Bayesian approach to micromechanical parameter identification using Integrated Digital Image Correlation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F23%3A00366897" target="_blank" >RIV/68407700:21110/23:00366897 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.ijsolstr.2023.112388" target="_blank" >https://doi.org/10.1016/j.ijsolstr.2023.112388</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ijsolstr.2023.112388" target="_blank" >10.1016/j.ijsolstr.2023.112388</a>

Result language

angličtina

Original language name

Bayesian approach to micromechanical parameter identification using Integrated Digital Image Correlation

Original language description

Micromechanical parameters are essential in understanding the behavior of materials with a heterogeneous structure, which helps to predict complex physical processes such as delamination, cracks, and plasticity. However, identifying these parameters is challenging due to micro-macro length scale differences, required high resolution, and ambiguity in boundary conditions, among others. The Integrated Digital Image Correlation (IDIC) method, a state-of-the-art full-field deterministic approach to parameter identification, is widely used but suffers from high sensitivity to boundary data errors and is limited to identification of parameters within well-posed problems. This article employs Bayesian approach to estimate micromechanical shear and bulk moduli of fiber-reinforced composite samples under plane strain assumption, and to improve handling of boundary noise. The main purpose of this article is to quantify the effect of uncertainty in the boundary conditions in the stochastic setting. To this end, the Metropolis–Hastings Algorithm (MHA) is employed to estimate probability distributions of bulk and shear moduli and boundary condition parameters using IDIC, considering a fiber-reinforced composite sample under plane strain assumption. The performance and robustness of the MHA are compared to two versions of deterministic IDIC method, under artificially introduced random and systematic errors in kinematic boundary conditions. Although MHA is shown to be computationally more expensive and in certain cases less accurate than the recently introduced Boundary-Enriched IDIC, it offers significant advantages, in particular being able to optimize a large number of parameters while obtaining statistical characterization as well as insights into individual parameter relationships. The paper furthermore highlights the benefits of the non-normalized approach to parameter identification with MHA (leading, within deterministic IDIC, to an ill-posed formulation), which significantly improves the robustness in handling the boundary noise.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20301 - Mechanical engineering

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

International Journal of Solids and Structures

ISSN

0020-7683

e-ISSN

1879-2146

Volume of the periodical

2023

Issue of the periodical within the volume

280

Country of publishing house

GB - UNITED KINGDOM

Number of pages

18

Pages from-to

1-18

UT code for WoS article

001035354500001

EID of the result in the Scopus database

2-s2.0-85163745734