توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Predicting and Optimizing the physical–mechanical properties of epoxy\rubber\nano CaCO3 system using Taguchi approach, ANN and ANFIS methods
نویسنده(ها): ، ، ،
اطلاعات انتشار: کنفرانس بین المللی فرآورش پلیمرها، سال
تعداد صفحات: ۶
In this paper recycled tire rubber powder, epoxy resin, glass fiber mat and CaCO3 nano– powder are mixed and molded at different conditions. The mold temperature and other parameters are calculated and conducted at three different levels of A,B,C using taguchi method which yielded a L9(34) array. Thereafter, tensile strength, impact and failure tests were measured using ASTM standard test method. We predicted the physical–mechanical properties, modulus, impact and also the pressure strength of the samples using artificial neural network and ANFIS methods. Comparing the obtained results with experimental ones showed the least root mean square errors (RMSE) and the best regression (R2). Therefore, the predicted results obtained through our method are very well adopted with the experimental data<\div>
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