Toward a Computational Steering Framework for Large-Scale Composite Structures Based on Continually and Dynamically Injected Sensor Data

被引:11
作者
Bazilevs, Y. [1 ]
Marsden, A. L. [2 ]
di Scalea, F. Lanza [1 ]
Majumdar, A. [3 ]
Tatineni, M. [3 ]
机构
[1] Univ Calif San Diego, Dept Struct Engn, 9500 Gilman Dr, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Dept Mech & Aerosp Engn, La Jolla, CA 92093 USA
[3] Univ Calif San Diego, San Diego Supecomp Ctr, La Jolla, CA 92093 USA
来源
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2012 | 2012年 / 9卷
关键词
DDDAS; fluid-structure interaction; composite structures; optimization and control; high-performance computing; WIND TURBINE ROTORS; ISOGEOMETRIC ANALYSIS; 3D SIMULATION; OPTIMIZATION; ALGORITHMS; SURFACES; GEOMETRY; SEARCH; JOINTS; NURBS;
D O I
10.1016/j.procs.2012.04.124
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Recent advances in simulation, optimization, structural health monitoring, and high-performance computing create a unique opportunity to combine the developments in these fields to formulate a Dynamics Data Driven Application System (DDDAS) framework. In this paper we propose such a framework, which consists of the following items and features: a structural health monitoring (SHM) system, an advanced fluid-structure interaction (FSI) simulation module, and a sensitivity analysis, optimization and control software module. High-performance computing (HPC) is employed for the various parts of the framework and is viewed as its essential element. The intended application of the developed framework is the analysis of medium-to-large-scale composite structures. These include aerospace structures, such as military aircraft fuselage and wings, helicopter blades, and unmanned aerial vehicles, and civil structures, such as wind turbine blades and towers. The proposed framework will continuously and dynamically integrate the SHM data into the FSI analysis of these structures. This capability allows one to: 1. Shelter the structures from excessive stress levels during operation; 2. Make informed decisions to perform structural maintenance and repair; and 3. Predict the remaining fatigue life of the structure.
引用
收藏
页码:1149 / 1158
页数:10
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