دانلود رایگان مقاله پیش بینی پیچ خوردگی با مدل سازی مواد مرکب سه بعدی با روش اجزا دیجیتال

Abstract

Model definition accuracy dictates the reliability of a predictive analysis for 3D woven composites (3DWC). The traditional modeling approach is based on analysis of ideal geometry with user specified imperfections. In that case, co-relating the actual imperfections arising from manufacturing processes with that of the model becomes an iterative process. In this study, a digital element (DE) approach is implemented for creating the woven architecture of the composite. This technique simulates the individual fibers and their interactions allowing the user to create a reference unit cell with imperfect geometry induced during manufacturing stages of 3DWCs. Thus the response and strength analysis account for the unique weaving signature and provide better predictions without the necessity to run iterative analysis procedures required for idealized geometry models. X-ray CT images or detailed statistical data for variations in specimen geometry are not required which makes this approach more attractive in terms of cost and creation time. A representative model created using the DE approach is used for prediction of compressive failure of 3DWC without having to seed imperfections for failure initiation. The analysis also captures the formation of a kink band as observed in experimental tests. Results of this study are compared with the experimental results and simulation results of idealized geometry reported previously in literature.

5. Conclusion

The digital element approach using DFMATM has been successfully implemented for modeling the imperfections and deviations in the fiber tow geometry. This method was used to analyze quasi-static buckling of 3D woven composites. A Riks analysis of this model accurately predicts critical buckling loads and the onset of kinking without seeding the model with artificial imperfections. The iterative procedure for and idealized geometry model required to estimate the imperfection in the actual specimen is eliminated. This approach also gives useful results to predict kink band formation in the specimen. As with previous studies, it was shown that the number of RUCs modeled affects the results. However, this method lends itself to multiple RUCs as we can digitally weave a larger portion and capture more unique geometry rather than just putting individual RUCs together as is typically done with an idealized geometry model. The accuracy of results increases as the model size approaches the specimen size used in conducting experiments.