• Composites Research
• /
• v.26 no.3
• /
• pp.201-206
• /
• 2013

The electrical resistance measurement was investigated as a damage monitoring method. In this study, 0.5 wt% Carbon nanotube reinforced polypropylene (CNT/PP) composites were evaluated under compressive fatigue loading. The shape of specimens was $20^{\circ}$ curved round type. Compression strength and electrical resistance were measured at different sections of specimen during compression. The microcracks of CNT/PP composites were detected based on the changing ratio of electrical resistance. Micro-damage during compressive fatigue test could be detected by electrical resistance measurements. The reason is that the contact points of CNTs in composites decreased under fatigue loading. During compressive fatigue test, larger change of electrical resistance was detected at the microcrack sections. It was proved that microcracks could be detected by electrical resistance measurement under compression test, whereas the real delamination parts were consistent with the predicted results by electrical resistance measurement.

• Advances in materials Research
• /
• v.13 no.1
• /
• pp.1-18
• /
• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.