Refinery crude preheat train (CPHT) is prone to fouling and ageing effects due to the complexity of processed crude feedstock preheated prior to distillation. This has serious implications on the thermal and hydraulic performance of the CPHT. As a result, efficient performance of crude preheat trains is compromised and as such, optimal scheduling cleaning operations are required to restore performance. In this paper, we attempt to review the subject of fouling/ageing control and mitigation in crude preheat train network by optimal scheduling cleaning approach. Three prominent optimisation techniques/models namely Mathematical Models (Mixed integer linear programming (MILP) and Mixed integer non-linear programming (MINLP) models); Artificial Intelligence (AI) Models; and Heuristic Techniques used for achieving optimal cleaning are outlined.

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In this study, a flexible porous polyvinyl alcohol (PVA)/graphene oxide (GO) composite film was developed and tested for flexible strain sensing and energy-storage applications. Morphology and mechanical properties were studied; tensile strength and Young’s modulus increased by 225% and 86.88%, respectively, at 0.5 wt% GO. The PVA/GO film possesses exceptional sensing ability to various mechanical strains, such as tension, compression, bending, and torsion. For example, the gauge factor of the PVA/GO film as a tensile-strain sensor was measured as 2.46 (246%). Under compression loads, the PVA/GO composite film showed piezoresistive and capacitive strain-sensing characteristics. Under 5 kPa of compression load, the relative resistance increased by 81% with a 100 msec response time; the relative capacitance increased by 160% with a 120 msec response time. The PVA/GO strain sensor exhibited high durability and reliability over 20 × 103 cycles of tensile strain and bending at 3.33 Hz. Moreover, the PVA/GO composite film showed good electrochemical properties due to its porous structure; the maximum capacitance was 124.7 F g−1 at 0.5 wt% GO. After 20 × 103 charging–discharging cycles, the capacitance retention rate was 94.45%, representing high stable capacitance performance. The results show that electrically conductive porous PVA nanocomposite films are promising candidates for strain sensing and energy-storage devices.

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