Stochastic Finite Element Analysis for Static Bending Beams with a Two-Dimensional Random Field of Material Properties

This study presents the development and application of the stochastic finite element method (SFEM) to analyze the static response of beams with a two-dimensional (2D) spatially varying elastic modulus. A 2D stationary stochastic field is employed to model the elastic modulus, capturing the material heterogeneity along both the longitudinal and vertical directions of the beam. The weighted integral method is applied to represent the random field as random variables and to compute the element stiffness matrices, while a first-order perturbation technique is utilized to estimate the statistical moments of the nodal displacement vector, including the mean and covariance matrix. This method enhances both computational efficiency and accuracy in capturing material heterogeneity compared to traditional approaches. The precision and effectiveness of the developed SFEM are evaluated through comparisons with Monte Carlo simulations (MCs), demonstrating strong agreement in the analysis of the coefficient of variation (COV) of displacement. A sensitivity analysis is conducted to examine the influence of the correlation length and dispersion of the stochastic field on the COV. The results indicate that the COV generally increases as these parameters grow, with the most significant variations occurring at small correlation lengths. As the correlation length becomes very large, the COV of displacement converges toward the standard deviation of the input stochastic field. Furthermore, the study reveals that the correlation length along the beam’s longitudinal axis has a more pronounced effect on the COV of displacement compared to the vertical correlation length.

Authors

Institutions

Publication Details

Journal
Modelling—International Open Access Journal of Modelling in Engineering Science
Published
2025-05-06
DOI
https://doi.org/10.3390/modelling6020037
Citations
1
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
1.40
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Stochastic Finite Element Analysis for Static Bending Beams with a Two-Dimensional Random Field of Material Properties

Dai Duc Mai and Hung Quoc Nguyen, Van Cuong Giap, Nguyen Xuan Tung, Sy Dan Dao
1 citations
Modelling—International Open Access Journal of Modelling in Engineering Science
Probabilistic and Robust Engineering Design
1.40
article

Stochastic Finite Element Analysis for Static Bending Beams with a Two-Dimensional Random Field of Material Properties

Dai Duc Mai and Hung Quoc Nguyen, Van Cuong Giap, Nguyen Xuan Tung, Sy Dan Dao
article en
1 citations

Abstract

This study presents the development and application of the stochastic finite element method (SFEM) to analyze the static response of beams with a two-dimensional (2D) spatially varying elastic modulus. A 2D stationary stochastic field is employed to model the elastic modulus, capturing the material heterogeneity along both the longitudinal and vertical directions of the beam. The weighted integral method is applied to represent the random field as random variables and to compute the element stiffness matrices, while a first-order perturbation technique is utilized to estimate the statistical moments of the nodal displacement vector, including the mean and covariance matrix. This method enhances both computational efficiency and accuracy in capturing material heterogeneity compared to traditional approaches. The precision and effectiveness of the developed SFEM are evaluated through comparisons with Monte Carlo simulations (MCs), demonstrating strong agreement in the analysis of the coefficient of variation (COV) of displacement. A sensitivity analysis is conducted to examine the influence of the correlation length and dispersion of the stochastic field on the COV. The results indicate that the COV generally increases as these parameters grow, with the most significant variations occurring at small correlation lengths. As the correlation length becomes very large, the COV of displacement converges toward the standard deviation of the input stochastic field. Furthermore, the study reveals that the correlation length along the beam’s longitudinal axis has a more pronounced effect on the COV of displacement compared to the vertical correlation length.

Modelling—International Open Access Journal of Modelling in Engineering ScienceVol. 6(2)
Ho Chi Minh City University of Transport (VN), Hanoi Architectural University (VN), University of Transport and Communications (VN)
Openalex Percentile: Top 17%
Probabilistic and Robust Engineering Design
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.