Different industrial applications frequently use overhead cranes for moving and lifting huge loads. It applies to civil construction, metallurgical production, rivers, and seaports. The primary purpose of this paper is to control the motion/position of the overhead crane using a PID controller using Genetic Algorithms (GA) and Bee Algorithms (BA) as optimization tools. Moreover, Fuzzy Logic modified PID Controller is applied to obtain better controller parameters. The mathematical model uses an analytical method, and the PID model employs Simulink in MATLAB. The paper presents the PID parameters determination with a different approach. The development of membership functions, fuzzy rules employ the Fuzzy Logic toolbox. Both inputs and outputs use triangular membership functions. The result shows that the optimized value of the PID controller with the Ziegler-Nichols approach is time-consuming and will provide only the initial parameters. However, PID parameters obtained with the optimization method using GA and BA reached the target values. The results obtained with the fuzzy logic controller (0.227% overshoot) show improvement in overshoot than the conventional PID controller (0.271% overshoot).

The impact of environmental conditions on the mechanical properties of composites is critical for various industries, particularly marine. The paper examines the effect of saltwater conditions on the mechanical properties of basalt, carbon, and glass fibers/epoxy hybrid composites. The composite samples were manufactured using Vacuum Assisted Resin Transfer Molding (VARTM) and then immersed in saltwater solution before tests. The tests were performed using Instron 8801 with 100 kilonewtons (kN) capacity. The environmental effects on the mechanical properties were supported by the Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) analysis of the water. The ICP-OES analysis result shows a transfer of ions from the fiber to the saltwater solution. As a result, the mass gain of all the samples increases with the conditioning period, while the tensile and flexural properties show degradation. Moreover, the hybrid composites show a gradual failure mode compared with non-hybrid composites. In addition, the failure modes and morphological analysis of the failed test samples were presented. Delamination, explosive failure, and fiber breakage characterize the tensile failure mode of basalt/epoxy (BE) and its hybrids. However, the glass/epoxy (GE) and carbon/epoxy (CE) show fractures in two or three sections. In addition, compressive failure, tensile failure, shear failures, delamination, and fiber breakage were detected in the flexural samples.

Fatigue is a sudden failure of components below the maximum strength of the material when subjected to repeated loading. This paper studies the fatigue behavior of basalt, carbon, and glass fibers/epoxy hybrid composites under three-point flexural loading and a saltwater environment. Five different composite panels were manufactured using the VARTM. The samples were then immersed in a saltwater solution for 60, 120, and 180 days before conducting the tests. Three-point static and fatigue tests were conducted using UTM as per ASTM D7264-07 and ASTM D7774-12. The S-N and stiffness degradation curves were plotted, and the morphology of the fatigue samples was investigated using SEM. In addition, the ion penetration in the solution was detected with ICP-OES analysis. The result shows that bending fatigue properties of all composite samples show a degradation as the immersion period increases. This might be due to micro-hole formation as the ions move from the sample to the saltwater solution. K E Y W O R D S flexural test, hybrid composites, ICP-OES, saltwater condition, SEM, three-point fatigue Highlights • Composite specimens were immersed in a saltwater solution for 2, 4, and 6 months.

The optimal design of parameters is vital for the effective use of hybrid composite laminated structures. This is due to a highly dependent property of laminated composite structures strength on its fiber orientation, stacking sequence and the number of ply in each laminate. The main aim of this study is to apply Learning-Oriented Artificial Algae Algorithm for optimization of the weight of rectangular hybrid composite laminated plate subjected to compressive in-plane loading. The design parameters are number of plies and stacking sequence of the laminate. The critical buckling factor is the constraint of the optimization process. The parameters of the hybrid composite plate are optimized using Learning-Oriented Artificial Algae Algorithm with the aim of minimizing weight. The performance of the algorithm was compared with previous studies that employed the GA and ACO algorithms. The Learning-Oriented method is integrated to reduce the number of functions evaluated and in turn reducing computational cost. The results showed that Learning-Oriented Artificial Algae Algorithm outperformed GA and ACO, and hence can be successfully applied in the optimization of laminated composite structures.