Matching Items (3)
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- All Subjects: Additive Manufacturing
- Creators: Peralta, Pedro
Description
Solid-state and non-equilibrium processings are of great interest to researchers due to their ability to control and refine bulk and/or surface microstructure of metallic alloys and push them to surpass their conventional properties limit. In this dissertation, solid-state processing i.e., Shear Assisted Processing and Extrusion (ShAPE), and non-equilibrium processes i.e., surface mechanical attrition (SMAT) and additive manufacturing (AM) techniques were used to process the magnesium and aluminum alloys respectively. A synergistic investigation of processing-induced microstructural modification and its effect on corrosion resistance was performed using various ex-situ, quasi in-situ, and in-situ electrochemical, microscopy, and spectroscopy characterization techniques. To evaluate the effect of the same processing condition on a range of microstructures, a variety of magnesium alloys such as AZ31B, Mg-3Si, ZK60, and Pure Mg were processed using a novel solid-state processing method, namely ShAPE. It induced a significant grain refinement, homogenized distribution of second phases, and low residual strain in AZ31B alloy, which contributed toward a noble breakdown potential, stable protective film, and hence better corrosion resistance compared to the parent extruded counterpart. However, with variations in composition, volume fraction, and distribution of second phases with Mg-3Si and ZK60 magnesium alloy an opposite response was inferred indicating a strong dependence of corrosion on underlying microstructure compared to a processing condition. Non-equilibrium processes, i.e. SMAT and AM were utilized to process high-strength 7xxx series aluminum alloys. Continuous high energy impacts of hard balls in room temperature (RT SMAT) and liquid nitrogen (LN2 SMAT) flow environment generated a gradient nanocrystalline surface layer with the dissolution of inherent second phase and precipitation of new phases in aluminum 7075 alloys. RT SMAT showed a reduced anodic dissolution rate and improved film resistance, which was attributed to the thicker and composite oxide layer along with new nanoscale precipitates. Lastly, reactive AM was used to process aluminum 7075 and 7050 alloys which resulted in a refined and textureless microstructure. A reduction in corrosion resistance was observed with precipitation of excessive reactive particles (Ti and B4C) in AM alloys compared to wrought counterparts.
ContributorsBeura, Vikrant Kumar (Author) / Solanki, Kiran N (Thesis advisor) / Peralta, Pedro (Committee member) / Alford, Terry (Committee member) / Ankit, Kumar (Committee member) / Joshi, Vineet V (Committee member) / Arizona State University (Publisher)
Created2022
Description
The relationships between the properties of materials and their microstructures have been a central topic in materials science. The microstructure-property mapping and numerical failure prediction are critical for integrated computational material engineering (ICME). However, the bottleneck of ICME is the lack of a clear understanding of the failure mechanism as well as an efficient computational framework. To resolve these issues, research is performed on developing novel physics-based and data-driven numerical methods to reveal the failure mechanism of materials in microstructure-sensitive applications.
First, to explore the damage mechanism of microstructure-sensitive materials in general loading cases, a nonlocal lattice particle model (LPM) is adopted because of its intrinsic ability to handle the discontinuity. However, the original form of LPM is unsuitable for simulating nonlinear behavior involving tensor calculation. Therefore, a damage-augmented LPM (DLPM) is proposed by introducing the concept of interchangeability and bond/particle-based damage criteria. The proposed DLPM successfully handles the damage accumulation behavior in general material systems under static and fatigue loading cases.
Then, the study is focused on developing an efficient physics-based data-driven computational framework. A data-driven model is proposed to improve the efficiency of a finite element analysis neural network (FEA-Net). The proposed model, i.e., MFEA-Net, aims to learn a more powerful smoother in a multigrid context. The learned smoothers have good generalization properties, and the resulted MFEA-Net has linear computational complexity. The framework has been applied to efficiently predict the thermal and elastic behavior of composites with various microstructural fields. Finally, the fatigue behavior of additively manufactured (AM) Ti64 alloy is analyzed both experimentally and numerically. The fatigue experiments show the fatigue life is related with the contour process parameters, which can result in different pore defects, surface roughness, and grain structures. The fractography and grain structures are closely observed using scanning electron microscope. The sample geometry and defect/crack morphology are characterized through micro computed tomography (CT). After processing the pixel-level CT data, the fatigue crack initiation and growth behavior are numerically simulated using MFEA-Net and DLPM. The experiments and simulation results provided valuable insights in fatigue mechanism of AM Ti64 alloy.
ContributorsMeng, Changyu (Author) / Liu, Yongming (Thesis advisor) / Hoover, Christian (Committee member) / Li, Lin (Committee member) / Peralta, Pedro (Committee member) / Wang, Liping (Committee member) / Arizona State University (Publisher)
Created2023
Description
The design of energy absorbing structures is driven by application specific requirements like the amount of energy to be absorbed, maximum transmitted stress that is permissible, stroke length, and available enclosing space. Cellular structures like foams are commonly leveraged in nature for energy absorption and have also found use in engineering applications. With the possibility of manufacturing complex cellular shapes using additive manufacturing technologies, there is an opportunity to explore new topologies that improve energy absorption performance. This thesis aims to systematically understand the relationships between four key elements: (i) unit cell topology, (ii) material composition, (iii) relative density, and (iv) fields; and energy absorption behavior, and then leverage this understanding to develop, implement and validate a methodology to design the ideal cellular structure energy absorber. After a review of the literature in the domain of additively manufactured cellular materials for energy absorption, results from quasi-static compression of six cellular structures (hexagonal honeycomb, auxetic and Voronoi lattice, and diamond, Gyroid, and Schwarz-P) manufactured out of AlSi10Mg and Nylon-12. These cellular structures were compared to each other in the context of four design-relevant metrics to understand the influence of cell design on the deformation and failure behavior. Three new and revised metrics for energy absorption were proposed to enable more meaningful comparisons and subsequent design selection. Triply Periodic Minimal Surface (TPMS) structures were found to have the most promising overall performance and formed the basis for the numerical investigation of the effect of fields on the energy absorption performance of TPMS structures. A continuum shell-based methodology was developed to analyze the large deformation behavior of field-driven variable thickness TPMS structures and validated against experimental data. A range of analytical and stochastic fields were then evaluated that modified the TPMS structure, some of which were found to be effective in enhancing energy absorption behavior in the structures while retaining the same relative density. Combining findings from studies on the role of cell geometry, composition, relative density, and fields, this thesis concludes with the development of a design framework that can enable the formulation of cellular material energy absorbers with idealized behavior.
ContributorsShinde, Mandar (Author) / Bhate, Dhruv (Thesis advisor) / Peralta, Pedro (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2023