The primary objectives of this work are two-fold. First, additive manufacturing (AM) and rapid prototype (RP) testing are evaluated for use in production of a wind tunnel (WT) models. Second, an approach was developed to incorporate stability and control (SandC) WT data into aircraft conceptual design multidisciplinary design optimization (MDO). Both objectives are evaluated in terms of data quality, time, and cost. FDM(TM) and PolyJet AM processes were used for model production at low cost and time. Several models from a representative tailless configuration, ICE 101, were printed and evaluated for strength, cost and time of production. Furthermore, a NACA 0012 model with 20% chord flap was manufactured. Both models were tested in the Virginia Tech (VT) Open-Jet WT for force and moment acquisition. A 1/15th scale ICE 101 model was prepared for manufacturing, but limits of FDM(TM) technology were identified for production. An approach using WT data was adapted from traditional surrogate-based optimization (SBO), which uses computational fluid dynamics (CFD) for data generation. Split-plot experimental designs were developed for analysis of the WT SBO strategy using historical data and for WT testing of the NACA 0012. Limitations of the VT Open-Jet WT resulted in a process that was not fully effective for a MDO environment. However, resolution of ICE 101 AM challenges and higher quality data from a closed-section WT should result in a fully effective approach to incorporate AM and RP testing in an aircraft conceptual design MDO. / Master of Science

A key advantage of Additive Manufacturing (AM) is the opportunity to design and fabricate complex structures that cannot be made via traditional means. However, this potential is significantly constrained by the use of a facet-based geometry representation (e.g., the STL and the AMF file formats); which do not contain any volumetric information and often, designing/slicing/printing complex geometries exceeds the computational power available to the designer and the AM system itself. To enable efficient design and fabrication of complex/multi-material complex structures, several algorithms are presented that represent and process solid models as a set of voxels (three-dimensional pixels). Through this, one is able to efficiently realize parts featuring complex geometries and functionally graded materials. This thesis specifically aims to explore applications in three distinct fields namely, (i) Design for AM, (ii) Design for Manufacturing (DFM) education, and (iii) Reverse engineering from imaging data wherein voxel-based representations have proven to be superior to the traditional AM digital workflow. The advantages demonstrated in this study cannot be easily achieved using traditional AM workflows, and hence this work emphasizes the need for development of new voxel based frameworks and systems to fully utilize the capabilities of AM. / MS

Metal additive manufacturing (AM) is an emerging technology for producing parts with virtually no constraint on the geometry. AM builds a part by depositing materials in a layer-by-layer fashion. Despite the benefits in several critical applications, quality issues are one of the primary concerns for the widespread adoption of metal AM. Addressing these issues starts with a better understanding of the underlying physics and includes monitoring and controlling the process in a real-world manufacturing environment. Digital Twins (DTs) are virtual representations of physical systems that enable fast and accurate decision-making. DTs rely on Artificial Intelligence (AI) to process complex information from multiple sources in a manufacturing system at multiple levels. This information typically comes from partially known process physics, in-situ sensor data, and ex-situ quality measurements for a metal AM process. Most current AI models cannot handle ill-structured information from metal AM. Thus, this work proposes three novel machine-learning methods for improving the quality of metal AM processes. These methods enable DTs to control quality in several processes, including laser powder bed fusion (LPBF) and additive friction stir deposition (AFSD). The proposed three methods are as follows 1. Process improvement requires mapping the process parameters with ex-situ quality measurements. These mappings often tend to be non-stationary, with limited experimental data. This work utilizes a novel Deep Gaussian Process-based Bayesian optimization (DGP-SI-BO) method for sequential process design. DGP can model non-stationarity better than a traditional Gaussian Process (GP), but it is challenging for BO. The proposed DGP-SI-BO provides a bagging procedure for acquisition function with a DGP surrogate model inferred via Stochastic Imputation (SI). For a fixed time budget, the proposed method gives 10% better quality for the LPBF process than the widely used BO method while being three times faster than the state-of-the-art method. 2. For metal AM, the process physics information is usually in the form of Partial Differential Equations (PDEs). Though the PDEs, along with in-situ data, can be handled through Physics-informed Neural Networks (PINNs), the activation function in NNs is traditionally not designed to handle multi-scale PDEs. This work proposes a novel activation function Self-scalable tanh (Stan) function for PINNs. The proposed activation function modifies the traditional tanh function. Stan function is smooth, non-saturating, and has a trainable parameter. It can allow an easy flow of gradients and enable systematic scaling of the input-output mapping during training. Apart from solving the heat transfer equations for LPBF and AFSD, this work provides applications in areas including quantum physics and solid and fluid mechanics. Stan function also accelerates notoriously hard and ill-posed inverse discovery of process physics. 3. PDE-based simulations typically need to be much faster for in-situ process control. This work proposes to use a Fourier Neural Operator (FNO) for instantaneous predictions (1000 times speed up) of quality in metal AM. FNO is a data-driven method that maps the process parameters with a high dimensional quality tensor (like thermal distribution in LPBF). Training the FNO with simulated data from PINN ensures a quick response to alter the course of the manufacturing process. Once trained, a DT can readily deploy the model for real-time process monitoring. The proposed methods combine complex information to provide reliable machine-learning models and improve understanding of metal AM processes. Though these models can be independent, they complement each other to build DTs and achieve quality assurance in metal AM. / Doctor of Philosophy / Metal 3D printing, technically known as metal additive manufacturing (AM), is an emerging technology for making virtually any physical part with a click of a button. For instance, one of the most common AM processes, Laser Powder Bed Fusion (L-PBF), melts metal powder using a laser to build into any desired shape. Despite the attractiveness, the quality of the built part is often not satisfactory for its intended usage. For example, a metal plate built for a fractured bone may not adhere to the required dimensions. Improving the quality of metal AM parts starts with a better understanding the underlying mechanisms at a fine length scale (size of the powder or even smaller). Collecting data during the process and leveraging the known physics can help adjust the AM process to improve quality. Digital Twins (DTs) are exactly suited for the task, as they combine the process physics and the data obtained from sensors on metal AM machines to inform an AM machine on process settings and adjustments. This work develops three specific methods to utilize the known information from metal AM to improve the quality of the parts built from metal AM machines. These methods combine different types of known information to alter the process setting for metal AM machines that produce high-quality parts.

With the growing need to meet aggressive emissions targets in the aerospace industry in the coming decades, the electrification of propulsion systems has become an area of great research and commercial interest. In order to achieve full electrification of larger commercial aircraft, it is critical to improve power and energy densities of components within the propulsion system. The power densities of electric motors are steadily rising to meet this requirement. Among the various motor designs available, the high-speed radial flux permanent magnet motor is presented as an architecture capable of achieving high efficiencies and power densities. Increasing power densities, however, poses challenges for the thermal management system as higher losses need to be dissipated from a relatively small machine package. One of the failure modes specific to permanent magnet motors is the demagnetization of the magnets in the rotor at higher temperatures which leads to a loss in performance. Therefore it is critical that the thermal management system of the rotor must effectively dissipate the losses generated in the magnets and other components within the rotor. This thesis discusses the mechanical and thermal design of a 150 kW high-speed radial flux surface mounted permanent magnet motor for aerospace propulsion applications. The thesis first introduces the current landscape of aerospace electrification, focusing specifically on electric and hybrid propulsion architectures, currently available electric motors for aerospace propulsion, and ongoing aircraft electrification projects. A review is then provided of the current state-of-the-art in rotor cooling designs for high-speed speed radial flux motors for traction applications before introducing the design of the motor proposed in this thesis. The discussion of the mechanical design provides a high level overview of the design, manufacturing, and assembly of the stator and rotating assemblies while the thermal design provides a brief overview of the stator cooling design and a deep dive on the rotor cooling design. Computational Fluid Dynamics (CFD) is used along with the Taguchi method for robust design to optimize the rotor cooling design for minimizing the magnet temperatures. Analysis for the optimized rotor cooling discussed is provided before providing recommendations for future work. / Thesis / Master of Applied Science (MASc)

The goal of this research is to aid the development of large-scale additive manufacturing of jointless underbody hulls for the Army Ground Vehicle Systems by 1) generating an improved mechanical and metallurgical database and 2) understanding the Additive Friction Stir Deposition (AFSD) process. AFSD is a solid-state additive manufacturing process that is a high strain rate and a hot working process that deforms material onto a substrate and builds a component layer by layer. This unique, solid-state additive manufacturing process has the potential for scalability into ground vehicle applications on the extra large-scale due to its solid-state nature. Two different aluminum alloys were investigated: Al-Mg-Si (6061) and Al-Zn-Mg-Cu (7075). AFSD builds were evaluated in the transverse or through layer direction (Z) and the 6061 material was also evaluated in the longitudinal direction (X). Uniaxial tensile testing was performed to generate mechanical property data while fractography, and metallography were used to better understand the metallurgical implications of this process. This research determined that the refinement of the grain size caused by the AFSD process had little or no strengthening effect on the mechanical properties of either alloy. Instead, the as-deposited condition in both alloys were soft with good ductility due to the dissolution of the strengthening particles. After heat treatment, the elongation and fracture mode of the 6061 alloy was dependent on the layer direction. Failure often initiated at interfaces and affected the materials' elastic-plastic behavior. For the 7075 alloy, the strength and failure mechanism of the material were affected by the presence of the graphite lubricant used during processing. The use of graphite increased the variability of the mechanical properties results and caused premature failure in numerous samples. In both alloys, the heat treatment caused grain coarsening to varying degrees which can affect the mechanical behavior. From these results, it was found that a precipitation strengthening heat treatment is required for material deposited with AFSD to achieve the minimum mechanical property standards for a forging. Recommendations and future work include 1) investigating the effect of residual stresses on AFSD components, 2) determining the fatigue properties of AFSD materials, 3) continuing to increase the database of mechanical properties for AFSD materials, and 4) developing additional lubricants for the AFSD process. / Master of Science / The results of this research will be used to help generate design requirements for large-scale additively manufactured parts such as underbody tank hulls. This research generated and expanded on the mechanical and metallurgical understanding of solid-state additively manufactured aluminum. The solid-state additive process used was Additive Friction Stir Deposition. Like its name, this process uses a rotating tool head to apply friction to a solid bar of aluminum that then generates heat which makes the metal soft enough to stir and deposit into a layer. Another layer is then deposited on top and repeated layer by layer until the final part is completed. Other metal additive manufacturing processes that involve melting and then rapidly cooling the material degrade the quality of the metal material. The first part of this research investigated the mechanical properties in different layer directions either pulling along the build direction or against the layers. The results showed that a heat treatment was required to improve the strength of the aluminum to meet current standards of quality. However, the ability of the aluminum to elongate depended on the orientation of the layers. The second part of this research investigated the effect that a graphite lubricant used on the aluminum feedstock to help prevent the material from sticking in the tool head affected the mechanical properties. The results show that the graphite lubricant did not dissolve or disappear into the metal and caused a reduction in the elongation of the aluminum. Recommendations for extra large-scale metal additive manufacturing are to design parts to apply the highest stress along the layer direction and to eliminate the use of the graphite lubricant.

The continuous miniaturization of electronic devices and the corresponding increase in computing powers have led to a significant growth in the density of heat dissipation within these devices. This increase in heat generation has challenged conventional air fan cooling and alternative solutions for heat removal are required to avoid overheating and part damage. Micro/Mini channel heat sinks (M/MCHS) that use liquids for heat removal appear as an attractive solution to this problem as they provide large heat transfer area per volume. Mini/microchannels traditionally have suffered from geometrical and material restrictions due to fabrication constraints. An emerging new additive manufacturing technique called binder jetting has the potential to overcome some of those restrictions. In this study, a straight minichannel heat sink is manufactured from stainless steel using binder jetting, and it is experimentally evaluated. The hydraulic performance of the heat sink is tested over a range of Reynolds numbers (150-1200). The comparison between the hydraulic results and standard correlations confirms that the targeted geometry was produced, although the high surface roughness created an early transition from laminar-to-turbulent flow. The heat transfer performance was also experimentally characterized at different heat flux conditions ($3000W/m^2$, $5000W/m^2$, $6500W/m^2$), and a range of Reynolds numbers (150-800). These results indicated that convection heat transfer coefficients on the order of $1000 W/m^2-K$ can be obtained with a simple heat sink design. Finally, the effects of the contact resistance on the results are studied, and contact resistance is shown to have critical importance on the thermal measurements. / Master of Science / The continuous miniaturization of electronic devices and the corresponding increase in computing powers have led to a significant growth in the density of heat dissipation within these devices. This increase in heat generation has challenged conventional air fan cooling and alternative solutions for heat removal are required to avoid overheating and part damage. Micro/Mini channel heat sinks (M/MCHS) that use water instead of air for heat removal appear as an attractive solution to this problem as they provide large heat transfer area per volume due to the small channels. Mini/microchannels are distinguished from conventional channels by the hydraulic diameter, where they range from $10mu m$ to $2mm$. M/MCHS are typically manufactured from a highly conductive metals with the channels fabricated on the surface. However, mini/microchannels traditionally have suffered from geometrical and material restrictions due to fabrication constraints. Complex features like curves or internall channels are difficult or even impossible to manufacture. An emerging new additive manufacturing technique called binder jetting has the potential to overcome some of those restrictions. Binder jetting possess unique advantageous as it uses precise control of a liquid binder applied to a bed of fine powder to create complex geometries Furthermore, it does not require extreme heating during the fabrication process. The advantages of binder jetting include that it is low cost, high speed, can be applied to a variety of materials, and the ability to scale easily in size. In this study, a straight minichannel heat sink is manufactured from stainless steel using binder jetting, and this heat sink is experimentally evaluated. The hydraulic performance of the heat sink is tested over different water flow rates (Reynolds numbers between 150-1200). The comparison between the hydraulic results and standard correlations confirms that the targeted geometry was produced, although the high surface roughness created an early transition from laminar-to-turbulent flow. The surface roughness effect should be considered in future designs of additively manufactured minichannels. The heat transfer performance was also experimentally characterized at different heat flux conditions ($3000W/m^2$, $5000W/m^2$, $6500W/m^2$), and different water flow conditions (Reynolds numbers 150-800). These results indicated that convection heat transfer coefficients on the order of $1000 W/m^2-K$ can be obtained with a simple heat sink design. However, a mismatch between the experimental data and the correlation requires further investigation. Finally, the effects of the contact resistance on the results are studied, and contact resistance is shown to have critical importance on the thermal measurements.

Large format 3D printing of thermoplastic polymers is a fast growing technology for industrial tools manufacturing and enables the production of meters long workpiece in a fraction of time, material and cost than conventional subtractive solutions. Due to the scale and timing imposed by the industry, Large Format Additive Manufacturing (LFAM) is mostly based on screw extrusion of thermoplastic pellets offering a significantly higher deposition rate and lower material costs compared to the well-known filament extrusion 3D printing (FFF). Carbon fiber reinforced polymers are commonly used in large-scale 3D printing as they minimize distortions and internal stresses during deposition preventing delamination and failure of the printed component. The technology stands out for the exceptional melt deposition rate; the lack of a temperature-controlled build chamber, and the low surface-to-volume proportion of the printed strand, making the temperature management of the deposited material particularly challenging in large-scale 3D printing. Print overcooling may lead to poor adhesion between layers eventually resulting in delamination, excessive heat build-up, on the other hand, is likely to result in sagging and print failure. Print thermal behavior and temperature management are closely related to material, part design and deposition strategy. Even though numerous software solutions for predictive process simulation as well as active feedback print controls for parameters optimization are emerging, common practice still relies on restricted set of strategies deduced by trial and error testing sessions; the best printing configuration is specifically custom-made for each print, an approach that could severely hinder the technology potential. This research is conducted as part of the project of CMS S.p.a., a company specialized in the production of CNC multi-axis machining centers, to develop and market an all-around tool manufacturing solution that would combine milling and Screw Extrusion Additive Manufacturing (SEAM). The study aims to develop a flexible and versatile cooling model that can predict the best process window for large-scale additive manufactured parts and automatically generate the best printing parameters for a generic printing strategy according to part material and shape. Next, the model was incorporated inside a path generation slicing software that operates with the same process parameters, unique solution on the market. Any given material is described by a specific set of variables that can be experimentally derived using a simple standardized procedure. Four industrially relevant materials were investigated for thermal model and software validation. In the framework of large format 3D printed tool manufacturing, 40 wt% carbon fiber reinforced polyamide 6 (PA6) and 20 wt% carbon fiber reinforced acrylonitrile-butadiene-styrene (ABS), polycarbonate (PC), and polyetherimide (PEI) play a strategic role in most applications. In addition, the research offers a physical, mechanical and thermal characterization of the printed workpiece providing a comprehensive guideline for part design, arrangement, and thermal compensation for traditional CFRP manufacturing tools. Finally, for each material, a real tool manufacturing case study and post-processed surface qualification is presented.

The goal of this work is to develop and characterize a manufacturing process that is able to create metal matrix composites with complex cellular geometries. The novel manufacturing method uses two distinct additive manufacturing processes: i) fabrication of patternless molds for cellular metal castings and ii) printing an advanced cellular ceramic for embedding in a metal matrix. However, while the use of AM greatly improves the freedom in the design of MMCs, it is important to identify the constraints imposed by the process and its process relationships. First, the author investigates potential differences in material properties (microstructure, porosity, mechanical strength) of A356 — T6 castings resulting from two different commercially available Binder Jetting media and traditional 'no-bake' silica sand. It was determined that they yielded statistically equivalent results in four of the seven tests performed: dendrite arm spacing, porosity, surface roughness, and tensile strength. They differed in sand tensile strength, hardness, and density. Additionally, two critical sources of process constraints on part geometry are examined: (i) depowdering unbound material from intricate casting channels and (ii) metal flow and solidification distances through complex mold geometries. A Taguchi Design of Experiments is used to determine the relationships of important independent variables of each constraint. For depowdering, a minimum cleaning diameter of 3 mm was determined along with an equation relating cleaning distance as a function of channel diameter. Furthermore, for metal flow, choke diameter was found to be significantly significant variable. Finally, the author presents methods to process complex ceramic structure from precursor powders via Binder Jetting AM technology to incorporate into a bonded sand mold and the subsequently casted metal matrix. Through sintering experiments, a sintering temperature of 1375 °C was established for the ceramic insert (78% cordierite). Upon printing and sintering the ceramic, three point bend tests showed the MMCs had less strength than the matrix material likely due to the relatively high porosity developed in the body. Additionally, it was found that the ceramic metal interface had minimal mechanical interlocking and chemical bonding limiting the strength of the final MMCs. / Ph. D.

One of the major limitations in Fused Filament Fabrication (FFF), a form of additive manufacturing, is the lack of composites with superior mechanical properties. Traditionally, carbon and glass fibers are widely used to improve the physical properties of polymeric matrices. However, the blending methods lead to fiber breakage, preventing generation of long fiber reinforced filaments essential for printing load-bearing components. Our approach to improve tensile properties of the printed parts was to use in-situ composites to avoid fiber breakage during filament generation. In the filaments generated, we used thermotropic liquid crystalline polymers (TLCPs) to reinforce acrylonitrile butadiene styrene (ABS) and a high performance thermoplastic, polyphenylene sulfide (PPS). The TLCPs are composed of rod-like monomers which are highly aligned under extensional kinematics imparting excellent one-dimensional tensile properties. The tensile strength and modulus of the 40 wt.% TLCP/ABS filaments was improved by 7 and 20 times, respectively. On the other hand, the 67 wt.% TLCP/PPS filament tensile strength and modulus were improved by 2 and 12 times, respectively. The filaments were generated using dual extrusion technology to produce nearly continuously reinforced filaments and to avoid matrix degradation. Rheological tests were taken advantage of to determine the processing conditions. Dual extrusion technology allowed plasticating the matrix and the reinforcing polymer separately in different extruders. Then continuous streams of TLCP were injected below the TLCP melting temperature into the matrix polymer to avoid matrix degradation. The blend was then passed through a series of static mixers, subdividing the layers into finer streams, eventually leading to nearly continuous fibrils which were an order of magnitude lower in diameter than those of the carbon and glass fibers. The composite filaments were printed below the melting temperature of the TLCPs, and the conditions were determined to avoid the relaxation of the order in the TLCPs. On printing, a matrix-like printing performance was obtained, such that the printer was able to take sharp turns in comparison with the traditionally used fibers. Moreover, the filaments led to a significant improvement in the tensile properties on using in FFF and other conventional technologies such as injection and compression molding. / Doctor of Philosophy / In this work two thermoplastic matrices, acrylonitrile butadiene styrene (ABS) and polyphenylene sulfide (PPS), were reinforced with higher melting thermoplastics of superior properties called thermotropic liquid crystalline polymers (TLCPs). This was done so that the resulting filaments could be 3D-printed without melting the TLCPs. The goal of this work was to generate nearly continuous reinforcement in the filaments and to avoid matrix degradation, and, hence, a technology called dual extrusion technology was used for the filament generation. The temperatures required for filament generation were determined using rheology, which involves the study of flow behavior of complex fluids. Dual extrusion technology allows processing of the constituent polymers separately at different temperatures, followed by a continuous injection of multiple TLCP-streams into the matrix polymers. In addition, the use of static mixers (metallic components kept in the path of flow to striate incoming streams) leads to further divisions of the TLCP-streams which are eventually drawn by pulling to orient the TLCP phase. The resulting filaments exhibited specific properties (normalized tensile properties) higher than aluminum and contained fibers that were nearly continuous, highly oriented, and an order in magnitude lower in diameter than those of carbon and glass fiber, which are commonly used reinforcements. High alignment and lower fiber diameter are essential for printing smoother printed parts. The filaments were intended to be printed without melting the TLCPs. However, previous studies involving the use of TLCP reinforced composites in conventional technologies have reported the occurrence of orientation relaxation on postprocessing, which decreases their tensile v properties. Therefore, temperatures required for 3D printing were determined using compression molding to retain filament properties on printing to the maximum extent. On printing using an unmodified 3D printer, parts were printed by taking 180º turns during material deposition. Contrarily, the use of continuous carbon fibers required a modified 3D printer to allow impregnation during 3D printing. Moreover, the performance comparison showed that the continuous carbon fibers could not be deposited in tighter loops. The properties of the printed parts were higher than those obtained on using short fibers and approaching those of the continuous fiber composites.

This thesis proposes a new method for detecting malicious cyber-physical attacks on additive manufacturing (AM) systems. The method makes use of a physical hash, which links digital data to the manufactured part via a disconnected side-channel measurement system. The disconnection ensures that if the network and/or AM system become compromised, the manufacturer can still rely on the measurement system for attack detection. The physical hash takes the form of a QR code that contains a hash string of the nominal process parameters and toolpath. It is manufactured alongside the original geometry for the measurement system to scan and compare to the readings from its sensor suite. By taking measurements in situ, the measurement system can detect in real-time if the part being manufactured matches the designer's specification. A proof-of-concept validation was realized on a material extrusion machine. The implementation was successful and demonstrated the ability of this method to detect the existence (and absence) of malicious attacks on both process parameters and the toolpath. A case study for detecting changes to the toolpath is also presented, which uses a simple measurement of how long each layer takes to build. Given benchmark readings from a 30x30 mm square layer created on a material extrusion system, several modifications were able to be detected. The machine's repeatability and measurement technique's accuracy resulted in the detection of a 1 mm internal void, a 2 mm scaling attack, and a 1 mm skewing attack. Additionally, for a short to moderate length build of an impeller model, it was possible to detect a 0.25 mm change in the fin base thickness. A second case study is also presented wherein dogbone tensile test coupons were manufactured on a material extrusion system at different extrusion temperatures. This process parameter is an example of a setting that can be maliciously modified and have an effect on the final part strength without the operator's knowledge. The performance characteristics (Young's modulus and maximum stress) were determined to be statistically different at different extrusion temperatures (235 and 270 °C). / Master of Science