熔模精铸K4169合金复杂蜗壳薄壁结构陷预测与工艺多目标优化

张恒睿, 董一巍, 王海东, 杨磊磊, 廖玉婷

精密成形工程 ›› 2025, Vol. 17 ›› Issue (11) : 47-57.

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精密成形工程 ›› 2025, Vol. 17 ›› Issue (11) : 47-57. DOI: 10.3969/j.issn.1674-6457.2025.11.004
先进材料智能成形技术

熔模精铸K4169合金复杂蜗壳薄壁结构陷预测与工艺多目标优化

  • 张恒睿1, 董一巍1,*, 王海东2, 杨磊磊2, 廖玉婷1
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Defect Prediction and Multi-objective Process Optimization in Investment Casting of K4169 Superalloy Thin-walled Complex Volute Structures

  • ZHANG Hengrui1, DONG Yiwei1,*, WANG Haidong2, YANG Leilei2, LIAO Yuting1
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摘要

目的 解决K4169高温合金复杂蜗壳薄壁结构件熔模铸造中缩孔缩松缺陷难控制、浇注系统体积冗余等问题,为铸件的高质量、低成本制造提供优化方案。方法 依托ProCAST有限元平台开展全流程数值模拟,采用多点S型双铂铑热电偶实测铸造过程中的温度数据,反求铸件与模壳的界面换热系数,提升模拟精度;构建回归模型,基于NSGA-II算法与TOPSIS方法生成帕累托前沿解集,确定最优工艺参数;优化浇注系统结构,调整铸件放置姿态,通过试验验证优化效果,对比模拟与实测缺陷位置、体积及铸件力学性能数据。结果 模拟与实测温度的平均绝对误差控制在±2 ℃以内,均方根误差为2.1 ℃;最优工艺参数如下:浇注温度为1 450 ℃、预热温度为1 050 ℃。结构优化后,缩孔缩松总体积减少63%,浇注系统体积降低29%;实际生产的铸件室温抗拉强度达890 MPa、屈服强度达680 MPa,均满足设计要求,生产合格率提升至80%。结论 界面换热系数模型有效提升了模拟精度,浇注系统与工艺参数的协同优化同时实现了缺陷的控制与材料利用率的提升,在铸造工程中兼具实用性与高效性。

Abstract

The work aims to address issues such as difficult control of shrinkage porosity defects and redundant volume of the gating system in the investment casting of thin-walled complex volute components made of K4169 superalloy, and to provide an optimized scheme for the high-quality and low-cost manufacturing of the castings. A full-process numerical simulation was conducted based on the ProCAST finite element platform. Multi-point S-type double platinum-rhodium thermocouples were used to measure temperature data during the casting process, and the interfacial heat transfer coefficient between the casting and the mold shell was inversely calculated to improve simulation accuracy. A regression model was established, and the Pareto frontier solution set was generated according to the NSGA-II algorithm and the TOPSIS method to determine the optimal process parameters. The structure of the gating system was optimized, the placement posture of the casting was adjusted, and tests were carried out to verify the optimization effect. Data on defect location, volume, and mechanical properties of the casting from simulation and actual measurement were compared. The average absolute error between simulated and measured temperatures was controlled within ±2 ℃, with a root mean square error of 2.1 ℃. The optimal process parameters were determined as a pouring temperature of 1 450 ℃ and a preheating temperature of 1 050 ℃. After structural optimization, verification showed that the total volume of shrinkage porosity decreased by 63%, and the volume of the gating system reduced by 29%. For the castings produced in actual production, the room-temperature tensile strength reached 890 MPa, and the yield strength reached 680 MPa, all meeting the design requirements. The production qualification rate was increased to 80%. In conclusion, the interfacial heat transfer coefficient model effectively improves simulation accuracy. The coordinated optimization of the gating system and process parameters achieves both defect control and improvement of material utilization, and it has both practicality and efficiency in casting engineering. KEY WORDS: superalloy; aviation volute structure; investment casting; numerical simulation; multi-objective process optimization; shrinkage defects

关键词

高温合金 / 航空蜗壳结构 / 熔模铸造 / 数值模拟 / 多目标工艺优化 / 缩孔缩松缺陷

Key words

superalloy / aviation volute structure / investment casting / numerical simulation / multi-objective process optimization / shrinkage defects

引用本文

导出引用
张恒睿, 董一巍, 王海东, 杨磊磊, 廖玉婷. 熔模精铸K4169合金复杂蜗壳薄壁结构陷预测与工艺多目标优化[J]. 精密成形工程. 2025, 17(11): 47-57 https://doi.org/10.3969/j.issn.1674-6457.2025.11.004
ZHANG Hengrui, DONG Yiwei, WANG Haidong, YANG Leilei, LIAO Yuting. Defect Prediction and Multi-objective Process Optimization in Investment Casting of K4169 Superalloy Thin-walled Complex Volute Structures[J]. Journal of Netshape Forming Engineering. 2025, 17(11): 47-57 https://doi.org/10.3969/j.issn.1674-6457.2025.11.004
中图分类号: TG249.5    TB31   

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基金

国家自然科学基金(52475491,51705440); 航空科学基金(20170368001,20230003068002,20240003068001); 华中科技大学智能制造装备与技术全国重点实验室开放基金(IMETKF2024013); 四川省科技计划(2025YFHZ0039)

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