Towards Graphene-Based Composites

Diego Al-Farsi, Kavya Wang

Open Access Journal of Engineering Applications · doi:10.55555/oajea.2018.4202.004

1. Introduction

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.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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