This paper presents a finite element (FE) model developed using commercial FE software COMSOL to simulate the multiphysical process of pieozoelectric vibration energy harvesting (PVEH), involving the dynamic mechanical and electrical behaviours of piezoelectric macro fibre composite (MFC) on carbon fibre composite structures. The integration of MFC enables energy harvesting, sensing and actuation capabilities, with applications found in aerospace, automotive and renewable energy. There is an existing gap in the literature on modelling the dynamic response of PVEH in relation to real-world vibration data. Most simulations were either semi-analytical MATLAB models that are geometry unspecific, or basic FE simulations limited to sinusoidal analysis. However, the use of representative environment vibration data is crucial to predict practical behaviour for industrial development. Piezoelectric device physics involving solid mechanics and electrostatics were combined with electrical circuit defined in this FE model. The structure was dynamically excited by interpolated vibration data files, while orthotropic material properties for MFC and carbon fibre composite were individually defined for accuracy. The simulation results were validated by experiments with <10% deviation, providing confidence for the proposed multiphysical FE model to design and optimise PVEH smart composite structures.

A sustainable power supply for a wide range of applications, such as powering sensors for structural health monitoring and wireless sensor nodes for data transmission and communication used in unmanned air vehicles, automobiles, renewable energy sectors, and smart city technologies, is targeted. This paper presents an experimental and numerical study that describes an innovative technique to harvest energy resulted from environmental vibrations. A piezoelectric energy harvester was integrated onto a carbon fibre reinforced polymer (CFRP) laminate structure using the co-curing method. The integrated composite with the energy harvester was lightweight, flexible and provided robust and reliable energy outcomes, which can be used to power different low-powered wireless sensing nodes. A normalised power density of 97 µW cm −3 m −2 s 4 was obtained from resonance frequency of 46 Hz sinusoidal waves at ampitlude of 0.2 g; while the representative environmental vibration waves in various applications (aerospace, automotive, machine and bridge infrastructure) were experimentally and numerically investigated to find out the energy that can be harvested by such a multifunctional composite structure. The results showed the energy harvested at different vibration input from various industrial sectors could be sufficient to power an autonomous structural health monitoring system

The introduction of heterogeneous wireless mesh technologies provides an opportunity for higher network capacity, wider coverage, and higher quality of service (QoS). Each wireless device utilizes different standards, data formats, protocols, and access technologies. However, the diversity and complexity of such technologies create challenges for traditional control and management systems. This paper proposes a heterogeneous metropolitan area network architecture that combines an IEEE 802.11 wireless mesh network (WMN) with a long-term evolution (LTE) network. In addition, a new heterogeneous routing protocol and a routing algorithm based on reinforcement learning called cognitive heterogeneous routing are proposed to select the appropriate transmission technology based on parameters from each network. The proposed heterogeneous network overcomes the problems of sending packets over long paths, island nodes, and interference in WMNs and increases the overall capacity of the combined network by utilizing unlicensed frequency bands instead of buying more license frequency bands for LTE. The work is validated through extensive simulations that indicate that the proposed heterogeneous WMN outperforms the LTE and Wi-Fi networks when used individually. The simulation results show that the proposed network achieves an increase of up to 200% in throughput compared with Wi-Fi-only networks or LTE-only networks.

Structural health monitoring is directly linked to structural performance, hence it is one of the main parameters in the safety of operation. This paper presents the development of an innovative structural health monitoring system for woven fabric carbon fibre reinforced polymer (CFRP) laminates fabricated using both vacuum assisted resin transfer moulding and pre-preg technique. The sensing system combines the ability to monitor strain due to applied loads, as well as to detect, and assess damage due to low velocity impact events. Bending loads were applied on a beam-type specimen and changes in electrical resistance, due to piezoresistivity of carbon fibres, were monitored. The change in electrical resistance was a function of applied load and reversible up to 0.13 % strain. Two thicknesses of composite panel, 2.09 (vacuum assisted resin transfer moulding) and 1.63 mm (pre-preg) were made, and were subjected to a range of low velocity impact energies. The resultant damage areas, as measured using ultrasonic C-scanning, were plotted against changes in electrical resistance to provide a correlation plot of damage area against impact energy. An inverse analysis, using this correlation plot, was performed to predict the damage area from a

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