留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

一种加速的参数化模型降阶方法

刘营 李鸿光 李韵

刘营, 李鸿光, 李韵. 一种加速的参数化模型降阶方法[J]. 航空动力学报, 2019, 34(10): 2264-2270. doi: 10.13224/j.cnki.jasp.2019.10.020
引用本文: 刘营, 李鸿光, 李韵. 一种加速的参数化模型降阶方法[J]. 航空动力学报, 2019, 34(10): 2264-2270. doi: 10.13224/j.cnki.jasp.2019.10.020
LIU Ying, LI Hongguang, LI Yue. Accelerated parametric model order reduction method[J]. Journal of Aerospace Power, 2019, 34(10): 2264-2270. doi: 10.13224/j.cnki.jasp.2019.10.020
Citation: LIU Ying, LI Hongguang, LI Yue. Accelerated parametric model order reduction method[J]. Journal of Aerospace Power, 2019, 34(10): 2264-2270. doi: 10.13224/j.cnki.jasp.2019.10.020

一种加速的参数化模型降阶方法

doi: 10.13224/j.cnki.jasp.2019.10.020
基金项目: 国家自然科学基金(11427801)

Accelerated parametric model order reduction method

  • 摘要: 参数化模型降阶(PMOR)方法离线阶段训练数据的过程比较耗时,因此提出了一种加速方法。在基于矩阵插值的PMOR方法的基础上,采用组合近似的重分析技术对基于振型向量的模型降阶(MOR)过程进行加速,利用初始刚度分解矩阵生成迭代计算基向量以对系统矩阵降阶,通过降阶矩阵生成参数化模型的振型向量,对参数空间上的采样点重复整个加速计算过程生成离线数据库。并以电磁振动台动圈为例,采用普通方法和加速方法对均布采样样本点展开仿真研究,结果表明,在保证所构建的离线模型数据库准确度的前提下,此方法能减少80%以上的MOR计算时间,且随着采样点的增多,增速越明显,可以大幅度提高参数化降阶模型离线训练效率。

     

  • [1] SCHILDERS W H A,VAN DER VORST H A,ROMMES J.Model order reduction:theory,research aspects and pplications[M].Berlin:Springer,2008.
    [2] GRESSICK W,WEN J T,FISH J.Order reduction for large-scale finite element models:a systems perspective[J].International Journal for Multiscale Computational Engineering,2005,3(3):337-362.
    [3] QUARTERONI A.Reduced order methods for modeling and computational eduction[M].Berlin:Springer,2014.
    [4] TANG X,HU X,YANG W,et al.Novel torsional vibration modeling and assessment of a power-split hybrid electric vehicle equipped with a dual-mass flywheel[J].IEEE Transactions on Vehicular Technology,2018,67(3):1990-2000.
    [5] ZHANG T,LI H G.Adaptive pole placement control for vibration control of a smart cantilevered beam in thermal environment[J].Journal of Vibration and Control,2013,19(10):1460-1470.
    [6] BUI-THANH T,WILLCOX K,GHATTAS O.Parametric reduced-order models for probabilistic analysis of unsteady aerodynamic applications[J].AIAA Journal,2008,46(10):2520-2529.
    [7] ANNONI J,SEILER P.A method to construct reduced-order parameter-varying models[J].International Journal of Robust and Nonlinear Control,2017,27(4):582-597.
    [8] ANTOULAS A C.An overview of approximation methods for large-scale dynamical systems[J].Annual Reviews in Control,2005,29(2):181-190.
    [9] FENG L.Parameter independent model order reduction[J].Mathematics and Computers in Simulation,2005,68(3):221-234.
    [10] BURGARD S,SOMMER A,FARLEO,et al.Reduced-order models of finite-element systems featuring shape and material parameters[J].Electromagnetics,2014,34(3/4):143-160.
    [11] GEUSS M,PANZER H,LOHMANN B.On parametric model order reduction by matrix interpolation[C]//2013 European Control Conference (ECC).Zurich,Switzerland:IEEE,2013:3433-3438.
    [12] BENNER P,FENG L.A robust algorithm for parametric model order reduction based on implicit moment matching[C]//Reduced order methods for modeling and computational reduction.Cham Switzerland:Springer,2014:159-185.
    [13] SON N T.A real time procedure for affinely dependent parametric model order reduction using interpolation on Grassmann manifolds[J].International Journal for Numerical Methods in Engineering,2013,93(8):818-833.
    [14] PANZER H,MOHRING J,EID R,et al.Parametric model order reduction by matrix erpolation[J].Automatisierungstechnik,2010,58(8):475-484.
    [15] AMSALLEM D,FARHAT C.An online method for interpolating linear parametric reduced-order models[J].SIAM Journal on Scientific Computing,2011,33(5):2169-2198.
    [16] AMSALLEM D,CORTIAL J,CARLBERG K,et al.A method for interpolating on manifolds structural dynamics reduced-order models[J].International Journal for Numerical Methods in Engineering,2009,80(9):1241-1258.
    [17] DEGROOTE J,VIERENDEELS J,WILLCOX K.Interpolation among reduced-order matrices to obtain parameterized models for design,optimization and probabilistic analysis[J].International Journal for Numerical Methods in Fluids,2010,63(2):207-230.
    [18] FENG L,BENNER P,KORVINK J G.Parametric model order reduction accelerated by subspace recycling[C]//Proceedings of the 48h IEEE Conference on Decision and Control (CDC) Held Jointly with 2009 28th Chinese Control Conference.Shanghai:IEEE,2009:4328-4333.
    [19] AHUJA K,BENNER P,DE STURLER E,et al.Recycling BiCGSTAB with an application to parametric model order reduction[J].SIAM Journal on Scientific Computing,2015,37(5):429-446.
  • 加载中
计量
  • 文章访问数:  400
  • HTML浏览量:  2
  • PDF量:  330
  • 被引次数: 0
出版历程
  • 收稿日期:  2019-02-25
  • 刊出日期:  2019-10-28

目录

    /

    返回文章
    返回