Nanocomposite development in the aerospace industry has been encouraged due to their considerable structural enhancements, particularly for material composed of carbon nanotubes included in a polymer matrix. In an effort to explore the nanocomposites’ material properties, previous works have made use of a computational micromechanics model for the analysis of the effective electrical conductivi...

The present work describes a computational mechanism based failure analysis conducted for 3D-printed continuous carbon fiber reinforced thermoplastic composites (CFRTPCs), which could not be seen in the available literature. material is investigated on intraply evaluation and adopts different criteria constituents. micromechanical modeling employs Asymptotic Homogenization technique comprises s...

This study presents a microstructural model applicable to additively manufactured (AM) austenitic SS 316L components fabricated via direct energy deposition (DED) process. The is primarily intended give an understanding of the effect microscale and mesoscale features, such as grains melt pool sizes, on mechanical properties components. Based experimental observations, initial assumptions for nu...

Textile composites describe a broad range of polymer composite materials with textile reinforcements, from woven and non-crimp commodity fabrics to three dimensional textiles. In a general manner textile composites are based on textile preforms manufactured by some textile processing technique and on some resin infiltration and consolidation technique. Due to the complex three-dimensional struc...

Bio-based materials have been extensively studied in recent decades. These based on vegetable aggregates are highly heterogeneous, and their complex behaviour depends the of constituents as well spatial distribution, size, shape. Classically, homogenization methods used for prediction heterogeneous because they allow to take into-account microscopic phenomena characteristics governing macroscop...

A new micro-mechanical model for predicting the non-linear elasto-plastic behavior of short fiber reinforced composites is presented. The developed based on a two-step Orientation Averaging method, and capable accommodating wide variety micro-structural parameters. In first step, Finite Element Analyses are performed unit cell (single surrounded by matrix). Then, response up-scaled calibrating ...

Introducing steel fibers into traditional concrete can improve its mechanical properties and crack resistance, but few studies have considered how the fiber shape bond-slip effect between matrix affect behavior of concrete. This paper establishes a three-dimensional representative volume element (3D RVE) fiber-reinforced (SFRC) with random distribution, different shapes, interfacial strengths u...

The use of high strength steel (HSS) cold-formed hollow section is significant interest in the construction sector due to competitive costs. accurate simulation ductile fracture failure at micro and macro scale critical for improving validity predicting structural behaviour HSS sections welded joints. In this study, S700 material studied using Gurson-Tvergaard-Needleman (GTN) damage model. Repr...

In this paper, we show how a simple convolutional neural network (CNN) can be trained to predict homogenised elastic properties of composite material based on its representative volume element (RVE). We consider both 2D and 3D composites featuring two components with fixed isotropic properties. The dataset used train the is obtained in stages. first stage generation random RVEs computation thei...

Flow-induced shear stresses have been found to be a stimulatory factor in pre-osteoblastic cells seeded in 3D porous scaffolds and cultured under continuous flow perfusion. However, due to the complex internal structure of the scaffolds, whole scaffold calculations of the local shear forces are computationally-intensive. Instead, representative volume elements (RVEs), which are obtained by extr...