Isogeometric Fatigue Damage Prediction in Large-Scale Composite Structures Driven by Dynamic Sensor Data

被引:81
作者
Bazilevs, Y. [1 ]
Deng, X. [1 ]
Korobenko, A. [1 ]
di Scalea, F. Lanza [1 ]
Todd, M. D. [1 ]
Taylor, S. G. [2 ]
机构
[1] Univ Calif San Diego, Dept Struct Engn, La Jolla, CA 92093 USA
[2] Los Alamos Natl Lab, Los Alamos, NM 87545 USA
来源
JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME | 2015年 / 82卷 / 09期
基金
新加坡国家研究基金会;
关键词
fatigue damage; DDDAS; IGA; Kirchholl-Love shells; digital twin; REPRESENTATIVE VOLUME ELEMENTS; MODAL-ANALYSIS; PART II; MICROSTRUCTURES; SIMULATION; FRAMEWORK; SYSTEMS; MODELS;
D O I
10.1115/1.4030795
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
In this paper, we combine recent developments in modeling of fatigue-damage, isogeometric analysis (IGA) of thin-shell structures, and structural health monitoring (SHIM) to develop a computational steering framework for fatigue-damage prediction in foil-scale laminated composite structures. The main constituents of' the proposed framework are described in detail, and the framework is deployed in the context of an actual fatigue test of a full-scale wind-turbine blade structure. The results indicate that using an advanced computational model informed by in situ SHM data leads to accurate prediction of the damage zone formation, damage progression, and eventual failure of the structure. Although the blade fatigue simulation was driven by test data obtained prior tel the computation, the proposed computational steering framework may be deployed concurrently with structures undergoing fatigue loading.
引用
收藏
页数:12
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