Browsing by Author "Feng, Shuo"

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    Knowledge-based bidirectional thermal variable modelling for directed energy deposition additive manufacturing
    (Informa UK Limited, 2024-09-05) Qin, Jian; Taraphdar, Pradeeptta; Sun, Yongle; Wainwright, James; Lai, Wai Jun; Feng, Shuo; Ding, Jialuo; Williams, Stewart
    Directed energy deposition additive manufacturing (DED-AM) has gained significant interest in producing large-scale metallic structural components. In this paper, a knowledge-based machine learning (ML) approach, combining both physics-based simulation and data-driven modelling, is proposed for a study on thermal variables of DED-AM. This approach enables both forward and backward predictions, which breaks down the barriers between the basic process parameters and key process attributes. Process knowledge plays a critical role to enable the prediction and enhance the accuracy in both prediction directions. The proposed ML approach successfully predicted the thermal variables of wire arc based DED-AM for forward modelling and the process parameters for backward modelling, typically within 7% errors. This approach can be further generalised as a powerful modelling tool for design, control, and evaluation of DED-AM processes regarding build geometry and properties, as well as an essential constituent element in a digital twin of a DED-AM system.
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    Revealing internal flow behaviour in arc welding and additive manufacturing of metals
    (Nature Publishing Group, 2018-12-21) Aucott, Lee; Dong, Hongbiao; Mirihanage, Wajira; Atwood, Robert; Kidess, Anton; Gao, Shian; Wen, Shuwen; Marsden, John; Feng, Shuo; Tong, Mingming; Connolley, Thomas; Drakopoulos, Michael; Kleijn, Chris R.; Richardson, Ian M.; Browne, David J.; Mathiesen, Ragnvald H.; Atkinson, Helen
    Internal flow behaviour during melt-pool-based metal manufacturing remains unclear and hinders progression to process optimisation. In this contribution, we present direct time-resolved imaging of melt pool flow dynamics from a high-energy synchrotron radiation experiment. We track internal flow streams during arc welding of steel and measure instantaneous flow velocities ranging from 0.1 m s−1 to 0.5 m s−1. When the temperature-dependent surface tension coefficient is negative, bulk turbulence is the main flow mechanism and the critical velocity for surface turbulence is below the limits identified in previous theoretical studies. When the alloy exhibits a positive temperature-dependent surface tension coefficient, surface turbulence occurs and derisory oxides can be entrapped within the subsequent solid as result of higher flow velocities. The widely used arc welding and the emerging arc additive manufacturing routes can be optimised by controlling internal melt flow through adjusting surface active elements.