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  • Open Access

    PROCEEDINGS

    Multi-Scale Microstructure Manipulation of an Additively Manufactured CoCrNi Medium Entropy Alloy for Superior Mechanical Properties and Tunable Mechanical Anisotropy

    Chenze Li1, Manish Jain1,2, Qian Liu1, Zhuohan Cao1, Michael Ferry3, Jamie J. Kruzic1, Bernd Gludovatz1, Xiaopeng Li1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.011290

    Abstract Laser powder bed fusion (LPBF) additive manufacturing (AM) technology has become a versatile tool for producing new microstructures in metal components, offering novel mechanical properties for different applications. In this work, enhanced ductility (~55% elongation) and tunable mechanical anisotropy (ratio of ductility along vertical to horizontal orientation from ~0.2 to ~1) were achieved for a CoCrNi medium entropy alloy (MEA) by multi-scale synergistic microstructure manipulation (i.e., melt pool boundary, grain morphology and crystallographic texture) through adjusting key LPBF processing parameters (e.g., laser power and scan speed). By increasing the volumetric energy density (VED) from 68.3… More >

  • Open Access

    PROCEEDINGS

    Adaptive Quality Enhancement in Robotic Laser-Directed Energy Deposition Through Melt Pool Simulation

    Jungyeon Kim1, Lequn Chen1, Seung Ki Moon1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012511

    Abstract Robotic Laser-Directed Energy Deposition (L-DED) offers significant advantages in terms of workplace size and kinematic flexibility for part fabrication. However, its potential is hindered by challenges such as toolpath precision and speed inconsistency compared to traditional CNC machines. These limitations critically affect melt pool dynamics, temperature consistency, and ultimately, the geometric integrity of fabricated parts, areas that are still not thoroughly understood or quantified.
    This preliminary research aims to investigate the impact of these inaccuracies on melt pool morphology and part quality, utilizing in-situ collected speed/position data with a digital twin model, notably the Eagar-Tsai… More >

  • Open Access

    PROCEEDINGS

    Multi-Modality In-Situ Monitoring Big Data Mining for Enhanced Insight into the Laser Powder Bed Fusion Process, Structure, and Properties

    Xiayun Zhao1,*, Haolin Zhang1, Md Jahangir Alam1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.2, pp. 1-2, 2024, DOI:10.32604/icces.2024.011479

    Abstract Laser powder bed fusion (LPBF) is one predominant additive manufacturing (AM) technology for producing metallic parts with sophisticated designs that can find numerous applications in critical industries such as aerospace. To achieve precise, resilient, and intelligent LPBF, a comprehensive understanding of the dynamic processes and material responses within the actual conditions of LPBF-based AM is essential. However, obtaining such insights is challenging due to the intricate interactions among the laser, powder, part layers, and gas flow, among other factors. Multimodal in-situ monitoring is desired to visualize diverse process signatures, allowing for the direct and thorough… More >

  • Open Access

    PROCEEDINGS

    In-Situ Monitoring of Interplay Between Melt Pool, Spatter and Vapor in Laser Powder Bed Fusion Additive Manufacturing

    Xin Lin1,2,3, Kunpeng Zhu1,2,3,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012499

    Abstract This paper reveals the interplay mechanism between melt pool, spattering and vapors, aiming to further improve the forming quality through in-situ monitoring with a CMOS camera. A Residual Network based on Convolutional Block Attention Module and Focal loss function is proposed to extract multi-scale features of single tracks and learn about their behavior changes. A t-SNE clustering analysis is utilized to analysis a large amount of time sequence data on the melt pool by collecting the schlieren photographs. It is found that patterns of unstable melt pool changing corelate to the defects in single tracks, More >

  • Open Access

    ARTICLE

    Prediction of Melt Pool Dimension and Residual Stress Evolution with Thermodynamically-Consistent Phase Field and Consolidation Models during Re-Melting Process of SLM

    Kang-Hyun Lee1, Gun Jin Yun1,2,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 87-112, 2021, DOI:10.32604/cmc.2020.012688 - 30 October 2020

    Abstract Re-melting process has been utilized to mitigate the residual stress level in the selective laser melting (SLM) process in recent years. However, the complex consolidation mechanism of powder and the different material behavior after the first laser melting hinder the direct implementation of the re-melting process. In this work, the effects of re-melting on the temperature and residual stress evolution in the SLM process are investigated using a thermo-mechanically coupled finite element model. The degree of consolidation is incorporated in the energy balance equation based on the thermodynamically-consistent phase-field approach. The drastic change of material… More >

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