Hysteretic damping optimization in carbon nanotube nanocomposites
Source abstract
Abstract
Abstract Optimization of the hysteretic damping capacity of carbon nanotube (CNT) nanocomposites is carried out via a differential evolution algorithm coupled with an ad hoc finite element implementation of a nonlinear 3D mesoscale theory. Such theory describes the hysteresis due to the shear stick-slip between the nanotubes and the polymer chains of the hosting matrix. The amount of energy dissipated through the CNT-matrix stick-slip depends on the nanocomposite constitutive parameters such as the elastic mismatch, the nanofiller content/distribution, and the CNT-matrix interfacial shear strength . The optimization problem seeks to determine the set of material parameters that can give rise to the best damping capacity of the nanocomposite. The objective function is defined as the area below the damping ratio curve versus the strain amplitude over the range of strains of interest. The results confirm that the genetic-type nanocomposite damping optimization making use of a sound mechanical model of the material response can be an effective design method providing the right mix of phases overcoming a costly error-and-trial approach to manufacturing and testing.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Carbon Nanotubes in Composites · Nonlocal and gradient elasticity in micro/nano structures · Composite Structure Analysis and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (33)
Show source-provided references
1. Vibrations of carbon nanotube-reinforced composites10.1016/j.jsv.2009.11.020 ↗
2. Moving towards high-power, high-frequency and low-resistance CNT supercapacitors by tuning the CNT length, axial deformation and contact resistance10.1088/0957-4484/23/30/305401 ↗
3. Design and characterization of a carbon-nanotube-reinforced adhesive coating for piezoelectric ceramic discs10.1088/0964-1726/18/12/125001 ↗
4. Debonding model of carbon nanotubes in a nanostructured composite10.1016/j.compstruct.2012.08.049 ↗
5. The effect of interfacial shear strength on damping behavior of carbon nanotube reinforced composites10.1016/j.ijsolstr.2012.08.031 ↗
6. Nonlinear modeling of carbon nanotube composites dissipation due to interfacial stick-slip10.1016/j.ijplas.2013.07.009 ↗
7. Three-dimensional modeling of interfacial stick-slip in carbon nanotube nanocomposites10.1016/j.ijplas.2016.10.012 ↗
8. Mechanical, thermal and interfacial performances of carbon fiber reinforced composites flavored by carbon nanotube in matrix/interface10.1016/j.compstruct.2016.10.022 ↗
9. Single-wall carbon nanotubes/epoxy elastomers exhibiting high damping capacity in an extended temperature range10.1016/j.compscitech.2009.01.030 ↗
10. Energy dissipation due to interfacial slip in nanocomposites reinforced with aligned carbon nanotubes10.1021/acsami.5b01459 ↗
11. Identification of energy dissipation mechanisms in CNT-reinforced nanocomposites10.1088/0957-4484/27/10/105707 ↗
12. Hysteretic damping in XNBR e MWNT nanocomposites at low and high compressive strains10.1016/j.compositesb.2015.04.005 ↗
13. Effect of nanofiller shape on viscoelasticity of rubber nanocomposite investigated by FEA10.1016/j.compositesb.2015.10.020 ↗
14. Multiscale modeling of interphase in crosslinked epoxy nanocomposites10.1016/j.compositesb.2017.03.059 ↗
15. Effect of functionalization of single-wall carbon nanotubes (SWNTs) on the damping characteristics of SWNT-based epoxy composites via multiscale analysis10.1016/j.compositesa.2011.07.030 ↗
16. Nonlinear multiscale modeling approach to characterize elastoplastic behavior of CNT/polymer nanocomposites considering the interphase and interfacial imperfection10.1016/j.ijplas.2012.09.010 ↗
17. The impact of interfacial properties on the macroscopic performance of carbon nanotube composites. A FEM-based multiscale study10.1016/j.compstruct.2015.10.025 ↗
18. The effect of time-dependent slightly weakened interface on the viscoelastic properties of CNT/polymer nanocomposites10.1016/j.compstruct.2016.03.022 ↗
19. Multiscale modeling of carbon nanotube reinforced concrete10.1016/j.compstruct.2017.09.061 ↗
20. A hysteretic multiscale formulation for nonlinear dynamic analysis of composite materials10.1007/s00466-014-1032-2 ↗
21. Nonclassical responses of oscillators with hysteresis10.1023/A:1024423626386 ↗
22. Lacarbonara · 2013
23. Seifert R, Patil M, Seidel G, Reich G. Multi-functional topology optimization of piezoresistive nanocomposite beams. In: ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems; 2015: paper No. SMASIS2015-8958.10.1115/SMASIS2015-8958 ↗
24. Effect of processing parameters and strain rate on mechanical properties of carbon nanotube-filled polypropylene nanocomposites10.1016/j.compositesb.2013.11.023 ↗
25. Optimization and prediction of mechanical and thermal properties of Graphene/LLDPE nanocomposites by using artificial neural networks10.1155/2016/5340252 ↗
26. Modeling and optimization for microstructural properties of Al/SiC nanocomposite by artificial neural network and genetic algorithm10.1016/j.eswa.2014.03.038 ↗
27. Thongvigitmanee T, May GS. Optimization of nanocomposite integral capacitor fabrication using neural networks and genetic algorithm. In: 27th Annual IEEE/SEMI International Electronics Manufacturing Technology Symposium; 2002. P. 123–29.10.1109/IEMT.2002.1032737 ↗
28. Neural network-based control for the fiber placement composite manufacturing process10.1007/BF02650058 ↗
29. Logg · 2012
30. Differential evolution. A simple and efficient heuristic for global optimization over continuous spaces10.1023/A:1008202821328 ↗
31. Computational cost reduction of nondominated sorting using the M-front10.1109/TEVC.2014.2366498 ↗
32. Measurement of carbon nanotube-polymer interfacial strength10.1063/1.1579568 ↗
33. Stress-induced fragmentation of multiwall carbon nanotubes in a polymer matrix10.1063/1.120680 ↗