Prediction of Directional Young's Modulus of Particulate Reinforced MMC using Finite Element Methods

Bhowmik, Krishnendu; Nandy, Tuhin; Kumar, P. Vijaya; Khutia, Niloy; Chowdhury, Amit Roy

doi:10.1088/1757-899x/377/1/012057

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…However, if the fiber length exceeds the dimensions of the RVE, the interactions resemble parallel springs, leading to a diminished reinforcement effect. The β and the

also interact, and when β is >10, these interactions become dominating factors in determining the directional effective Young’s Modulus [ 83 ].…”

Section: Discussionmentioning

confidence: 99%

Simulation of a Composite with a Polyhydroxybutyrate (PHB) Matrix Reinforced with Cylindrical Inclusions: Prediction of Mechanical Properties

Gómez-Gast,

Rivera-Santana,

Otero

et al. 2023

Polymers

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Biocomposite development, as a sustainable alternative to fossil-derived materials with diverse industrial applications, requires expediting the design process and reducing production costs. Simulation methods offer a solution to these challenges. The main aspects to consider in simulating composite materials successfully include accurately representing microstructure geometry, carefully selecting mesh elements, establishing appropriate boundary conditions representing system forces, utilizing an efficient numerical method to accelerate simulations, and incorporating statistical tools like experimental designs and re-regression models. This study proposes a comprehensive methodology encompassing these aspects. We present the simulation using a numerical homogenization technique based on FEM to analyze the mechanical behavior of a composite material of a polyhydroxybutyrate (PHB) biodegradable matrix reinforced with cylindrical inclusions of flax and kenab. Here, the representative volume element (RVE) considered the geometry, and the numerical homogenization method (NHM) calculated the macro-mechanical behavior of composites. The results were validated using the asymptotic homogenization method (AHM) and experimental data, with error estimations of 0.0019% and 7%, respectively. This model is valuable for predicting longitudinal and transverse elastic moduli, shear modulus, and Poisson’s coefficient, emphasizing its significance in composite materials research.

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“…However, if the fiber length exceeds the dimensions of the RVE, the interactions resemble parallel springs, leading to a diminished reinforcement effect. The β and the

also interact, and when β is >10, these interactions become dominating factors in determining the directional effective Young’s Modulus [ 83 ].…”

Section: Discussionmentioning

confidence: 99%

Simulation of a Composite with a Polyhydroxybutyrate (PHB) Matrix Reinforced with Cylindrical Inclusions: Prediction of Mechanical Properties

Gómez-Gast,

Rivera-Santana,

Otero

et al. 2023

Polymers

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“…Further, for a given volume fraction of pore, ellipsoidal pore shows more height than spherical one along major axis and hence higher height fraction (ratio of pore height and RVE length). Higher value of height fraction leads to comparatively higher overall modulus [41]. The results for normalized overall modulus (Ec/Em) versus number of pores for ellipsoidal pores (axis ratio of 1.5) are presented in Figure 7b.…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 98%

Design optimization of effective modulus through variation in pore geometries of Stainless Steel 316L

Bhowmik,

Dey,

Datta

et al. 2023

Preprint

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Three-dimensional finite element analyses are carried out using cubic shaped representative volume element with spherical and ellipsoidal pores. The aim of this present study is to design a metal block with targeted effective modulus of elasticity in different directions with various types of pore morphology and %porosity. Parametric study in terms of porosity percentage, number of pores, axis ratio (ratio of major to minor axis of ellipsoidal pores) and orientation angle are performed. Scaffold used for bone grafting is anisotropic in nature. Adequate selection of the parameter can define the effective moduli in X and Y directions. Design optimization is employed using genetic algorithm to achieve the required properties. Artificial neural network metamodels are developed using finite element simulated data to act as the objective functions. In present study stainless steel (316L) is considered for the analysis. However, present method can be applied in material independent way.

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Prediction of Directional Young's Modulus of Particulate Reinforced MMC using Finite Element Methods

Cited by 2 publications

References 8 publications

Simulation of a Composite with a Polyhydroxybutyrate (PHB) Matrix Reinforced with Cylindrical Inclusions: Prediction of Mechanical Properties

Simulation of a Composite with a Polyhydroxybutyrate (PHB) Matrix Reinforced with Cylindrical Inclusions: Prediction of Mechanical Properties

Design optimization of effective modulus through variation in pore geometries of Stainless Steel 316L

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