Hysteretic damping optimization in carbon nanotube nanocomposites

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.

[1]  G. Formica,et al.  Damage model of carbon nanotubes debonding in nanocomposites , 2013 .

[2]  K. W. Wang,et al.  Effect of functionalization of single-wall carbon nanotubes (SWNTs) on the damping characteristics of SWNT-based epoxy composites via multiscale analysis , 2011 .

[3]  F. Gardea,et al.  Energy dissipation due to interfacial slip in nanocomposites reinforced with aligned carbon nanotubes. , 2015, ACS applied materials & interfaces.

[4]  P. F. Lichtenwalner.  Neural network-based control for the fiber placement composite manufacturing process , 1993 .

[5]  M. AlMaadeed,et al.  Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks , 2016 .

[6]  Anders Logg,et al.  Automated Solution of Differential Equations by the Finite Element Method: The FEniCS Book , 2012 .

[7]  M. Cho,et al.  Multiscale modeling of interphase in crosslinked epoxy nanocomposites , 2017 .

[8]  M. Auad,et al.  Single-wall carbon nanotubes/epoxy elastomers exhibiting high damping capacity in an extended temperature range , 2009 .

[9]  Li Liu,et al.  Effect of nanofiller shape on viscoelasticity of rubber nanocomposite investigated by FEA , 2016 .

[10]  G. Lanzara,et al.  Moving towards high-power, high-frequency and low-resistance CNT supercapacitors by tuning the CNT length, axial deformation and contact resistance , 2012, Nanotechnology.

[11]  M. Shokrieh,et al.  The effect of time-dependent slightly weakened interface on the viscoelastic properties of CNT/polymer nanocomposites , 2016 .

[12]  Walter Lacarbonara,et al.  Nonlinear modeling of carbon nanotube composites dissipation due to interfacial stick–slip , 2014 .

[13]  R. Esmaeili,et al.  Modeling and optimization for microstructural properties of Al/SiC nanocomposite by artificial neural network and genetic algorithm , 2014, Expert Syst. Appl..

[14]  D. Khastgir,et al.  Hysteretic damping in XNBR – MWNT nanocomposites at low and high compressive strains , 2016 .

[15]  Sidney R. Cohen,et al.  Measurement of carbon nanotube-polymer interfacial strength , 2003 .

[16]  G. Formica,et al.  Three-dimensional modeling of interfacial stick-slip in carbon nanotube nanocomposites , 2017 .

[17]  Reshef Tenne,et al.  Stress-induced fragmentation of multiwall carbon nanotubes in a polymer matrix , 1998 .

[18]  Xiao-jie Li,et al.  Mechanical, thermal and interfacial performances of carbon fiber reinforced composites flavored by carbon nanotube in matrix/interface , 2017 .

[19]  F. Chang,et al.  Design and characterization of a carbon-nanotube-reinforced adhesive coating for piezoelectric ceramic discs , 2009 .

[20]  F. Gardea,et al.  Identification of energy dissipation mechanisms in CNT-reinforced nanocomposites , 2016, Nanotechnology.

[21]  V. Papadopoulos,et al.  Multiscale modeling of carbon nanotube reinforced concrete , 2017 .

[22]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[23]  M. Cho,et al.  Nonlinear multiscale modeling approach to characterize elastoplastic behavior of CNT/polymer nanocomposites considering the interphase and interfacial imperfection , 2013 .

[24]  V. Papadopoulos,et al.  The impact of interfacial properties on the macroscopic performance of carbon nanotube composites. A FE 2 -based multiscale study , 2016 .

[25]  F. Stan,et al.  Effect of processing parameters and strain rate on mechanical properties of carbon nanotube–filled polypropylene nanocomposites , 2014 .

[26]  Kiyoshi Tanaka,et al.  Ieee Transactions on Evolutionary Computation Computational Cost Reduction of Non-dominated Sorting Using the M-front , 2022 .

[27]  W. Lacarbonara,et al.  Nonclassical Responses of Oscillators with Hysteresis , 2003 .

[28]  M. Papadrakakis,et al.  The effect of interfacial shear strength on damping behavior of carbon nanotube reinforced composites , 2012 .

[29]  Savvas P. Triantafyllou,et al.  A hysteretic multiscale formulation for nonlinear dynamic analysis of composite materials , 2014 .

[30]  Walter Lacarbonara,et al.  Vibrations of carbon nanotube-reinforced composites , 2010 .