• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Vienna International Conference on Mathematical Modelling >Space-Time Reduced Basis Methods for Time-Periodic Partial Differential Equations
【24h】

Space-Time Reduced Basis Methods for Time-Periodic Partial Differential Equations

机译：时间周期减少时间周期部分微分方程的基础方法

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We consider parameter-dependent time-periodic parabolic problems as they occur e.g. in the modeling of rotating propellers. The goal is to determine the parameters (e.g. design or steering parameters) such that a given output of interest (e.g. the efficiency of the propeller) is maximized. A standard approach to numerically solve such problems is a time-stepping (fixed-point) scheme. This approach, however, often suffers from some drawbacks, in particular within the Reduced Basis Method (RBM). First, there might be long transient phases before a periodic or steady state is reached, which is particularly disadvantageous in the online phase. Moreover, corresponding error estimates usually include sums over time-steps which might become inaccurate. Instead, we consider a space-time variational formulation using periodic basis functions in time, which avoids the need for fixed-point iterations. Based on this variational formulation, we develop a space-time RBM using wavelets in time and derive corresponding a-posteriori error estimates. We present numerical results indicating the efficiency of the method as well as the effectivity of the derived error bounds.
机译：我们考虑参数依赖的时间定期抛物面问题，因为它们发生了如此。在旋转螺旋桨的建模中。目标是确定参数（例如设计或转向参数），使得感兴趣的给定输出（例如，螺旋桨的效率）最大化。在数值解决这些问题的标准方法是一个时间级步进（定点）方案。然而，这种方法通常遭受一些缺点，特别是在减少的基础方法（RBM）内。首先，在达到周期性或稳态之前可能存在长的瞬态相位，这在在线阶段是特别不利的。此外，相应的错误估计通常包括可能变得不准确的时间步长的总和。相反，我们考虑使用周期性的基础函数在时间上考虑空时变化配方，这避免了对固定点迭代的需求。基于该变分制定，我们使用时间的小波开发空间RBM，并导出相应的A-Bouthiori误差估计。我们呈现数值结果，表明该方法的效率以及派生误差界限的有效性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号