Dynamic simulation provides an efficient approach for improving the efficiency of parabolic trough power plants and control circuits. In the dynamic simulation, the possibilities and operating conditions of the plant are evaluated regarding materials, processes, emissions, or economics. Several studies related to the dynamic simulation of the parabolic trough technology are summarised and discussed in this work. This study is the first research that presents a thorough description of the advanced control circuits used in the solar field and thermal storage system of a parabolic trough power plant. This power plant was implemented using advanced process simulation software (APROS). The dynamic model was built based on the real specifications of the power plant.

Thin-walled members are increasingly used in structural applications, especially in light structures like in constructions and aircraft structures because of their high strength-to-weight ratio. Perforations are often made on these structures for reducing weight and to facilitate the services and maintenance works like in aircraft wing ribs. This type of structures suffers from buckling phenomena due to its dimensions, and this suffering increases with the presence of holes in it. This study investigated experimentally and numerically the buckling behavior of aluminum alloy 6061-O thin-walled lipped channel beam with specific holes subjected to compression load. A nonlinear finite elements analysis was used to obtain the buckling loads of the beams. Experimental tests were done to validate the finite element results. Three factors namely; shape of holes, opening ratio  D/Do and the spacing ratio S/Do were chosen to study their effects on the buckling strength of the channel beams. Finite elements results were obtained by using Taguchi method to identify the best combination of the three parameters for optimum critical buckling load, whereas determining the contribution of each parameter on buckling strength was implemented by using the analysis of variance technique (ANOVA) method. Results showed that the combination of parameters that gives the best buckling strength is the hexagonal hole shape, D/Do=1.7 and S/Do= 1.3 and the opening ratio (or size of holes) is the most effective on buckling behavior.

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The inverse kinematic equation for a robot is very important to the control robot’s motion and position. The solving of this equation is complex for the rigid robot due to the dependency of this equation on the joint configuration and structure of robot link. In light robot arms, where the flexibility exists, the solving of this problem is more complicated than the rigid link robot because the deformation variables (elongation and bending) are present in the forward kinematic equation. The finding of an inverse kinematic equation needs to obtain the relation between the joint angles and both of the end-effector position and deformations variables. In this work, a neural network has been proposed to solve the problem of inverse kinematic equation. To feed the neural network, experimental data were taken from an elastic robot arm for training the network, these data presented by joint angles, deformation variables and end-effector positions. The results of network training showed a good fit between the output results of the neural network and the targets data. In addition, this method for finding the inverse of kinematic equation proved its effectiveness and validation when applying the results of neural network practically in the robot’s operating software for controlling the real light robot’s position.