Search

This work involved the precise prediction and in‐depth analysis of cure‐induced warping of T‐shaped parts with inconsistent layup. First, the warping mechanism of this kind of part was studied. Then, a finite element analysis (FEA) that considered the parts' structural characteristics and inconsistent layup using the curing mechanical constitutive model was developed to predict the warping. Following verification of the model's accuracy, the effects of material and structural characteristics on warping were investigated. When designing T‐shaped parts, selecting materials with lower thermal expansion coefficients can help minimize warping. Additionally, increasing the radius of the chamfer at the rib and flange connections is also effective. By taking into account the effects of structural parameters and inconsistent layup by using both classical laminated plate theory and artificial neural networks (ANN), a rapid and accurate surrogate model for warping prediction was finally developed. It was discovered that the two‐layer ANN model performed better than the other two models and could predict warping with accuracy and speed. For the parts analyzed in this work, this model is able to identify the fluctuations of warping captured by FEA. Moreover, by defining deviation as the difference between the predicted values of the surrogate model and the FEA, it can be observed that the majority of deviations for the validation set are within ±1.5 mm. This demonstrates that the two‐layer ANN possesses strong generalization ability and high accuracy in predicting warping. Highlights: The inconsistent layup could significantly affect the T‐shaped part's warping.Cutting off a part's rib may significantly reduce its warping.A rapid and accurate model for warping prediction was developed.The layup and structure's influence could be identified by the two‐layer ANN. [ABSTRACT FROM AUTHOR]

Highlights The objective of this work is to devise a post‐forming technique capable of accurately and significantly altering the shape of fully cured thermosetting composite parts. To accomplish this goal, the viscoelastic behavior and resulting deformation of fully cured parts at elevated temperatures were predicted and examined using viscoelastic mechanics, finite element analysis (FEA), surrogate modeling, and the particle swarm optimization (PSO) method. Firstly, the mechanism of fully cured parts' shape adjustment based on viscoelastic mechanics was introduced, and a method was established for the inverse identification of the stress relaxation ratio in the different directions of material. Secondly, an FEA model for predicting post‐forming was developed based on the standard linear‐solid viscoelastic model. A dataset was then compiled using parameterized FEA to train a rapid prediction model for post‐forming. The influence of various forming and structural parameters on the post‐forming process was examined. The results indicate that layup has the most significant impact, followed by displacement and temperature. The radial basis function was selected to construct the precise surrogate model after comparing it with the Kriging model and the Response Surface Methodology (RSM) model. Ultimately, to achieve the desired shape after post‐forming, the PSO method can be employed to determine the ideal combination of forming parameters. The post‐forming method could adjust the shape of fully cured composites. The mechanism of post‐forming is based on viscoelastic behavior. An accurate FEA based on the standard linear‐solid model was established. The radial basis function was developed for quick and precise prediction. The particle swarm optimization could obtain the ideal forming parameters. [ABSTRACT FROM AUTHOR]

This study seeks to explain the influence of the main geometric parameters on the asymmetric C-shaped composites' curing deformation. A numerical model appropriate for cure simulation was described and verified through experiments. Then, the model was used to evaluate the influence of different parameters instead of experiments. It was found that the mold's radius has the most significant effect on the deformation. Apart from the central angle, all other parameters have a similar impact on the twist angles. While the in-plane twist angle constantly increases in relation to the center angle, the out-of-plane twist angle initially increases and then drops. [ABSTRACT FROM AUTHOR]

This study aims to produce variant composite structures that can precisely maintain equilibrium after changing stable states. A rapid and precise prediction method for the cure‐induced bi‐stable warping was developed, and the inverse design for the required part's structural and material parameters was investigated. Firstly, the mechanism causing the warping was investigated. Then, in order to acquire basic data for a data‐driven model to achieve rapid and accurate warping prediction, a finite element analysis (FEA) was developed, with most of the prediction deviations being under 10%. Additionally, deformation forms of variant parts with various layups and shapes were studied to offer guidance for the different shape requirements. The structural and material parameters were analyzed using the response surface methodology and sensitivity analysis. After removing parameters like all rubbery properties with low influence, basic data from the parameterized FEA was utilized to build a precise proxy model. Finally, for the variant structures requiring reasonable shape forms, the inverse design of the material, layup, and sizes can be achieved using the proxy model and the non‐dominated sorting genetic algorithm II. All optimization results were validated using FEA or experiments. The deformation form in the two steady states of each case meets the specifications. The shape difference between the produced part and the required shape is less than 5 mm, and the design deviation for the maximum deformation is less than 10%. Consequently, the rapid prediction and inverse design methods for the bi‐stable shape of variant composite parts were effective and accurate. Highlights: All the rubbery properties are almost uncorrelated to the bi‐stable warping.The proxy model can rapidly and precisely predict the bi‐stable shape.The inverse design can be achieved for a part requiring proper bi‐stable shapes.The design part can precisely maintain equilibrium with the required shapes. [ABSTRACT FROM AUTHOR]

In this work, we used finite element analysis method (FEA), response surface methodology (RSM), and Sobol sensitivity analysis method to investigate the factors affecting the spring-in of U-shaped composite parts with drop-off plies. A FEA was introduced to calculate the spring-in, and demonstrated by two case parts of T300/8552 and T800/AC531. A mathematical model based on FEA-RSM was established by analyzing flange parameters, material properties, the size of the drop-off area, and its distance from the cross-section. In addition, all the factors were compared and ranked by sensitivity analysis. Finally, the parameters of the drop-off area were optimized. [ABSTRACT FROM AUTHOR]