Quantifying Relationship between Infill Percentage and Tensile Strength of Fused Deposition Modeled Thermoplastic Polyurethane

With the advent of additive manufacturing (AM), understanding the effects of changing 3D printing settings is critical for engineering pursuits. One of the most widespread methods, known as Fused Deposition Modeling (FDM), has been well-researched by consumer hobbyists and members of the general public. However, an empirical analysis is needed for scientific research and projects, and few have been performed to prove the relationship between a printing setting and material strength quantitatively. This lack of literature is partly due to the breadth of printers and factors that can affect an FDM model’s printability. This project tensile tested one Thermoplastic Polyurethane (TPU) brand at various infills. It analyzed the effects of infill percentage on the tensile strength and moduli of elasticity. Additionally, it interprets the data and details further testing to validate a hypothesis formed from the study results. The data used will also be showcased with another group who will use it to help validate their study. This study aims to clearly show that the process of printing a part is as imperative to the success of a project as creating a design and choosing materials

Biomechanics of Developmental Dysplasia of the Hip - An engineering study of closed reduction utilizing the Pavlik harness for a range of subtle to severe dislocations in infants.

Developmental Dysplasia of the Hip (DDH) is an abnormal condition where hip joint dislocation, misalignment, or instability is present in infants. Rates of incidence of DDH in newborn infants have been reported to vary between 1 and 20 per 1000 births, making it the most common congenital malformation of the musculoskeletal system. DDH early detection and treatment is critical to avoid the use of surgical treatment in infants and to prevent future complications such as osteoarthritis in adult life. To this day several non-surgical treatments involving the use of harnesses and braces have been proposed to treat DDH in infants, with the Pavlik harness being the current non-surgical standard used to treat DDH at early stages. Although the Pavlik harness has been proven to be successful treating subtle dislocations, severe dislocations do not always reduce. Until now the use of the harness remains an empirical method, and its effectiveness often depends on physician expertise or trial-error procedures; thus a clear guideline has not been established to determine the best optimal harness configuration to treat both subtle and severe dislocations. The goal of this dissertation is to understand the connection between reductions for subtle and severe dislocations and passive muscle forces and moments generated while the harness is used during treatment. While the understanding of DDH biomechanics will provide a valuable clinically applicable approach to optimize and increase harness success rate, it is not without its difficulties. This research has created and developed a three-dimensional based on patient-specific geometry of an infant lower limb. The kinematics and dynamics of the lower limb were defined by modeling the hip, femur, tibia, fibula, ankle, foot, and toe bones. The lines of action of five (5) adductor muscles, namely, the Adductor Brevis, Adductor Longus, Adductor Magnus, Pectineus, and Gracilis were identified as mediators of reduction and its mechanical behavior was characterized using a passive response. Four grades (1-4) of dislocation as specified by the International Hip Dysplasia Institute (IHDI) were considered, and the computer model was computationally manipulated to represent physiological dislocations. To account for proper harness modeling, the femur was restrained to move in an envelope consistent with its constraints. The model of the infant lower limb has been used to analyze subtle and severe dislocations. Results are consistent with previous studies based on a simplified anatomically-consistent synthetic model and clinical reports of very low success of the Pavlik harness for severe dislocations. Furthermore the findings on this work suggest that for severe dislocations, the use of the harness could be optimized to achieve hyperflexion of the lower limb leading to successful reduction for cases where the harness fails. This approach provides three main advantages and innovations: 1) the used of patient-specific geometry to elucidate the biomechanics of DDH; 2) the ability to computationally dislocate the model to represent dislocation severity; and 3) the quantification of external forces needed to accomplish reduction for severe dislocations. This study aims to offer a practical solution to effective treatment that draws from engineering expertise and modeling capabilities and also draws upon medical input. The findings of this work will lay the foundation for future optimization of non-surgical methods critical for the treatment of DDH

Designing Of Energy Efficient Indoor Environments Using A Localized Radial Basis Function Meshless Method

Around the world, the energy over consumption issue has been one of the key socio-economic and political challenges, which has drastically worsened over the last few years. Over the years engineers and environmentalists have proposed several approaches to improve energy efficiency. One is to reduce energy demand by improving consumption habits and a second approach is to introduce the use of a greener concept by using biomaterials in a diverse and more efficient manner in engineering construction to create energy efficient environments. This work will investigate the effects of using green stabilized earth materials to provide and enhance thermal regulation for indoor environments. This effects can be compared to what skin does to regulate body temperature in humans, animals, and plants. On this effort the thermal behavior of several biomaterials will be analyzed using a computational tool in order to test the mechanical properties of biomaterials and also several geometry configurations to minimize the energy needed for heating and cooling an environment. In this research a localized radial basis function (LRBF) meshless method, developed by the Computational Mechanics Lab (CML) at the University of Central Florida, has been implemented to test several wall geometrical configuration using known biomaterials such as clay. The advantage of using the LRBF meshless method in this particular research is based in the accuracy of the numerical method and also because it decreases computation time regardless of model complexity geometry without the need of mesh generation. This research includes a complete description of the LRBF meshless method, as well as a quantification of cooling methods that have been used by past civilizations and recent construction standards but have not been validated on scientific basis. Results are presented which will demonstrate the effectiveness of using integrated sheets of biomaterials in engineering construction to increase energy efficiency in indoor environments

Validation of a Biomechanical Injury and Disease Assessment Platform Applying an Inertial-Based Biosensor and Axis Vector Computation

Inertial kinetics and kinematics have substantial influences on human biomechanical function. A new algorithm for Inertial Measurement Unit (IMU)-based motion tracking is presented in this work. The primary aims of this paper are to combine recent developments in improved biosensor technology with mainstream motion-tracking hardware to measure the overall performance of human movement based on joint axis-angle representations of limb rotation. This work describes an alternative approach to representing three-dimensional rotations using a normalized vector around which an identified joint angle defines the overall rotation, rather than a traditional Euler angle approach. Furthermore, IMUs allow for the direct measurement of joint angular velocities, offering the opportunity to increase the accuracy of instantaneous axis of rotation estimations. Although the axis-angle representation requires vector quotient algebra (quaternions) to define rotation, this approach may be preferred for many graphics, vision, and virtual reality software applications. The analytical method was validated with laboratory data gathered from an infant dummy leg’s flexion and extension knee movements and applied to a living subject’s upper limb movement. The results showed that the novel approach could reasonably handle a simple case and provide a detailed analysis of axis-angle migration. The described algorithm could play a notable role in the biomechanical analysis of human joints and offers a harbinger of IMU-based biosensors that may detect pathological patterns of joint disease and injury

Challenges in Kinetic-Kinematic Driven Musculoskeletal Subject-Specific Infant Modeling

Musculoskeletal computational models provide a non-invasive approach to investigate human movement biomechanics. These models could be particularly useful for pediatric applications where in vivo and in vitro biomechanical parameters are difficult or impossible to examine using physical experiments alone. The objective was to develop a novel musculoskeletal subject-specific infant model to investigate hip joint biomechanics during cyclic leg movements. Experimental motion-capture marker data of a supine-lying 2-month-old infant were placed on a generic GAIT 2392 OpenSim model. After scaling the model using body segment anthropometric measurements and joint center locations, inverse kinematics and dynamics were used to estimate hip ranges of motion and moments. For the left hip, a maximum moment of 0.975 Nm and a minimum joint moment of 0.031 Nm were estimated at 34.6° and 65.5° of flexion, respectively. For the right hip, a maximum moment of 0.906 Nm and a minimum joint moment of 0.265 Nm were estimated at 23.4° and 66.5° of flexion, respectively. Results showed agreement with reported values from the literature. Further model refinements and validations are needed to develop and establish a normative infant dataset, which will be particularly important when investigating the movement of infants with pathologies such as developmental dysplasia of the hip. This research represents the first step in the longitudinal development of a model that will critically contribute to our understanding of infant growth and development during the first year of life

Tensile Testing of 3D Printed TPU Samples for Pediatric Biomaterial Applications

Additive Manufacturing (AM) has, in recent years, become one of the most widespread and preferred prototyping methods. The most popular additive manufacturing method is Fused Deposition Modeling. FDM’s popularity is primarily attributed to its 3 major strengths of rapid prototyping, variability in material choice, and subject specific nature. The medical industry is one of the larger industries that has benefited from 3D printing especially in the terms of medical trainers. Unfortunately, most medical trainers that are developed (either being 3d printed or through traditional manufacturing processes) are poor substitutes for the human body. This can be attributed to either a poor design or poor material choice. FDM printing is the obvious solution to these issues, but one of the largest problems in 3D printing for engineers is that the properties of most filaments after extrusion are not well-known. Additionally, 3D prints are rarely 100% solid in FDM which makes assuming the material properties of the base materials inaccurate. This project seeks to test 3D printed samples at numerous different infills of a common 3D printing material known as Thermoplastic Polyurethane of TPU using ASTM D638. The test samples will be printed across numerous printers with the same settings to determine whether different printers influence the material properties after a print. Once tensile testing has been completed the curves will be imported into an FEA software to be tested on numerous bone geometries to determine if TPU is a suitable material to use to mimic pediatric bones

A Patient-Specific Model of the Biomechanics of Hip Reduction for Neonatal Developmental Dysplasia of the Hip: Investigation of Strategies for Low to Severe Grades of Developmental Dysplasia of the Hip

A physics-based computational model of neonatal Developmental Dysplasia of the Hip (DDH) following treatment with the Pavlik Harness (PV) was developed to obtain muscle force contribution in order to elucidate biomechanical factors influencing the reduction of dislocated hips. Clinical observation suggests that reduction occurs in deep sleep involving passive muscle action. Consequently, a set of five (5) adductor muscles were identified as mediators of reduction using the PV. A Fung/Hill-type model was used to characterize muscle response. Four grades (1–4) of dislocation were considered, with one (1) being a low subluxation and four (4) a severe dislocation. A three-dimensional model of the pelvis– femur lower limb of a representative 10 week-old female was generated based on CT-scans with the aid of anthropomorphic scaling of anatomical landmarks. The model was calibrated to achieve equilibrium at 901 flexion and 801 abduction. The hip was computationally dislocated according to the grade under investigation, the femur was restrained to move in an envelope consistent with PV restraints, and the dynamic response under passive muscle action and the effect of gravity was resolved. Model results with an anteversion angle of 501 show successful reduction Grades 1–3, while Grade 4 failed to reduce with the PV. These results are consistent with a previous study based on a simplified anatomically-consistent synthetic model and clinical reports of very low success of the PV for Grade 4. However our model indicated that it is possible to achieve reduction of Grade 4 dislocation by hyperflexion and the resultant external rotation

Using Machine Learning to Diagnose Misaligned CT Scans

The usage of machine learning has grown exponentially in recent years; However, its applicable uses for medical diagnosis are still in an early stage. Conditions such as Developmental Dysplasia of the Hip (DDH), Cerebral Palsy (CP), and Femoracetabular Impingement (FAI) rely heavily on imaging techniques such as Ultrasound and Computed Tomography (CT) scans. Radiologists use multiple manually computed metrics using these images to diagnose conditions. This is time-intensive and requires an aligned image to get accurate diagnoses. The proposed application uses a deep learning detection algorithm to assist in the metric computation process. The algorithm is implemented using MATLAB R2023A and is trained on CT data gathered from 60 healthy participants. The algorithm performed well on images aligned according to the standard anteroposterior alignment used for radiological measurement. However, the variance of the metrics computation significantly increases when faced with severe misalignment in the craniocaudal or mediolateral axes. Additional algorithm improvements must be made to overcome this increased variance

A Patient-Specific Model Of The Biomechanics Of Hip Reduction For Neonatal Developmental Dysplasia Of The Hip: Investigation Of Strategies For Low To Severe Grades Of Developmental Dysplasia Of The Hip

A physics-based computational model of neonatal Developmental Dysplasia of the Hip (DDH) following treatment with the Pavlik Harness (PV) was developed to obtain muscle force contribution in order to elucidate biomechanical factors influencing the reduction of dislocated hips. Clinical observation suggests that reduction occurs in deep sleep involving passive muscle action. Consequently, a set of five (5) adductor muscles were identified as mediators of reduction using the PV. A Fung/Hill-type model was used to characterize muscle response. Four grades (1-4) of dislocation were considered, with one (1) being a low subluxation and four (4) a severe dislocation. A three-dimensional model of the pelvis-femur lower limb of a representative 10 week-old female was generated based on CT-scans with the aid of anthropomorphic scaling of anatomical landmarks. The model was calibrated to achieve equilibrium at 90° flexion and 80° abduction. The hip was computationally dislocated according to the grade under investigation, the femur was restrained to move in an envelope consistent with PV restraints, and the dynamic response under passive muscle action and the effect of gravity was resolved. Model results with an anteversion angle of 50° show successful reduction Grades 1-3, while Grade 4 failed to reduce with the PV. These results are consistent with a previous study based on a simplified anatomically-consistent synthetic model and clinical reports of very low success of the PV for Grade 4. However our model indicated that it is possible to achieve reduction of Grade 4 dislocation by hyperflexion and the resultant external rotation

Rbf-Trained Pod-Accelerated Cfd Analysis Of Wind Loads On Pv Systems

Purpose - Wind loading calculations are currently performed according to the ASCE 7 standard. Values in this standard were estimated from simplified models that do not necessarily take into account relevant flow characteristics. Thus, the standard does not have provisions to handle the majority of rooftop photovoltaic (PV) systems. Accurate solutions for this problem can be produced using a full-fledged three-dimensional computational fluid dynamics (CFD) analysis. Unfortunately, CFD requires enormous computation times, and its use would be unsuitable for this application which requires real-time solutions. To this end, a real-time response framework based on the proper orthogonal decomposition (POD) method is proposed. Design/methodology/approach - A real-time response framework based on the POD method was used. This framework used beforehand and off-line CFD solutions from an extensive data set developed using a predefined design space. Solutions were organized to form the basis snapshots of a POD matrix. The interpolation network using a radial-basis function (RBF) was used to predict the solution from the POD method given a set of values of the design variables. The results presented assume varying design variables for wind speed and direction on typical PV roof installations. Findings - The trained POD-RBF interpolation network was tested and validated by performing the fast-algebraic interpolation to obtain the pressure distribution on the PV system surface and they were compared to actual grid-converged fully turbulent 3D CFD solutions at the specified values of the design variables. The POD network was validated and proved that large-scale CFD problems can be parametrized and simplified by using this framework. Originality/value - The solar power industry, engineering design firms and the society as a whole could realize significant savings with the availability of a real-time in situ wind-load calculator that can prove essential for plug-and-play installation of PV systems. Additionally, this technology allows for automated parametric design optimization to arrive at the best fit for a set of given operating conditions. All these tasks are currently prohibited because of the massive computational resources and time required to address large-scale CFD analysis problems, all made possible by a simple but robust technology that can yield massive savings for the solar industry