Even though it is widely known that mechanical properties of papers are dependent upon fiber morphology such as fiber length and cell wall thickness, existing macroscopic models are limited in describing the microscopic traits of pulp. Thus, we proposed a multiscale model by integrating a macroscopic model (i.e., Purdue model ) and a microscopic model (i.e., kinetic Monte Carlo algorithm) to capture the dynamic evolution of the fiber morphology as well as conventional pulp quality index such as Kappa number. Then, a reduced‐order model is identified to handle the computational requirement of the multiscale model, and implemented to a model‐based controller to regulate both the fiber length and the Kappa number which are expressed in the forms of conflicting objective functions. The epsilon‐constraint method is employed to find the Pareto optimal sets to provide decision makers with the degree of freedom to choose one according to their preferred end‐use paper properties.

中文翻译：

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间歇式纸浆蒸煮器中木纤维形态的多尺度建模和多目标控制

尽管众所周知，纸张的机械性能取决于纤维形态，例如纤维长度和孔壁厚度，但现有的宏观模型在描述纸浆的微观特性方面受到限制。因此，我们通过整合宏观模型（即普渡模型）提出了多尺度模型）和微观模型（即动力学蒙特卡洛算法）来捕获纤维形态的动态演变以及常规纸浆质量指数（例如卡伯值）。然后，确定降阶模型以处理多尺度模型的计算要求，并将其实施到基于模型的控制器，以调节以冲突目标函数形式表示的纤维长度和Kappa数。使用epsilon约束方法来找到Pareto最优集，从而为决策者提供根据其首选的最终用途纸张属性选择一个的自由度。