Pipe size sensitivity in pressure relief networks using genetic algorithms
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Abstract
This paper utilizes a stochastic optimization approach using genetic algorithms, for conducting rigorous pipe size sensitivity assessments onto the design of pressure relief networks. By sampling high performance candidates, only the finest options can survive. The pressure relief network system that was investigated in this work was previously reported in literature. The problem is constrained and involves minimizing a cost objective function that evaluates the overall network performance, in which the best pipe size combination should be selected for each segment within the network. The overall goal of this paper was to seek cost-effective designs for the pressure relief piping system by exploring different ranges of pipe diameters that are available for each segment in the network and comparing how the overall design of the system is affected, when the number of pipe size options to select from is varied.
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