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This study proposes a duty cycle-based direct search method that capitalizes on a bioinspired optimization algorithm known as the salp swarm algorithm (SSA). The goal is to improve the tracking capability of the maximum power point (MPP) controller for optimum power extraction from a photovoltaic system under dynamic environmental conditions. The performance of the proposed SSA is tested under a transition between uniform irradiances and a transition between partial shading (PS) conditions with a focus on convergence speed, fast and accurate tracking, reduce high initial exploration oscillation, and low steady-state oscillation at MPP. Simulation results demonstrate the superiority of the proposed SSA algorithm in terms of tracking performance. The performance of the SSA method is better than the conventional (hill-climbing) and among other popular metaheuristic methods. Further validation of the SSA performance is conducted via experimental studies involving a DC-DC buck-boost converter driven by TMS320F28335 DSP on the Texas Instruments Experimenter Kit platform. Hardware results show that the proposed SSA method aligns with the simulation in terms of fast-tracking, convergence speed, and satisfactory accuracy under PS and dynamic conditions. The proposed SSA method tracks maximum power with high efficiency through its superficial structures and concepts, as well as its easy implementation. Moreover, the SSA maintains a steady-state oscillation at a minimum level to improve the overall energy yield. It thus compensates for the shortcomings of other existing methods.

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Carbon-fiber-reinforced plastic materials have attracted several applications, including the fused deposition modelling (FDM) process. As a cheaper and more environmentally friendly alternative to its virgin counterpart, the use of milled recycled carbon fiber (rCF) has received much attention. The quality of the feed filament is important to avoid filament breakage and clogged nozzles during the FDM printing process. However, information about the effect of material parameters on the mechanical and physical properties of short rCF-reinforced FDM filament is still limited. This paper presents the effect of fiber loading (10 wt%, 20 wt%, and 30 wt%) and fiber size (63 µm, 75 µm, and 150 µm) on the filament’s tensile properties, surface roughness, microstructure, porosity level, density, and water absorptivity. The results show that the addition of 63 µm fibers at 10 wt% loading can enhance filament tensile properties with minimal surface roughness and porosity level. The addition of rCF increased the density and reduced the material’s water intake. This study also indicates a clear trade-off between the optimized properties. Hence, it is recommended that the optimization of rCF should consider the final application of the product. The findings of this study provide a new manufacturing strategy in utilizing milled rCF in potential 3D printing-based applications.

This studyaimed at improving the performance and efficiency of conventional static photovoltaic (PV) systems by introducing a metaheuristic algorithm-based approach that involves reconfiguring electrical wiring using switches under different shading profiles. Themetaheuristicalgorithmused wasthe firefly algorithm (FA), which controls the switching patterns under non-homogenous shading profiles and tracks the highest global peak of power produced by the numerous switching patterns. This study aimed to solve the current problems faced by static PV systems, such as unequal dispersion of shading affecting solar panels, multiple peaks, and hot spot phenomena, which can contribute to significant power loss and efficiency reduction. The experimental setup focusedon software development and the system or model developed in the MATLAB Simulink platform. Athorough and comprehensive analysis was done by comparing the proposed method’s overall performance and power generation with thenovel static PVseries–parallel (SP) topology and totalcross-tied (TCT) scheme. The SP configuration is widely used in the PV industry. However, the TCT configuration has superior performance and energy yield generation compared to other static PV configurations, such as the bridge-linked (BL) and honey comb (HC) configurations. The results presented in this paper provide valuable information about the proposed method’s features with regard toenhancing the overall performance and efficiency of PV arrays.

Drilling is an essential secondary process for near net-shape of hybrid composite as to achieve the required dimensional tolerances prior to final application. Dimensional tolerance is often influenced by the surface integrity or surface roughness of the workpart. Thus, this paper aims to employ the Taguchi and response surface methodologies in minimizing the surface roughness of drilled carbon-glass hybrid fibre reinforced polymer (CGCG) using tungsten carbide, K20 drill bits. The effects of spindle speed, feed rate and tool geometry on surface roughness were evaluated and optimum cutting conditions for minimizing the aforementioned response was determined. Subsequently, response surface methodology (RSM) was utilised in finding the empirical relationships between experimental parameters and surface roughness based on the Taguchi results. The experimental analyses reveal that surface roughness is greatly influenced by feed rate and tool geometry rather than the spindle speed. This is due to the increment of feed that attributed to the increased strain rate and hence, deteriorated the surface roughness of the hybrid composite. The predicted results (via regression model) and theoretical results (via additivity law) were in good agreement with experiment results. This indicates that the regression model from response surface methodology (RSM) can be used to predict the surface roughness in machining of CGCG hybrid composite.

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Fibre reinforced composites are widely used in various sectors such as aerospace, wind energy and automotive. Due to its versatility and low cost for rapid prototyping and production applications, additive manufacturing technology has grown exponentially over the past few years. In this paper, performances of glass fibre and carbon fibre reinforced composites in additive manufacturing are reviewed from the perspective of mechanical properties. From the review, the reinforcements generally improve mechanical properties, in particular for tensile modulus and tensile strength. The paper presents a benchmark of additive manufacturing technologies for composite material as well as the spotlights of further research in the usage of carbon and glass fibres in rapid prototyping processes.