Salas Santiago D, Cecchis Dany De, Piguave Bryan V, Romagnoli José A
Escuela 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.
Department of Chemical Engineering, Louisiana State University, Baton Rouge, LA 70803, United States.
IFAC Pap OnLine. 2021;54(3):522-527. doi: 10.1016/j.ifacol.2021.08.295. Epub 2021 Sep 8.
Air separation systems are crucial in the production of oxygen, which has gained particular relevance during the COVID-19 outbreak. Mechanical ventilation can compensate respiratory deficiencies along with the use of medical oxygen in vulnerable patients infected with this disease. In this contribution, a many-objective simulation-based optimization framework is proposed for determining eleven decision variables for the operation of an air separation unit. The framework combines the capabilities of the process simulator PRO/II with a Python environment. Three objective functions are optimized together towards the construction of a 3-D Pareto front. Results provide insightful information regarding the most adequate operating conditions of the unit, including the definition of an operational window rather than a single operational point.
空气分离系统在氧气生产中至关重要，在新冠疫情期间其重要性尤为凸显。机械通气可与使用医用氧气一起，补偿感染该疾病的脆弱患者的呼吸缺陷。在本论文中，提出了一个基于多目标模拟的优化框架，用于确定空气分离装置运行的11个决策变量。该框架将过程模拟器PRO/II的功能与Python环境相结合。三个目标函数共同优化，以构建三维帕累托前沿。结果提供了有关该装置最适宜运行条件的深刻见解信息，包括定义一个运行窗口而非单个运行点。
