X-ray Computed Tomography and Digital Volume Correlation Investigation of Defect Evolution and Strain Localization in Additively Manufactured 316L SS Tensile Coupons
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Miers, John Carter↗
Engineering topics
Saldana, Christopher J.
Publications and source records attributed to Saldana, Christopher J..
High throughput structure–property relationship for additively manufactured 316L/IN625 alloy mixtures leveraging 2-step Bayesian estimation
While the fabrication of graded materials by directed energy deposition (DED) has led to accelerated materials discovery, the ability to rapidly explore sufficiently large material composition spaces is limited due to the time-intensive nature of conventional materials characterization techniques. The present study investigates the viability of small punch test (SPT) protocols for rapidly evaluating DED-fabricated alloy mixtures of stainless steel 316L (316L) and Inconel 625 (IN625). The SPT protocols evaluated in this study include both the recently established two-step Bayesian estimation framework as well as the empirical relationships established in prior literature. It is shown that these protocols are capable of reliably and quantitatively tracking the changes in the mechanical properties of the alloy mixtures studied. Enhancement of mechanical properties was observed with the addition of IN625 to 316L, which is attributed to the austenite stabilization in the matrix and the formation of fine δ - Ni3Nb precipitates. It is shown that CALPHAD-based Scheil model simulations predicted the formation of different precipitate phases for each composition. The novel protocols presented in this paper open new avenues for high throughput material explorations for additive manufacturing.
2-step Bayesian estimation↗
ON PROCESS STABILITY IN WAAM-CMT OF ALUMINUM ALLOYS
Wire-arc additive manufacturing (WAAM) has become a cost-efficient metal additive manufacturing process. However, depositing aluminum with WAAM is challenging due to its sensitivity to heat input (linear energy density), which can cause undesirable surface topology waviness if not controlled. Thus, a process window is needed that can produce stable geometry and deposition conditions while minimizing production times. In this study, 5183 aluminum alloy wire is used to deposit 10-layer walls with varying wire feed speeds (WFS) and traverse speeds (TS) (at a constant WFS/TS ratio) and varying interpass temperature (IPT). In-situ process data consisting of optical contact-tip-workpiece-distance (CTWD) and current/voltage measurements are collected to determine process condition stability throughout the build. Part geometry is measured using a 3D scanner and build porosity is characterized via digital X-ray. A process window is identified that produces stable surface topology and process conditions at a minimal production time.
aluminum alloy↗
Porosity Determination and Classification of Laser Powder Bed Fusion AlSi10Mg Dogbones Using Machine Learning [Slides]
Angular pores (lack of fusion) pores are more detrimental to the health of the part due to induced stress concentrations. Three types of porosity found in AM parts: keyhole porosity, gas porosity, and lack of fusion porosity. In this research, we address the question, "Which machine learning and/or machine vision techniques work best to segment porosity and determine the type of porosity observed in the sample?"
42 ENGINEERING↗
Understanding the role of segmentation on process-structure–property predictions made via machine learning
Here, the present study investigated the effect of porosity surface determination methods on performance of machine learning models used to predict the tensile properties of AlSi10Mg processed by laser powder bed fusion from micro-computed tomography data. Machine learning models applied in this work include support vector machines, neural networks, decision trees, and Bayesian classifiers. The effects of isosurface thresholding and local gradient approaches for porosity segmentation, as well as image filtering schemes, on model precision were evaluated for samples produced under differing levels of global energy density.
36 MATERIALS SCIENCE↗
Initial Process Planning of a Hybrid Multi-Tasking Platform
Abstract Applications of hybrid technology are expanding from refurbishment and repair to low quantity, specialty part production, which are staple characteristics in medical implant, energy, and aerospace industry sectors, among others. This expansion has led to the development of the Mazak VC-500A/5X AM HWD, a wire fed laser cladding unit equipped with a standard 5 axis CNC. This unit is capable of building near net geometry of complex medium to large parts within a profitable timeframe, due to its comparatively high rate of deposition to that of a powder fed hybrid system. In this study, deposition and machining capabilities of the VC-500A/5X AM HWD are assessed through the production of three different test geometries by different process plans. Production of these test geometries is supported by an open loop sensor package primarily for monitoring machine health, data collection, and machine operator aid. The viability of extended deposition followed by machining is evaluated against a more cyclical strategy of reoccurring deposition and machining operations. Lastly, common defects in as-built geometries are evaluated and addressed through revisions to original process plans and toolpaths, indicating the need for continued innovation in hybrid manufacturing specific CAM/CAD software, as well as closed loop machine monitoring and quality control.
DeWitte, Lisa N.↗