Abstract
The productivity of shell and tube heat exchangers are governed by various geometrical parameters like tube diameter, tube thickness, tube length, tube pitch, tube layout, installation area and baffle spacing of the heat exchanger. The operational efficiency of heat exchangers is highly influenced by the characteristics of heat exchanger parameters. The exchanger efficiency gets trapped due to many incongruities’ effects like over-pressure, bio-fouling, chemical fouling and corrosion. The selection of optimum design configuration is essential to achieve higher operational efficiency for a heat exchanger. But the performance and reliability of the optimization process play a key role in selecting and deselecting significant and insignificant parameters, respectively. So, cognitive selection of parameters and henceforth a reliable optimization process is required to identify optimal design for a heat exchanger. Moreover, economic factors also contribute to attain a consolidated yield result for a heat exchanger. This research proposes an optimal configuration with the help of ensemble output obtained by multi-criteria decision making and nature-based optimization algorithm. It has been found that exchange efficiency in optimal configuration is boosted by 22% from prototype heat exchanger.
Highlights
Shell and tube double-pipe heat exchangers (STHEs) are extensively used for process optimization in various enterprises like food processing, power generation, chemical plants and automobile industry.[1,2,3] The performance of STHEs depends primarily on surface area of exchange and flow resistance of the fluids
The tube diameter (TD), tube thickness (TT), tube length (TL), Tube pitch (TP) Tube layout (Tl) and A are accountable for the portion of surface area available to exchange heat between fluids, whereas baffles have a proportional effect on the resistance and turbulence in the fluids and it impacts the cost of pumping the fluid into an exchanger.[9]
This study utilized the ensemble output from particle swarm optimization (PSO),[27,28,29,30,31] GA32–34 and enhanced particle swarm optimization (EPSO)[35,36] to identify the best fit configuration for HE in view of optimal exchange efficiency (EE). This investigation utilized the advantages of multi-criteria decision-making (MCDM) methods like analytical hierarchy process (AHP), weighted sum method (WSM) and weighted product method (WPM) to rank the relevant variables as per their significance and the PSO, GA (section ‘Sawtooth genetic algorithm (SGA)’) and EPSO maximize the benchmark function to identify the best configuration for an HE to produce an optimal EE
Summary
Shell and tube double-pipe heat exchangers (STHEs) are extensively used for process optimization in various enterprises like food processing, power generation, chemical plants and automobile industry.[1,2,3] The performance of STHEs depends primarily on surface area of exchange and flow resistance of the fluids. The cost of installation, maintenance and replacement of the material will again depend on the amount of surface area that can be made available for the exchange where the increase in surface area will end up with enhanced expense.[10]
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