In this study, a combined analytical and finite element‐based micromechanical modeling is performed to characterize the elastic properties of carbon nanotube (CNT) reinforced polymer nanocomposites and validated with experimental work. First, coordinates of armchair and zigzag type CNTs are generated using MATLAB based on the geometric structure of the CNTs and imported to the computational software ANSYS to model and characterize the elastic properties of the individual single‐walled CNT (SWCNT) and multi‐walled CNT by applying various loading and boundary conditions. The present developed finite element method (FEM) model of CNTs is validated with the available literature in terms of elastic properties. Subsequently, the equivalent elastic properties of CNT reinforced epoxy nanocomposites are determined through representative volume element (RVE) model by finite element simulations and Mori‐Tanaka homogenization techniques by replacing CNTs with equivalent fibers as microinclusions. The equivalent elastic properties of nanocomposite obtained by the FEM and analytical model are compared and validated with the experimental results. Further, the detailed parametric study is performed to investigate the influence of tube chirality, volume fraction, and orientation of CNT in terms of the elastic properties of the nanocomposite. It was observed that the armchair type CNT reinforced nanocomposites are stiffer than the zigzag type SWCNT reinforced nanocomposites in terms of elastic moduli. Further, it was noticed that the tube chirality and the number of walls of CNTs have significantly influenced the elastic behavior of nanocomposites. It can be concluded that the presented combined model provides an efficient methodology and comprehensive understanding to analyze the elastic behavior of CNTs and CNT reinforced nanocomposites. So, the presented combined numerical and experimental study could serve as a guideline in micromechanical modeling and characterization of elastic behavior of CNT‐reinforced polymer nanocomposites.
In laminated composite structures, delamination is one of the most common defects. The delamination affects the vibration characteristics of laminates, and thus these indicators can be used to detect the potentially catastrophic failures and measures the health characteristics of laminates. In this study, particle swarm optimization (PSO) and artificial neural network (ANN) are used to optimize and predict the influences of location and size of delamination on the dynamic behavior of composite plates. The classical laminated plate theory
In this study, the instability regions of a honeycomb sandwich plate are investigated for different end conditions under periodic in-plane loading. The core layer of the sandwich plate is made of carbon nanotube (CNT)/glass fiber-reinforced honeycomb and the face layers of CNT/glass fiber- reinforced laminated composite. The governing equations are derived using classical laminated plate theory (CLPT) and solved numerically by using finite element formulation. The effectiveness of the developed finite element formulation is demonstrated by comparing the results in terms of natural frequencies with those available in the literature. The effects of CNT wt.% on the core material, CNT wt.% on the skin material, ply orientation and various end conditions on the variation of natural frequencies, loss factors and instability regions are studied. Finally, some inferences for the effects of CNT reinforcement on the honeycomb sandwich plate subjected to the periodic in-plane loads are discussed.
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