The reduction of greenhouse gas emissions and future perspectives of circular economy ask for new solutions to produce commodities and fine chemicals. Large‐scale bubble columns operated by gaseous substrates such as CO, CO2, and H2 to feed acetogens for product formations could be promising approaches. Valid in silico predictions of large‐scale performance are needed to dimension bioreactors properly taking into account biological constraints, too. This contribution deals with the trade‐off between sophisticated spatiotemporally resolved large‐scale simulations using computationally intensive Euler–Euler and Euler–Lagrange approaches and coarse‐grained 1‐D models enabling fast performance evaluations. It is shown that proper consideration of gas hold‐up is key to predict biological performance. Intrinsic bias of 1‐D models can be compensated by reconsideration of Sauter diameters derived from uniquely performed Euler–Lagrange computational fluid dynamics.

中文翻译：

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协同应用一维建模和 CFD 设计工业规模鼓泡塔合成气生物反应器


温室气体排放的减少和循环经济的未来前景需要新的解决方案来生产商品和精细化学品。由 CO、CO2 和 H2 等气态底物操作的大型气泡塔为产乙酸菌提供产物形成可能是有前途的方法。还需要对大规模性能进行有效的计算机预测，以正确确定生物反应器的尺寸，同时考虑到生物限制。该贡献涉及使用计算密集型欧拉-欧拉和欧拉-拉格朗日方法进行复杂时空解析的大规模模拟与实现快速性能评估的粗粒度一维模型之间的权衡。结果表明，正确考虑含气量是预测生物性能的关键。一维模型的固有偏差可以通过重新考虑源自独特执行的欧拉-拉格朗日计算流体动力学的索特直径来补偿。