对于海恩斯282的老化热处理设计,采用高通量实验和可解释的机器学习进行了电线料添加剂制造
Xin Wang1, Luis Fernando Ladinos Pizano1, Soumya Sridar1
1Physical Metallurgy and Materials Design Laboratory, Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Science and technology of advanced materials
|May 31, 2024
概括
研究人员优化了电线料增材制造 (WFAM) 超级合金的热处理方法. 机器学习为海恩斯282发现了新的老化条件,提高了与造材料匹配的产量强度.
科学领域:
- 材料科学 材料科学 材料科学
- 金工业是金工业的一个方面.
- 增材制造 增材制造 增材制造
背景情况:
- 由于热循环,超级合金的线添加制造 (WFAM) 会产生复杂的微观结构.
- 优化后热处理对于实现AM超级合金所需的机械性能至关重要.
研究的目的:
- 开发一种有效的方法来设计WFAM海恩斯282超级合金的热处理.
- 为了确定影响衰老过程中增强的关键微观结构特征.
主要方法:
- 这是一种混合方法,结合了高通量实验,降水模拟和机器学习.
- 分析微观结构特征,如马素 (γ') 半径,体积分数和矩阵组成.
- 对新设计的老化条件进行实验验证.
主要成果:
- 玛素 (γ') 半径被确定为加强海恩斯282.2的最关键的微结构特征.
- 使用机器学习模型发现了新的老化条件 (770°C50小时,730°C200小时).
- 优化的热处理成功地提高了WFAM海恩斯282的率强度,达到与造对应品相当的水平.
结论:
- 开发的混合方法使AM超级合金的高效和有效的热处理设计成为可能.
- 这种方法显著提高了生产高性能AM合金的潜力.
- 根据关键的微观结构特征优化老化条件是释放WFAM超级合金全部潜力的关键.
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