Prediction of Elastic Properties of Micro Particle (B4C) Reinforced Polymer Composites Using Finite Element Analysis and Analytical Expressions

Abstract

Particle reinforced Composite (PRC) materials are also an important class of polymer composites and these are also used for different engineering applications. Improvements in mechanical properties of this class of materials are under research for diversified applications. The present research work is focused on the evolution of the mechanical properties of the PRC where spherical shaped B4C particles of diameter in microns are reinforced in a Polymer matrix. The effectiveness of the particle contribution regarding Elastic properties of Particle Reinforced Composite at various particle weight fractions is examined by Finite Element Analysis. The experimental approach is the best way to determine the properties of the composite but it is expensive and time-consuming. Therefore, FEM and analytical methods are the viable methods for the determination of the composite properties. The Finite element results were obtained by adopting Micromechanics approach in association with Finite Element Method. Assuming a uniform distribution of particles and considering one unit-cell of the whole array, the properties of the composite materials are determined. The predicted Elastic properties from FEA is compared with analytical results. Results suggested that B4C particles are good reinforcement for the enhancement of Elastic properties of Polypropylene.

Authors and Affiliations

Sai Krishna Golla, P. Prasanthi

Keywords

Related Articles

Unique User Identification across Multiple Social Networks

There are number of social network sites that belt uphill the subject of a large amount of people regarding the world. All social networking sites differ from each toting taking place based occurring for the subject of...

The Future Scope of Business Intelligence (BI)

Business intelligence (BI) is a broad category of application on programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI appl...

Enhanced Data Forensics Technique Based On Parallel Processing and Multilevel File Binning

Data forensic comes from forensic science. Forensic science is the scientific method of gathering and examining information about the past. This is especially important in law enforcement where forensics is done in rela...

slugPerformance Analysis of Clustering Algorithms in Data Mining

Clustering is a primary data description method in data mining which group’s most similar data. The data clustering is an important problem in a wide variety of fields. Including data mining, pattern recognition, and bi...

Unified MPPT Control Strategy for Z-Source Inverter

This Paper proposes the PV array connected Z-source inverter is widely used because it boost up output voltage and reduces the harmonics and improves efficiency. Here single stage Photovoltaic power conversion system us...

Download PDF file
  • EP ID EP22735
  • DOI http://doi.org/10.22214/ijraset.2016.10072
  • Views 206
  • Downloads 4

How To Cite

Sai Krishna Golla, P. Prasanthi (2016). Prediction of Elastic Properties of Micro Particle (B4C) Reinforced Polymer Composites Using Finite Element Analysis and Analytical Expressions. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(10), -. https://europub.co.uk/articles/-A-22735