Otimização multiobjetivo de vaso de pressão tipo IV para armazenamento de hidrogênio usando método dos elementos finitos e metodologia de superfície de resposta

Abstract

Hydrogen fuel cells for vehicles are entering the automotive market and many other markets, offering benefits such as reduced harmful gas emissions, enhanced energy security, and increased transportation efficiency. One of the major challenges in this field is the development of technologies for storing hydrogen in a manner that allows safe transportation and storage from the production site to the end consumer. Hydrogen storage requires a more sophisticated pressure storage vessel compared to a gasoline tank, for example. The primary challenge with hydrogen storage cylinders lies in their construction and design, particularly in identifying alternative materials and configurations of different fibers that can withstand the rated internal working pressure. In this study, numerical simulations will be conducted using the Finite Element Method (FEM) to evaluate various laminate configurations, including different orientations and fiber thicknesses. The objective is to assess the minimum probability of failure. To enhance computational efficiency, the Response Surface Methodology (RSM) will be utilized to create an objective function, which will be optimized using the Genetic Algorithm (GA). The ideal parameters of the pressure vessel will be validated using the Method of Finite Elements (MEF). Initially, numerical simulations will be performed using FEM on a type IV composite pressure vessel. A polyamide 6 (PA6) liner with a carbon fiber weave will be considered, along with different orientations and constant thickness of the laminated layers. The objective is to minimize the Tsai-Wu safety factor for each combination. Some data obtained from the FEM will be used to create a customized inverse factor (IRF) response surface model. This model will be used to determine the reserve strength of the material based on the Tsai-Wu Failure Criterion, which adequately represents the influence of these parameters on the mechanical response of the pressure vessel. Subsequently, the multi-objective optimization method of genetic algorithms will be employed to find the optimal values of the design variables that ensure the lowest weight and minimum probability of failure. The results demonstrate the effectiveness of this methodology, which will then be validated using the Finite Element Method (FEM) to confirm the ideal parameters of the pressure vessel.