The success of an autoclave process is related to the temperature characteristics of the mold. An inhomogeneous temperature field in the mold affects the quality of composite parts, which may lead to residual stress, voids, and other manufacturing defects of composite parts. In order to meet high-quality production demands, the temperature field in a mold should be investigated precisely. The temperature distribution in a large frame mold is critically evaluated in this work. Then, a method to control the temperature distribution in a large frame mold is proposed. A computational fluid dynamics (CFD) model of the autoclave process is developed to predict the temperature evolution of the large frame mold. The model is validated by experimental results, which shows good agreement with a relative difference of 5.92%. The validated CFD model is then applied to analyze the temperature distribution characters in the mold with different control conditions. The results show that the temperature difference decreases by 13.3% when the mold placement angle is changed from 180 to 168°.
Machining distortion is a recurring problem in the machining of monolithic aircraft parts. This paper aims to study the machining distortion minimization of monolithic aircraft parts. Firstly, the energy principle of machining distortion was analyzed. Then, a rapid prediction model of the final part distortion for beam parts was proposed based on the equivalent stress, and the initial bending strain energy contained in the final part was used to characterize the bending distortion risk of the final part. Numerical simulation and milling experiments verified the effectiveness of the proposed prediction model. The relative error between the experimental and calculated results does not exceed 26.5%. Finally, the influence of initial residual stress fluctuation, part geometry and the part location on part distortion was analyzed from the energy point of view. The obtained results indicated that the expected final part distortion can be minimized by adjusting these three factors.
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