• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文学位 >Application of the discrete adjoint method to coupled multidisciplinary unsteady flow problems for error estimation and optimization.
【24h】

Application of the discrete adjoint method to coupled multidisciplinary unsteady flow problems for error estimation and optimization.

机译：离散伴随方法在耦合多学科非定常流动问题中的应用，用于误差估计和优化。

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Adjoint methods have found applications in several key areas of computational fluid dynamics (CFD), namely, shape optimization and goal based adaptive solutions. CFD has become an essential tool in the design process by enabling the rapid testing of multiple designs, and currently it is normal practice to use CFD in conjunction with optimization algorithms for design improvement. In the context of shape optimization problems based on CFD, adjoint methods offer the significant advantage of computing sensitivity derivatives of the optimization cost function with respect to the set of design parameters, at a cost that is essentially independent of the number of design parameters. Adjoint methods reduce the cost of obtaining the complete gradient vector at any point in the design space equivalent to that of a single flow solution at the same point in the design space. This immediately enables the use of all gradient based optimization algorithms and lifts any restrictions on the number of design parameters required for the adequate definition of the optimization problem.;Adaptive techniques in CFD constitute the other aspect where adjoint methods have have made great inroads. Typical adaptive solutions of the governing flow equations rely on estimating the local error in an evolving solution to target regions of the computational mesh for increased discrete resolution. The main goal of any adaptive solution method is the overall increase in solution accuracy with minimal increase in computational cost. However, targeting local error in the solution does not translate into efficient use of computational resources, since ultimately it is the accurate estimation of boundary integrated functional quantities such as load coefficients that are of importance to the user. Contrary to local error-based methods, adjoint methods allow the adaptation of the computational mesh specifically for the improvement of functionals such as load coefficients. This is achieved by mathematically establishing a clear relationship between the functional of interest and the regions of the computational mesh that are most relevant to it.;The current work extends the use of adjoint methods to multiple governing disciplines that are tightly coupled, and more importantly unsteady in nature. The adjoint method is derived in a very general form for the purpose of computing the gradient vector for use in shape optimization in the context of coupled multidisciplinary unsteady equations. It is shown that computing the gradient vector in unsteady problems involves solving the analysis problem forward in time and then solving the adjoint problem backward in time. While adjoint methods have been used successively to drive spatial mesh adaptation, the current work extends the use of the computed unsteady adjoint variables for estimating temporal discretization error, which is then applied to temporal mesh adaptation. Additionally, the computed adjoint variables are also used for the estimation of algebraic error in the solution arising due to intentional or nonintentional partial convergence of the governing equations. Results indicate that the adaptation of the temporal resolution and convergence tolerance limits using adjoint-based error estimates is able to outperform traditional adaptation methods such as uniform refinement and those based on local error estimates. All of the development is carried out in a fully unstructured mesh framework with dynamic deformation of the computational spatial mesh.
机译：伴随方法已发现在计算流体动力学（CFD）的几个关键领域中的应用，即形状优化和基于目标的自适应解决方案。通过快速测试多个设计，CFD已成为设计过程中必不可少的工具，目前，通常将CFD与优化算法结合使用以进行设计改进。在基于CFD的形状优化问题的背景下，伴随方法具有显着的优势，即相对于设计参数集计算优化成本函数的灵敏度导数，其成本基本上与设计参数的数量无关。伴随方法降低了在设计空间中任一点上获得完整梯度矢量的成本，该成本与在设计空间中同一点处的单个流动解决方案的成本等效。这立即启用了所有基于梯度的优化算法的使用，并解除了对适当定义优化问题所需的设计参数数量的任何限制。CFD中的自适应技术构成了伴随方法取得重大进展的另一方面。控制流方程的典型自适应解决方案依赖于估计正在演变的解决方案中局部误差，以解决计算网格目标区域的问题，从而提高离散分辨率。任何自适应解决方案方法的主要目标是在不增加计算成本的情况下总体提高解决方案精度。但是，针对解决方案中的局部错误不会转化为对计算资源的有效利用，因为最终对用户而言重要的是对边界积分功能量（例如负载系数）的准确估计。与基于局部误差的方法相反，伴随方法允许对计算网格进行调整，以专门用于改善功能（如负载系数）。这是通过在数学上建立目标函数和与之最相关的计算网格区域之间的明确关系来实现的。当前工作将伴随方法的使用扩展到紧密耦合的多个管理学科，更重要的是本质上不稳定。伴随方法以非常通用的形式导出，目的是计算梯度矢量，以便在耦合的多学科非定常方程的上下文中进行形状优化。结果表明，计算非定常问题中的梯度矢量需要及时解决分析问题，然后及时解决伴随问题。尽管相继使用了相继方法来驱动空间网格自适应，但当前的工作扩展了对计算的非平稳相伴变量的使用，以估计时间离散化误差，然后将其应用于时间网格自适应。另外，计算出的伴随变量还用于估计由于控制方程的有意或无意部分收敛而引起的解中的代数误差。结果表明，使用基于伴随的误差估计对时间分辨率和收敛容限进行的调整能够胜过传统的调整方法，例如统一改进和基于局部误差估计的调整方法。所有的开发都是在完全非结构化的网格框架中进行的，并且计算空间网格会动态变形。

著录项

  • 作者

    Mani, Karthik.;

  • 作者单位

    University of Wyoming.;

  • 授予单位 University of Wyoming.;
  • 学科 Engineering Aerospace.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 220 p.
  • 总页数 220
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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