An imprecise multiscale uncertainty quantification framework for fiber reinforced composites

被引:1
作者
Zhao, Haodong [1 ]
Zhou, Changcong [1 ]
机构
[1] Northwestern Polytech Univ, Dept Engn Mech, Xian 710072, Peoples R China
关键词
Composites; Multiscale analysis; P-box; Uncertainty quantification; Radome structure; SENSITIVITY-ANALYSIS; RELIABILITY; MODELS;
D O I
10.1016/j.probengmech.2024.103686
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The study focuses on the reliability and global sensitivity analysis of fiber-reinforced composite radome structures, considering uncertainty from a multiscale perspective. Macroparameters are estimated based on micro- parameters using the multiscale analysis method for composites, and a reliability analysis model of the composite structure at the macrolevel is constructed. The material performance mechanism is explored in depth, both "from bottom to top" and "from top to bottom", to reveal its inherent laws. Due to insufficient variable distribution information, an imprecise probabilistic model is introduced to characterize the uncertainty effect in multiscale composite analysis. A nested optimization calculation method is applied to obtain reliability and sensitivity results. To ensure both calculation accuracy and efficiency, the regression and classification problems encountered in the proposed framework are addressed using two support vector machine models. The reliability and sensitivity analysis under the imprecise probabilistic framework can help engineers identify significant influential factors, thereby guiding the design of composite radome structures.
引用
收藏
页数:12
相关论文
共 50 条
[41]   Experimental and numerical characterization of mechanical properties of hemp fiber reinforced composites using multiscale analysis approach [J].
Dhaliwal, Gurpinder S. ;
Dueck, Stephen Michael ;
Newaz, Golam M. .
SN APPLIED SCIENCES, 2019, 1 (11)
[42]   Displacement-based multiscale modeling of fiber-reinforced composites by means of proper orthogonal decomposition [J].
Radermacher A. ;
Bednarcyk B.A. ;
Stier B. ;
Simon J. ;
Zhou L. ;
Reese S. .
Advanced Modeling and Simulation in Engineering Sciences, 3 (1)
[43]   QUANTIFICATION OF MATERIAL AND GEOMETRIC DEFECTS VARIABILITY IN FIBER-REINFORCED COMPOSITES WITH PLY WAVINESS DEFECTS [J].
Diaz-Montiel, Paulina ;
Ayala, Gabriela Gonzalez ;
Rivera, Adrian ;
Mauk, Rebekah ;
Reiner, Coleman ;
Venkataraman, Satchi .
PROCEEDINGS OF ASME 2023 AEROSPACE STRUCTURES, STRUCTURAL DYNAMICS, AND MATERIALS CONFERENCE, SSDM2023, 2023,
[44]   A self-consistent homogenization framework for dynamic mechanical behavior of fiber reinforced composites [J].
Prakash, Chandra ;
Ghosh, Somnath .
MECHANICS OF MATERIALS, 2022, 166
[45]   Microstructure model reduction and uncertainty quantification in multiscale deformation processes [J].
Kouchmeshky, Babak ;
Zabaras, Nicholas .
COMPUTATIONAL MATERIALS SCIENCE, 2010, 48 (02) :213-227
[46]   Uncertainty quantification of mechanical properties for three-dimensional orthogonal woven composites. Part II: Multiscale simulation [J].
Tao, Wei ;
Zhu, Ping ;
Xu, Can ;
Liu, Zhao .
COMPOSITE STRUCTURES, 2020, 235
[47]   Basic Framework and Main Methods of Uncertainty Quantification [J].
Zhang, Juan ;
Yin, Junping ;
Wang, Ruili .
MATHEMATICAL PROBLEMS IN ENGINEERING, 2020, 2020
[48]   Fracture modeling of fiber reinforced concrete in a multiscale approach [J].
Congro, Marcello ;
Mejla Sanchez, Eleazar Cristian ;
Roehl, Deane ;
Marangon, Ederli .
COMPOSITES PART B-ENGINEERING, 2019, 174
[49]   Inverse uncertainty quantification for imprecise structure based on evidence theory and similar system analysis [J].
Lixiong Cao ;
Jie Liu ;
Xianghua Meng ;
Yue Zhao ;
Zhongbo Yu .
Structural and Multidisciplinary Optimization, 2021, 64 :2183-2198
[50]   Inverse uncertainty quantification for imprecise structure based on evidence theory and similar system analysis [J].
Cao, Lixiong ;
Liu, Jie ;
Meng, Xianghua ;
Zhao, Yue ;
Yu, Zhongbo .
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2021, 64 (04) :2183-2198