基于数据同化的薄板坯连铸结晶器热流计算方法
A numerical approach for heat flux estimation in thin slabs continuous casting molds using data assimilation
摘要：
在目前的工作中，我们考虑的工业问题，估计在实时的结晶器钢热流在连铸结晶器。我们通过首先考虑模具建模问题（直接问题）来解决这个问题。然后，我们将热通量估计问题作为估计Neumann边界条件的逆问题，该边界条件具有在模具域内部的逐点温度测量数据。我们还考虑了具有总热通量测量以及温度测量的情况。我们开发了两种方法来解决这个反问题。第一种是传统的Alifanov正则化，第二种是利用热通量的参数化。我们开发了后一种方法有一个离线在线分解与计算效率的在线部分进行实时。在这项工作的最后一部分，我们测试这些方法的学术和工业基准。结果表明，参数化方法优于Alifanov正则化的性能和计算成本。此外，它被证明是强大的测量噪声。最后，测试证实，计算成本是适合的实时估计的热流。
英文摘要：
In the present work, we consider the industrial problem of estimating in real-time the mold-steel heat flux in continuous casting mold. We approach this problem by first considering the mold modeling problem (direct problem). Then, we plant the heat flux estimation problem as the inverse problem of estimating a Neumann boundary condition having as data pointwise temperature measurements in the interior of the mold domain. We also consider the case of having a total heat flux measurement together with the temperature measurements. We develop two methodologies for solving this inverse problem. The first one is the traditional Alifanov's regularization, the second one exploits the parameterization of the heat flux. We develop the latter method to have an offline-online decomposition with a computationally efficient online part to be performed in real-time. In the last part of this work, we test these methods on academic and industrial benchmarks. The results show that the parameterization method outclasses Alifanov's regularization both in performance and computational cost. Moreover, it proves to be robust with respect to the measurements noise. Finally, the tests confirm that the computational cost is suitable for real-time estimation of the heat flux.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
