Unlike traditional stochastic scaffold fabrication techniques, additive manufacturing (AM) can be used to create tissue-specific three-dimensional scaffolds with controlled porosity and pore geometry (meso-structure). However, due to the relatively few biocompatible materials available for processing in AM machines, direct fabrication of tissue scaffolds is limited. To alleviate material limitations and improve feature resolution, a new indirect scaffold fabrication method is developed. A four step fabrication process is explored: Fused Deposition Modeling (FDM) is used to fabricate scaffold patterns of varied pore size and geometry. Next, scaffold patterns are surface treated, and then mineralized via simulated body fluid (SBF); forming a bone-like ceramic throughout the scaffold pattern. Finally, mineralized patterns are heat treated to pyrolyze the pattern and sinter the minerals. Two scaffold meso-structures are tested: "tube" and "backfill." Two pattern materials are tested [acrylonitrile butadiene styrene (ABS) and investment cast wax (ICW)] to determine which material is the most appropriate for mineralization and sintering. Mineralization is improved through plasma surface treatment and dynamic flow conditions. Appropriate burnout and sintering temperatures to remove pattern material are determined experimentally. While the "tube scaffolds" were found to fail structurally, "backfill scaffolds" were successfully created using the new fabrication process. The "backfill scaffold" meso-structure had wall thicknesses of 470 – 530 µm and internal channel diameters of 280 – 340 µm, which is in the range of appropriate pore size for bone tissue engineering. "Backfill scaffolds" alleviated material limitations, and had improved feature resolution compared to current indirect scaffold fabrication processes. / Master of Science

Master of Science / As parts in any device age, something inevitably breaks. When dealing with a broken metallic part, one can either replace it or repair it. Repairing is generally preferred so long as it is not too costly. Unfortunately, repairing a component is often more expensive due to the material being difficult to work with or the geometry being too intricate to fix. Additive manufacturing, commonly known as 3D printing, allows precise placement of material to build a part and has allowed the repair of complex parts. However, some materials are severely weakened using traditional additive manufacturing technologies, which melt small amounts of material and force it to cool in place quickly. To combat this, methods that do not require the material to melt could be used. Currently, these methods place a large amount of material at once, causing significant waste if the excess needs to be removed. Therefore, this work aims to create a small-scale device using a traditional milling machine. It was shown to be capable of placing small amounts of material while offering the advantage of not melting the metal. In the future, it could provide an avenue to repair previously unreachable.

Impedance-based Non-Destructive Evaluation for Additive Manufacturing (INDEAM) is rooted in the field of Structural Health Monitoring (SHM). INDEAM generalizes the structure-to-itself comparisons characteristic of the SHM process through introduction of inter-part comparisons: instead of comparing a structure to itself over time, potentially-damaged structures are compared to known-healthy reference structures. The purpose of INDEAM is to provide an alternative to conventional nondestructive evaluation (NDE) techniques for additively manufactured (AM) parts. In essence, the geometrical complexity characteristic of AM processes combined with a phase-change of the feedstock during fabrication complicate the application of conventional NDE techniques by limiting direct access for measurement probes to surfaces and permitting the introduction of internal defects that are not present in the feedstock, respectively. NDE approaches that are capable of surmounting these challenges are typically highly expensive. In the first portion of this work, the procedure for impedance-based NDE is examined in the context of INDEAM. In consideration of the additional variability inherent in inter-part comparisons - as opposed to part-to-itself comparisons - the metrics used to quantify damage or change to a structure are evaluated. Novel methods of assessing damage through impedance-based evaluation are proposed and compared to existing techniques. In the second portion of this work, the INDEAM process is applied to a wide variety of test objects. This portion considers how the sensitivity of the INDEAM process is affected by defect type, defect size, defect location, part material, and excitation frequency. Additionally, a procedure for studying the variance introduced during the process of instrumenting a structure is presented and demonstrated. / Doctor of Philosophy / Impedance-based Non-Destructive Evaluation for Additive Manufacturing (INDEAM) is a quality control approach for detecting defects in structures. As indicated by the name, impedance-based evaluation is discussed in this work in the context of qualifying additively manufactured (3D printed) structures. INDEAM fills a niche in the wider world of nondestructive evaluation techniques by providing a less expensive means to qualify structures with complex geometry. Complex geometry complicates inspection by preventing direct, physical access to all the surfaces of a part. Inspection approaches for parts with complex geometry suffuse a structure with energy and measure how the energy propagates through the structure. A prominent technique in this space is CT scanning, which measures how a structure attentuates x-rays passing through it. INDEAM uses piezoelectric materials to both vibrate a structure and measure its response, not unlike listening for the dull tone of a cracked bell. By applying voltage across a piezoelectric patch glued to a structure, the piezoelectric deforms itself and the bonded structure. By monitoring the electrical current needed to produce that voltage, the ratio of applied voltage to current draw---impedance---can be calculated, which can be thought of as a measure of how a system stores and dissipates energy. When the applied voltage oscillates near a resonant frequency of a structure (the pitch of a rung bell, for example) the structure vibrates much more intensely, and that additional movement dissipates more energy due to viscosity, friction, and transmitting sound into the air. This phenomenon is reflected in the measured impedance, so by calculating the impedance value over a large range of frequencies, it is possible to identify many resonances of the structure. So, the impedance value is tied to the vibrational properties of the structure, and the vibration of the structure is tied to its geometry and material properties. One application of this relationship is called impedance-based structural health monitoring: taking measurements of a structure when it is first built as a reference, then measuring it again later to watch for changes that indicate emerging damage. In this work, the reference measurement is established by measuring a group of control structures that are known to be free of defects. Then, every time a new part is fabricated, its impedance measurements will be compared to the reference. If it matches closely enough, it is assumed good. In both cases, impedance values don't indicate what the change is, just that there was a change. A large portion of this work is devoted to determining the types and sizes of defects that can be reliably detected through INDEAM, what effect the part material plays, and how and where the piezoelectric should be mounted to the part. The remainder of this work discusses new methods for conducting impedance-based evaluation. In particular, overcoming the extra uncertainty introduced by moving from part-to-itself structural health monitoring comparisons to the part-to-part quality control comparisons discussed in this work. A new method for mathematically comparing impedance values is introduced which involves extracting the resonant properties of the structure rather than using statistical tools on the raw impedance values. Additionally, a new method for assessing the influence of piezoelectric mounting conditions on the measured impedance values is demonstrated.

In recent years, there has been a growing concern over the adverse effects of traditional fossil fuels on the environment and health. Therefore, there is an increased interest in hydrogen as a fossil-free fuel source, making the need for hydrogen solutions apparent. This supports the purpose and research questions of this study, which aim to determine the suitable materials for handling hydrogen and the necessary design for structural integrity to withstand pressure. This will be achieved through additive manufacturing using polymers. The study also considers the potential of additive manufacturing for large-scale production. After conducting literature studies, polymers are of special interest due to their different structural build compared to metals. Metals do not handle hydrogen well because of the phenomenon known as hydrogen embrittlement. The preferred material properties in polymers are a crystalline structure, high density, and strong mechanical properties. The design and production are conducted using SolidWorks, with simulations of pressure and topology optimization, making it possible to create a part ready for 3-D printing after slicing. The results provide insights into the effects of parameter adjustments on the structure of the parts and the feasibility of large-scale production through additive manufacturing. By analysing the slicer program, conclusions can be made that additive manufacturing is a viable option for large-scale production, given the availability of multiple printers. However, the conclusion regarding the optimal design for handling pressurized hydrogen could not be made due to a lack of time for testing.

<p dir="ltr">Repeated loading and unloading cycles lead to the formation of strain in the material which causes initiation of the crack formation this phenomenon is called fatigue. Fatigue properties are critical for structures subject to cyclic load; hence fatigue analysis is used to predict the life of the material. Fatigue analysis plays an important role in optimizing the design of the 3D printed material and predicting the fatigue life of the 3D printed component.</p><p><br></p><p dir="ltr">The main objective of this thesis is to predict the fatigue behavior of different microstructures of Ti-64 titanium alloy by using the PRISMS-Fatigue open-source framework. To achieve this goal Ti-64 microstructure models were created using programming scripts, then the structures were exported to a finite element visualization software package, with all the required properties embedded in the pipeline. The PRISMS-Fatigue framework is used to conduct a fatigue analysis on 3D printed materials, using the Fatigue Indicator Parameters (FIP), which measure the driving force of fatigue crack formation in the microstructurally small crack growth.</p><p><br></p><p dir="ltr">Three different microstructures, i.e., cubic equiaxed, random equiaxed, and rolled equiaxed microstructures, are analyzed. The FIP results show that the cubic equiaxed grains have the best fatigue resistance due to their isotropic structural characteristics. Additionally, the grain size effect using 1 and 10 micrometers is investigated. The results show that the 1 micrometer grain size cubic equiaxed microstructure has a better fatigue resistance because as grains are small and they have a higher mechanical strength.</p>

Doctor of Philosophy / The long-term research goal of this dissertation is to enable flaw-free production of metal parts using the laser powder bed fusion (LPBF) additive manufacturing (AM) process. As a step towards this long-term goal, the goal of this work is to predict and control the thermal history of an LPBF part. The thermal history is the spatiotemporal distribution of temperature in an LPBF part as it is created layer by layer. Thermal history is the primary cause of flaw formation in LPBF. To realize this goal, the objective of this dissertation is to establish and advance a novel thermal modeling method based on the concept of spectral graph theory, which is more than 10 times faster than existing finite element-based methods for the same level of accuracy. The central hypothesis is that physics-guided prediction, optimization, and control of thermal history mitigates flaw formation and enhances functionally critical properties of LPBF-processed parts when compared to parts produced without control of thermal history. The practical rationale and need for this work are as follows. LPBF is becoming increasingly prevalent due to its ability to fabricate complex structures that would otherwise be impossible with traditional subtractive and formative manufacturing processes. The freedom of geometry afforded by AM processes such as LPBF enables designers to place a stronger emphasis on design efficiency rather than the manufacturability of components. It also facilitates greater supply chain flexibility, reducing part lead times and costs. For example, making an aerospace part weighing just one kilogram with traditional subtractive and formative techniques requires processing 20 kilograms of raw material—a buy-to-fly ratio of 20:1—and lead times for new parts are often several months long. LPBF reduces the buy-to-fly ratio to less than 5:1, and the lead time is just a few weeks. Despite these advantages, LPBF has seen limited industry adoption and use, especially in safety-critical applications, due to the tendency of the process to form flaws. Approximately one in three parts are affected by flaws. Flaw formation leads to inconsistent part properties and can cause catastrophic failures in safety-critical aerospace, defense, and biomedical applications. Flaw formation in LPBF parts is mainly attributed to the thermal history. Thermal history, in turn, is influenced by complex design-process-material-machine interactions that require mathematical modeling. Rapid and accurate prediction of the thermal history can enable practitioners to avoid flaw formation and achieve desired part properties by optimizing the part design and process parameters before the part is printed. This dissertation leverages the graph theory modeling to address the burgeoning practical need for a rapid, accurate, and experimentally validated physics-based approach for mitigating flaw formation and ensuring part quality in LPBF

Medical practitioners rely heavily on visualization of medical imaging to get a better understanding of the patient's anatomy. Most cancer treatment and surgery today are performed using medical imaging. Medical imaging is therefore of great importance to the medical industry. Medical imaging continues to depend heavily on a series of 2D scans, resulting in a series of 2D photographs being displayed using light boxes and/or computer monitors. Today, these 2D images are increasingly combined into 3D solid models using software. These 3D models can be used for improved visualization and understanding of the problem at hand, including fabricating physical 3D models using additive manufacturing technologies. Generating precise 3D solid models automatically from 2D scans is non-trivial. Geometric and/or topologic errors are common, and often costly manual editing is required to produce 3D solid models that sufficiently reflect the actual underlying human geometry. These errors arise from the ambiguity of converting from 2D data to 3D data, and also from inherent limitations of the .STL fileformat used in additive manufacturing. This thesis proposes a new, robust method for automatically generating 3D models from 2D scanned data (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)), where the resulting 3D solid models are specifically generated for use with additive manufacturing. This new method does not rely on complicated procedures such as contour evolution and geometric spline generation, but uses volume reconstruction instead. The advantage of this approach is that the original scan data values are kept intact longer, so that the resulting surface is more accurate. This new method is demonstrated using medical CT data of the human nasal airway system, resulting in physical 3D models fabricated via additive manufacturing. / Master of Science / Medical practitioners rely heavily on medical imaging to get a better understanding of the patient’s anatomy. Most cancer treatment and surgery today are performed using medical imaging. Medical imaging is therefore of great importance to the medical industry. Medical imaging continues to depend heavily on a series of 2D scans, resulting in a series of 2D photographs being displayed using light boxes and/or computer monitors. With additive manufacturing technologies (also known as 3D printing), it is now possible to fabricate real-size physical 3D models of the human anatomy. These physical models enable surgeons to practice ahead of time, using realistic true scale model, to increase the likelihood of a successful surgery. These physical models can potentially also be used to develop organ implants that are tailored specifically to each patient’s anatomy. Generating precise 3D solid models automatically from 2D scans is non-trivial. Automated processing often causes geometric and topological (logical) errors, while manual editing is frequently too labor intensisve and time consuming to be considered practical solution. This thesis proposes a new, robust method for automatically generating 3D models from 2D scanned data (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)), where the resulting 3D solid models are specifically generated for use with additive manufacturing. The advantage of this proposed method is that the resulting fabricated surfaces are more accurate.

Composite structures have demonstrated great potential to improve mechanical performance in various applications, including ballistics protection. This study demonstrates that the integration of geometrically optimized composites into core-face sheet assemblies provide great impact resistance. The research investigated the performance of two composite manufacturing methods under low-velocity impact through residual strength and damage comparisons. Corrugated core composites were produced with traditional manufacturing methods, namely compression molding, using twelve stacking sequences. These stacking sequences were chosen to represent four laminate groups, where a unique fiber orientation scheme was employed across three laminate thicknesses (6, 8, and 12 layers). In contrast, honeycomb and auxetic cell cores were produced using continuous fiber-reinforced 3D printing. To maintain consistency, both the corrugated cores and the advanced cell cores were produced with para-aramid fibers, though the matrix differed between the two manufacturing methods. The cores were subjected to a consistent drop-weight impact event under various impact cases where the makeup of the assembly differed. The findings of this testing showed that external damage decreased as layer count increased for the laminates and that the addition of a silica damping material significantly improved post-impact, out-of-plane compressive response. In addition, testing proved that the cross-ply, longitudinally dominant laminates & the honeycomb printed composite exhibit exceptional out-of-plane compressive strength prior to and after impact. The cross-ply core retained 58.0% of its pre-impact stiffness & 68.3% of its pre-impact strength while the honeycomb core retained 88.0% of its pre-impact stiffness and did not fail under the maximum compressive load. Aside from impact testing, theoretical and numerical analyses were performed. Classic Laminate Plate Theory was employed to predict laminate engineering constants, while finite element models were created to simulate the in-plane response of the cores. The theoretical approach roughly approximated the longitudinal modulus, though the error was significant. In contrast, the finite element models developed closely mirrored experimental tensile behavior, with peak stress predicted within 5% of experimental results. The compressive response was also well captured by the model, though the displacement to buckling onset was underpredicted by 38.0%.

Ion-containing macromolecules continue to stimulate new opportunities for emerging electro-active applications ranging from high performance energy devices to water purification membranes. Progress in polymer synthesis and engineering now permit well-defined, ion-containing macromolecules with tunable morphologies, mechanical performance, ion conductivity, and 3D structure in order to address these globally challenged technologies. Achieving tailored chemical compositions with high degrees of phase separation for optimizing conductivity and water adsorption remains a constant synthetic challenge and presents an exciting opportunity for engineering sophisticated macromolecular architectures. This dissertation will introduce unprecedented charged polymers using conventional free radical and anionic polymerization to incorporate ionic functionalities based on phosphonium cations. This new class of copolymers offers unique properties with ionic functionality for tailorable electro-active performance. / Ph. D.

There is a link between the thermal and electrical properties of metal. The equation which links these two properties is called the Wiedemann-Franz Law. Also there is an emerging technology within Additive Manufacturing called Binder Jet Printing which can print high purity copper without heat stress within the material. Due to the Binder Jet Printings ability to print high resolution prints without any print through, this makes future use of this technology a necessity for future electrical and thermal components within computers . However a thermal and electrical conductivity analysis of binder jetted copper has never been performed, and needs to be for simulation with this material. Therefore within this thesis the relationship of the thermal and electrical properties of printed binder jetted copper part will be researched. To find the electrical resistivity of binder jetted copper, three sets of 2mm diameter rods where printed and then placed within a modified four wire resistance method test. For the thermal conductivity measurements a laser flash diffusivity machine was used, and three sets of 11 copper disks of approximately 1cm diameter by 1mm where printed. The data shows a strong linear trend linking electrical resistivity to the density ratio of the copper. Within the thermal conductance measurement, a lot more variability was seen within the three different prints. The 70% density ratio prints saw a large 13% spread in density ratios throughout the prints, which is believed to be caused by improper sintering due to temperature gradients near the door of the kiln. The 82% density prints saw better grouping of density ratios by placing the specimens in the back of the kiln. Lastly, the 92% prints saw the best density ratio grouping but the largest thermal conductivity variance. Even though the scatter plot for the thermal conductivity measurements are not as precise as the electrical resistivity measurements, it still shows a linear trend which matches the NASA data from 1971. Overall, these linear trends can be modeled and compiled into a new form of the Wiedemann-Franz law, which accounts for the density ratio of the binder jetted print. / Master of Science