使用混合优化算法优化模具轮廓,精确控制聚合物溶液中的挤出膨胀

IF 2.7 2区 工程技术 Q2 MECHANICS Journal of Non-Newtonian Fluid Mechanics Pub Date : 2024-06-04 DOI:10.1016/j.jnnfm.2024.105277
Alireza Maddah, Azadeh Jafari
{"title":"使用混合优化算法优化模具轮廓,精确控制聚合物溶液中的挤出膨胀","authors":"Alireza Maddah,&nbsp;Azadeh Jafari","doi":"10.1016/j.jnnfm.2024.105277","DOIUrl":null,"url":null,"abstract":"<div><p>In recent years, many researchers have focused on improving the die design process for polymer extrusion. This study proposes the development of an efficient and robust numerical approach to improve the die-designing process of polymer melts using the Giesekus model. The proposed technique uses a hybrid optimization algorithm to systematically minimize an objective function to achieve the desired extrudate shape. First, we examine the proposed objective function for the 2D axisymmetric test case using the Golden Section optimization algorithm to obtain a circular extrudate of high-density polyethylene (HDPE) with the desired radius at moderate Weissenberg numbers from 1 to 3.75. To provide more insights into the viscoelastic nature of the problem, the optimization was repeated for a viscoelastic fluid with a higher viscosity ratio and a lower mobility factor at very high Weissenberg numbers, specifically 45, 60, 75, and 90. The proposed approach performs quite well across a broad range of Weissenberg numbers. Subsequently, a hybrid optimization algorithm that combines Nelder-Mead and Bayesian optimization algorithms is employed to achieve the desired extrudate shape for various extrudate profiles in 3D cases, including rectangular and square cross-sections, at a Weissenberg number of one. To gain additional insights into the viscoelastic nature of the problem, optimization was conducted for the rectangular extrudate with a 2:1 aspect ratio at higher Weissenberg numbers, i.e. Weissenberg number from 1 to 2.6. The results of the three-dimensional case studies indicate that both the Nelder-Mead and Bayesian optimization algorithms are efficient and robust, converging relatively quickly in all cases studied. The Nelder-Mead algorithm appears to be more robust, exhibiting fewer oscillations when reaching the optimum point. On the other hand, the Bayesian optimization algorithm can reach the global optimum point at a computational cost comparable to Nelder-Mead, while achieving greater accuracy. In conclusion, these findings indicates that using this hybrid optimization algorithm in the polymer extrusion die-designing process can provide a high level of efficiency and robustness.</p></div>","PeriodicalId":54782,"journal":{"name":"Journal of Non-Newtonian Fluid Mechanics","volume":"330 ","pages":"Article 105277"},"PeriodicalIF":2.7000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing die profiles using a hybrid optimization algorithm for the precise control of extrudate swell in polymer solutions\",\"authors\":\"Alireza Maddah,&nbsp;Azadeh Jafari\",\"doi\":\"10.1016/j.jnnfm.2024.105277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In recent years, many researchers have focused on improving the die design process for polymer extrusion. This study proposes the development of an efficient and robust numerical approach to improve the die-designing process of polymer melts using the Giesekus model. The proposed technique uses a hybrid optimization algorithm to systematically minimize an objective function to achieve the desired extrudate shape. First, we examine the proposed objective function for the 2D axisymmetric test case using the Golden Section optimization algorithm to obtain a circular extrudate of high-density polyethylene (HDPE) with the desired radius at moderate Weissenberg numbers from 1 to 3.75. To provide more insights into the viscoelastic nature of the problem, the optimization was repeated for a viscoelastic fluid with a higher viscosity ratio and a lower mobility factor at very high Weissenberg numbers, specifically 45, 60, 75, and 90. The proposed approach performs quite well across a broad range of Weissenberg numbers. Subsequently, a hybrid optimization algorithm that combines Nelder-Mead and Bayesian optimization algorithms is employed to achieve the desired extrudate shape for various extrudate profiles in 3D cases, including rectangular and square cross-sections, at a Weissenberg number of one. To gain additional insights into the viscoelastic nature of the problem, optimization was conducted for the rectangular extrudate with a 2:1 aspect ratio at higher Weissenberg numbers, i.e. Weissenberg number from 1 to 2.6. The results of the three-dimensional case studies indicate that both the Nelder-Mead and Bayesian optimization algorithms are efficient and robust, converging relatively quickly in all cases studied. The Nelder-Mead algorithm appears to be more robust, exhibiting fewer oscillations when reaching the optimum point. On the other hand, the Bayesian optimization algorithm can reach the global optimum point at a computational cost comparable to Nelder-Mead, while achieving greater accuracy. In conclusion, these findings indicates that using this hybrid optimization algorithm in the polymer extrusion die-designing process can provide a high level of efficiency and robustness.</p></div>\",\"PeriodicalId\":54782,\"journal\":{\"name\":\"Journal of Non-Newtonian Fluid Mechanics\",\"volume\":\"330 \",\"pages\":\"Article 105277\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Non-Newtonian Fluid Mechanics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0377025724000934\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MECHANICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Non-Newtonian Fluid Mechanics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0377025724000934","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MECHANICS","Score":null,"Total":0}
引用次数: 0

摘要

近年来,许多研究人员致力于改进聚合物挤出的模具设计过程。本研究提出开发一种高效、稳健的数值方法,利用 Giesekus 模型改进聚合物熔体的模具设计过程。所提出的技术采用混合优化算法,系统地最小化目标函数,以实现所需的挤出物形状。首先,我们使用黄金分割优化算法对二维轴对称测试案例中的目标函数进行了检验,以获得具有所需半径的高密度聚乙烯(HDPE)圆形挤出物,魏森伯格数在 1 到 3.75 之间。为了更深入地了解问题的粘弹性本质,我们对粘弹性流体进行了重复优化,该流体具有较高的粘度比和较低的流动因子,魏森伯格数非常高,具体为 45、60、75 和 90。所提出的方法在很宽的魏森伯格数范围内都表现良好。随后,在魏森伯格数为 1 的三维情况下,采用了一种混合优化算法,该算法结合了内尔德-梅德算法和贝叶斯优化算法,以实现各种挤出物轮廓所需的挤出物形状,包括矩形和正方形横截面。为了进一步深入了解问题的粘弹性本质,在较高的魏森伯格数(即魏森伯格数从 1 到 2.6)条件下,对长宽比为 2:1 的矩形挤出物进行了优化。三维案例研究的结果表明,Nelder-Mead 算法和贝叶斯优化算法都很高效、稳健,在所有研究案例中收敛都相对较快。Nelder-Mead 算法似乎更稳健,在达到最佳点时表现出较少的振荡。另一方面,贝叶斯优化算法能以与 Nelder-Mead 算法相当的计算成本达到全局最优点,同时获得更高的精度。总之,这些研究结果表明,在聚合物挤出模具设计过程中使用这种混合优化算法可以提供较高的效率和稳健性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Optimizing die profiles using a hybrid optimization algorithm for the precise control of extrudate swell in polymer solutions

In recent years, many researchers have focused on improving the die design process for polymer extrusion. This study proposes the development of an efficient and robust numerical approach to improve the die-designing process of polymer melts using the Giesekus model. The proposed technique uses a hybrid optimization algorithm to systematically minimize an objective function to achieve the desired extrudate shape. First, we examine the proposed objective function for the 2D axisymmetric test case using the Golden Section optimization algorithm to obtain a circular extrudate of high-density polyethylene (HDPE) with the desired radius at moderate Weissenberg numbers from 1 to 3.75. To provide more insights into the viscoelastic nature of the problem, the optimization was repeated for a viscoelastic fluid with a higher viscosity ratio and a lower mobility factor at very high Weissenberg numbers, specifically 45, 60, 75, and 90. The proposed approach performs quite well across a broad range of Weissenberg numbers. Subsequently, a hybrid optimization algorithm that combines Nelder-Mead and Bayesian optimization algorithms is employed to achieve the desired extrudate shape for various extrudate profiles in 3D cases, including rectangular and square cross-sections, at a Weissenberg number of one. To gain additional insights into the viscoelastic nature of the problem, optimization was conducted for the rectangular extrudate with a 2:1 aspect ratio at higher Weissenberg numbers, i.e. Weissenberg number from 1 to 2.6. The results of the three-dimensional case studies indicate that both the Nelder-Mead and Bayesian optimization algorithms are efficient and robust, converging relatively quickly in all cases studied. The Nelder-Mead algorithm appears to be more robust, exhibiting fewer oscillations when reaching the optimum point. On the other hand, the Bayesian optimization algorithm can reach the global optimum point at a computational cost comparable to Nelder-Mead, while achieving greater accuracy. In conclusion, these findings indicates that using this hybrid optimization algorithm in the polymer extrusion die-designing process can provide a high level of efficiency and robustness.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
5.00
自引率
19.40%
发文量
109
审稿时长
61 days
期刊介绍: The Journal of Non-Newtonian Fluid Mechanics publishes research on flowing soft matter systems. Submissions in all areas of flowing complex fluids are welcomed, including polymer melts and solutions, suspensions, colloids, surfactant solutions, biological fluids, gels, liquid crystals and granular materials. Flow problems relevant to microfluidics, lab-on-a-chip, nanofluidics, biological flows, geophysical flows, industrial processes and other applications are of interest. Subjects considered suitable for the journal include the following (not necessarily in order of importance): Theoretical, computational and experimental studies of naturally or technologically relevant flow problems where the non-Newtonian nature of the fluid is important in determining the character of the flow. We seek in particular studies that lend mechanistic insight into flow behavior in complex fluids or highlight flow phenomena unique to complex fluids. Examples include Instabilities, unsteady and turbulent or chaotic flow characteristics in non-Newtonian fluids, Multiphase flows involving complex fluids, Problems involving transport phenomena such as heat and mass transfer and mixing, to the extent that the non-Newtonian flow behavior is central to the transport phenomena, Novel flow situations that suggest the need for further theoretical study, Practical situations of flow that are in need of systematic theoretical and experimental research. Such issues and developments commonly arise, for example, in the polymer processing, petroleum, pharmaceutical, biomedical and consumer product industries.
期刊最新文献
A lattice Boltzmann flux solver with log-conformation representation for the simulations of viscoelastic flows at high Weissenberg numbers Analysis of the shear thickening behavior of a fumed silica suspension using QL-LAOS approach Suppression and augmentation in vortex shedding frequency due to fluid elasticity The influence of thixotropy on bubble growth in thixotropic yield stress fluids: Insights from numerical simulations Viscoelastic model hierarchy for fiber melt spinning of semi-crystalline polymers
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1