from the finite element models. These models are very convenient to develop and capable of being applied for other types of material and cutting conditions. Thus, they represent an efficient way to reduce the amount of experiments needed to improve a tooling, the machining process, and thereby provide an effective way to increase the machining productivity of manufacturing companies. / Thesis / Master of Applied Science (MASc)

Noise levels in areas adjacent to high performance jets have increased monotonically in the past few years. When personnel are exposed to such high noise fields, the need for better hearing protection is inevitable. Adequate hearing protection may be achieved through the use of circumaural ear defenders, earplugs or both. This thesis focuses on identifying the dominant physical phenomena, responsible for the low frequency (0 – 300 Hz) acoustic response inside the earmuffs. A large volume earcup is used with the undercut seal for the study. The significance of this research is the use of finite element methods in the area of hearing protection design. The objectives of this research are to identify the dominant physical phenomena responsible for the loss of hearing protection in the lower frequency range, and develop FE models to analyze the effects of structural and acoustic modes on the acoustic pressure response inside the earcup. It is found that there are two phenomena, which are primarily responsible for the lower frequency acoustic response inside the earmuffs. These modes are recognized in this thesis as the piston mode and the Helmholtz mode. The piston mode occurs due to the dynamics of the earcup and seal at 150 Hz, which results in loss of hearing protection. The Helmholtz mode occurs due to the presence of leaks. The resonant frequency of the Helmholtz mode and the pressure response depends on the leak size. / Master of Science