In nearly all mechanical constructions, vibrations can gradually damage structures. For that reason, it is imperative to develop a mathematical model that describes these vibrations for the purpose of minimizing their consequences during the design. If we consider the structure’s size and complexity, as well as the repetitive nature which characterizing these procedures, an exact reanalysis is a long and expensive option. That being the case, several methods have been developed to help predict a system’s dynamic behavior. In this work, we develop a method of Modal Reanalysis, which is precise, efficient, and useful for both conservative and dissipative structures. This technique can also decrease issues related to these structures, and consider the effects resulting from modal truncation. The originality lies in the structure of the obtained formula, where attention is focused on the contribution of the unknown modes. Such contribution can be either calculable for a finite element model, or identifiable from experiment model tests.
This article is composed of two parts, the first part is devoted to a presentation of five metaheuristic optimization algorithms, the SSA algorithm (the salp swarm algorithm) which is based on the linear displacement of salps in the oceans to find their target, the CSA algorithm (the cuckoo search algorithm) which is based on the behavior of cuckoos to find and lay their eggs in host nests, the GWO algorithm (the optimization of gray wolves ) which is based on the behavior of gray wolves in nature through a social hierarchy, the FA algorithm (the firefly algorithm) which is based on the light attractiveness of fireflies to each other in nature and finally the BA algorithm (the bat algorithm) which is based on the process of hunting micro bats through echolocation. And the second part concerns the resolution of a constrained real mechatronic optimization problem, it is about a numerical computation by the algorithms which one discussed in the first part, of the optimal geometry of a support of a marketing plate, under well-defined constraints, this support must guarantee mechanical resistance against compressive and buckling forces generated by the plate, and according to the results obtained by each algorithm we will deduce the optimal solution of the problem.
This study deals with highlighting the effect of punched copper sheet-based reinforcement on the microstructural and mechanical properties of Al-based metallic composite with 1100 Al sheets acting as a matrix. Consequently, homogeneous and heterogeneous joints were prepared based on diffusion bonding and were analyzed by optical microscope (OM) and scanning electronic microscope, for the mechanical properties of the prepared composites without heat treatment and after aging at 180°C were measured by microhardness tester and tensile test machine, the experimental results demonstrated good adherence of Al and Cu as well as high mechanical properties in the case of punched Cu sheet.
Researchers and scientific developers today have a huge amount of data to process, they need a solution as quickly as possible, which is why they have developed this metaheuristic based on natural genetic evolution. The genetic algorithm does not take into account all the alternatives, but it is a quick technique to find a decent solution to problems with a lot of data. In many areas, data must be processed as quickly as possible and in this article we have discussed a new way to find the optimum coverage ratio for futures contracts, with the objective of decreasing the risk that one must face in the derivatives market, against fluctuations in the prices of any underlying asset of the futures contracts either commodities, exchange rates or stock market indices ..., in our case we have chosen oil as an example of an application on the fluctuation of commodity prices of a 10-year data margin, by applying the Ederington variance minimization hedge model as an objective function of our genetic optimization algorithm on MATLAB software.
Lightweight electronic devices and increasing power density are driving designers to constantly improve the performance of electronic systems. Among the frequent loads experienced by this equipment are electrical power cycles and thermal cycles. The combination of these cycles often leads to the failure of the electronic device and consequently to the failure of the entire system. Among the most stressed components in this equipment are the solder joints, whose material is SAC305. In this study, the aim is to study the evolution of the thermal gradient in the case of Power Cycling and Thermal Cycling, either alternated, so it is the Joule and Peltier effects alone, or combined, so it is the combination of the two effects mentioned above plus the heat flow generated during the submission of the equipment in a virtual thermal chamber and its impact on the thermal deformation of solder joints. The finite element method (FEM) is used to simulate the coupled electrical, thermal and mechanical fields in the assembly and to evaluate the response of the solder joints exposed to the mentioned process. Stresses and Strains are evaluated.
The work that has been done in this paper is to describe the method used in crash simulation that is suitable in the ground transportation industry. The work was spread over three related phases; a theoretical approach which explains the method and the analytical equations to represent these crash phenomena based on the principle of virtual work. A numerical approach which explains the method of integration used in the codes of calculation to solve the analytical equation detailed in the first step, By basing on the method of the FE and the temporal integration with explicit schema for a better representativeness of this type of phenomenon. The last part focuses on a digital crash study case by detailing all the verification phases in order to guarantee the quality and the numerical credibility of the model which makes it possible to analyze the shock scenario and the objectives to be achieved.