论文标题
海军海底进化体系结构：一个预测动态海底粗糙度的平台
The Naval Seafloor Evolution Architecture: A Platform for Predicting Dynamic Seafloor Roughness
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。
Predicting the temporal and spatial dynamics of seafloor roughness is important for understanding bottom boundary layer hydrodynamics. The Navy Seafloor Evolution Architecture (NSEA) is a platform for modeling the dynamic nature of the seafloor by combining hydrodynamic forcing information and observations from diverse sources. NSEA's three modules include a specification of hydrodynamic forcing, a seafloor evolution model, and a model to generate roughness realizations. It can be run in forward mode to predict seafloor roughness including the uncertainty from forcing information, or in inverse mode to estimate parameters from observed seafloor roughness. The model is demonstrated and shown to have good agreement with a field dataset of observed seafloor roughness. Similarly running in inverse mode, NSEA was demonstrated to predict the observed mean sediment grain size with good agreement. NSEA's modularity allows for a wide range of applications in hydrodynamic and acoustic modeling, and is built within an expandable framework that lends for coupling to such models with minimal effort.
