arrow
返回

CFD-based aeroelastic reduced-order modeling robust to structural parameter variations

delete2017-08-01
delete27
PRE
AI
M
Maximilian Winter *
F
Florian M. Heckmeier
C
Christian Breitsamter
DOI:10.1016/j.ast.2017.03.030delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
This article deals with the development of two efficient computational-fluid-dynamics (CFD) based models for the computation of unsteady aerodynamic motion-induced forces. In contrast to established reduced-order modeling (ROM) approaches, which are generally fixed to a given set of structural eigenmodes, the proposed methods can be applied for variable mode shapes. Hence, the generated aerodynamic models remain valid to some extent even if mass and stiffness variations within the underlying finite-element (FE) model are considered. In this way, additional computationally demanding CFD computations are avoided once the model has been obtained. Under this premise, two modeling frameworks robust to structural parameter variations are developed, while so-called basis modes are employed to approximate arbitrary mode shapes. Firstly, a time-domain ROM originating from linear system identification principles (SI-ROM) is presented and, secondly, a frequency-domain approach based on a small disturbance CFD solver (SD-ROM) is proposed. Moreover, two different strategies for the basis mode generation are evaluated. The first method is based on a local approximation using radial basis functions, whereas the second method uses two-dimensional Chebyshev polynomials in order to yield a global approximation of the structural grid deformations. Both novel ROM approaches combined with the two basis mode construction techniques are demonstrated and assessed regarding their efficiency and accuracy. The results in terms of the well-known AGARD 445.6 wing configuration demonstrate that the proposed methods can reproduce the unsteady aerodynamic forces accurately, while the computational effort is significantly reduced. Moreover, generic modifications with respect to the FE model are considered to indicate the potential of the new methods regarding aircraft aeroelastic design and optimization. (C) 2017 Elsevier Masson SAS. All rights reserved.
Keyword:
Aeroelasticity
Reduced-order modeling
Unsteady aerodynamics
Computational fluid dynamics
Variable mode shapes
System identification
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Aerospace Science and Technology 封面图
Aerospace Science and Technology
IF:
5.8
论文数:
1.0W
被引数:
3.0W

机构

T
Technical University of Munich
学者数:
5.2W
论文数: 3.9W
被引数: 6.2W
引用论文

引用论文

Sample Throughput and Data Quality at the Leibniz-Labor AMS Facility
err2016-07-18
err0
errOAAI
errM.-J. Nadeau; P. M. Grootes; Markus Schleicher; Peter Hasselberg; Anke Rieck; Malte Bitterling
err分享
err收藏
ASSOCIATION OF SMOKING AND SEVERITY OF COVID-19 INFECTION AMONG 5,889 PATIENTS IN MALAYSIA: A MULTI-CENTER OBSERVATIONAL STUDY
err2022-03-01
err0
errOAAI
errNorliana Ismail; Noraryana Hassan; Muhammad Hairul Nizam Abd Hamid; Ummi Nadiah Yusoff; Noor Raihan Khamal; Mohd Azahadi Omar; Xin Ci Wong; Mohan Dass Pathmanathan; Shahanizan Mohd Zin; Faizah Muhammad Zin; Mohamad Haniki Nik Mohamed; Norashidah Mohd Nor
err分享
err收藏
err分享
err收藏
Lessons Learned from the Young Breast Cancer Survivorship Network
err2017-11-30
err0
PREAI
errSilvia Gisiger-Camata; Timiya S. Nolan; Jacqueline B. Vo; Jennifer R. Bail; Kayla A. Lewis; Karen Meneses
err分享
err收藏
BPI22-019: Guidelines and Recommendations for the Adjuvanted Recombinant Zoster Vaccine in Immunocompromised Cancer Patients
err2022-03-31
err0
PREAI
errAnamaria Jorga; Leonard R Friedland; Nicolas Lecrenier; Ekaterina Safonova; Peter Vink; Robyn Widenmaier
err分享
err收藏
学者 查看更多内容