Minimum Entropy Generation Rate and Maximum Yield Optimization of Sulfuric Acid Decomposition Process Using NSGA-II

Area of Science:

• Chemical Engineering
• Thermodynamics

Background:

• Sulfuric acid decomposition is crucial for sulfur recovery.
• Finite-time thermodynamics (FTT) provides a framework for analyzing irreversible processes.
• Optimizing reactor performance involves balancing competing objectives like entropy generation and product yield.

Purpose of the Study:

• To analyze the impact of inlet temperature, pressure, and flow rate on entropy generation rate (EGR) and SO2 yield in a tubular plug-flow sulfuric acid decomposition reactor.
• To apply multi-objective optimization to find a Pareto-improved design balancing minimum EGR and maximum SO2 yield.
• To provide theoretical guidance for optimizing sulfuric acid decomposition reactors.

Main Methods:

• Analysis based on the theory of finite-time thermodynamics (FTT).
• Utilizing the second-generation non-dominated solution sequencing genetic algorithm (NSGA-II) for multi-objective optimization.
• Investigating the influence of three key design parameters: inlet temperature, inlet pressure, and inlet total mole flow rate.

Main Results:

• Minimum total EGR and maximum SO2 yield are conflicting objectives, requiring a trade-off.
• Multi-objective optimization using NSGA-II achieved Pareto improvements for the reactor design.
• The optimized reactor design demonstrated a 9% reduction in total EGR and a 14% increase in SO2 yield compared to the reference reactor.

Conclusions:

• The study successfully optimized a sulfuric acid decomposition reactor by balancing EGR and SO2 yield.
• The NSGA-II algorithm proved effective for multi-objective optimization in this chemical engineering context.
• The findings offer valuable theoretical insights for the practical design and operation of sulfuric acid decomposition reactors.