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Reliability-Based Design Optimization of Polymer Nanocomposites (PNCs) Based on Percolation Model Considering Correlated Input Variables
Journal article   Peer reviewed

Reliability-Based Design Optimization of Polymer Nanocomposites (PNCs) Based on Percolation Model Considering Correlated Input Variables

Jaehyeok Doh, Sang-In Park and Nagarajan Raghavan
Taehan Kigye Hakhoe nonmunjip. A, Vol.44(3), pp.229-240
01/03/2020

Abstract

Engineering Engineering, Mechanical Science & Technology Technology
In this study, by utilizing the code of the percolation model developed in-house for polymer nanocomposites (PNCs), reliability-based design optimization (RBDO) of PNCs was conducted to ensure the reliability of the percolation threshold and to maximize electrical conductivity. The code that was developed takes tunneling resistance into consideration. According to reported studies, carbon nanotube (CNT) diameters and lengths follow the lognormal and the Weibull distribution respectively. To reflect the probability distribution concerning the geometric parameters of the CNTs and a correlation between random input variables, a Nataf transformation, which is a joint cumulative distribution function (CDF) approximated by using the marginal CDF and the covariance of correlated input variables, was employed. RBDO was performed according to the correlation coefficients and the different probability distribution types of random variables. As an outcome of this study, a guideline for a practical PNC design is proposed to enhance electrical performances efficiently.

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