Extensions to New Topics

  • Ercan M. Dede
  • Jaewook Lee
  • Tsuyoshi Nomura
Part of the Simulation Foundations, Methods and Applications book series (SFMA)


The field of multiphysics simulation is rapidly evolving due to continual increases in computing power and the multidisciplinary nature of engineering today. In this final chapter of the book, we collect our thoughts on how the numerical examples provided in this text may be extended to emerging ideas (or topics that have received limited attention) and that make use of state-of-the-art computational tools and optimization algorithms. While many of the case studies provided throughout this book incorporated two physical processes, only one example in Chap.  5 was focused on the simultaneous optimization of a system subject to three distinctly separate, yet coupled, physical phenomena. Here, we set forth a greater number of ideas related to these complex systems and leave it to the reader to explore them on their own. The relevance of such extensions is that most electromechanical applications require the tight integration and handling of more than two physical processes in three dimensions, are highly constrained, and involve specific interface considerations. Thus, topics including the scaling-up of systems, treatment of surfaces and interfaces, and the constraint of systems for manufacturability are covered.


Topology Optimization Electromechanical Device Solder Bond Multiphysics Simulation Free Material Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Aage N, Lazarov BS (2013) Parallel framework for topology optimization using the method of moving asymptotes. Struct Multidiscip O 47:493–505. doi: 10.1007/s00158-012-0869-2 CrossRefMATHMathSciNetGoogle Scholar
  2. 2.
    Azernikov S, Fischer A (2004) Efficient surface reconstruction method for distributed CAD. Comput Aided Des 36:799–808. doi: 10.1016/j.cad.2003.09.006 CrossRefGoogle Scholar
  3. 3.
    Christiansen AN, Nobel-Jørgensen M, Aage N, Sigmund O, Baerentzen JA, (2014) Topology optimization using an explicit interface representation. Struct Multidiscip O 49:387–399. doi: 10.1007/s00158-013-0983-9
  4. 4.
    Darveaux R (2000) Effect of simulation methodology on solder joint crack growth correlation. In: Proceedings of the 50th electronic components and technology conference, Las Vegas, 21–24 May 2000. doi: 10.1109/ECTC.2000.853299
  5. 5.
    Dedè L, Borden MJ, Hughes TJR (2012) Isogeometric analysis for topology optimization with a phase field model. Arch Comput Method E 19:427–465. doi: 10.1007/s11831-012-9075-z CrossRefGoogle Scholar
  6. 6.
    Evgrafov A, Rupp CJ, Maute K, Dunn ML (2008) Large-scale parallel topology optimization using a dual-primal substructuring solver. Struct Multidiscip O 36:329–345. doi: 10.1007/s00158-007-0190-7 CrossRefMATHMathSciNetGoogle Scholar
  7. 7.
    Fischer A (2011) Engineering-oriented geometry methods for modeling and analyzing scanned data. J Comput Inf Sci Eng 11:021002. doi: 10.1115/1.3593415 CrossRefGoogle Scholar
  8. 8.
    Gain A (2013) Polytope-based topology optimization using a mimetic-inspired method. Dissertation, University of Illinois at Urbana-ChampaignGoogle Scholar
  9. 9.
    Guest JK, Prévost JH, Belytschko T (2004) Achieving minimum length scale in topology optimization using nodal design variables and projection functions. Int J Numer Meth Eng 61:238–254. doi: 10.1002/nme.1064 CrossRefMATHGoogle Scholar
  10. 10.
    Haslinger J, Kočvara M, Leugering G, Stingl M (2010) Multidisciplinary free material optimization. SIAM J Appl Math 70:2709–2728. doi: 10.1137/090774446 CrossRefMATHMathSciNetGoogle Scholar
  11. 11.
    Jansen M, Lazarov BS, Schevenels M, Sigmund O (2013) On the similarities between micro/nano lithography and topology optimization projection methods. In: 10th world congress on structural and multidisciplinary optimization, Orlando, 19–24 May 2013Google Scholar
  12. 12.
    Lee J, Nomura T, Dede EM (2012) Heat flow control in thermo-magnetic convective systems using engineered magnetic fields. Appl Phys Lett 101:123507. doi: 10.1063/1.4754119 CrossRefGoogle Scholar
  13. 13.
    Lee J, Yoon SW (2012) Topology design optimization of electromagnetic vibration energy harvester to maximize power output. J Magn 18:283–288. doi: 10.4283/JMAG.2013.18.3.283 CrossRefGoogle Scholar
  14. 14.
    Lipson H, Kurman M (2013) Fabricated: the new world of 3D printing. Wiley, IndianapolisGoogle Scholar
  15. 15.
    Malone E, Lipson H (2008) Multi-material freeform fabrication of active systems. In: Proceedings of the ASME 2008 9th biennial conference on engineering systems design and analysis, Haifa, 7–9 July 2008. doi: 10.1115/ESDA2008-59313
  16. 16.
    Noh JY, Yoon GH (2012) Topology optimization of piezoelectric energy harvesting devices considering static and harmonic dynamic loads. Adv Eng Softw 53:45–60. doi: 10.1016/j.advengsoft.2012.07.008 CrossRefGoogle Scholar
  17. 17.
    Nomura T, Dede EM, Lee J, Yamasaki S, Matsumori T, Kawamoto A, Kikuchi N (2014) General topology optimization method with continuous and discrete orientation design using isoparametric projection (submitted)Google Scholar
  18. 18.
    Ohkado M, Nomura T, Matsumori T, Kawamoto A, Fujikawa H, Sato K, Yamasaki S, Nishiwaki S (2011) Structural optimization of SPPs color filter using a level set-based topology optimization method incorporating the ALE method. In: 9th world congress on structural and multidisciplinary optimization, Shizuoka, 13–17 June 2011Google Scholar
  19. 19.
    Ohkado M, Nomura T, Miura A, Fujikawa H, Ikeda N, Sugimoto Y, Nishiwaki S (2013) Structural optimization of metallic infrared filters based on extraordinary optical transmission. T MRS Jap 38:167–170. doi: 10.14723/tmrsj.38.167 Google Scholar
  20. 20.
    Ozaki T, Nomura T, Fujitsuka N, Shimaoka K, Akashi T (2013) Topology optimization using multistep mapping from 2D photomask to 3D structure for designing reinforcing rib. Sensors Actuat A-Phys (in press). doi: 10.1016/j.sna.2013.08.033
  21. 21.
    Qian X (2013) Topology optimization in B-spline space. Comput Method Appl M 265:15–35. doi: 10.1016/j.cma.2013.06.001 CrossRefMATHGoogle Scholar
  22. 22.
    Qian X, Sigmund O (2013) Topological design of electromechanical actuators with robustness toward over- and under-etching. Comput Method Appl M 253:237–251. doi: 10.1016/j.cma.2012.08.020 CrossRefMathSciNetGoogle Scholar
  23. 23.
    Rangarajan R, Lew AJ (2012) Universal meshes: a new paradigm for computing with nonconforming triangulations. Accessed 19 March 2014
  24. 24.
    Seo YD, Kim HJ, Youn SK (2010) Isogeometric topology optimization using trimmed spline surfaces. Comput Method Appl M 199:3270–3296. doi: 10.1016/j.cma.2010.06.033 CrossRefMATHMathSciNetGoogle Scholar
  25. 25.
    Sigmund O (2001) Design of multiphysics actuators using topology optimization-Part I: one-material structures. Comput Method Appl M 190:6577–6604. doi: 10.1016/S0045-7825(01)00251-1
  26. 26.
    Sigmund O (2009) Manufacturing tolerant topology optimization. Acta Mech Sinica 25:227–239. doi: 10.1007/s10409-009-0240-z CrossRefMATHGoogle Scholar
  27. 27.
    van Dijk NP, Maute K, Langelaar M, van Keulen F (2013) Level-set methods for structural topology optimization: a review. Struct Multidiscip O 48:437–472. doi: 10.1007/s00158-013-0912-y CrossRefGoogle Scholar
  28. 28.
    Yamasaki S, Nomura T, Kawamoto A, Sato K, Nishiwaki S (2011) A level set-based topology optimization method targeting metallic waveguide design problems. Int J Numer Meth Eng 87:844–868. doi: 10.1002/nme.3135 CrossRefMATHMathSciNetGoogle Scholar
  29. 29.
    Ye H, Lin M, Basaran C (2002) Failure modes and FEM analysis of power electronic packaging. Finite Elem Anal Des 38:601–612. doi: 10.1016/S0168-874X(01)00094-4 CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Toyota Research Institute of North AmericaAnn ArborUSA
  2. 2.Korea Aerospace UniversityGoyang-siKorea, Republic of (South Korea)
  3. 3.Toyota Central R&D Labs.NagakuteJapan

Personalised recommendations