Browsing by Author "Yu, Hang Z."

Now showing 1 - 6 of 6
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    Additive friction stir deposition: a deformation processing route to metal additive manufacturing
    Yu, Hang Z.; Mishra, Rajiv S. (2021-02-01)
    As the forging counterpart of fusion-based additive processes, additive friction stir deposition offers a solid-state deformation processing route to metal additive manufacturing, in which every voxel of the feed material undergoes severe plastic deformation at elevated temperatures. In this perspective article, we outline its key advantages, e.g. rendering fully-dense material in the as-printed state with fine, equiaxed microstructures, identify its niche engineering uses, and point out future research needs in process physics and materials innovation. We argue that additive friction stir deposition will evolve into a major additive manufacturing solution for industries that require high load-bearing capacity with minimal post-processing.
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    Additive Friction Stir-Enabled Solid-State Additive Manufacturing for the Repair of 7075 Aluminum Alloy
    Griffiths, R. Joey; Petersen, Dylan T.; Garcia, David; Yu, Hang Z. (MDPI, 2019-08-23)
    The repair of high strength, high performance 7075 aluminum alloy is essential for a broad range of aerospace and defense applications. However, it is challenging to implement it using traditional fusion welding-based approaches, owing to hot cracking and void formation during solidification. Here, the use of an emerging solid-state additive manufacturing technology, additive friction stir deposition, is explored for the repair of volume damages such as through -holes and grooves in 7075 aluminum alloy. Three repair experiments have been conducted: double through-hole filling, single through-hole filling, and long, wide-groove filling. In all experiments, additive friction stir deposition proves to be effective at filling the entire volume. Additionally, sufficient mixing between the deposited material and the side wall of the feature is always observed in the upper portions of the repair. Poor mixing and inadequate repair quality have been observed in deeper portions of the filling in some scenarios. Based on these observations, the advantages and disadvantages of using additive friction stir deposition for repairing volume damages are discussed. High quality and highly flexible repairs are expected with systematic optimization work on process control and repair strategy development in the future.
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    In situ investigation of stress-induced martensitic transformation in granular shape memory ceramic packings
    Rauch, Hunter A.; Chen, Yan; An, Ke; Yu, Hang Z. (2019-04-15)
    Stress-induced martensitic transformation can occur in granular shape memory materials when individual particles experience high stresses and transform from a high-symmetry austenite phase to a low symmetry martensite phase. This involves a highly heterogeneous distribution of the driving force and very low mechanical constraint for martensite nucleation, so the transformation behavior can be dramatically different from the well-documented case of monolithic solids. In this work, we investigate the stress-induced martensitic transformation in granular shape memory ceramic packings, which consist of single-crystal micro-particles of ZrO2-12 at%CeO2 and ZrO2-15 at%CeO2. Through in situ neutron diffraction, we study how the phase fraction, lattice strain, and integral peak broadness evolve during external loading, unloading, and subsequent heating. Several peculiar features are discovered, including (i) a continuous mode of transformation with a wide range of transformation loads, (ii) co-evolution of the packing structure, contact deformation, and martensitic transformation, and (iii) a strong correlation between the peak broadening and the transformed phase fraction. In addition, we show the first direct evidence of reversible stress-induced martensitic transformation in granular materials. We finally discuss the mechanism for martensite nucleation and growth in granular packings and show how that leads to the observed transformation characteristics.
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    In situ melt pool measurements for laser powder bed fusion using multi sensing and correlation analysis
    Wang, Rongxuan; Garcia, David; Kamath, Rakesh R.; Dou, Chaoran; Ma, Xiaohan; Shen, Bo; Choo, Hahn; Fezzaa, Kamel; Yu, Hang Z.; Kong, Zhenyu (James) (Nature Portfolio, 2022-08-12)
    Laser powder bed fusion is a promising technology for local deposition and microstructure control, but it suffers from defects such as delamination and porosity due to the lack of understanding of melt pool dynamics. To study the fundamental behavior of the melt pool, both geometric and thermal sensing with high spatial and temporal resolutions are necessary. This work applies and integrates three advanced sensing technologies: synchrotron X-ray imaging, high-speed IR camera, and high-spatial-resolution IR camera to characterize the evolution of the melt pool shape, keyhole, vapor plume, and thermal evolution in Ti-6Al-4V and 410 stainless steel spot melt cases. Aside from presenting the sensing capability, this paper develops an effective algorithm for high-speed X-ray imaging data to identify melt pool geometries accurately. Preprocessing methods are also implemented for the IR data to estimate the emissivity value and extrapolate the saturated pixels. Quantifications on boundary velocities, melt pool dimensions, thermal gradients, and cooling rates are performed, enabling future comprehensive melt pool dynamics and microstructure analysis. The study discovers a strong correlation between the thermal and X-ray data, demonstrating the feasibility of using relatively cheap IR cameras to predict features that currently can only be captured using costly synchrotron X-ray imaging. Such correlation can be used for future thermal-based melt pool control and model validation.
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    Physics-informed neural network for phase imaging based on transport of intensity equation
    Wu, Xiaofeng; Wu, Ziling; Shanmugavel, Sibi Chakravarthy; Yu, Hang Z.; Zhu, Yunhui (Optica Publishing Group, 2022-11)
    Non-interferometric quantitative phase imaging based on Transport of Intensity Equation (T1E) has been widely used in bio-medical imaging. However, analytic TIE phase retrieval is prone to low-spatial frequency noise amplification, which is caused by the iliposedness of inversion at the origin of the spectrum. There are also retrieval ambiguities resulting from the lack of sensitivity to the curl component of the Poynting vector occurring with strong absorption. Here, we establish a physics-informed neural network (PINN) to address these issues, by integrating the forward and inverse physics models into a cascaded deep neural network. We demonstrate that the proposed PINN is efficiently trained using a small set of sample data, enabling the conversion of noise-corrupted 2-shot TIE phase retrievals to high quality phase images under partially coherent LED illumination. The efficacy of the proposed approach is demonstrated by both simulation using a standard image database and experiment using human buccal epitehlial cells. In particular, high image quality (SSIM = 0.919) is achieved experimentally using a reduced size of labeled data (140 image pairs). We discuss the robustness of the proposed approach against insufficient training data, and demonstrate that the parallel architecture of PINN is efficient for transfer learning.
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    Towards underwater additive manufacturing via additive friction stir deposition
    Griffiths, R. Joey; Gotawala, Nikhil; Hahn, Greg D.; Garcia, David; Yu, Hang Z. (Elsevier, 2022-11)
    Given the challenges in feed material supply and quality control, metal additive manufacturing has rarely been implemented in austere environments, especially underwater. This paper explores the underwater operation potential of an emerging solid-state additive technology: additive friction stir deposition, wherein material feeding and bonding are enabled by mechanical forces with minimal influences from water. It is demonstrated that additive friction stir deposition of 304 stainless steel can be successfully performed with the print head and substrate immersed in water. High temperature is reached in the deposition zone (>60% melting temperature); the material deposition behavior is similar to that in typical open-air operation. The as-deposited material is fully-dense, having fewer annealing twins and a substantially smaller grain size than the feed material (4.98 lm vs. 31.44 lm). Such microstructural changes stem from dynamic recrystallization caused by the large strain and high temperature introduced during deposition. In addition to grain refinement, small equiaxed dispersoids (-2-3 lm or less) are formed and evenly distributed in the austenite steel matrix. Rich in Cr, Mn, and O, these particles likely result from the reaction between the elements in stainless steel and water at elevated temperatures. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).