Free access
Research Article
Jun 5, 2019

A Local Sensitivity-Based Multiscale Stochastic Stress Analysis of a Unidirectional Fiber-Reinforced Composite Material Considering Random Location Variation of Multifibers

Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5, Issue 3

Abstract

This paper describes an efficient computational method for estimating the probabilistic properties of the maximum microscopic stresses in a unidirectional fiber-reinforced composite material against microscopic random variations of fibers locations. Some microscopic geometrical random variations will cause a large variation of the microscopic stresses, even if the influence on the homogenized elastic properties is small. The random variation of the microscopic stresses will have a significant influence on the apparent strength of composites, and therefore, estimation of the random variation will be important for reliability-based design of a composite structure. Further, for more precise analysis, a unit cell containing many inclusions should be employed. When the number of random variables becomes large, a multipoint approximation-based approach will not be appropriate. Therefore, a computational approach with a local surrogate constructed by a successive sensitivity analysis is proposed in this paper. The realizations of the microscopic stresses are estimated with the successive sensitivity-based local surrogate, and the probabilistic properties of the stresses are estimated with using the approximated realizations in the Monte Carlo simulation. As an example, the multiscale stochastic stress analysis of a unidirectional fiber-reinforced composite plate under unidirectional tensile load along the transverse direction is performed with considering randomness in fibers locations. For this problem, probabilistic properties as the expectation and coefficient of variation of the maximum microscopic stresses in resin are estimated. From comparisons between the direct Monte Carlo simulation and the proposed method, validity and effectiveness of the proposed approach are discussed. This article is available in the ASME Digital Collection at https://doi.org/10.1115/1.4043400.

Information & Authors

Information

Published In

Go to ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
Volume 5Issue 3September 2019

History

Received: Aug 6, 2018
Revision received: Nov 18, 2018
Published online: Jun 5, 2019
Published in print: Sep 1, 2019

Authors

Affiliations

Sei-ichiro Sakata [email protected]
Department of Mechanical Engineering, Kindai University, 3-4-1, Kowakae, Higashi-Osaka City, Osaka 577-8502, Japan e-mail: [email protected]
Takuro Sakamoto [email protected]
Department of Mechanical Engineering, Graduate School of Kindai University, 3-4-1, Kowakae, Higashi-Osaka City, Osaka 577-8502, Japan e-mail: [email protected]

Funding Information

Japan Society for the Promotion of Science10.13039/501100001691: 16K05995

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share