通过反分析优化铬镍铁合金 718 直接金属沉积中的烧结参数

Mahmoud Afshari, M. Khandaei, Reza Shoja Razavi, Seyed Masoud Barekat
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摘要

目的输送到零件表面的净功率(即实际热通量)是激光熔化过程中的一个关键参数,其精确控制对数值求解有很大影响。本文研究了激光增材制造参数(包括激光功率、扫描速度和粉末喷射率)对热效率、传递到零件的净功率以及粉末流动导致的功率损耗的影响。设计/方法/途径采用响应面法,使用 k 型热电偶测量激光沉积 Inconel 718 的激光净功率。利用热电偶获得的温度历史记录,通过反分析方法计算出净功率。结果表明,在激光功率为 400 W、扫描速度为 2 mm/s、粉末注射速率为 200 mg/s 的条件下,热效率、零件功率和功率损耗可以同时得到优化。微观结构分析表明,在最佳参数条件下形成了无微观结构缺陷的高质量样品。此外,最佳样品的主枝晶臂间距高于其他样品:利用反分析法预测 Inconel 718 超合金激光金属沉积过程中的热效率和功率损耗。找到 Inconel 718 超合金激光金属沉积过程中热效率、表面功率和功率损耗的最佳值。研究激光金属沉积过程中激光功率、粉末注入率和扫描速度对 Inconel 718 超合金热效率和功率损耗的影响。
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Sintering parameter optimization by inverse analysis in direct metal deposition of Inconel 718
Purpose The net power delivered to the surface of parts (i.e. the actual heat flux) is a key parameter in the laser melting process and its exact control has a great impact on the numerical solutions. In this paper, the impact of laser additive manufacturing parameters including laser power, scanning speed and powder injection rate on thermal efficiency, net power delivered to the part and power loss due to powder flow has been investigated. Design/methodology/approach The response surface method was applied to measure the net laser power in laser deposited Inconel 718 using k-type thermocouples. The temperature history obtained by thermocouples was used to calculate the net power delivered by inverse analysis method. The applied model is Rosenthal's optimized model, in which all the thermal properties of the material are considered to vary with temperature. Findings The results indicated that the thermal efficiency, power delivered to the part and power loss can be optimized simultaneously at laser power of 400 W, scanning speed of 2 mm/s and powder injection rate of 200 mg/s. The microstructure analysis indicated that a high-quality sample without microstructural defects was formed under optimal condition of parameters. Moreover, the primary dendrite arm spacing for the optimal sample was higher than that obtained for other samples. Originality/value The novelty of this research summarized as follows: Prediction of the thermal efficiency and power loss during the laser metal deposition of Inconel 718 superalloy using the inverse analysis. Finding the optimal values of thermal efficiency, power delivered to the surface and power loss in the laser metal deposition of Inconel 718 superalloy. Investigating the effect of laser power, powder injection rate and scanning speed on the thermal efficiency and power loss of Inconel 718 superalloy during the laser metal deposition.
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Extreme roughness reduction and ultrafine quality of innovative dual function material extrusion 3D printer Design for additive manufacturing of topology-optimized structures based on deep learning and transfer learning Sintering parameter optimization by inverse analysis in direct metal deposition of Inconel 718 Temperature and strain rate-dependent compression properties of 3D-printed PLA: an experimental and modeling analysis Mapping and prospective of additive manufacturing in the context of Industry 4.0 and 5.0
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