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3DPrinting_Suresh
This document discusses new design paradigms enabled by 3D printing. It notes that 3D printing allows for geometric complexity at no added cost, unlike traditional manufacturing. This enables optimal and aesthetically complex part designs that may be stronger yet lighter. However, new design tools are needed to create such optimal complex parts. The document presents topology optimization as one such new tool that can design parts with minimum weight subject to stress constraints. It also discusses how GPU-based simulation can enable real-time topology optimization designs for 3D printing. In conclusion, 3D printing coupled with new design and simulation tools will lead to greater design freedom and more optimal lightweight complex parts.
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3DPrinting_Suresh
- 1. New Design Paradigmsfor 3D Printing Krishnan Suresh Associate Professor Mechanical Engineering
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- 3. CAD: Underlying Philosophy Influencedby traditional manufacturing Controlled Complexity 3D Printing: Complexity is Free
- 4. Simple vs Complex 3DPrinting Geometric complexity is free Controlled Complexity
- 5. Why Complexity? Why designcomplex parts? - Aesthetics - Optimal - Assembly-free (3ders.com) (mmsonline.com) (bathsheba.com)
- 6. Optimal Design &Complexity ? Stronger and lighter (but more complex) (3ders.com)
- 7. How to designsuch optimal parts? Optimal Designs ~ Complex & Beautiful “For the first time, our capacity to manufacture has exceeded our capacity to design” - Opening remark, 2013 ISAT/DARPA Workshop Conventional CAD?
- 8. Example Remove material, butkeep it stiff! A B ?
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- 16. Topology Optimization (3D) 60%weight 50% weight 16 6% weight
- 17. Hook Design • Strong •Lite • Controlled complexity Geometric complexity is free
- 18. New design tools for3d printing will emerge
- 19. Simulation Questions Conventional FEA: Incapable! CanI print? Will it break?
- 20. Optimal Design Design Space Finite ElementAnalysis (FEA) Optimal? Change Topology No 100’s of iterations! 20 Conventional FEA: Incredibly slow!
- 21. Optimal Design Size Optistruct Intel Xeon,12 core, 92 GB (180,60,30) 20 hours
- 22. New Simulation Methods for HighPerformance Computing
- 23. CPU vs. GPU Cache RAM GPU Memory 50~1000GFLOP GPUCPU 10~50 GFLOP (1~12 cores) (100~2000 cores)
- 24. GPU Off-the-shelf PCI hardware($100 - $500) Vendors: NVidia, ATI,
- 25. Trends in Computing ComputingSpeed Memory Speed Memory starved computation Takes more time to fetch 2 numbers than to multiply (Brodtkorb 13)
- 26. New simulation tools for3d printing will emerge
- 27. Optimal Designs PareTO Intel i7,8 cores, 8 GB 42 mins Size Optistruct Intel Xeon, 12 core, 92 GB (180,60,30) 20 hours PareTO Nvidia GTX 480, 1.5 GB 4 mins UW-Madison
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- 31. Topology Optimization Minimize weightwithin design-space subject to stress constraints under 4 different load-conditions!
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- 33. PareTO: Maximize Stiffness Optimaldesign for Maximizing Stiffness (30% vol fraction) Time taken: 8 mins Laptop CPU: I7 with 480M GPU
- 34. PareTO: Maximize Strength Optimaldesign for Maximizing Strength (30% vol fraction) Time taken: 14 mins Laptop CPU: I7 with 480M GPU Optimal topology
- 35. Going beyond 3DPrinting
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- 37. Bridge Problem V =30% 1 min 10 secs
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- 40. Designing Braces forBuildings
- 41. Acknowledgements Graduate Students NSF UW-Madison Kulicke andSoffa Luvata Design Concepts Publications available at www.ersl.wisc.edu suresh@engr.wisc.edu