Predictive modeling is the key factor for saving time and resources with respect to manufacturing processes such as fermentation processes arising e.g.\ in food and chemical manufacturing processes. According to Zhang et al. (2002), the open-loop dynamics of yeast are highly dependent on the initial cell mass distribution. This can be modeled via population balance models describing the single-cell behavior of the yeast cell. There have already been several population balance models for wine fermentation in the literature. However, the new model introduced in this paper is much more detailed than the ones studied previously. This new model for the white wine fermentation process is based on a combination of components previously introduced in literature. It turns it into a system of highly nonlinear weakly hyperbolic partial/ordinary integro-differential equations. This model becomes very challenging from a theoretical and numerical point of view. Existence and uniqueness of solutions to a simplified version of the introduced problem is studied based on semigroup theory. For its numerical solution a numerical methodology based on a finite volume scheme combined with a time implicit scheme is derived. The impact of the initial cell mass distribution on the solution is studied and underlined with numerical results. The detailed model is compared to a simpler model based on ordinary differential equations. The observed differences for different initial distributions and the different models turn out to be smaller than expected. The outcomes of this paper are very interesting and useful for applied mathematicians, winemakers and process engineers.
翻译:预测模型是节省生产过程的时间和资源的关键因素,例如食品和化学制造过程中产生的发酵过程。据张等人(2002年)称,酵酵的开环动态高度依赖初始细胞质量分布。可以通过描述酵母细胞单细胞行为的人口平衡模型进行模拟。文献中已经存在几种葡萄发酵的人口平衡模型。然而,本文件采用的新模型比以前研究的模型更详细得多。白葡萄酒发酵过程的新模型以文献中以前引入的成分组合为基础。它将酵酵酵的开放环动态高度依赖初始细胞质量分布。可以通过描述酵母细胞单细胞行为的人口平衡模型进行模拟。在文献中已经存在几种关于葡萄发酵问题简化版本的解决方案的深度和独特性模型。对于其数字解决方案而言,一种基于一定量的配制和时间隐含式模型的数值方法,其基础是以前引入的成分组合。它将它变成一个高度非线性系统,它变成一个高度不精细的双向部分/偏向异形的系统系统。这一模型的模型将产生更简单的细胞分配结果,对不同的模型进行更精确的对比。对于不同的数值分析后,对不同的细胞结果的模型进行更精确的模型进行不同的分析,对不同的分析后,然后对不同的细胞分配将采用不同的模型进行不同的计算。根据不同的模型进行不同的计算。根据不同的模型进行不同的计算。