journal article·2021-09

Design of porous and graded NiTi smart energy absorbers considering synthetic uncertainty in parameters

Sourav Gur, George N Frantziskonis

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Abstract

The synthetic uncertainty (SU) method is introduced and applied to the optimal design of energy absorbing NiTi shape memory alloy (SMA) bars. A sensitivity analysis for a large number of stochastic parameters identifies geometrical grading, porosity, and imposed maximum nominal stress as critical design parameters for the energy dissipation capacity of the bars. Parametric uncertainty on the optimal design of the energy absorber is incorporated and estimated through the SU formalism. The SU method provides a unified approach to discover the critical design parameters, quantify uncertainty, and optimally design a system around its extreme response (maximum or minimum). Therefore, the SU method is placed next to the robust design optimization (RDO) process, yet with a discovery component. It is found that variations in porosity and shape factor can significantly alter the stress-strain response and energy dissipation capacity. For a given value of maximum nominal stress, it is found that there exists an optimal combination of shape factor and porosity which maximizes the energy dissipation capacity of a tapered and porous NiTi bar.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Shape Memory Alloy Transformations · Topology Optimization in Engineering · Probabilistic and Robust Engineering Design

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Civil and Environmental Engineering, Indian Institute of Technology Patna, Patna, Bihar, India

Civil and Architectural Engineering and Mechanics, University of Arizona, Tucson, AZ, USA

Materials Science and Engineering, University of Arizona, Tucson, AZ, USA

Funding

science and engineering research board · Indian Institute of Technology (IIT) Patna

References (50)

Show source-provided references
1. 10.1007/s00707-014-1191-410.1007/s00707-014-1191-4 ↗
2. 10.1016/j.jmbbm.2014.11.02310.1016/j.jmbbm.2014.11.023 ↗
3. 10.1137/05064514210.1137/050645142 ↗
4. 10.1137/10078635610.1137/100786356 ↗
5. 10.1017/S096249290400018210.1017/S0962492904000182 ↗
6. 10.1016/j.commatsci.2012.02.03110.1016/j.commatsci.2012.02.031 ↗
7. 10.1186/1752-0509-8-7710.1186/1752-0509-8-77 ↗
8. 10.1088/1361-651X/aa666210.1088/1361-651X/aa6662 ↗
9. 10.1155/2016/751264210.1155/2016/7512642 ↗
10. 10.1088/0965-0393/24/7/07500610.1088/0965-0393/24/7/075006 ↗
11. 10.1002/stc.202110.1002/stc.2021 ↗
12. 10.1016/j.commatsci.2018.05.03110.1016/j.commatsci.2018.05.031 ↗
13. 10.1177/1045389X1558862810.1177/1045389X15588628 ↗
14. 10.1016/j.ymssp.2015.10.00410.1016/j.ymssp.2015.10.004 ↗
15. 10.1177/1045389X1987340810.1177/1045389X19873408 ↗
16. 10.1007/0-387-34471-310.1007/0-387-34471-3 ↗
17. Lagoudas DC · Shape Memory Alloys: Modeling and Engineering Applications · 2008
18. 10.1007/s00707-015-1433-010.1007/s00707-015-1433-0 ↗
19. 10.1016/j.jallcom.2008.02.05910.1016/j.jallcom.2008.02.059 ↗
20. 10.1016/j.commatsci.2013.03.01110.1016/j.commatsci.2013.03.011 ↗
21. 10.1063/1.487671510.1063/1.4876715 ↗
22. 10.1016/S1359-6462(99)00255-910.1016/S1359-6462(99)00255-9 ↗
23. 10.1140/epjb/e2011-20661-410.1140/epjb/e2011-20661-4 ↗
24. Nekouei M · Acta Mechanica · 2019 · 13 · 1
25. 10.1093/comjnl/7.4.30810.1093/comjnl/7.4.308 ↗
26. 10.1115/1.216524110.1115/1.2165241 ↗
27. 10.1016/j.ijsolstr.2008.06.00510.1016/j.ijsolstr.2008.06.005 ↗
28. 10.1615/Int.J.UncertaintyQuantification.v1.i2.4010.1615/Int.J.UncertaintyQuantification.v1.i2.40 ↗
29. Raykar VC · 2006 · 524
30. 10.1007/s00158-013-0883-z10.1007/s00158-013-0883-z ↗
31. 10.1016/j.actamat.2013.02.03210.1016/j.actamat.2013.02.032 ↗
32. 10.1016/j.jallcom.2012.06.02710.1016/j.jallcom.2012.06.027 ↗
33. 10.1016/j.matdes.2013.03.09110.1016/j.matdes.2013.03.091 ↗
34. 10.1016/j.jallcom.2011.12.15110.1016/j.jallcom.2011.12.151 ↗
35. 10.1088/0964-1726/22/2/02503010.1088/0964-1726/22/2/025030 ↗
36. 10.1177/1045389X1350578310.1177/1045389X13505783 ↗
37. 10.1016/j.matdes.2017.03.06910.1016/j.matdes.2017.03.069 ↗
38. Taguchi G · 1987
39. Taylor JR · 1983
40. 10.1016/S0020-7683(00)00315-210.1016/S0020-7683(00)00315-2 ↗
41. 10.1016/j.mechmat.2003.05.00310.1016/j.mechmat.2003.05.003 ↗
42. 10.1137/S106482750138782610.1137/S1064827501387826 ↗
43. 10.1016/j.ijimpeng.2003.08.00710.1016/j.ijimpeng.2003.08.007 ↗
44. 10.1016/j.cma.2014.01.02710.1016/j.cma.2014.01.027 ↗
45. 10.1016/j.msea.2007.02.14710.1016/j.msea.2007.02.147 ↗
46. 10.1016/j.jallcom.2012.09.14510.1016/j.jallcom.2012.09.145 ↗
47. 10.1016/j.scriptamat.2007.07.04310.1016/j.scriptamat.2007.07.043 ↗
48. 10.1021/jp401670r10.1021/jp401670r ↗
49. 10.1115/1.219825010.1115/1.2198250 ↗
50. 10.1016/j.ijsolstr.2005.06.04310.1016/j.ijsolstr.2005.06.043 ↗