Pinto Mariano Adriano, Bastos Borba Costa Caliane, de Franceschi de Angelis Dejanira, Maugeri Filho Francisco, Pires Atala Daniel Ibraim, Wolf Maciel Maria Regina, Maciel Filho Rubens
Laboratory of Optimization, Design and Advanced Control (LOPCA), School of Chemical Engineering, University of Campinas (UNICAMP), 3083-970 Campinas, SP, Brazil.
Appl Biochem Biotechnol. 2009 Nov;159(2):366-81. doi: 10.1007/s12010-008-8450-6. Epub 2008 Dec 11.
In this work, the mathematical optimization of a continuous flash fermentation process for the production of biobutanol was studied. The process consists of three interconnected units, as follows: fermentor, cell-retention system (tangential microfiltration), and vacuum flash vessel (responsible for the continuous recovery of butanol from the broth). The objective of the optimization was to maximize butanol productivity for a desired substrate conversion. Two strategies were compared for the optimization of the process. In one of them, the process was represented by a deterministic model with kinetic parameters determined experimentally and, in the other, by a statistical model obtained using the factorial design technique combined with simulation. For both strategies, the problem was written as a nonlinear programming problem and was solved with the sequential quadratic programming technique. The results showed that despite the very similar solutions obtained with both strategies, the problems found with the strategy using the deterministic model, such as lack of convergence and high computational time, make the use of the optimization strategy with the statistical model, which showed to be robust and fast, more suitable for the flash fermentation process, being recommended for real-time applications coupling optimization and control.
在这项工作中，研究了用于生产生物丁醇的连续闪蒸发酵过程的数学优化。该过程由三个相互连接的单元组成，如下所示：发酵罐、细胞保留系统（切向微滤）和真空闪蒸罐（负责从发酵液中连续回收丁醇）。优化的目标是在期望的底物转化率下使丁醇生产率最大化。比较了两种优化该过程的策略。其中一种策略中，该过程由一个具有通过实验确定的动力学参数的确定性模型表示，另一种策略中，由使用因子设计技术结合模拟得到的统计模型表示。对于这两种策略，该问题都被写成非线性规划问题，并使用序列二次规划技术求解。结果表明，尽管两种策略得到的解非常相似，但使用确定性模型的策略存在诸如缺乏收敛性和计算时间长等问题，这使得使用统计模型的优化策略更适合闪蒸发酵过程，因为该策略显示出稳健且快速，推荐用于优化与控制相结合的实时应用。
