Approximation of potential-driven flow dynamics in large-scale self-similar tree networks
Approximation of potential-driven flow dynamics in large-scale self-similar tree networks
复制标题
大规模自相似树网络中势驱动流动力学的近似
DOI：
10.1098/rspa.2011.0113
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
M. Sen
中科院分区：
文献类型：
--
作者：
Jason Mayes;M. Sen
大规模流网络的动态分析由于其建模产生的大型微分代数方程组而变得困难。为了简化分析，必须充分降低数学模型的复杂度。对于自相似树网络，可以使用网络结构来实现这种减少，从而允许简单的分析解决方案。对于非常大但有限的网络，解析解更难获得。然而，在无限极限下，分析有时会大大简化。结果表明，将大型有限网络近似为无限不仅简化了分析，而且提供了出色的近似解。
Dynamic analysis of large-scale flow networks is made difficult by the large system of differential-algebraic equations resulting from its modelling. To simplify analysis, the mathematical model must be sufficiently reduced in complexity. For self-similar tree networks, this reduction can be made using the network’s structure in way that can allow simple, analytical solutions. For very large, but finite, networks, analytical solutions are more difficult to obtain. In the infinite limit, however, analysis is sometimes greatly simplified. It is shown that approximating large finite networks as infinite not only simplifies the analysis, but also provides an excellent approximate solution.
影响因子：
2.4
作者：
Kelly, James F.;McGough, Robert J.
通讯作者：
McGough, Robert J.