The production and application of carbon nanotubes (CNTs) in different fields have increased exponentially in the last decades. CNT reinforced composites (CNTRC) materials exhibit exceptional strength and stiffness properties as well as improved fatigue performance and fracture toughness. In addition, CNTs are electrically conductive fillers and can form conductive networks in CNTRCs. The electrical conductivity and associated piezoresistive behaviors can, therefore, endow polymeric CNTRCs with strain self-sensing capabilities, making them ideal candidates for structural health monitoring (SHM) and related applications.
The electro-mechanical properties of CNTRCs are influenced by different factors, such as CNT type, alignment, volume fraction and aspect ratio. To evaluate such factors and enable material optimization, recent research efforts have focused on developing robust numerical techniques to predict the sensing capabilities of these materials. Notably, the performance and service life of CNTRC components are highly susceptible to crack growth. Therefore, it is important that numerical tools used to simulate crack-type defects in these composites be able to predict the influence of crack growth on the structural integrity and sensing capabilities of CNTRC components.
Herein, Professor Luis Rodríguez-Tembleque, Mr. J. Vargas, Dr. Enrique García-Macías, Professor Federico C. Buroni and Professor Andrés Sáez from Universidad de Sevilla developed an eXtended Finite Element Method (XFEM)-based computational framework for simulating the crack growth in CNTRC nanocomposite plates. The developed framework, was implemented in the commercial software ANSYS, was applied to conduct virtual monitoring of the effect of crack growth on the mechanical response, electrical conductivity and sensing performance of self-sensing CNTRC polymer plates. The work is currently published in the journal, Composite Structures.
In brief, the proposed framework follows a two-step scheme. In the first step, the mechanical properties were homogenized using the proposed framework to establish the strain responses of the cracked composites. In the second step, the electrical conductivity and piezoresistive properties of the elements within the composite domains were homogenized as per the strain state to compute the electrical resistance between the electrodes. These steps provided a clear definition of the non-homogenous electrical conductivity problem that was later solved using coupled-field elements provided by the ANSYS software. This framework was validated for stationary cracks and applied to a series of crack-growth configurations.
The authors have shown that the cracks and their growth significantly modified the electrical properties and self-sensing performance of the CNTRC. A better sensor efficiency was observed at lower crack permittivity. However, the piezoresistive effect under electrically impermeable crack-face conditions was generally negligible. This suggested that the crack-growth-induced discontinuity in the electrical field was relatively higher that piezoresistivity effects triggered by the strain field modification. Furthermore, the measured electrical resistances were highly sensitive to changes in the orientation and the size of the cracks.
In summary, the effects of crack growth on the electricalmechanical properties of CNTRC materials were successfully simulated and virtually monitored using the proposed numerical XFEM scheme. The changes in the electrical resistance between the electrodes, as well as changes in piezoresistivity, were correlated with the presence of cracks in the domains of the CNTRC plates, allowing prompt detection of the growth and severity of the cracks. The effectiveness and applicability of the proposed framework was successfully validated. In a statement to Advances in Engineering, Professor Luis Rodríguez-Tembleque, first and corresponding author stated that the study provided useful insights that would advance the application of CNTRC materials in virtual and on-site SHM.
Rodríguez-Tembleque, L., Vargas, J., García-Macías, E., Buroni, F.C., & Sáez, A. (2022). XFEM crack growth virtual monitoring in self-sensing CNT reinforced polymer nanocomposite plates using ANSYS. Composite Structures, 284, 115137.