Industrial & Engineering Chemistry Research · 2002 · 183 citations · 7 references
EngineeringChemical EngineeringMechanical EngineeringDesign OptimizationProcess Systems EngineeringThermodynamicsProcess EngineeringProcess SynthesisRefrigerationRefrigeration SystemsThermal DesignThermodynamic OptimizationOperating ConditionsOptimization Of Operating ConditionsRefrigerant MixturesRefrigerant System DesignRefrigerant SystemsRefrigeration Plant DesignRefrigeration TechnologyThermodynamic Analysis
Using refrigerant mixtures can yield more energy‑efficient and compact refrigeration systems, yet designing such mixed‑refrigerant systems is challenging and existing methods are scarce, leaving many operations far from optimal. The study introduces a novel method for selecting refrigerant compositions in mixed‑refrigerant systems. The method systematically synthesizes complete system designs by integrating thermodynamic analysis with nonlinear programming, where thermodynamics provides confidence and guides the optimization of composition, pressures, and flow rates. Case studies demonstrate that the approach effectively reduces energy consumption and enhances process efficiency in mixed‑refrigerant systems.
Using mixtures as refrigerants in the design of refrigeration systems offers significant opportunities in the search for more energy-efficient and compact designs. However, the design of mixed-refrigerant systems is extremely difficult, and few successful design methods are available. As a result, many existing operations can be far from the optimal conditions. In this paper, a novel method for the selection of refrigerant compositions has been proposed. Using this approach, a systematic synthesis method for the complete design of mixed-refrigerant systems has been developed. This approach combines the power of thermodynamics and nonlinear programming (NLP) techniques. Whereas NLP can determine the optimal choice of process operating conditions, thermodynamics simultaneously provides insights into and confidence in the solution. More importantly, the use of thermodynamic analysis in this approach helps overcome the complexity in NLP optimization for determining key design variables, including refrigerant composition, operating pressures, and flow rates. Case studies demonstrate that the method is effective and that mixed-refrigerant systems can significantly save energy and improve process efficiency.
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