{"title":"动态再结晶随机蜂窝自动机有限元模型的网格敏感性研究","authors":"M. Sitko","doi":"10.21741/9781644903131-250","DOIUrl":null,"url":null,"abstract":"Abstract. Predicting microstructure morphology evolution under hot forming conditions and determining final material properties are essential for optimizing metal-forming processes. Cellular Automata (CA) is a widely employed full-field method for modeling microstructure morphology changes during various metal-forming processes. However, at higher temperatures and under conditions of substantial microstructure evolution, the CA method encounters limitations related to computational domain geometry changes. The use of random cellular automata (RCA) offers a more realistic representation of this phenomenon, although it requires additional effort in algorithm optimization for acceptable execution times. This paper contributes to an overarching research effort focused on developing a discontinuous dynamic recrystallization model (DRX) by directly incorporating RCA into the finite element (FE) framework. Different mesh sizes and their impact on the quality of the results are analyzed, and the minimum number of elements that do not degrade the results in the CA model are selected. The investigation aims to enhance the practicality of the proposed model, striking a balance between realistic microstructure representation and computational efficiency.","PeriodicalId":515987,"journal":{"name":"Materials Research Proceedings","volume":"138 6","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Mesh sensitivity study in the random cellular automata finite element model of dynamic recrystallization\",\"authors\":\"M. Sitko\",\"doi\":\"10.21741/9781644903131-250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract. Predicting microstructure morphology evolution under hot forming conditions and determining final material properties are essential for optimizing metal-forming processes. Cellular Automata (CA) is a widely employed full-field method for modeling microstructure morphology changes during various metal-forming processes. However, at higher temperatures and under conditions of substantial microstructure evolution, the CA method encounters limitations related to computational domain geometry changes. The use of random cellular automata (RCA) offers a more realistic representation of this phenomenon, although it requires additional effort in algorithm optimization for acceptable execution times. This paper contributes to an overarching research effort focused on developing a discontinuous dynamic recrystallization model (DRX) by directly incorporating RCA into the finite element (FE) framework. Different mesh sizes and their impact on the quality of the results are analyzed, and the minimum number of elements that do not degrade the results in the CA model are selected. The investigation aims to enhance the practicality of the proposed model, striking a balance between realistic microstructure representation and computational efficiency.\",\"PeriodicalId\":515987,\"journal\":{\"name\":\"Materials Research Proceedings\",\"volume\":\"138 6\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials Research Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21741/9781644903131-250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials Research Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21741/9781644903131-250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
摘要。预测热成形条件下的微观结构形态演变并确定最终材料性能对于优化金属成形工艺至关重要。细胞自动机(CA)是一种广泛应用的全场方法,用于模拟各种金属成型过程中的微观结构形态变化。然而,在温度较高和微观结构发生重大演变的条件下,CA 方法会遇到与计算域几何形状变化有关的限制。使用随机蜂窝自动机 (RCA) 可以更真实地反映这种现象,但需要额外的算法优化工作,以获得可接受的执行时间。本文通过直接将 RCA 纳入有限元(FE)框架,为开发非连续动态再结晶模型(DRX)的总体研究工作做出了贡献。本文分析了不同的网格尺寸及其对结果质量的影响,并选择了不会降低 CA 模型结果的最小元素数量。该研究旨在提高拟议模型的实用性,在真实的微观结构表示和计算效率之间取得平衡。
Mesh sensitivity study in the random cellular automata finite element model of dynamic recrystallization
Abstract. Predicting microstructure morphology evolution under hot forming conditions and determining final material properties are essential for optimizing metal-forming processes. Cellular Automata (CA) is a widely employed full-field method for modeling microstructure morphology changes during various metal-forming processes. However, at higher temperatures and under conditions of substantial microstructure evolution, the CA method encounters limitations related to computational domain geometry changes. The use of random cellular automata (RCA) offers a more realistic representation of this phenomenon, although it requires additional effort in algorithm optimization for acceptable execution times. This paper contributes to an overarching research effort focused on developing a discontinuous dynamic recrystallization model (DRX) by directly incorporating RCA into the finite element (FE) framework. Different mesh sizes and their impact on the quality of the results are analyzed, and the minimum number of elements that do not degrade the results in the CA model are selected. The investigation aims to enhance the practicality of the proposed model, striking a balance between realistic microstructure representation and computational efficiency.