通过新型轻量化参数优化方法比较激光选区熔化部件设计的不同细胞结构（英文）
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摘要
目的:1.提出一种在外型不变的部件内模拟不同细胞结构的方法;2.发展激光选区熔化(SLM)部件轻量化参数设计的新方法;3.利用这一方案实现优化设计并比较不同细胞结构的质量。创新点:1.提出基于拉丁超立方实验设计、遗传算法、克里金元模型和有限元方法的轻量化优化方案;2.该方法可通过较少的采样获得良好的结果并能克服几何奇点(内部网格细化算法)的问题。方法:1.进行内部细胞结构的生成和参数化;2.根据输入数据(设计变量和约束条件等)采用拉丁超立方实验设计模拟所选样本;3.利用先前的数据创建克里金元模型并利用预测的元模型来计算遗传算法演化过程中的适应函数;4.将模拟实现的优化结果添加到数据中更新元模型,并通过数次重复迭代提高元模型的准确度直至误差小于5%;5.将这一概念应用于不同的几何结构,然后通过SLM加工制造优化后的几何结构,并在弯曲载荷下进行测试。结论:1.该优化算法通过适当的参数化克服了SLM技术的相关限制,可适用于SLM部件的优化;2.立方单元格在计算机辅助设计定义、参数化和时间优化等方面有一些优势,但和有限元分析的估计结果相比,其存在的缺乏坚实支撑的水平条(悬挂结构)会造成机械性能损失;3.将立方单元结构与用户自定义的参数化增强相结合可以得到更有效的设计结果(更高的比刚度),但更多的设计变量也延长了所需要的优化时间。
Interest in lightweight geometries and cellular structures has increased due to the freeform capabilities of additive manufacturing technologies. In this paper, six different cellular structures were designed and parameterised with three design variables to carry out the lightweight optimisation of an initial solid sample. According to the limitations of conventional computer-aided design(CAD) software, a new parametric optimisation method was implemented and used to optimise these six types of structures. The best one in terms of optimisation time and stiffness was parameterised with nine design variables, changing the dimensions of the internal cellular structure and the reinforcement zones. These seven optimised geometries were manufactured in a Phenix ProX200 selective laser melting machine without using support. The samples obtained were tested under flexural load. The results show that the cubic cell structures have some advantages in terms of CAD definition, parameterisation and optimisation time because of their simpler geometry. However, from the flexural test results it can be concluded that this type of cell structure and those with horizontal bars experience a loss of stiffness compared to the estimates of the finite element analysis because of imperfections in the manufacturing process of hanging structures.
Interest in lightweight geometries and cellular structures has increased due to the freeform capabilities of additive manufacturing technologies. In this paper, six different cellular structures were designed and parameterised with three design variables to carry out the lightweight optimisation of an initial solid sample. According to the limitations of conventional computer-aided design(CAD) software, a new parametric optimisation method was implemented and used to optimise these six types of structures. The best one in terms of optimisation time and stiffness was parameterised with nine design variables, changing the dimensions of the internal cellular structure and the reinforcement zones. These seven optimised geometries were manufactured in a Phenix ProX200 selective laser melting machine without using support. The samples obtained were tested under flexural load. The results show that the cubic cell structures have some advantages in terms of CAD definition, parameterisation and optimisation time because of their simpler geometry. However, from the flexural test results it can be concluded that this type of cell structure and those with horizontal bars experience a loss of stiffness compared to the estimates of the finite element analysis because of imperfections in the manufacturing process of hanging structures.
引文
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Sachlos E,Czernuszka JT,2003.Making tissue engineering scaffolds work.Review:the application of solid freeform fabrication technology to the production of tissue engineering scaffolds.European Cells and Materials,5:29-40.
Salmi A,Calignano F,Galati M,et al.,2018.An integrated design methodology for components produced by laser powder bed fusion(L-PBF)process.Virtual and Physical Prototyping,13(3):191-202.https://doi.org/10.1080/17452759.2018.1442229
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Yang SF,Leong KF,Du ZH,et al.,2001.The design of scaffolds for use in tissue engineering.Part I.Traditional factors.Tissue Engineering,7(6):679-689.https://doi.org/10.1089/107632701753337645
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Yoo DJ,2011.Computer-aided porous scaffold design for tissue engineering using triply periodic minimal surfaces.International Journal of Precision Engineering and Manufacturing,12(1):61-71.https://doi.org/10.1007/s12541-011-0008-9
Zhang K,Liu TT,Liao WH,et al.,2018.Influence of laser parameters on the surface morphology of slurry-based Al2O3 parts produced through selective laser melting.Rapid Prototyping Journal,24(2):333-341.https://doi.org/10.1108/RPJ-12-2016-0201
Aremu A,Ashcroft I,Wildman R,et al.,2013.The effects of bidirectional evolutionary structural optimization parameters on an industrial designed component for additive manufacture.Proceedings of the Institution of Mechanical Engineers,Part B:Journal of Engineering Manufacture,227(6):794-807.https://doi.org/10.1177/0954405412463857
Autodesk,2015.Netfabb Software:Additive Manufacturing and Design Software.Autodesk.http://www.netfabb.com/
Autodesk Within,2015.Within-Software-General Overview.Autodesk.http://withinlab.com/software/
Bagheri ZS,Melancon D,Liu L,et al.,2017.Compensation strategy to reduce geometry and mechanics mismatches in porous biomaterials built with selective laser melting.Journal of the Mechanical Behavior of Biomedical Materials,70:17-27.https://doi.org/10.1016/j.jmbbm.2016.04.041
Calignano F,2018.Investigation of the accuracy and roughness in the laser powder bed fusion process.Virtual and Physical Prototyping,13(2):97-104.https://doi.org/10.1080/17452759.2018.1426368
Campanelli SL,Contuzzi N,Angelastro A,et al.,2010.Capabilities and performances of the selective laser melting process.In:Er MJ(Ed.),New Trends in Technologies:Devices,Computer,Communication and Industrial Systems.InTech,p.233-252.
Dassault Systèmes,2013.SOLIDWORKS Help:Node to Surface Contact.Dassault Systèmes.http://help.solidworks.com/2013/English/SolidWorks/cw orks/c_Node_to_Surface_Contact.htm
Dotcheva M,Thomas D,Millward H,2009.An evaluation of rapid manufactured cellular structures to enhance injection moulding tool performance.International Journal of Materials Engineering and Technology,1(2):105-127.
Gibson I,Rosen DW,Stucker B,2009.Additive Manufacturing Technologies:Rapid Prototyping to Direct Digital Manufacturing.Springer,New York,USA.
González SG,2010.Solid Works Simulation.RA-MA S.A.,Madrid,Spain(in Spanish).
Hutmacher DW,Sittinger M,Risbud MV,2004.Scaffoldbased tissue engineering:rationale for computer-aided design and solid free-form fabrication systems.Trends in Biotechnology,22(7):354-362.https://doi.org/10.1016/j.tibtech.2004.05.005
ISO/ASTM International,2015.Additive ManufacturingGeneral Principles-Terminology,ISO/ASTM 52900:2015.ISO/ASTM International,Switzerland.
Jorge MA,da Conceicao Batista F,Almeida HA,et al.,2007.Virtual and Rapid Manufacturing:Advanced Research in Virtual and Rapid Prototyping.CRC Press,Boca Raton,USA.
Kranz J,Herzog D,Emmelmann C,2015.Design guidelines for laser additive manufacturing of lightweight structures in TiAl6V4.Journal of Laser Applications,27(S1):S14001.https://doi.org/10.2351/1.4885235
Kulkarni VR,Tambe AG,2013.Optimization and finite element analysis of steering knuckle.Proceedings of Altair Technology Conference.
Labeas GN,Sunaric MM,2010.Investigation on the static response and failure process of metallic open lattice cellular structures.Strain,46(2):195-204.https://doi.org/10.1111/j.1475-1305.2008.00498.x
Lophaven SN,Nielsen HB,S?ndergaard J,2002a.DACE-a Matlab Kriging Toolbox,Version 2.0.IMM-TR-2002-12,Technical University of Denmark,Kongens Lyngby,Denmark.
Lophaven SN,Nielsen HB,S?ndergaard J,2002b.Aspects of the Matlab Toolbox Dace.IMMREP-2002-13,Technical University of Denmark,Kongens Lyngby,Denmark.
Lynch ME,Gu WJ,El-Wardany T,et al.,2013.Design and topology/shape structural optimisation for additively manufactured cold sprayed components.Virtual and Physical Prototyping,8(3):213-231.https://doi.org/10.1080/17452759.2013.837629
Materialise 3-matic,2015.Materialise 3-matic Lightweight Structures Module.Materialise 3-matic.http://software.materialise.com/3-matic-lightweight-struc tures-module
MathWorks,2015.Lhsdesign:Latin Hypercube Sample.MathWorks,Spain.http://es.mathworks.com/help/stats/lhsdesign.html
Monzón M,2018.Biomaterials and additive manufacturing:osteochondral scaffold innovation applied to osteoarthritis(BAMOS project).Journal of Zhejiang UniversitySCIENCE A(Applied Physics&Engineering),19(4):329-330.https://doi.org/10.1631/jzus.A18NW001
Mullen L,Stamp RC,Brooks WK,et al.,2009.Selective laser melting:a regular unit cell approach for the manufacture of porous,titanium,bone in-growth constructs,suitable for orthopedic applications.Journal of Biomedical Materials Research Part B:Applied Biomaterials,89B(2):325-334.https://doi.org/10.1002/jbm.b.31219
Murr LE,Gaytan SM,Medina F,et al.,2010.Next-generation biomedical implants using additive manufacturing of complex,cellular and functional mesh arrays.Philosophical Transactions of the Royal Society A:Mathematical,Physical and Engineering Sciences,368(1917):1999-2032.https://doi.org/10.1098/rsta.2010.0010
Peltola SM,Melchels FP,Grijpma DW,et al.,2008.A review of rapid prototyping techniques for tissue engineering purposes.Annals of Medicine,40(4):268-280.https://doi.org/10.1080/07853890701881788
Pepelnjak T,Gantar G,Kuzman K,2001.Numerical simulations in optimisation of product and forming process.Journal of Materials Processing Technology,115(1):122-126.https://doi.org/10.1016/S0924-0136(01)00744-0
Protasov CE,Khmyrov RS,Grigoriev SN,et al.,2017.Selective laser melting of fused silica:interdependent heat transfer and powder consolidation.International Journal of Heat and Mass Transfer,104:665-674.https://doi.org/10.1016/j.ijheatmasstransfer.2016.08.107
Sachlos E,Czernuszka JT,2003.Making tissue engineering scaffolds work.Review:the application of solid freeform fabrication technology to the production of tissue engineering scaffolds.European Cells and Materials,5:29-40.
Salmi A,Calignano F,Galati M,et al.,2018.An integrated design methodology for components produced by laser powder bed fusion(L-PBF)process.Virtual and Physical Prototyping,13(3):191-202.https://doi.org/10.1080/17452759.2018.1442229
Siemens PLM Software,2010.Femap Version 10.2:What’s New.Siemens PLM Software.https://appliedcax.com/support-and-training/technical-on line-seminars/seminars/2010-12-02_seminar.pdf
Sing SL,Yeong WY,Wiria FE,et al.,2017.Direct selective laser sintering and melting of ceramics:a review.Rapid Prototyping Journal,23(3):611-623.https://doi.org/10.1108/RPJ-11-2015-0178
Sing SL,Wiria FE,Yeong WY,2018.Selective laser melting of lattice structures:a statistical approach to manufacturability and mechanical behavior.Robotics and Computer-Integrated Manufacturing,49:170-180.https://doi.org/10.1016/j.rcim.2017.06.006
Synopsys,2015.Simpleware Software Solutions:3D Image Data Visualization,Analysis and Model Generation with Simpleware.Synopsys.http://www.simpleware.com
Thomas D,2009.The Development of Design Rules for Selective Laser Melting.PhD Thesis,University of Wales,Cardiff,UK.
Wohlers T,Caffrey T,2014.Wohlers Report 2014:3D Printing and Additive Manufacturing State of the Industry Annual Worldwide Progress Report.Wohlers Associates,Fort Collins,USA.
Wong KV,Hernandez A,2012.A review of additive manufacturing.ISRN Mechanical Engineering,2012:208760.https://doi.org/10.5402/2012/208760
Yang SF,Leong KF,Du ZH,et al.,2001.The design of scaffolds for use in tissue engineering.Part I.Traditional factors.Tissue Engineering,7(6):679-689.https://doi.org/10.1089/107632701753337645
Yap CY,Chua CK,Dong ZL,et al.,2015.Review of selective laser melting:materials and applications.Applied Physics Reviews,2(4):041101.https://doi.org/10.1063/1.4935926
Yeong WY,Chua CK,Leong KF,et al.,2004.Rapid prototyping in tissue engineering:challenges and potential.Trends in Biotechnology,22(12):643-652.https://doi.org/10.1016/j.tibtech.2004.10.004
Yoo DJ,2011.Computer-aided porous scaffold design for tissue engineering using triply periodic minimal surfaces.International Journal of Precision Engineering and Manufacturing,12(1):61-71.https://doi.org/10.1007/s12541-011-0008-9
Zhang K,Liu TT,Liao WH,et al.,2018.Influence of laser parameters on the surface morphology of slurry-based Al2O3 parts produced through selective laser melting.Rapid Prototyping Journal,24(2):333-341.https://doi.org/10.1108/RPJ-12-2016-0201