This work focuses on the development and implementation of a simulation-based approach for the detection of partial and extended blockages within an edible oil pipeline system. Blockages, whether partial or extended, pose a significant operational and safety risks. This study employs computational fluid dynamics (CFD) simulations to model the flow behaviour of edible oil through pipeline under varying conditions. It leverages advanced computational fluid dynamics (CFD) simulations to analyze pressure, velocity, and temperature variations along the pipeline. By simulating scenarios with different blockage characteristics, there is establishment of distinctive patterns indicative of partial and extended obstructions. Through extensive analysis of simulation data, sensing element, and monitoring system, processing signal input and response output, the system can accurately pinpoint the location and severity of blockages, providing crucial insights for timely intervention. The detection system represents a significant advancement in pipeline monitoring technology, offering a proactive and accurate approach to identify blockages and mitigate potential risks and ensure the uninterrupted flow of edible oil, thereby enabling timely intervention and maintenance.
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