Flexibility analyses are widespread in chemical engineering to quantify allowed deviations from nominal conditions. Standard approaches to perform flexibility analysis can be hard to apply if process constraints are difficult to handle, as it happens in bioprocesses with dynamic constraints. Here, focusing on the computation of the traditional flexibility index in problems with complicating constraints, we apply symbolic regression to build algebraic expressions of the said complicating constraints, simplifying the flexibility analysis of complex process models by enabling the application of state-of-the-art deterministic solvers. Our approach is applied to an ethanol production in fed-batch operation mode and a chromatographic process of antibodies. The performance is assessed in terms of model building time, predictive accuracy of the model, and the time required to solve the flexibility formulations. Overall, our approach, which focuses on computing the original flexibility index, provides an alternative way to analyse the flexibility of processes entailing complicating constraints.

中文翻译：

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具有复杂过程约束的过程单元的基于代数代理的灵活性分析

灵活性分析在化学工程中广泛使用，用于量化与标称条件的允许偏差。如果过程约束难以处理，则执行灵活性分析的标准方法可能很难应用，就像在具有动态约束的生物过程中发生的那样。在这里，重点关注复杂约束问题中传统灵活性指数的计算，我们应用符号回归来构建所述复杂约束的代数表达式，通过启用最新状态的应用来简化复杂过程模型的灵活性分析。艺术确定性求解器。我们的方法适用于补料分批操作模式下的乙醇生产和抗体的色谱过程。性能是根据模型构建时间、模型的预测准确性以及求解灵活性公式所需的时间来评估的。总的来说，我们的方法侧重于计算原始灵活性指数，提供了另一种方法来分析涉及复杂约束的流程的灵活性。