Uncertainty Propagation and Global Sensitivity Analysis of a Surface Acoustic Wave Gas Sensor Using Finite Elements and Sparse Polynomial Chaos Expansions

被引:1
|
作者
Hamdaoui, Mohamed [1 ]
机构
[1] Univ Lorraine, UMR LEM3 7239, 7 Rue Felix Savart, F-57000 Metz, France
来源
VIBRATION | 2023年 / 6卷 / 03期
关键词
surface acoustic wave; gas sensor; sparse polynomial chaos; Sobol' indices; global sensitivity analysis; SAW SENSOR; SIMULATION; RESONATOR; INDEXES;
D O I
10.3390/vibration6030038
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The aim of this work is to perform an uncertainty propagation and global sensitivity analysis of a surface acoustic wave (SAW) gas sensor using finite elements and sparse polynomial chaos. The SAW gas sensor is modeled using finite elements (FEM) under COMSOL, and the sensitivity to DCM of its Sezawa mode is considered to be the quantity of interest. The importance of several geometrical (width and PIB thickness), material (PIB Young's modulus and density), and ambient (pressure, temperature, and concentration) parameters on the sensor's sensitivity is figured out by means of Sobol' indices using sparse polynomial chaos expansions. It is shown that when the variability of the input parameters is low (inferior to 5%), the only impacting parameter is the cell width. However, when the variability of the input parameters reaches medium levels (around 10%), all the input parameters except the ambient temperature are impacting the sensor's sensitivity. It is also reported that in the medium variability case, the sensor's sensitivity experiences high variations that can lead to a degradation of its performances.
引用
收藏
页码:610 / 624
页数:15
相关论文
共 50 条
  • [11] Propagation of Uncertainty in the MUSIC Algorithm Using Polynomial Chaos Expansions
    Van der Vorst, Thomas
    Van Eeckhaute, Mathieu
    Benlarbi-Delai, Aziz
    Sarrazin, Julien
    Horlin, Francois
    De Doncker, Philippe
    2017 11TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), 2017, : 820 - 822
  • [12] On using polynomial chaos for modeling uncertainty in acoustic propagation
    Creamer, DB
    JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2006, 119 (04): : 1979 - 1994
  • [13] Global sensitivity analysis in the context of imprecise probabilities (p-boxes) using sparse polynomial chaos expansions
    Schobi, Roland
    Sudret, Bruno
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2019, 187 : 129 - 141
  • [14] Development of a Sparse Polynomial Chaos Expansions Method for Parameter Uncertainty Analysis
    Wang, C. X.
    Liu, J.
    Li, Y. P.
    Zhao, J.
    Kong, X. M.
    4TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL ENGINEERING AND SUSTAINABLE DEVELOPMENT (CEESD 2019), 2020, 435
  • [15] Polynomial chaos expansions for uncertainty propagation and moment independent sensitivity analysis of seawater intrusion simulations
    Rajabi, Mohammad Mahdi
    Ataie-Ashtiani, Behzad
    Simmons, Craig T.
    JOURNAL OF HYDROLOGY, 2015, 520 : 101 - 122
  • [16] Adaptive sparse polynomial chaos expansions for global sensitivity analysis based on support vector regression
    Cheng, Kai
    Lu, Zhenzhou
    COMPUTERS & STRUCTURES, 2018, 194 : 86 - 96
  • [17] Global sensitivity analysis of solid oxide fuel cells with Bayesian sparse polynomial chaos expansions
    Shao, Qian
    Gao, Enlai
    Mara, Thierry
    Hu, Heng
    Liu, Tong
    Makradi, Ahmed
    APPLIED ENERGY, 2020, 260 (260)
  • [18] Sparse polynomial chaos expansions for global sensitivity analysis with partial least squares and distance correlation
    Zhou, Yicheng
    Lu, Zhenzhou
    Cheng, Kai
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2019, 59 (01) : 229 - 247
  • [19] Global sensitivity analysis using sparse grid interpolation and polynomial chaos
    Buzzard, Gregery T.
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2012, 107 : 82 - 89
  • [20] Sparse polynomial chaos expansions for global sensitivity analysis with partial least squares and distance correlation
    Yicheng Zhou
    Zhenzhou Lu
    Kai Cheng
    Structural and Multidisciplinary Optimization, 2019, 59 : 229 - 247