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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