Monday  |  Milwaukee  |  11:40 AM–12:00 PM

#19408, Investigation of the Effect of Critical Parameters on the Strength Distribution of the Global Load Sharing Model: A Statistical Approach

Fiber composite materials play a pivotal role in a variety of engineering applications due to their ability to withstand different load-bearing requirements. To effectively capture the intricate load transfer mechanism within composite materials, one commonly used model is the Global Load Sharing (GLS) model. Despite the contributions of various authors in understanding the mechanics and statistical aspects of this load-sharing model, there exists a notable gap in comprehending the influence of key parameters on the overall performance of this model. To gain useful insights into this load-sharing model, a statistical approach was employed to investigate the effects of critical parameters on the model. The Weibull length model was used to characterize the behavior of the fiber data to account for the impact of gauge length on fiber strength. Parameter estimation was carried out on experimental datasets to obtain the key Weibull parameters that describe the mechanical properties of the fibers used in the composite. We leveraged a Maximum Likelihood Estimation (MLE) method to estimate these Weibull parameters because of the asymptotically unbiased property of this estimation method. Monte Carlo simulations were also utilized to establish the relationship between the critical parameters for this model. This process is crucial because it provides us with useful insights for effectively predicting the behavior of the composite material under the GLS condition. This talk will focus on the effects of these critical parameters on the resulting strength distribution of the GLS model. To enhance the robustness of the results obtained, we showcase the results across three different high-strength engineered fibers used for various engineering applications.

Dumbari Kabari   Rochester Institute of Technology
Amy Engelbrecht-Wiggans   Rochester Institute of Technology