数据驱动镍基铸造高温合金设计及复杂铸件精确成形

doi:10.11900/0412.1961.2021.00355

金属学报

2022, Vol. 58

Issue (1): 89-102 DOI: 10.11900/0412.1961.2021.00355

研究论文

本期目录 | 过刊浏览

数据驱动镍基铸造高温合金设计及复杂铸件精确成形

汪东红¹, 孙锋¹^,²(

), 疏达¹^,²(

), 陈晶阳³, 肖程波³, 孙宝德¹^,²

^1. 上海交通大学材料科学与工程学院上海市先进高温材料及其精密成形重点实验室金属基复合材料国家重点实验室上海 200240
^2. 上海交通大学材料基因组联合研究中心上海 200240
^3. 中国航发北京航空材料研究院先进高温结构材料重点实验室北京 100095

Data-Driven Design of Cast Nickel-Based Superalloy and Precision Forming of Complex Castings

WANG Donghong¹, SUN Feng¹^,²(

), SHU Da¹^,²(

), CHEN Jingyang³, XIAO Chengbo³, SUN Baode¹^,²

^1. Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming and State Key Laboratory of Metal Matrix Composites, School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
^2. Materials Genome Initiative Center, Shanghai Jiao Tong University, Shanghai 200240, China
^3. Science and Technology on Advanced High Temperature Structural Materials Laboratory, AECC Beijing Institute of Aeronautical Materials, Beijing 100095, China

引用本文:

汪东红, 孙锋, 疏达, 陈晶阳, 肖程波, 孙宝德. 数据驱动镍基铸造高温合金设计及复杂铸件精确成形[J]. 金属学报, 2022, 58(1): 89-102.
Donghong WANG, Feng SUN, Da SHU, Jingyang CHEN, Chengbo XIAO, Baode SUN. Data-Driven Design of Cast Nickel-Based Superalloy and Precision Forming of Complex Castings[J]. Acta Metall Sin, 2022, 58(1): 89-102.

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摘要:

材料基因组工程与材料智能制备加工技术的发展为航空发动机高温合金关键热端部件的研发与制造提供了新的思路。针对航空发动机涡轮机匣类结构件高温合金材料与铸造成型的需求，开发了高通量并发式的热动力学模拟软件系统，结合镍基铸造高温合金的筛选判据，从520万余种成分组合中筛选并研制了一种新型镍基铸造高温合金，815℃、400 MPa下高温持久性能优于国外Inconel 939高温合金。针对高温合金复杂铸件的精密成型，开展了数据驱动铸件变形全流程集成计算，揭示蜡模注射工艺参数与尺寸映射关系以及凝固变形过程中工艺参数与尺寸精度关联关系，提出了一种基于数据驱动的工艺参数优化方法。建立了基于“模型+算法”的数据驱动的铸造冒口设计方法，结合试验设计和多目标遗传算法，优化了铸造工艺参数，试验验证后铸件工艺出品率提高13.39%。基于数据驱动的成分设计与基于数据模型的工艺设计结合，将加速航空材料与构件的研发与应用。

关键词 ：高通量成分设计, 高温合金, 数据驱动, 智能铸造

Abstract：

The development of material genomics engineering and intelligent material-processing technology provides new ideas for researching, developing, and manufacturing key thermal superalloy components of aeroengines. Based on the demand for superalloy materials and casting processing, a high-throughput dynamic simulation software system was developed. Combined with the screening criteria of nickel-based casting superalloy, a new nickel-based casting superalloy was selected and developed from more than 5.2 million-component combinations. High-temperature durability at 815^oC and 400 MPa is better than foreign Inconel 939 superalloy. For the precision molding of complex superalloy casting, the data-driven process of the casting deformation is integrated, which reveals the correlation between the process parameters and size precision during solidification deformation. Thus, a data-driven process parameter optimization method is proposed herein. A data-driven casting outlet design method based on the model and algorithm, combined with the test design and multi-target genetic algorithm, which optimized the casting process parameters, was established, and the production rate of the casting process increased by 13.39% after the test verification. The combination of data-driven component design and data model-based process design will accelerate the development and application of aviation materials and components.

Key words： high throughput composition design superalloy data driven intelligent casting

收稿日期: 2021-08-23

ZTFLH:

TG146.3

基金资助:国家重大专项项目(J2019-VI-0004-0117);国家自然科学基金项目(51821001);国家重点研发计划项目;先进高温结构材料重点实验室开放基金(6142903200105)

作者简介: 汪东红，男，1984年生，博士

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https://www.ams.org.cn/CN/10.11900/0412.1961.2021.00355 或 https://www.ams.org.cn/CN/Y2022/V58/I1/89

图1 新型镍基铸造高温合金热动力学模拟软件系统框架

图2 典型性质图和特征参量

表1 高通量合金成分计算范围 (mass fraction / %)

图3 基于集成计算材料工程的(ICME)铸造工艺设计

图4 精密铸造中基于数据驱动框架的变形预测模型

表2 用于蜡模尺寸误差仿真的设计变量及其区间

表3 用于凝固变形仿真的设计变量及其范围

图5 基于数据驱动的缩松缺陷与铸造工艺设计框架

表4 用于预测缩松缺陷的设计变量及其区间

图6 母合金铸棒、力学性能试棒以及环套环典型铸件形状与尺寸

表5 筛选出的合金基础成分 (mass fraction / %)

图7 筛选合金与几种典型铸造合金蠕变性能对比(JMatPro模拟结果)

图8 Alloy 1和Alloy 2的SEM像

图9 Alloy 1和Alloy 2的枝晶间共晶形貌，及γ/γ'共晶、MC碳化物的EDS分析

图10 SJTU-1合金典型性能曲线

图11 蜡模注射成型优化结果

图12 蜡模注射成型工艺参数之间的关系矩阵

图13 蜡模注射成型工艺参数之间的二维响应面模型

图14 铸造工艺参数对铸件尺寸误差的贡献度

图15 铸造工艺参数对平均直径和椭圆度的2D关系图谱

图16 输入与平均直径和椭圆度之间的3D关系

图17 工艺参数和结构参数对铸件工艺出品率和安全距离的影响

图18 实际被测样品

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