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- Creators: Liu, Yongming
Description
The purpose of this honors project is to analyze the difference between different powder separation techniques, and their suitability for my capstone project – ‘Effect of Powder Reuse on DMLS (Direct Metal Laser Sintering) Product Integrity’. Due to the nature of my capstone project, my group needs to characterize foreign contaminants in IN 718 (Ni-based superalloy) powder with a mean diameter around 40um. In order to clearly analyze the contaminants and recycle useful IN 718 powders, powder separation is favorable since the filtered samples will be much easier to characterize rather than inspect all the powders at once under microscope. By conducting literature review, I found that powder separation is commonly used in Geology, and Chemistry department. To screen which combination of techniques could be the best for my project, I have consulted several research specialists, obtained adequate knowledge about powder separation. Accordingly, I will summarize the pros and cons of each method with regard the specific project that I am working on, and further explore the impacts of each method under economical, societal, and environmental considerations. Several powder separation techniques will be discussed in details in the following sections, including water elutriation, settling column, magnetic separation and centrifugation. In addition to these methods, sieving, water tabling and panning will be briefly introduced. After detailed comparison, I found that water elutriation is the most efficient way to purity IN718 powder for reuse purpose, and recovery rate is as high as 70%, which could result in a significant reduction in the manufacturing cost for Honeywell since currently Honeywell only use virgin powders to build parts, and 90% of the leftover powders are discarded.
ContributorsLuo, Zheyu (Author) / Adams, James (Thesis director) / Tasooji, Amaneh (Committee member) / Materials Science and Engineering Program (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
This study aims to provide a foundation for future work on photo-responsive polymer composite materials to be utilized in additive manufacturing processes. The curing rate of 2,2-dimethoxy-2-phenyl-acetophenone (DMPA) in thin (<20 µm) and thick (>2 mm) layers of DMPA and poly(ethylene glycol) diacrylate (PEG-DA) mixtures was assessed for 5.0 w/v% (grams per 100 mL) concentrations of DMPA dissolved in PEG-DA. The polymerization rate and quality of curing was found to decrease as the concentration of DMPA increased beyond 1.0 w/v%; thus, confirming the existence of an optimum photo-initiator concentration for a specific sheet thickness. The optimum photo-initiator concentration for a 3-3.1 mm thick sheet of PEG-DA microstructure was determined to be between 0.3 and 0.38 w/v% DMPA. The addition of 1,6-hexanediol or 1,3-butanediol to the optimum photo-initiator concentrated solution of DMPA and PEG-DA was found to increase the Tg of the samples; however, the samples could not fully cure within 40-50 s, which suggested a decrease in polymerization rate. Lastly, the DMPA photo-initiator does not produce gaseous byproducts and is translucent when fully cured, which makes it attractive for infusion with strengthening materials because quality light penetration is paramount to quick polymerization rates. It is recommended that more trials be conducted to evaluate the mechanical properties of the optimum curing rate for DMPA and PEG-DA microstructures as well as a mechanical property comparison following the addition of either of the two alcohols.
ContributorsPiper, Tyler Irvin (Author) / Green, Green (Thesis director) / Lind, Mary Laura (Committee member) / School of Sustainability (Contributor) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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
Description
Additive manufacturing (AM) has been extensively investigated in recent years to explore its application in a wide range of engineering functionalities, such as mechanical, acoustic, thermal, and electrical properties. The proposed study focuses on the data-driven approach to predict the mechanical properties of additively manufactured metals, specifically Ti-6Al-4V. Extensive data for Ti-6Al-4V using three different Powder Bed Fusion (PBF) additive manufacturing processes: Selective Laser Melting (SLM), Electron Beam Melting (EBM), and Direct Metal Laser Sintering (DMLS) are collected from the open literature. The data is used to develop models to estimate the mechanical properties of Ti-6Al-4V. For this purpose, two models are developed which relate the fabrication process parameters to the static and fatigue properties of the AM Ti-6Al-4V. To identify the behavior of the relationship between the input and output parameters, each of the models is developed on both linear multi-regression analysis and non-linear Artificial Neural Network (ANN) based on Bayesian regularization. Uncertainties associated with the performance prediction and sensitivity with respect to processing parameters are investigated. Extensive sensitivity studies are performed to identify the important factors for future optimal design. Some conclusions and future work are drawn based on the proposed study with investigated material.
ContributorsSharma, Antriksh (Author) / Liu, Yongming (Thesis advisor) / Nian, Qiong (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
Description
Additively Manufactured Thin-wall Inconel 718 specimens commonly find application in heat exchangers and Thermal Protection Systems (TPS) for space vehicles. The wall thicknesses in applications for these components typically range between 0.03-2.5mm. Laser Powder Bed Fusion (PBF) Fatigue standards assume thickness over 5mm and consider Hot Isostatic Pressing (HIP) as conventional heat treatment. This study aims at investigating the dependence of High Cycle Fatigue (HCF) behavior on wall thickness and Hot Isostatic Pressing (HIP) for as-built Additively Manufactured Thin Wall Inconel 718 alloys. To address this aim, high cycle fatigue tests were performed on specimens of seven different thicknesses (0.3mm,0.35mm, 0.5mm, 0.75mm, 1mm, 1.5mm, and 2mm) using a Servohydraulic FatigueTesting Machine. Only half of the specimen underwent HIP, creating data for bothHIP and No-HIP specimens. Upon analyzing the collected data, it was noticed that the specimens that underwent HIP had similar fatigue behavior to that of sheet metal specimens. In addition, it was also noticed that the presence of Porosity in No-HIP specimens makes them more sensitive to changes in stress. A clear decrease in fatigue strength with the decrease in thickness was observed for all specimens.
ContributorsSaxena, Anushree (Author) / Bhate, Dhruv (Thesis advisor) / Liu, Yongming (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2021