This investigation aims to understand and improve the deposition quality and rates of cold spray for additive manufacturing in a way that is economically sound and without the detrimental temperature effects seen in traditional metallic additive manufacturing processes. It focuses on materials that are desired by the additive manufacturing community and built upon the current knowledge in cold spray. This thesis is presented as a collection of published, or soon to be published, manuscripts accompanied by an introduction, literature review, and conclusion. The effect of a non-spherical particle morphology was the first objective investigated. Titanium has been shown repeatedly to require pure helium at very high temperatures and pressures to get dense coatings, however, the unique coral-like morphology resulting from the Armstrong Process was revealed as a key to successful deposition with nitrogen. Using low pressure cold spray, under conditions that would be considered mild, a deposition efficiency of 100% and a porosity of nearly 0% was achieved. This is a promising approach for cold spray as a method for additive manufacturing of titanium parts. The low powder cost and the advantages of additive manufacturing could allow for a substantial cost savings in titanium part production when compared to traditional manufacturing methods. With these cost saving advantages, additive manufacturing of titanium using Armstrong process powder and CS could lead to a paradigm shift of titanium production, allowing titanium to enter markets that under traditional methods would be far too expensive. Unfortunately, this unique powder morphology was not available in other materials. To address the low deposition efficiency of the other metals of interest, such as aluminum and stainless steel, the concept of mixing the propellant gas was introduced in the second objective. Considering the relative costs of gases, powder, electricity, and labour, the second paper focuses on the concept of optimizing the amount of helium to produce the minimum component cost. It was found that for the specific stainless steel and aluminum alloy powders discussed, costs could be reduced by 44% and 59%, respectively, using the gas mixing system. However, no cost saving was found for the most inexpensive of the powders, pure aluminum. For gas mixing to be effective, the cost of helium must be offset by the cost of the powders. Therefore, low-cost powders, such as pure aluminum, results in pure nitrogen as the least expensive option. This however doesn’t address the low deposition efficiency that is preventing its adoption in cold spray additive manufacturing. The third objective addresses just this, an improvement in deposition efficiency without the introduction of expensive helium. In this study, aluminum particles were preheated using a novel particle preheater that does not clog. This resulted in a deposition efficiency increase of 260% with a minimal increase in electrical costs. These three objectives, while studied and published separately, all relate to the purpose of this work to improve the process economics without detrimental temperature effects. These findings have been (or will be) published in international peer reviewed journals to add to the collective knowledge.

Heat exchangers are integral parts for thermal management and find countless applications in automotive, aerospace, energy, nuclear power plants, HVAC, etc. Due to intensive research & development and technological advancements in manufacturing technologies, there is an increasing rise in demand for high-performance heat exchangers. In the automotive and aerospace industries, heat exchangers are expected to deliver better thermal efficiency and improve the system’s overall functionality in which they are installed by saving space and being lightweight. Additive Manufacturing (AM) is a ground-breaking and promising technology that offers avenues of opportunities to manufacture parts that were almost impossible to be produced with conventional manufacturing and can improve part performance with lightweight and compact designs. Laser-Based Powder Bed Fusion (LPBF), one of the well-known AM techniques, provides freedom to design complex geometries and fabricate them in a layer-by-layer fashion by exposing a high-density laser on a vertically moving powder bed. The study focuses on the application of AM in re-designing heat exchangers under given design requirements using LPBF. It includes exploring Triply Periodic Minimal Surfaces (TPMS) based structures such as gyroid and realizing them as heat exchanger core. Computational gyroid-based heat exchanger core models were designed and analyzed for thermal and fluid dynamics characteristics. A parametric study and analysis based on gyroid TPMS network type, periodic length, thickness, aspect ratio, and functional grading were carried out to optimize heat exchanger performance as per design conditions and validate their manufacturability using LPBF. Successful printable designs were further used to develop and manufacture prototypes. The study concludes with a comparison between additively manufactured gyroid-based design and conventional shell-and-tube design based on the thermal performance from CFD analysis and the weight of prototypes. It was found that the thermal performance from CFD analysis showed an 18.96% improvement, whereas weight was reduced by 14.8% for the gyroid-based design as compared to the conventional shell-and-tube design. / Thesis / Master of Applied Science (MASc)

Laser Powder Bed Fusion (L-PBF) is a metal additive manufacturing technique that uses a laser beam as a heat source to melt metal powder selectively. Because of the process small layer thicknesses, laser beam diameter, and powder particle size, L-PBF allows the fabrication of novel geometries and complex internal structures with enhanced properties. However, the main disadvantages of the L-PBF process are high costs and a lengthy production time. As a result, shortening the manufacturing process while maintaining comparable properties is exceptionally beneficial. Inconel 625 (IN625) is a nickel-based superalloy becoming increasingly popular in marine, petroleum, nuclear, and aerospace applications. However, the properties of IN625 parts produced by casting or forging are challenging to control due to their low thermal conductivity, high strength and work hardening rate, and high chemical complexity. Furthermore, IN625 alloy is regarded as a difficult-to-machine material. As a result, it is worthwhile to seek new technologies to manufacture complex-shaped IN625 parts with high dimensional accuracy. IN625 alloy is known for its excellent weldability and high resistance to hot cracking; thus, IN625 alloy appears to be a promising candidate for additive manufacturing. This thesis presents an experimentally focused study on optimizing L-PBF processing parameters in IN625 superalloy to increase process productivity while maintaining high material density and hardness. This study had four stages: preliminary, exploratory, modelling, and optimization. The first stage was devoted to conducting a literature review and determining the initial processing parameters. The second stage concentrated on determining the process window, for which single tracks were printed with two high levels of laser power (300, 400 W), five levels of scan speed (500, 700, 900, 1100, 1300 mm/s), and five levels of powder layer thickness (30, 60, 90, 120, 150 µm). Then, the process window was defined after investigating the top views and cross-sections of the tracks. Stage 3 involved printing 48 cubes (10 × 10 × 10 mm^3) with a laser power of 400 W, scan speeds of (700, 900, 1100, 1300 m/s), layer thicknesses of (60, 90, 120, 150 µm), and overlap percentages of (10, 30, 50%). As a result, the density of cubes was measured, and a statistical multiple regression analysis was used to predict it. Stage 4 involved estimating four sets of ideal processing parameters (based on statistical modelling of relative density) and printing 24 cubes (10 × 10 × 10 mm^3), six samples for each set. Finally, the relative density, hardness, and productivity of the samples were assessed, and a trade-off was determined. Even with the thickest powder layer of 150 µm (highest process productivity), samples with a mean relative density greater than 99% (i.e., 99.31% by Archimedes principle and 99.82% by image analysis) were printed. These findings are consistent with previously published results for L-PBF IN625 samples manufactured with smaller layer thicknesses ranging from 20 to 40 µm while maintaining comparable material hardness. The findings of this study are noteworthy because IN625 parts can be printed with higher powder layer thicknesses (less production time) while retaining similar material properties to those published with typical layer thicknesses ranging from 20 to 40 µm. Reduced production time due to optimized processing parameters can lead to significant energy and cost savings. / Thesis / Master of Applied Science (MASc)

Quality assurance has been one of the major challenges in laser-based additive manufacturing (AM) processes. This study proposes a novel process modeling methodology for layer-wise in-situ quality monitoring based on image series analysis. An image-based autoregressive (AR) model has been proposed based on the image registration function between consecutively observed thermal images. Image registration is used to extract melt pool location and orientation change between consecutive images, which contains sensing stability information. Subsequently, a Gaussian process model is used to characterize the spatial correlation within the error matrix. Finally, the extracted features from the aforementioned processes are jointly used for layer-wise quality monitoring. A case study of a thin wall fabrication by a Directed Laser Deposition (DLD) process is used to demonstrate the effectiveness of the proposed methodology.

The Sensor Analysis and Intelligence Laboratory (SAIL) at Mississippi State University's (MSU's) Center for Advanced Vehicular Systems (CAVS) incorporated sensors with unmanned aerial vehicles (UAVs). Mounting plates were created to secure the sensors to the UAVs for data collection. This study’s purpose was to detail the process that went in to creating two different versions of the mount plates. One version of the mounting system was cut from G10 fiberglass sheets, and the other version was made from 3D printing with polylactic acid (PLA). Characteristics such as cost, time, and simplicity of the manufacturing methods are compared in this study. Plate performance characteristics such as compatibility, weight, and success/failure are also discussed. Detailing the advantages and limitations of either approach will aid future researchers’ decision-making process for their own studies. They can use this study as a foundational framework for deciding which mount would best fit with their system requirements.

The aim of this work is to model, manufacture, and test an optimized Messerschmitt-BölkowBlohm beam using additive manufacturing. The implemented method is the Solid Isotropic Material with Penalization of a minimum compliance design. The Taubin smoothing technique was used to attenuate geometric noise and minimize the formation of overhanging angles and residual stresses due to the thermal activity of the selective laser melting process. The optimized model required examination and repair of local errors such as surface gaps, non-manifold vertices, and intersecting facets. A comparison between experimental and numerical results of the linear elastic regimes showed that the additively manufactured structure was less stiff than predicted. Potential contributors are discussed, including the formation of an anisotropic microstructure throughout the layer-by-layer melting process. In addition, the effect of selective laser melting process on the mechanical properties of stainless steel 316l-0407 and its influence on structural performance was described.

Additive manufacturing is becoming more popular as a construction technique for various design fields. 3D Concrete Printing is one type of additive manufacturing in which layers of concrete are stacked on top of each other by pushing concrete through a nozzle onto a printing bed. These layers create three-dimensional solid objects from a digital file. 3D Concrete Printing promises to be extremely beneficial for design flexibility, cost, time, safety, environmental impact, and error reduction. This study explores the potential of 3D Concrete Printing technology in landscape architecture by exploring current research, case studies, expert interviews, and design prototype documentation. The study results indicate that 3D Concrete Printing technology has great potential for future use; however, there are also some challenges. Analysis of the responses aims to provide a basis for understanding the technology's performance, design process, and the potential of the 3DCP in landscape architecture design.

Additive manufacturing (AM) is a novel fabrication technique capable of producing highly complex parts. Nevertheless, a major challenge is improving the quality of the fabricated parts. While there are several ways of approaching this problem, developing data-driven methods that use AM process signatures to identify these part anomalies can be rapidly applied to improve the overall part quality during the build. The objective of this dissertation is to model multiple processes within the AM to quantify the quality of the parts and reduced the uncertainty due to variation in input process parameters. The objective of first study is to build a new layer-wise process signature model to characterize the thermal-defect relationship. Based on melt pool images, we propose novel layer-wise key process signatures, which are calculated using multilinear principal component analysis (MPCA) and are directly correlated with layer-wise quality of the part. Second study broadens the spectrum of the dissertation to include mechanical properties, where a novel two-phase modeling methodology is proposed for fatigue life prediction based on in-situ monitoring of thermal history. In final study, our objective is to pave the way toward a better understanding of the uncertainty in the process-defect-structures relationship using an inverse robust design exploration method. The method involves two steps. In the first step, mathematical models are developed to characterize and model the forward flow of information in the intended additive manufacturing process. In the second step, inverse robust design exploration is carried out to investigate satisfying design solutions that meet multiple AM goals.

Additive manufacturing has shown the ability to produce highly complex geometries that are not easily manufactured through traditional means. However, the implications of building these complex geometries regarding thermal history requires more attention. AM process simulations have proven to be computationally expensive and require large amounts of pre-processing to execute. This thesis will start with a review of additive manufacturing along with current modeling efforts. Then, the development of a pre-processing tool for finite element simulations of these processes is presented. It is shown that the pre-processing tool significantly decreases the total time-to-simulation by removing manual steps. Finally, a study using this tool is conducted to analyze the thermal histories of a cube and a cylinder with two different scan strategies and explore differences in resulting thermal history. It is shown that less temperature fluctuations and a lower final temperature result from an offset scan strategy and a cylindrical geometry.

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