The aim of this study is to analyze the effect of different geometries and sections on the mechanical properties of epoxy specimens. Five tensile tests were carried out on three types of series. The experimental results obtained were 1812.21 MPa, 3.90% and 41.91 MPa for intact specimens, 1450.41 MPa, 2.16% and 21.28 MPa for specimens with hole and 750.77 MPa, 2.77% and 11.89 MPa for specimens with elliptical -notched for Young's modulus, strain and stress respectively. In addition, the experimental results indicated that the mechanical properties of both (Young's modulus value and stress value) were higher in an intact specimen. Afterwards, the nonlinear functional relationship of input parameters between epoxy sample geometries and sections was established using the response surface model (RSM) and the artificial neural network (ANN) to predict the output parameters of mechanical properties (Young's modulus and stress). In addition, the design of experiment was developed by the Analysis of the Application of Variance (ANOVA). The results showed the superiority of the ANN model over the RSM model, where the correlation coefficient values for the model datasets exceed ANN (R2 = 0.984 for Young's modulus and R2 = 0.981 for the constraint).

The presence of geometric discontinuity in a material reduces considerably its resistance to mechanical stresses, therefore reducing the service life of materials. The analysis of structural behaviour in the presence of geometric discontinuities is important to ensure the proper use, especially if it is regarding a material of weak mechanical properties such as a polymer. The objective of the present work is to analyse the effect of the notch presence of variable geometric shapes on the tensile strength of epoxy-type polymer specimens. A series of tensile tests were carried out on standardised specimens, taking into account the presence or absence of a notch. Each series of tests contains five specimens. Two notch shapes were considered: circular (hole) and elliptical. The experimental results in terms of stress–strain clearly show that the presence of notches reduces considerably the resistance of the material, where the maximum stress for the undamaged specimen was 41.22 MPa and the lowest stress for the elliptical-notched specimen was 11.21 MPa. A numerical analysis by the extended finite element method (XFEM) was undertaken on the same geometric models; in addition, the results in stress–strain form were validated with the experimental results. A remarkable improvement was obtained (generally an error within 0.06%) for strain, maximum stress, Young’s modulus and elongation values. An exponential decrease was noted in the stress, strain, and Young’s modulus in the presence of a notch in the material.

Partial shading conditions (PSCs) in photovoltaic (PV) systems generate multiple local maximum power points (LMPPs) and a single global maximum power point (GMPP) in the power–voltage (P–V) characteristics, challenging conventional maximum power point tracking (MPPT) methods. This study presents an FPGA-in-the-Loop (FIL) co-simulation of a Systematic-Sequencing Adaptive Particle Swarm Optimization (SS-APSO) algorithm for MPPT under dynamically varying shading conditions. The proposed method combines deterministic particle initialization, adaptive particle reordering, and switching among wide exploration, re-exploration and exploitation modes to enhance global search capability. The controller is implemented on a Xilinx Artix-7 FPGA using fixed-point arithmetic and a finite-state-machine architecture in VHDL and is evaluated through MATLAB/Simulink–FIL co-simulation for two PV configurations: four series-connected modules (4S) and two parallel-connected strings of two series modules (2S2P). The results demonstrate tracking efficiencies generally exceeding 98% under different shading within 0.181 s for both configurations, while in FIL co-simulation, it reaches the GMPP within 0.203. The close agreement between simulation and FIL co-simulation results demonstrates the effectiveness of the proposed SS-APSO-MPPT controller for PV systems.

Insulated panels play a crucial role due to their ability to offer a lightweight and cost-effective solution for various applications across different fields, characterised by diverse geometries. In this investigation, three distinct honeycomb shapes - hexagonal, RE-entrant, and starfish - each measuring 57 mm x 120 mm with a thickness of 10 mm, are selected. Epoxy compounds reinforced with date palm, jute, and luffa fibres are utilised in the study. The design of these honeycomb structures was executed using CATIA V5R20® software, while their load-bearing capacity (under compression) was numerically analysed using the ABAQUS-CAE® calculation code. A comparative numerical analysis was conducted to evaluate the performance of the samples based on the different types of honeycombs employed. Following compression tests conducted at a rate of 0.2 mm/min, the findings revealed that the starfish structure exhibited the highest pressure-carrying capacity. Specifically, it sustained loads of 2220.75 N for the epoxy sample, 3107.74 N for the date palm fibre samples, and 3352.20 N for sisal fibre samples. Notably, the sisal fibre sample demonstrated the highest strength, 4338.33 N, while comparatively lower strength values were observed for RE-entrant geometries, particularly for the honeycomb reinforced with date palm fibres.

The primary aim of this research is to enhance the distribution of rotor blades in a turbofan engine to achieve superior static balancing. To this end, an advanced optimisation method is proposed to ensure that the mass imbalance correction stays within the allowed tolerance limits, even after the rotor blades' positions are altered during maintenance activities. This proposed method leverages a genetic algorithm that is refined through the integration of various optimisation techniques. The use of MATLAB® code plays a crucial role in this process, providing the computational power and flexibility needed to implement and test the optimisation algorithm effectively. In practical terms, the method involves adjusting the positions of the rotor blades to minimise the static imbalance, which can significantly impact the performance and longevity of the engine. By maintaining the mass correction within specified tolerances, the engine can operate more smoothly and efficiently, reducing wear and tear and potentially extending its operational lifespan. The integration of MATLAB® allows for precise calculations and simulations, ensuring that the proposed adjustments are both feasible and effective in real-world scenarios. This approach not only improves the immediate balance of the rotor but also ensures that the balance is maintained over time, even with the positional changes that occur during routine maintenance.