The performance of reinforced rubber compounds depends on the filler composition while the reinforcement and dissipation mechanisms still remain unclear. Herein linear and nonlinear dynamic rheological responses of ca...The performance of reinforced rubber compounds depends on the filler composition while the reinforcement and dissipation mechanisms still remain unclear. Herein linear and nonlinear dynamic rheological responses of carbon black/silica hybrid filler filling nature rubber compounds are investigated. The rheological contributions of dynamically retarded bulk phase and filler network are revealed to be crucial at high and low frequencies, respectively, and the bulk phase is shown to be of vital importance for the occurrence of nonlinear Payne effect at mediate frequencies. A framework for simultaneously solving reinforcement and dissipation varying with filler composition and content is suggested, providing a new perspective in understanding the filling effect for manufacturing high-performance rubber materials.展开更多
In this study, an application of artificial neural network （ANN） has been presented in modeling and studying the effect of compounding variables on abrasion behavior of rubber formulations. Three case studies were c...In this study, an application of artificial neural network （ANN） has been presented in modeling and studying the effect of compounding variables on abrasion behavior of rubber formulations. Three case studies were carried out in which the experiment data were collected according to classical response surface designs. Besides developing the ANN models, we developed response surface methodology （RSM） to confirm the ANN predictions. A simple relation was employed for determination of relative importance of each variable according to ANN models. It was shown through these case studies that ANN models delivered very good data fitting and their simulating curves could help the researchers to better understand the abrasion behavior.展开更多
基金financially supported by the National Natural Science Foundation of China(Nos.51573157,51333004 and51373149)the Natural Science Foundation of Zhejiang Province(No.R14E030003)+2 种基金the Major Projects of Science and Technology Plan of Guizhou Province(No.(2013)6016)the Open Project Foundation in Shanghai Aerospace System Engineering Institutethe SAST Innovation Fund(No.yy-F08052015100029)
文摘The performance of reinforced rubber compounds depends on the filler composition while the reinforcement and dissipation mechanisms still remain unclear. Herein linear and nonlinear dynamic rheological responses of carbon black/silica hybrid filler filling nature rubber compounds are investigated. The rheological contributions of dynamically retarded bulk phase and filler network are revealed to be crucial at high and low frequencies, respectively, and the bulk phase is shown to be of vital importance for the occurrence of nonlinear Payne effect at mediate frequencies. A framework for simultaneously solving reinforcement and dissipation varying with filler composition and content is suggested, providing a new perspective in understanding the filling effect for manufacturing high-performance rubber materials.
文摘In this study, an application of artificial neural network （ANN） has been presented in modeling and studying the effect of compounding variables on abrasion behavior of rubber formulations. Three case studies were carried out in which the experiment data were collected according to classical response surface designs. Besides developing the ANN models, we developed response surface methodology （RSM） to confirm the ANN predictions. A simple relation was employed for determination of relative importance of each variable according to ANN models. It was shown through these case studies that ANN models delivered very good data fitting and their simulating curves could help the researchers to better understand the abrasion behavior.
