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毕业设计方案论证
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定模拼块A1.dwg
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推杆固定板A1.dwg
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!【详情如下】【注塑塑料模具类】CAD图纸+word设计说明书.doc[19000字,42页]【需要咨询购买全套设计请加QQ97666224】.bat

任务书.doc

设计说明书.doc[19000字,42页]

毕业设计方案论证

毕业设计翻译

侧型芯1A4.dwg

侧型芯2A4.dwg

侧型芯3A4.dwg

侧滑块A1.dwg

凹模板A1.dwg

动模型芯1A4.dwg

动模型芯2A4.dwg

动模型芯3A4.dwg

动模型芯垫板A2.dwg

动模座板A1.dwg

动模拼块A1.dwg

塑件图.dwg

定位圈A4.dwg

定模型芯A4.dwg

定模型芯垫板A2.dwg

定模座板A1.dwg

定模拼块A1.dwg

定模板A1.dwg

推杆固定板A1.dwg

推板A1.dwg

支撑板A1.dwg

楔紧块A2.dwg

模具总装合模图A0.dwg

模具总装开模图A0.dwg

浇口套A4.dwg

限位挡块A4.dwg

限位片A4.dwg

目   次


1  塑料模具的现状1

2  塑件的成形工艺性分析3

2.1  课题题目介绍3

2.2  制件结构形状3

2.3  塑件材料的选择及其结构分析4

2.4  塑件工艺性分析5

2.5   ABS的主要技术指标5

2.6   ABS的注射成型工艺6

3  模具结构形式的拟定6

3.1  确定型腔数量及排列方式6

3.2  模具结构形式的确定7

4  注塑机型号的确定8

4.1  塑件注塑量的计算:8

4.2  注射机型号的确定9

4.3  注射机及型腔数量的校核9

4.4  注射机及参数量的校核10

4.5  模具与注射机安装部份的校核11

4.6  顶出行程校核11

5  分型面位置的确定11

5.1  分型面的形式11

5.2  分型面的设计原则11

5.3  分型面的确定12

6  浇注系统的形式和浇口的设计12

6.1  浇注系统设计原则12

6.2  主流道的设计13

6.3  分流道的设计14

6.4  冷料井的设计16

6.5  浇口的设计17

6.6  浇注系统的平衡19

6.7  排气系统的设计19

7  成型零件的设计20

7.1  成型零件的结构形式成型零件的选材21

7.2  成型零件的计算21

7.3  成型零件钢材的选用23

7.4  成型零件强度及支撑板厚度的计算25

8  模架的确定和标准件的选用26

8.1  定模座板27

8.2  定模板27

8.3  动模座板27

8.4  动模板27

8.5  支承板27

8.6  垫块27

8.7  推杆固定板28

8.8  推板28

9  导向机构的设计28

9.1  导向机构的作用28

9.2  导向结构的总体设计28

9.3  导柱的设计29

9.4  导套的设计29

10  侧向抽芯机构设计30

10.1  结构形式的确定30

10.2  斜导柱侧向抽芯力的计算30

10.3  斜导柱的设计31

10.4  滑块、倒滑槽及定位装置的设计31

10.5  楔紧块的设计32

11  脱模推出机构的设计33

11.1  推杆推出机构33

11.2  推出机构的导向和复位33

12  排气系统确定335

毕业设计总结37

致  谢39

参考文献40

参考文献


[1]冯晓曾等. 模具材料与热处理. 机械工业出版社,1985

[2]《模具制造手册》编写组. 模具制造手册. 北京:机械工业出版社,2000

[3]罗继相. 浅析我国模具行业现状及发展趋势和对策.模具技术,No.3,2001

[4]张容清. 模具设计与制造. 北京:高等教育出版社,2003.8.

[5]刘品,李哲.互换性与测量技术基础.哈尔滨工业大学出版社,2006

[6]吴生绪.塑料成形模具设计手册.北京:机械工业出版社,2008,1.

[7]杨占尧.塑料模具标准件及设计应用手册.北京:化学工业出版社,2008.

[8]屈华昌.塑料成型工艺与模具设计.北京:高等教育出版社,2008.

[9]吴宗泽,罗圣国.机械设计课程设计手册. 北京:高等教育出版社,2006

[10]孙凤勤.模具制造工艺与设备. 北京:机械工业出版社,2008.

[11]翟秀云.塑料自动成型用模具问题的探讨[J].攀枝花学院学报,2002.

[12]陈万林.实用注塑模具手册[M].机械工业出版社,2000-10.

[13]付丽.螺纹自动脱模的注塑模设计[M].轻工机械,2000.第1期.

[14]申开智,叶淑静.塑料成型模具[M].轻工业出版社,1982.

[15] 崔洪斌,杨海如 等编.AutoCAD2009机械图形设计.清华大学出版社.2008,8.

[16] 詹友刚 编著.Pro/ENGINEER中文野火版2.0基础教程.清华大学出版社.2007,2.

[17] 和庆娣,袁巍,刘昌丽 等编著.Pro/ENGINEER Wildfire 3.0中文版模具设计. 机械工业出版社.2007,1.

[18] 杨占尧 主编.塑料模具标准件及设计应用手册.化学工业出版社.2008,3.

[19] 吴生绪 主编.塑料成型模具设计手册.机械工业出版社。2008,3.


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机电工程学院 毕业设计方案 论证报告 设计题目 : 保持架注塑模设计及加工工艺性分析 学生姓名: 张苗欣 学 号: 20064480121 专业班级: 材料成型及控制工程 0601 班 指导教师: 董毅峰 2010 年 3 月 20 日 nts 目 录 一、塑料模具概况 简介 1 1、 塑 料 模具的现状 1 2、 塑料模具的发展趋势 2 二、方案论证 3 1、型腔的数目和布置方式的确定 3 1.1 型腔数目 4 1.2 型腔布局 5 2、分型面的确定 5 3、 浇注系统的确定 6 3.1 主流道 6 3.2 浇口 6 3.3 分流道 7 3.4 冷料穴和拉料杆 7 5、侧抽芯机构确定 8 6、合模导向机构 10 7、 推出机构 确定 10 8、 先复位机构的确定 10 9、排气系统确定 10 参考资料 12 nts 毕业设计( 方案论证报告 ) 1 一 、 塑料模具概况 简介 1、塑料模具现状 塑料工业是当今世界上增长最快的工业门类之一 , 上个世纪初以来,塑料由于原料来源广泛,综合性能优良,成型方便,性能价格上占有优势,已成为原四大材料 (钢铁、木材、煤、水泥 )之后的又一大新型材料。迄今,塑料的体积产量已超过了金属材料。在短短的 80 多年内,走过了金属材料两千多年的发展历程。塑料广泛应用于汽车、机械、宇航、舰船、电子电气、化工、纺织、医药卫生、建筑、军工、包装、家具、文体用品以及生活用品等各个领域。特别是近年来,具有光、电、磁、生物等功能的高分子材料的出现,使 得塑料的应用领域扩大到信息民、生物等新兴产业。塑料科技的高速发展,带动了塑料工业的蓬勃发展。 汽车工业:世纪初许多国家汽车工业重要改革措施之一是提高汽车速度、降低能耗,其主要对策是更多地采用塑料件以减轻车体重量。为此,塑料件在汽车中的用量迅速增长。据预测,年各类汽车中将有一半用可回收的塑料复合材料制造。 航空航天工业:世纪初,航空航天工业技术进步着眼点也是减轻机体总重量,以加快飞行速度,降低能耗。如美国洛克希德航空公司复合材料中心采用新型热塑性树脂为母体的增强复合材料制造的飞机,前体结构质量 可减轻,紧固件减轻。欧洲国家在航空航天发展规划上都非常重视使用高性能新型复合材料和高级复合材料,在宇宙空间站、人造卫星和航天飞船上用于制造蜂窝式结构的外壳、机体外板及其他结构件。 电子电气工业 : 目前,电子电气产品结构正向短、小、轻、薄方向发展,对高电磁性塑料合金、超导电塑料、电磁波屏蔽材料、光学性能材料、高性能复合料等,在量和质方面都提出了更高要求。另外,高性能电线、电缆,通信用塑料,光学纤维,新型传感器用塑料以及信息处理中用的各类记录、存贮材料,用静电记录膜,缩微用胶片等在信息化社会中需 求量日益增大,这些又大大促进了塑料材料的发展。 包装工业:人们对包装材料除了在性能方面(高阻透性、高耐热性、保鲜、无菌等)有更高要求外,还要求节省原料、降低能耗。塑料包装材料与传统包装材料比较具有较多优越性。如生产同规格的制品,纸的能耗是塑料的倍,生产过程中释放的二氧化碳及氮氧化物均比塑料高。世纪初,塑料包装材料仍将成为塑料的主要应用领域。 建材工业:塑料在建材工业中获得广泛应用。从材料生产能耗比较,如聚氯乙烯为,则钢材为,铝材为。从应用中节能效果比较,塑料管比金属管可减少输水能nts 毕业设计( 方案论证报告 ) 2 耗 ,塑料窗比铝窗节省采暖能耗约。由此可见,世纪初塑料建材作为节能材料,在许多国家中的需求量将持续增长。 2、塑料模具的发展趋势 模具 CAD/CAE/CAM/PDM 正向集成化、 3D 化、智能化、网络化和信息化方向发展。 模具软件功能集成化模具软件功能的集成化要求软件的功能模块比较齐全,同时各功能模块采用同一数据模型,以实现信息的综合管理与共享,从而支持模具设计、制造、装配、检验、测试及生产管理的全过程,达到实现最佳效益的目的。 模具设计、分析及制造的 3D 传统的 2D 模具结构设计已越来越不适应现代化 生产和集成化技术要求。模具设计、分析、制造的 3D 化、无纸化要求新一代模具软件以立体的、直观的感觉来设计模具所采用的 3D 数字化模型能方便地用于产品结构的 CAE 分析、模具可制造性评价和数控加工、成形过程模拟及信息的管理与共享。如 Pro/ENGINEER、 UG和 CATIA 等软件具备参数化、基于特征、全相关等特点,从而使模具并行工程成为可能。另外, Cimatron 公司的 Moldexpert, Delcam 公司的 Ps-mold 及日立造船的 Space-E/mold均是 3D 专业注塑模设计软件,可进行交互式 3D 型腔、型芯设计 、模架配置及典型结构设计。澳大利亚 Moldflow 公司的 3D直实感流动模拟软件 Moldflow Advisers 已经受到用户广泛的好评和应用。国内有华中理工大学研制的 HSC3D4.5F 及郑州工业大学的 Z-mold软件。面向制造、基于知识的智能化功能是衡量模具软件先进性和实用性的重要标志之一。 模具软件应用的网络化、信息化趋势随着模具在企业竞争、合作、生产和管理等方面的全球化、国际化,以及计算机软硬件技术的迅速发展,网络使得在模具行业应用虚拟设计、敏捷制造技术既有必要,也有可能。美国在其 21 世纪制造企业战 略中指出,到2006 年实现汽车工业敏捷生产 /虚拟工程方案,使汽车开发周期从 40 个月缩短到 4 个月。 随着信息化时代的来临,产品需求将越来越快,同时产品订单,客户输入信息的维护必须通过网络信息化实现,模具设计数据将以产品项目文件夹进行数据库管理,产品图形及技术资料通过系统进行审批流程,快捷高速的信息化时代将带领模具进入新进代。 二、方案论证及确定 1、 课题题目介绍 本次毕业设计的题目 为 : 保持架注塑模设计及加工工艺性分析 。保持架是一个带有铜nts 毕业设计( 方案论证报告 ) 3 质螺纹嵌件的固定架,是铰链结构的一部分,起到保持和固定轴的相对位置和 运动形式的作用。 2、 制件结构形状 塑料制件结构形状如图所示。制件由铜质螺纹嵌件和 ABS 塑料件组合而成, ABS 具有刚性好,冲击强度高、耐热、耐低温、耐化学药品性、机械强度和电器性能优良,易于加工,加工尺寸稳定性和表面光泽好,容易涂装,着色,还可以进行喷涂金属、电镀、焊接和粘接等二次加工性能 。 图 2-1 塑件模型 3、 塑件工艺性分析 如塑件图所示 ,塑件壁厚较大,生产批量为:中批;材料为 ABS, 无定形料, 流动性中等,吸湿大,必须充分干燥 ,并 需采取高料温、高模温 来提高 提高材料的流动性, 因塑件壁厚较大 故 成型工艺性良好,可以注塑成型。 4、 型腔的数目和布置方式的确定 4.1、型腔数目 nts 毕业设计( 方案论证报告 ) 4 图 4-1 型腔排列形式 如图,此 次 毕业设计,就型腔数目、流道和交口的位置如图。 型腔数目:可设计为一模两腔和一模四腔。 一模二腔,一模四腔,无本质正误之分,这两种方案在模具加工时均较为简单,且塑件的形状和尺寸一致性较好,有利于降低模具加工成本,缩短模具制造时间。为保证较高的生产效率,采用一模四腔显然优于一模两腔。 另外,如若考虑一模八腔的方案,则较一模四腔不合适, 模具型腔数目的增多,塑件的精度会降低(一般每增加一个型 腔塑件的尺寸精度便降低 4%-8%),同时模具的制造成本也提高。 同时,塑件质量较大,采用一模八腔时,注塑压力很大,对模具材料要求较高,同时对注塑机要求也随之提高,成本不断攀升。 4.2、型腔布局 采用平横式布局 多型腔模具的型腔在模具分型面上的排列方式可分为平衡式布置和非平衡式布置。平衡式布置的特点是从主流道到各型腔浇口分流道的长度、截面形状与尺寸均对应相同,可以实现个型腔均匀进料和同时充满型腔的目的,从而使所成型的塑件内在质量匀一稳定,力学性能一致。见下图 a)、 b)。 nts 毕业设计( 方案论证报告 ) 5 非平衡式布置的特点是从主流道到各分流道的长度不相同,因而不利于均衡进料,但可以明显缩短分流道的长度,节约塑件的原材料。为了使非平衡式布置的型腔也能达到同时充满的目的,往往各浇口的截面尺寸要制造的不同。 4.3 分型面的确定 分型面是决定模具结构形式的一个重要因素,分型面的类型、形状、及位置与模具的整体结构、浇注系统的设计、塑件的脱模机构和模具的制造工艺等有关,不仅直接关系到模具结构的复杂程度,也关系到塑件的成型质量。分型面的形状有平直分型面;倾斜分型面;阶梯分型面;曲面分型面;瓣合分型面(或垂直分型面)。 分型面的选择原则如下: ( 1)应选在塑件外形最大轮廓处; ( 2)应有利于塑件顺利脱模; ( 3)应保证塑件的尺寸尺寸精度及表面质量; ( 4)应有利于模具的加工; ( 5)应有利于排气。 依照分型面的选择原则为依据, 根据 制件的形状和嵌件的位置来考虑 图 a) 分型面方案 4.4 浇注系统的确定 4.4.1 主流道: 主流道是指 浇注系统中从注塑机喷嘴与模具接触处开始到分流道为止的塑料熔体的流动通道,是熔料最先流经模具的部分,它的形状和尺寸塑料熔体的流动速nts 毕业设计( 方案论证报告 ) 6 度和充模时间有较大的影响,因此,必须使熔体的温度降和压力损失最小。 浇口套的形式主要有以下三种: 图中( a)和( b)所示为浇口套与定位圈设计成两个零件的形式,以台阶的形式固定在定模版上,图( b)所示为穿过定模座板与定模板的形式,图( c)所示是把浇口套与定位圈设计成整体式的结构,通过螺钉固定在定模板上。 本次设计属于中小型模具设计,通常采用图( c)的结构形式。 4.4.2 分流道:流道的设计为塑料流动性提供最大帮助,同时利于加工即可。如左图所示在动模板上开设椭圆形分流道。见图 b)。 nts 毕业设计( 方案论证报告 ) 7 可以实现各型腔的均匀进料。并且可以容纳前锋冷料,有利于制件的成型,保证制件质量。 4.4.3 交口:如下图所示,因注塑量较大,且塑件为固定装置对表面质量要求不太严格,为便于加工和成型可采用采用平交口。见图 c)。 4.4.4 冷料穴与拉料杆 冷料穴的作用是容纳浇注系统流道中料流的前锋冷料,以免这些冷料注入型腔,既影响熔体填充速度,又影响成型塑料的质量。主流道末端的冷料穴除了上诉作用外,还便于在该处设置主流道拉料杆注塑结束模具分型时,在拉料杆的作用下,主流道凝料从定模浇口套中被拉出, 最后由推出机构将塑件和浇注系统凝料一起推出模外。 主流道采用 Z 型拉料杆。见下图 a)。 nts 毕业设计( 方案论证报告 ) 8 5、侧抽芯机构 分析 5.1 侧滑块的基本形式: 有塑件的结构可知,词素间的成性过程需要 侧抽芯机构 (包括一个圆柱侧型芯、一个长方体侧型芯和一个平板侧型芯),侧滑块的基本行式如下图: 因模具是一模四腔,故双边侧抽时,需要将三对六个侧型芯装在一个侧滑块上,由上图可知选用 d)、 e)两种形式的侧星系连接方式组合连接模具的侧型芯和侧滑块。 5.2 倒滑槽: 倒滑槽的基本形式如下: nts 毕业设计( 方案论证报告 ) 9 因侧型芯较多 (三对六个),侧滑块滑动过程中需要导板倒滑,所以选用 d)种形式得倒滑槽。可保证侧滑块顺利的滑动。 5.3 楔紧块 : 楔紧块的结构形式 如下图: 选用 b)加工简单,且有较好的刚度和强度能使侧滑块准确定位。 保证零件精度的同时,保证了模具的寿命。 5.4 定位装置: 选择 a)型定位装置, 结构简单便与加工切定位准确, 保证足够的抽拔力和抽拔距。 5.5 侧抽芯机构组合 : nts 毕业设计( 方案论证报告 ) 10 6、 合模导向机构确定 为了保证动模和定模两大部分或模内其他零件之间准确对合,以确保塑料制 件的形状和尺寸精度,并避免模内各零件发生碰撞和干涉。本次的合模导向机构选择比较常用的导柱导向机构。 7、 推出机构确定 因塑件壁厚较大 , ABS 材料 刚性好,冲击强度高 ,选用圆柱顶杆即可,通知应注意顶杆、型芯与侧抽芯机构的干涉问题。 8、 先复位机构的确定 由于模具结构采用了 推杆推出 机构,合模时 必须使各个推杆先退回到其工作位置,使下次注射成型顺利进行。使推出机构复位简单、最常用的方法是在推杆固定板上装上复位杆。复位杆为圆形截面,每副模具设置 4 根,其位置对称设置在推杆固定板的四周,以便推出机构在合模时能平稳复位 。 9、 排气系统确定 注塑模通常采用以下三种方式排气: ( 1)利用配合间隙排气; nts 毕业设计( 方案论证报告 ) 11 ( 2)在分型面上开设排气槽; ( 3)在分型面上开设排气槽。 由于本次设计的接插件比较小,可以借助分型间隙和其他配合间隙排气,而且不需额外开设排气槽。 nts 毕业设计( 方案论证报告 ) 12 参考资料 1模具实用技术丛书编委会 .塑料模具设计制造与应用实例 M.机械工业出版社 ,2002. 2翟秀云 .塑料自动成型用模具问题的探讨 J.攀枝花学院学报 ,2002. 3陈万林 .实用注塑模具手册 M.机械工业出版社 ,2000-10. 5付丽 .螺纹自动脱模的注塑模设计 M.轻工机械 ,2000.第 1 期 . 5申开智 ,叶淑静 .塑料成型模具 M.轻工业出版社 ,1982. 6 崔洪斌,杨海如 等编 .AutoCAD2009 机械图形设计 .清华大学出版社 .2008,8. 7 詹友刚 编著 .Pro/ENGINEER 中文野火版 2.0 基础教程 .清华大学出版社 .2007,2. 8 和庆娣,袁巍,刘昌丽 等编著 .Pro/ENGINEER Wildfire 3.0 中文版模具设计 .机械工业出版社 .2007,1. 9 杨占尧 主编 .塑料模具标准件及设计应用手册 .化学工业出版社 .2008, 3. 10 吴生绪 主编 .塑料成型模具设计手册 .机械工业出版社。 2008, 3. nts1 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Multi-Scale Modeling of Composite Materials and Structures with DIGIMAT to ANSYS Document Version 1.0, February 2009 Copyright, e-Xstream engineering, 2009 infoe-X www.e-X Materials: Engineering Plastics, Reinforced Plastics. e-Xstream Technology: DIGIMAT, Digimat-MF, Digimat-FE, Digimat to ANSYS, MAP. Complementary CAE Technology: Moldflow, Moldex3D, SigmaSoft, ANSYS. Industry: Material Suppliers, Automotive, Aerospace, Consumer & Industrial Products. TABLE OF CONTENT EXECUTIVE SUMMARY . 2 Material Multi-Scale Modeling: an introduction . 2 FE Homogenization: an application to nanocomposites . 5 Modeling Filler Clustering, a typical nanoeffect. 5 Result Comparison . 7 FE/MFH Coupled Computation: an application to an industrial part . 9 Problem Description . 9 Material Modeling . 10 Simulation Results . 11 Bibliography . 12 Legal Notice. eX, eXdigimat and e-Xstream engineering are registered trademarks of e-Xstream engineering SA. The other product and company names and logos are trademarks or registered trademarks of their respective owners. nts2 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 EXECUTIVE SUMMARY In this paper, we briefly introduce two multi-scale modeling approaches, namely the Mean-Field (MFH) and Finite Element Homogenization (FEH) methods. These powerful techniques relate the microscopic and macroscopic stress and strain fields when modeling material behaviors and hence can capture the influence of the material microstructure (i.e. fiber orientation, fiber content, fiber length, etc.) on its macroscopic response. To illustrate these techniques, we also present (i) an application of finite element homogenization to a nanostructure and (ii) the study of an injected glass fiber reinforced plastic neon light clasp using finite element computations at the macro scale coupled with MF homogenization at the micro scale. Material Multi-Scale Modeling: an introduction As a motivating example, let us consider a plastic part made up of a thermoplastic polymer reinforced with short glass fibers. As typical of the injection molding manufacturing process, the fiber distribution inside the final product will vary widely in terms of orientation and length, see Figure 1. The composite material will be both anisotropic and heterogeneous, which makes it extremely difficult to perform a reliable simulation of the product using a classical approach based on macroscopic constitutive models. However, a predictive simulation is possible via a multi-scale approach, which can be described in a rather general setting as follows. Figure 1: Fiber orientation distribution in an injected glass fiber-reinforced plastic clutch pedal. Courtesy of Rhodia & Trelleborg. Let us study a heterogeneous solid body whose microstructure consists of a matrix material and multiple phases of so-called “inclusions”, which can be short fibers, platelets, particles, micro-cavities or micro-cracks. Our objective is to predict the response of the body under given loads and boundary conditions (BCs), based on its microstructure. We can distinguish two scales, the microscopic and macroscopic levels, respectively. The former corresponds to the scale of the heterogeneities, while at the macro scale, the solid can be seen as locally homogeneous; see Figure 2. In practice, it would be computationally impossible to solve the mechanical problem at the fine micro scale. Therefore, we consider the macro scale and assume that each material point is the center of a representative volume element (RVE), which contains the underlying heterogeneous microstructure. Classical solid mechanics analysis is carried out at the macro scale, except that at each computation point, strain or stress values are transmitted as BCs to the underlying RVE. In other words, a numerical zoom is realized at each macro point. The RVE problems are solved and each of them returns stress and stiffness values, which are used at the macro scale. nts3 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Figure 2: Illustration of the multi-scale material modeling approach, after Nemat-Nasser and Hori (1). Now the only difficulty in this two-scales (and more generally multi-scale) approach is to solve the RVE problems. It can be shown that for a RVE under classical BCs, the macro strains and stresses are equal to the volume averages over the RVE of the unknown micro strain and stress fields inside the RVE. In linear elasticity, relating those two mean values gives the effective or overall stiffness of the composite at the macro scale. In order to solve the RVE problem, one can use the well-known finite element (FE) method, see Figures 7 to 10. This method offers the advantages of being very general and extremely accurate. However, it has two major drawbacks which are: serious meshing difficulties for realistic microstructures and a large CPU time for nonlinear problems, such as for inelastic material behaviour. Another completely different method is mean-field homogenization (MFH), which is based on assumed relations between volume averages of stress or strain fields in each phase of a RVE; see Figure 3. Compared to the direct FE method, and actually to all other existing scale transition methods, MFH is both the easiest to use and the fastest in terms of CPU time. However, two shortcomings of MFH are that it is unable to give detailed strain and stress fields in each phase and it is restricted to ellipsoidal inclusion shapes. Figure 3: Mean-field homogenization process: (i) local strains are computed based on the macro strains, (ii) local stresses are computed based on the local strains and according to each phase constitutive model, and (iii) macro stresses are computed by averaging the local stresses. nts4 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 A typical example of MFH is the Mori-Tanaka model (2) which is successfully applicable to two-phase composites with identical and aligned ellipsoidal inclusions. The model assumes that each inclusion of the RVE behaves as if it were alone in an infinite body made of the real matrix material. The BCs in the single inclusion problem correspond to the volume average of the strain field in the matrix phase of the real RVE. The single inclusion problem was solved analytically by J.D. Eshelby (3) in a landmark paper, which is the cornerstone of MFH models. Figure 4: Schematic of the Mori-Tanaka homogenization procedure. Mori-Tanaka and other MFH models were generalized to other cases, such as thermoelastic coupling, two-phase composites with misaligned fibers (using a multi-step approach) or multi-phase composites (using a multi-level method). The predictions have been extensively verified against direct FE simulation of RVEs or validated against experimental results. As a general conclusion, it was found that in linear (thermo)elasticity, MFH can give extremely accurate predictions of effective properties, although for distributed orientations, progress in closure approximation will be welcomed. Note also that MFH can be used for UD, and for each yarn in woven composites. An important and still ongoing effort both in theoretical modeling and in computational methods is the generalization of MFH to the material or geometric nonlinear realms. Such extension involves some major difficulties. The first one is linearization, where constitutive equations at microscale need to be linearized onto linear elastic- or thermoelastic-like format. The second issue is the definition of so-called comparison materials which are fictitious materials designed to possess uniform instantaneous stiffness operators in each phase. The next problem to be solved is first-order vs second-order homogenization. In first-order homogenization comparison materials are computed with real constitutive models but volume averages of strain or stress fields per phase. In a second-order formulation, richer statistical information, namely the variance of strain or stress fields per phase is also taken into account. Finally, a very technical difficulty concerns the computation of Eshelbys or Hills tensors and is related to the anisotropy of the comparison instantaneous stiffness operator. Within a coupled multi-scale analysis, FE method is used at macro scale, while at each Gauss integration point, MFH computation is carried out, either in the linear or nonlinear regime. This is the most feasible approach in practice. See Figure 5. Each inclusion RVE homogenization nts5 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Figure 5: Comparison between the classical FE and the coupled FE/Digimat-MF approaches. Extensive verification and validation results show that MFH can be used in practice for nonlinear problems and leads to good predictions in general, while work continues on improving accuracy in some situations (and reducing CPU time for coupled multi-scale analysis). FE Homogenization: an application to nanocomposites Most likely will nanomaterials be the materials of tomorrow, as they offer new horizons of applications in a wide variety of fields, e.g. nanoelectronics, bio-nanotechnology and nanomedicine. As such, more and more effort is put in understanding and modeling their behavior as well as acquiring know-how about nanoeffects. While new tools are being developed to tackle this engineering challenge, some are already available to the engineer of today. Among them: Finite Element Homogenization (FEH). Modeling Filler Clustering, a typical nanoeffect Material scientists face several challenges related to the design and the processing of nanocomposites as, at the nano scale, new physics and phenomena that are negligible at the macro scale enter the picture. For instance, uniform dispersion of the nanofiller inside the composite matrix is sought to improve the material mechanical properties, while clustering and percolation are desired when the conductivity of a base material, thermal or electrical, needs to be increased; see Figure 6. Achieving one or the other nowadays constitutes a challenge in terms of both material processing and study. nts6 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Dispersed Ag nanoparticles. (4) Clustered and percolated silica nanofiller in a polymer matrix. (5) Figure 6: Nanofiller dispersion. FEH, as it requires the studied geometry to be explicitly generated and meshed, allows an accurate modeling of percolation and clustering effects. As an illustration, we present the effect of clustering on the elastic mechanical properties of a macroscopic material point. Figure 7 presents two periodic nanostructures, also referred to as Representative Volume Element (RVE), that have been generated using Digimat-FE. Clustering parameters have been introduced to generate the rightmost geometry, whose inclusions are concentrated around 2 distinct clustering points. Volume fraction of the inclusion phase is 5% and the inclusions are spherical. Once meshed, these geometries will be subjected to uniaxial tensile conditions in the RVE x-, y- and z-directions and the finite element problem will be solved using the ANSYS finite element solver. Figure 7: Microstructures with uniformly distributed inclusions (left) and clustered inclusions (right). Clustering Percolation nts7 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Result Comparison Figure 8: S11 stress distribution in the inclusions (left) and in the matrix (right) for randomly placed inclusions. Figure 8 to 10 illustrate the stress distribution in the matrix and inclusion phases, in the case of the x-axis uniaxial tensile test. Due to the proximity of the inclusions around the clustering centers, stress concentrations appear. As such, up to 30% higher tensile stresses are observed for the clustered case, under x-direction uniaxial tensile loading conditions, see Figure 10. Figure 11 plots the S33 stress and E33 strain distribution in the inclusion and matrix phases, as well as in the RVE. One clearly observes the higher stress levels in the inclusion phase. Such higher stress concentrations, that are not observed for randomly or uniformly placed inclusions, could lead to debonding during loading. Figure 9: S11 stress distribution in the inclusions (left) and in the matrix (right) for clustered inclusions. nts8 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Figure 10: 2D section view of clustered (left) and random (right) RVEs. Tensile stress distribution. Figure 11: S33 stress (left) and E33 strain (right) distributions in the nano phases and in the RVE for both cases for a z-direction uniaxial loading. At this low volume fraction of inclusions, we see that clustering does not significantly alter the macroscopic mechanical properties of the material, see Table 1. Such a placement of nanoinclusions is thus preferably avoided by the material scientists when trying to increase the stiffness of a base material (Ematrix = 2195 MPa) by combination with a nanofiller (Efiller = 7000 MPa). Random MPa Clustered MPa E1 2319 2322 E2 2318 2324 E3 2317 2328 Average 2318 2325 Rel. Diff. 0.3% Table 1: Youngs moduli for both geometries, obtained by FEH. nts9 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 FE/MFH Coupled Computation: an application to an industrial part For many reasons (manufacturing costs and flexibility, processing methods, high strength vs. lightness ratio, etc.), injected parts made up of short glass fiber reinforced plastics have become omnipresent in our daily life. But when it gets to model such materials, can macroscopic constitutive material models capture effects such as the injection process? The answer is no, as they do not capture the influence of the fiber orientation which depends on the injection process. The following example, which consists of a neon light clasp subjected to loading, introduces the process of a coupled analysis between Moldex3D, DIGIMAT-MF and ANSYS. This process, which is illustrated in Figure 12, consists of the following steps: 1. The injection molding process is simulated using Moldex3D. Among the available results are the fiber orientation tensors that will serve as input to DIGIMAT in the structural simulation. 2. The orientation tensors computed in 1. are mapped from the injection mesh onto the coarser structural one using Map (the mapping tool available in DIGIMAT). 3. The structural simulation is run using the ANSYS finite element solver coupled with Digimat-MF, the multi-scale material modeler that performs MFH at each integration point of the structural mesh. Figure 12: Coupled analysis process. DIGIMAT takes the fiber orientation tensor obtained from Moldex3D as input, in addition to the material properties and serves as material modeler for the ANSYS finite element simulation. Problem Description The light clasp consists of four independent parts, see Figure 13 that also illustrates the contacts between the different parts. Two of them are made up of 30% glass fiber reinforced polyamide, Bergamid, and were injected. Their injection was simulated in Moldex3D. The slide and support block are assumed to be made up of steel. nts10 | P a g e C o p y r i g h t e - X s t r e a m e n g i n e e r i n g , 2 0 0 9 Closure of the clasp is simulated by imposing a displacement to the slide while blocking the support and part of the inner part. Symmetry boundary conditions are also applied to limit the study to half the part. The goal of the simulation is to evaluate the maximum von Mises stress in the outer part, during loading, and to compare the response obtained using a linear elastic model of the material and using DIGIMAT-MF to perform MFH with elastic glass fibers and an elasto-plastic model for the PA. Material Modeling To model the PAGF in DIGIMAT-MF, the following hypotheses are made: Glass fibers remain in their linear elastic domain. The polyamide behaves elasto-plastically. The fiber aspect ratio (length/diameter ratio) is 30. See Figure 14 for the tensile response of the material models. Figure 13: Representation of the neon light clasp
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