Verification of numerical homogenization approach in predicting thermal conductivities of fiber reinforced composites with voids and randomly distributed fibers

2020 ◽  
pp. 2050017
Author(s):  
C. Mahesh ◽  
K. Govindarajulu ◽  
V. Balakrishna Murthy
Keyword(s):  
Thermal Conductivity ◽  
Fiber Reinforced Composites ◽  
Reinforced Composites ◽  
Numerical Homogenization ◽  
Transverse Fiber ◽  
Material Component ◽  
Component Systems ◽  
Homogenization Approach ◽  
Processing Module ◽  
Computational Resources

The aim of this paper is to establish the homogenization approach that eliminates the difficulties encountered by the conventional numerical methods in analyzing thermal behavior of the multi-material component systems with minimum computational resources. Analysis of problems with intricacies or larger domains can be made simpler through finite element assisted homogenization approach. In this paper, applicability of homogenization approach is verified by considering two cases (i) composite with voids and (ii) composite with fibers distributed randomly. Fiber randomness case is investigated by Digital Image-Based (DIB) modeling technique in association with MATLAB’S image processing module. Also effect of transverse fiber crack on the effective thermal conductivity of the composite is studied. Results of homogenization approach compared with micro-mechanics approach yielded maximum percentage deviation of 1.72% for voids case and 1.49% for fiber randomness case.

scholarly journals Elastic Constants Prediction of 3D Fiber-Reinforced Composites Using Multiscale Homogenization

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 722 ◽  
Author(s):  
S. Z. H. Shah ◽  
Puteri S. M. Megat Yusoff ◽  
Saravanan Karuppanan ◽  
Zubair Sajid
Keyword(s):  
Experimental Data ◽  
Numerical Methods ◽  
Elastic Constants ◽  
Good Accuracy ◽  
Fiber Reinforced Composites ◽  
Reinforced Composites ◽  
Fiber Reinforced ◽  
Multi Scale ◽  
Homogenization Approach ◽  
Multiscale Homogenization

This paper presents a multi-scale-homogenization based on a two-step methodology (micro-meso and meso-macro homogenization) to predict the elastic constants of 3D fiber-reinforced composites (FRC). At each level, the elastic constants were predicted through both analytical and numerical methods to ascertain the accuracy of predicted elastic constants. The predicted elastic constants were compared with experimental data. Both methods predicted the in-plane elastic constants “ E x ” and “ E y ” with good accuracy; however, the analytical method under predicts the shear modulus “ G x y ”. The elastic constants predicted through a multiscale homogenization approach can be used to predict the behavior of 3D-FRC under different loading conditions at the macro-level.

scholarly journals A novel determination of the minimal size of a probabilistic representative volume element for fiber-reinforced composites’ thermal analysis

2018 ◽  
Vol 22 (6 Part A) ◽  
pp. 2551-2564
Author(s):  
Zecan Tu ◽  
Junkui Mao ◽  
Junjun Mao ◽  
Hua Jiang
Keyword(s):  
Thermal Conductivity ◽  
Thermal Analysis ◽  
Heat Flux ◽  
Thermal Gradient ◽  
Volume Fraction ◽  
Volume Element ◽  
Fiber Reinforced Composites ◽  
Reinforced Composites ◽  
Minimal Size ◽  
Fiber Reinforced

In order to provide an accurate thermal analysis method of fiber-reinforced composites, a novel model based on a probabilistic representative volume element (RVE) is presented in this paper. Monte Carlo methods, probability analysis and finite element analysis have been applied together. The effective transverse thermal conductivity, heat flux field, and thermal gradient field of typical fiber-reinforced composites are examined. The criteria of RVE have been determined, and the minimal size for thermal analysis is obtained using the main statistics and the cross-entropy theory. At the same time, the fiber-to-matrix ratio of thermal conductivity and volume fraction have been changed to determine the influence on heat transfer inside fiber-reinforced composites. It is shown that different purposes of simulations lead to different minimal RVE sizes. The numerical results indicate that the non-dimensional minimal RVE sizes for calculating the effective thermal conductivity, heat flux, and thermal gradient are 30, 80, and 80, respectively. Compared with the volume fraction, the fiber-to-matrix ratio of the thermal conductivity has a more significant effect on minimal RVE size. When the thermal conductivity ratio increases, the minimal size of the RVE increases at first, then it remains almost unchanged.

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