Details
| Original language | English |
|---|---|
| Pages (from-to) | 387-398 |
| Number of pages | 12 |
| Journal | Engineering fracture mechanics |
| Volume | 205 |
| Early online date | 25 Oct 2018 |
| Publication status | Published - Jan 2019 |
Abstract
We present a methodology to evaluate the uncertainty in several popular models for modelling damage and material failure, i.e. a gradient damage model, nonlocal model, phase field approach and cohesive zone model; the latter one is used in the context of the phantom node method though it can easily be used in the context of other computational methods for discrete fracture. The objective is to evaluate and compare the uncertainties in the current models and correlate them to practical observations. The Bayesian method is exploited to achieve this purpose based on experimental reference measurements. The developed methodology has been tested on mode-I fracture in concrete beams through well established three point bending test though other benchmark problems can be adopted for the comparison as well. The results from the current study are compared to the published experimental results. The methodology is implemented in three different steps. Firstly, a sensitivity analysis is performed to quantify the influence of uncertainties in the model parameters. Secondly, the coefficient of variation and average goodness of fit are calculated to evaluate the discrepancy of the predictions with respect to the corresponding measured experimental data. Finally, the posterior probability of models are updated to incorporate the uncertainties in both the model and the parameters, leading to an estimation of the model complexity. Based on the results, the gradient-enhanced damage is found to be the most probable model class with the lowest total model uncertainty. The present study can serve as a platform for future investigations on uncertainties associated with damage modelling and hence the concerned countermeasures.
Keywords
- Bayesian model, Damage modelling, Fracture mechanics, Model uncertainty, Sensitivity analysis
ASJC Scopus subject areas
- Materials Science(all)
- General Materials Science
- Engineering(all)
- Mechanics of Materials
- Engineering(all)
- Mechanical Engineering
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In: Engineering fracture mechanics, Vol. 205, 01.2019, p. 387-398.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Assessment of computational fracture models using Bayesian method
AU - Hamdia, K. M.
AU - Msekh, M. A.
AU - Silani, M.
AU - Thai, T. Q.
AU - Budarapu, P. R.
AU - Rabczuk, T.
PY - 2019/1
Y1 - 2019/1
N2 - We present a methodology to evaluate the uncertainty in several popular models for modelling damage and material failure, i.e. a gradient damage model, nonlocal model, phase field approach and cohesive zone model; the latter one is used in the context of the phantom node method though it can easily be used in the context of other computational methods for discrete fracture. The objective is to evaluate and compare the uncertainties in the current models and correlate them to practical observations. The Bayesian method is exploited to achieve this purpose based on experimental reference measurements. The developed methodology has been tested on mode-I fracture in concrete beams through well established three point bending test though other benchmark problems can be adopted for the comparison as well. The results from the current study are compared to the published experimental results. The methodology is implemented in three different steps. Firstly, a sensitivity analysis is performed to quantify the influence of uncertainties in the model parameters. Secondly, the coefficient of variation and average goodness of fit are calculated to evaluate the discrepancy of the predictions with respect to the corresponding measured experimental data. Finally, the posterior probability of models are updated to incorporate the uncertainties in both the model and the parameters, leading to an estimation of the model complexity. Based on the results, the gradient-enhanced damage is found to be the most probable model class with the lowest total model uncertainty. The present study can serve as a platform for future investigations on uncertainties associated with damage modelling and hence the concerned countermeasures.
AB - We present a methodology to evaluate the uncertainty in several popular models for modelling damage and material failure, i.e. a gradient damage model, nonlocal model, phase field approach and cohesive zone model; the latter one is used in the context of the phantom node method though it can easily be used in the context of other computational methods for discrete fracture. The objective is to evaluate and compare the uncertainties in the current models and correlate them to practical observations. The Bayesian method is exploited to achieve this purpose based on experimental reference measurements. The developed methodology has been tested on mode-I fracture in concrete beams through well established three point bending test though other benchmark problems can be adopted for the comparison as well. The results from the current study are compared to the published experimental results. The methodology is implemented in three different steps. Firstly, a sensitivity analysis is performed to quantify the influence of uncertainties in the model parameters. Secondly, the coefficient of variation and average goodness of fit are calculated to evaluate the discrepancy of the predictions with respect to the corresponding measured experimental data. Finally, the posterior probability of models are updated to incorporate the uncertainties in both the model and the parameters, leading to an estimation of the model complexity. Based on the results, the gradient-enhanced damage is found to be the most probable model class with the lowest total model uncertainty. The present study can serve as a platform for future investigations on uncertainties associated with damage modelling and hence the concerned countermeasures.
KW - Bayesian model
KW - Damage modelling
KW - Fracture mechanics
KW - Model uncertainty
KW - Sensitivity analysis
UR - http://www.scopus.com/inward/record.url?scp=85055513840&partnerID=8YFLogxK
U2 - 10.1016/j.engfracmech.2018.09.019
DO - 10.1016/j.engfracmech.2018.09.019
M3 - Article
AN - SCOPUS:85055513840
VL - 205
SP - 387
EP - 398
JO - Engineering fracture mechanics
JF - Engineering fracture mechanics
SN - 0013-7944
ER -