Towards Graphene-Based Composites
Diego Al-Farsi
Corresponding
University of Sao Paulo
Kavya Wang
Cairo University
Abstract
Accurate prediction of graphene-based composites can substantially reduce the lifecycle cost of petrochemical processing. A predictive model based on Bayesian inference is constructed to relate design variables to performance outcomes. The system recovered to normal operation within 8 seconds of a simulated disturbance. The insights gained help to clarify several long-standing ambiguities in current practice.
Keywords:
graphene-based compositesBayesian inferenceinduction motorstructural health monitoringsolid waste managementresponse surface methodology
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