Model and Analysis of Flexural Properties of Al₂O₃ Ceramic Prepared by Centrifugal Slip Casting Using BP Neural Network Model

Abstract:

BP neural network model was developed for prediction of the flexural properties of Al2O3 ceramic prepared by centrifugal slip casting. In this paper, the model can well reflect the relationship between the process parameters including solid content of Al2O3 ceramic slurries (w), centrifugal acceleration (v), sintering temperature (T) and flexural properties of sintered products including fracture strength ( ) and fracture toughness (KIC). According to the registered BP model, the effects of w, v and T on and KIC were analyzed. The predicted results agree with the actual data within reasonable experimental error, which shows that the BP model is a practically very useful tool in the flexural properties prediction of the Al2O3 ceramic prepared by centrifugal slip casting. The system reduces the time required for planning and optimizing of centrifugal process parameters.

• Periodical: Advanced Materials Research (Volumes 430-432)
• Pages: 664-668
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.430-432.664
• Online since: January 2012
• Authors: Jing Yuan Yu, Qiang Li, Xu Dong Sun
• Keywords: Al₂O₃ Ceramic, BP Neural Network (BPNN), Centrifugal Slip Casting, Flexural Properties

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