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- All Subjects: Mechanical Engineering
- Genre: Academic theses
Description
Additive manufacturing (AM) describes an array of methods used to create a 3D object layer by layer. The increasing popularity of AM in the past decade has been due to its demonstrated potential to increase design flexibility, produce rapid prototypes, and decrease material waste. Temporary supports are an inconvenient necessity in many metal AM parts. These sacrificial structures are used to fabricate large overhangs, anchor the part to the build substrate, and provide a heat pathway to avoid warping. Polymers AM has addressed this issue by using support material that is soluble in an electrolyte that the base material is not. In contrast, metals AM has traditionally approached support removal using time consuming, costly methods such as electrical discharge machining or a dremel.
This work introduces dissolvable supports to single- and multi-material metals AM. The multi-material approach uses material choice to design a functionally graded material where corrosion is the functionality being varied. The single-material approach is the primary focus of this thesis, leveraging already common post-print heat treatments to locally alter the microstructure near the surface. By including a sensitizing agent in the ageing heat treatment, carbon is diffused into the part decreasing the corrosion resistance to a depth equal to at least half the support thickness. In a properly chosen electrolyte, this layer is easily chemically, or electrochemically removed. Stainless steel 316 (SS316) and Inconel 718 are both investigated to study this process using two popular alloys. The microstructure evolution and corrosion properties are investigated for both. For SS316, the effect of applied electrochemical potential is investigated to describe the varying corrosion phenomena induced, and the effect of potential choice on resultant roughness. In summary, a new approach to remove supports from metal AM parts is introduced to decrease costs and further the field of metals AM by expanding the design space.
This work introduces dissolvable supports to single- and multi-material metals AM. The multi-material approach uses material choice to design a functionally graded material where corrosion is the functionality being varied. The single-material approach is the primary focus of this thesis, leveraging already common post-print heat treatments to locally alter the microstructure near the surface. By including a sensitizing agent in the ageing heat treatment, carbon is diffused into the part decreasing the corrosion resistance to a depth equal to at least half the support thickness. In a properly chosen electrolyte, this layer is easily chemically, or electrochemically removed. Stainless steel 316 (SS316) and Inconel 718 are both investigated to study this process using two popular alloys. The microstructure evolution and corrosion properties are investigated for both. For SS316, the effect of applied electrochemical potential is investigated to describe the varying corrosion phenomena induced, and the effect of potential choice on resultant roughness. In summary, a new approach to remove supports from metal AM parts is introduced to decrease costs and further the field of metals AM by expanding the design space.
ContributorsLefky, Christopher (Author) / Hildreth, Owen (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Azeredo, Bruno (Committee member) / Rykaczewski, Konrad (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Polymer fibers have broad applications in wearable electronics, bulletproof vests, batteries, fuel cells, filters, electrodes, conductive wires, and biomedical materials. Polymer fibers display light density and flexibility but are mostly weak and compliant. The ceramic, metallic, and carbon nanoparticles have been frequently included in polymers for fabricating continuous, durable, and functional composite fibers. Nanoparticles display large specific areas, low defect density and can transfer their superior properties to polymer matrices. The main focus of this thesis is to design, fabricate and characterize the polymer
anocarbon composite fibers with unique microstructures and improved mechanical/thermal performance. The dispersions and morphologies of graphene nanoplatelets (GNPs), the interactions with polyvinyl alcohol (PVA) molecules and their influences on fiber properties are studied. The fibers were fabricated using a dry-jet wet spinning method with engineered spinneret design. Three different structured fibers were fabricated, namely, one-phase polymer fiber (1-phase), two-phase core-shell composite fiber (2-phase), and three-phase co-axial composite fiber (3-phase). These polymer or composite fibers were processed at three stages with drawing temperatures of 100˚C, 150˚C, and 200˚C. Different techniques including the mechanical tester, wide-angle X-Ray diffraction (WAXD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), and differential scanning calorimeter (DSC) have been used to characterize the fiber microstructures and properties.
anocarbon composite fibers with unique microstructures and improved mechanical/thermal performance. The dispersions and morphologies of graphene nanoplatelets (GNPs), the interactions with polyvinyl alcohol (PVA) molecules and their influences on fiber properties are studied. The fibers were fabricated using a dry-jet wet spinning method with engineered spinneret design. Three different structured fibers were fabricated, namely, one-phase polymer fiber (1-phase), two-phase core-shell composite fiber (2-phase), and three-phase co-axial composite fiber (3-phase). These polymer or composite fibers were processed at three stages with drawing temperatures of 100˚C, 150˚C, and 200˚C. Different techniques including the mechanical tester, wide-angle X-Ray diffraction (WAXD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), and differential scanning calorimeter (DSC) have been used to characterize the fiber microstructures and properties.
ContributorsVerma, Rahul (Author) / Song, Kenan (Thesis advisor) / Jiang, Hanqing (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
Description
Stiffness and flexibility are essential in many fields, including robotics, aerospace, bioengineering, etc. In recent years, origami-based mechanical metamaterials were designed for better mechanical properties including tunable stiffness and tunable collapsibility. However, in existing studies, the tunable stiffness is only with limited range and limited controllability. To overcome these challenges, two objectives were proposed and achieved in this dissertation: first, to design mechanical metamaterials with metamaterials with selective stiffness and collapsibility; second, to design mechanical metamaterials with in-situ tunable stiffness among positive, zero, and negative.In the first part, triangulated cylinder origami was employed to build deployable mechanical metamaterials through folding and unfolding along the crease lines. These deployable structures are flexible in the deploy direction so that it can be easily collapsed along the same way as it was deployed. An origami-inspired mechanical metamaterial was designed for on-demand deployability and selective collapsibility: autonomous deployability from the collapsed state and selective collapsibility along two different paths, with low stiffness for one path and substantially high stiffness for another path. The created mechanical metamaterial yields unprecedented load bearing capability in the deploy direction while possessing great deployability and collapsibility. The principle in this prospectus can be utilized to design and create versatile origami-inspired mechanical metamaterials that can find many applications.
In the second part, curved origami patterns were designed to accomplish in situ stiffness manipulation covering positive, zero, and negative stiffness by activating predefined creases on one curved origami pattern. This elegant design enables in situ stiffness switching in lightweight and space-saving applications, as demonstrated through three robotic-related components. Under a uniform load, the curved origami can provide universal gripping, controlled force transmissibility, and multistage stiffness response. This work illustrates an unexplored and unprecedented capability of curved origami, which opens new applications in robotics for this particular family of origami patterns.
ContributorsZhai, Zirui (Author) / Nian, Qiong (Thesis advisor) / Zhuang, Houlong (Committee member) / Huang, Huei-Ping (Committee member) / Zhang, Wenlong (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2021
Description
Laser powder bed fusion (LPBF) additive manufacturing (AM) has received widespread attention due to its ability to produce parts with complicated design and better surface finish compared to other additive techniques. LPBF uses a laser heat source to melt layers of powder particles and manufactures a part based on the CAD design. This process can benefit significantly through computational modeling. The objective of this thesis was to understand the thermal transport, and fluid flow phenomena of the process, and to optimize the main process parameters such as laser power and scan speed through a combination of computational, experimental, and statistical analysis. A multi-physics model was built using to model temperature profile, bead geometry and elemental evaporation in powder bed process using a non-gaussian interaction between laser heat source and metallic powder. Owing to the scarcity of thermo-physical properties of metallic powders in literature, thermal conductivity, diffusivity, and heat capacity was experimentally tested up to a temperature of 1400 degrees C. The values were used in the computational model, which improved the results significantly. The computational work was also used to assess the impact of fluid flow around melt pool. Dimensional analysis was conducted to determine heat transport mode at various laser power/scan speed combinations. Convective heat flow proved to be the dominant form of heat transfer at higher energy input due to violent flow of the fluid around the molten region, which can also create keyhole effect. The last part of the thesis focused on gaining useful information about several features of the bead area such as contact angle, porosity, voids and melt pool that were obtained using several combinations of laser power and scan speed. These features were quantified using process learning, which was then used to conduct a full factorial design that allows to estimate the effect of the process parameters on the output features. Both single and multi-response analysis are applied to analyze the output response. It was observed that laser power has more influential effect on all the features. Multi response analysis showed 150 W laser power and 200 mm/s produced bead with best possible features.
ContributorsAhsan, Faiyaz (Author) / Ladani, Leila (Thesis advisor) / Razmi, Jafar (Committee member) / Kwon, Beomjin (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Cellular metamaterials arouse broad scientific interests due to the combination of host material and structure together to achieve a wide range of physical properties rarely found in nature. Stochastic foam as one subset has been considered as a competitive candidate for versatile applications including heat exchangers, battery electrodes, automotive, catalyst devices, magnetic shielding, etc. For the engineering of the cellular foam architectures, closed-form models that can be used to predict the mechanical and thermal properties of foams are highly desired especially for the recently developed ultralight weight shellular architectures. Herein, for the first time, a novel packing three-dimensional (3D) hollow pentagonal dodecahedron (HPD) model is proposed to simulate the cellular architecture with hollow struts. An electrochemical deposition process is utilized to manufacture the metallic hollow foam architecture. Mechanical and thermal testing of the as-manufactured foams are carried out to compare with the HPD model. Timoshenko beam theory is utilized to verify and explain the derived power coefficient relation. Our HPD model is proved to accurately capture both the topology and the physical properties of hollow stochastic foam. Understanding how the novel HPD model packing helps break the conventional impression that 3D pentagonal topology cannot fulfill the space as a representative volume element. Moreover, the developed HPD model can predict the mechanical and thermal properties of the manufactured hollow metallic foams and elucidating of how the inevitable manufacturing defects affect the physical properties of the hollow metallic foams. Despite of the macro-scale stochastic foam architecture, nano gradient gyroid lattices are studied using Molecular Dynamics (MD) simulation. The simulation result reveals that, unlike homogeneous architecture, gradient gyroid not only shows novel layer-by-layer deformation behavior, but also processes significantly better energy absorption ability. The deformation behavior and energy absorption are predictable and designable, which demonstrate its highly programmable potential.
ContributorsDai, Rui (Author) / Nian, Qiong (Thesis advisor) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Liu, Yongming (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2021
Description
Stereolithography (SLA) is an innovative additive manufacturing technique that has gained immense popularity in recent times due to its ability to produce complex and precise three-dimensional objects. However, the quality of the final product depends on the stability and homogeneity of the photocurable metallic ink used, which is crucial for manufacturing high-quality parts with good surface finish and higher density. To achieve homogeneity in the photocurable metallic resin, the study conducted on optimizing the printing ink for ultrafast layer less fabrication of 3D metal objects investigated the effectiveness of different dispersants such as KH 560, Triton X-100, BYK 2013, BYK 2030, and BYK 111. The use of dispersants plays a vital role in optimizing the ink and enhancing the surface finish and density of the final product. The rheology results showed that the appropriate dispersant has the potential to improve the properties of the printing ink and benefit the integrity of the printed green bodies and their surface finish. By using the optimized suspension, the study was able to fabricate parts with high metallic loading at an ultrafast speed using the Continuous Liquid Interface Production technique. FTIR analysis, sedimentation testing, and rheology study has been carried out which demonstrates the effects of the utilization of various dispersants optimally to improve the homogeneity and manufactured part’s integrity. Power law has been used to understand the viscosity behavior of dispersants in a photocurable ink with copper sulfate keeping the parameters such as shearing rate, stress, and torque intact. The microscopic images of the sintered parts showed high precision and an extremely smooth surface finish, which underscores the technique's potential to produce high-quality 3D metal objects. The solubility of dispersants significantly influenced the structural quality after washing and debinding processes. This study provides valuable information to design photocurable metallic suspensions for metal salts like copper sulfate pentahydrate.
ContributorsVerma, Harsh Pyarelal (Author) / Li, Xiangjia (Thesis advisor) / Nian, Qiong (Committee member) / Xie, Renxuan (Committee member) / Arizona State University (Publisher)
Created2023
Description
Polylactic Acid (PLA), a thermoplastic polymer is well-known for its biocompatibility, making it ideal for the manufacturing of biomedical devices. However, the current applications of PLA are commonly limited by its intrinsic polymer characteristics, such as low modulus, mechanical strength, and thermal conductivity. To enhance these physical properties, a biocompatible nanodiamond enhanced PLA filament has been studied. Thermogravimetric analysis was performed to unveil the composition of nanodiamond in the composite. Four printing parameters: nozzle temperature, layer height, infill pattern and printing speed were considered and the Taguchi L9 orthogonal array was implemented for the design of experiments. Fused deposition modeling (FDM) technique was utilized to 3D print the PLA/Nanodiamond samples by altering the four printing parameters considered and were tested according to the standards for tensile strength, flexural strength, and thermal conductivity. Using the Taguchi optimization approach and analysis of variance (ANOVA), the generated experimental data was used to find the optimum set of printing parameters. Finally, cell studies were performed to demonstrate the biocompatibility of PLA/Nanodiamond. All these results could aid in determining the working ranges for FDM fabrication of PLA/Nanodiamond for biomedical applications.
ContributorsPoornabodha, Nikhitha (Author) / Nian, Qiong (Thesis advisor) / Kang, Wonmo (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2022
Description
This dissertation is focused on the rheology scaling of metal particle reinforced polymermatrix composite made of solid and nanoporous metal powders to enable their
continuous 3D printing at high (>60vol%) metal content. There remained a specific
knowledge gap on how to predict successful extrusion with densely packed metals by
utilizing their suspension melt rheological properties. In the first project, the scaling of
the dynamic viscosity of melt-extrudate filaments made of Polylactic acid (PLA) and
gas-atomized solid NiCu powders was studied as a function of the metal’s volumetric
packing and feedstock pre-mixing strategies and correlated to its extrudability
performance, which fitted well with the Krieger-Dougherty analytical model. 63.4
vol% Filaments were produced by employing solution-mixing strategy to reduce
sintered part porosity and shrinkage. After sintering, the linear shrinkage dropped by
76% compared to the physical mixing. By characterizing metal particle reinforced
polymer matrix composite feedstock via flow-sweep rheology, a distinct extension of
shear-thinning towards high shear rates (i.e. 100 s-1) was observed at high metal content
– a result that was attributed to the improved wall adhesion. In comparison, physically mixed filament failed to sustain more than 10s-1 shear rate proving that they were prone
to wall slippage at a higher shear rate, giving an insight into the onset of extrusion
jamming. In the second project, nanoporous copper made out of electroless chemical
dealloying was utilized as fillers, because of their unique physiochemical properties.
The role of capillary imbibition of polymers into metal nanopores was investigated to
understand their effect on density, zero-shear viscosity, and shear thinning. It was
observed that, although the polymeric fluid’s transient concentration regulates its
wettability, the polymer chain length ultimately dictates its melt rheology, which consequentially facilitates densification of pores during vacuum annealing. Finally, it
was demonstrated that higher imbibition into nanopores leads to extrusion failure due
to a combined effect of volumetric packing increase and nanoconfinement, providing a
deterministic materials design tool to enable continuous 3D printing. The outcome of
this study might be beneficial to integrate nanoporous metals into binder-based 3D
printing technology to fabricate interdigitated battery electrodes and multifunctional 3D
printed electronics.
ContributorsHasib, Amm (Author) / Azeredo, Bruno (Thesis advisor) / Song, Kenan (Thesis advisor) / Nian, Qiong (Committee member) / Kwon, Beomjin (Committee member) / Li, Xiangjia (Committee member) / Arizona State University (Publisher)
Created2022
Description
Fatigue fracture is one of the most common types of mechanical failures seen in structures. Considering that fatigue failures usually initiate on surfaces, it is accepted that surface roughness has a detrimental effect on the fatigue life of components. Irregularities on the surface cause stress concentrations and form nucleation sites for cracks. As surface conditions are not always satisfactory, particularly for additively manufactured components, it is necessary to develop a reliable model for fatigue life estimation considering surface roughness effects and assure structural integrity. This research study focuses on extending a previously developed subcycle fatigue crack growth model to include the effects of surface roughness. Unlike other models that consider surface irregularities as series of cracks, the proposed model is unique in the way that it treats the peaks and valleys of surface texture as a single equivalent notch. First, an equivalent stress concentration factor for the roughness was estimated and introduced into an asymptotic interpolation method for notches. Later, a concept called equivalent initial flaw size was incorporated along with linear elastic fracture mechanics to predict the fatigue life of Ti-6Al-4V alloy with different levels of roughness under uniaxial and multiaxial loading conditions. The predicted results were validated using the available literature data. The developed model can also handle variable amplitude loading conditions, which is suggested for future work.
ContributorsKethamukkala, Kaushik (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2022