论文标题
部分可观测时空混沌系统的无模型预测
Review of microscale dynamics of dilution-induced asphaltene precipitation under controlled mixing conditions
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
As the most complex and heaviest component in bitumen, asphaltene precipitation induced by solvent dilution is important in oil sands extraction to remove solids and water from bitumen froth through dilution by paraffinic solvents. This review will compare asphaltene precipitation to dilution-induced solvent shifting in aqueous systems via the ouzo effect. We attempt to highlight similarities and differences in the evolution of nanodroplets and effects from solvent mixing conditions and point out mutual experimental techniques and modeling approaches for the research of both asphaltene precipitation and nanodroplet formation. The review will start from basic concepts in both asphaltene precipitation and the ouzo effect, then move on to the effects of solvent mixing on asphaltene precipitation in bulk. After that, we will introduce advances in microfluidic systems combined with cutting-edge experimental and simulation tools for asphaltene precipitation induced under controlled mixing with solvents and a droplet formation. Such comparison will inspire more in-depth understanding and control of asphaltene precipitation and the ouzo effect in aqueous systems.
