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Many-Objective Simulation-Based Optimization of an Air Separation Unit.

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  • 1Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Naturales y Matemáticas, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador.

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Summary
This summary is machine-generated.

This study optimizes air separation units for oxygen production, crucial for medical use during pandemics. The research defines an operational window for efficiency, not just a single setting.

Keywords:
3-D Pareto frontCryogenic air distillationMany-objective optimizationOperational window

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Area of Science:

  • Chemical Engineering
  • Process Systems Engineering

Background:

  • Air separation units are vital for producing oxygen, especially critical for medical applications during the COVID-19 pandemic.
  • Mechanical ventilation and medical oxygen are essential for supporting patients with respiratory deficiencies.

Purpose of the Study:

  • To develop a many-objective simulation-based optimization framework for air separation unit operation.
  • To determine optimal settings for eleven decision variables in air separation units.

Main Methods:

  • Integration of the PRO/II process simulator with a Python environment.
  • Application of a many-objective optimization approach to three objective functions.
  • Construction of a 3-D Pareto front to visualize trade-offs.

Main Results:

  • Identification of optimal operating conditions for air separation units.
  • The framework successfully generated a 3-D Pareto front, illustrating multi-objective optimization outcomes.
  • Insightful data was provided on the most suitable operational parameters.

Conclusions:

  • The proposed framework enables efficient optimization of air separation units.
  • Defining an operational window offers greater flexibility than a single setpoint.
  • This approach is valuable for ensuring adequate oxygen supply in critical situations.