Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2022Design and finite element study of Kevlar based combat helmet for protection against high-velocity impacts6citations
  • 2022Prediction of impact performance of fiber reinforced polymer composites using finite element analysis and artificial neural network28citations
  • 2022Low Velocity Impact Behavior of Fabric Reinforced Polymer Composites– A Review37citations

Places of action

Chart of shared publication
Mourad, Abdel-Hamid I.
3 / 5 shared
Stephen, Clifton
3 / 3 shared
Shivamurthy, B.
2 / 5 shared
Behara, Sai Rohit
2 / 2 shared
Kannan, Satish
1 / 1 shared
Thekkuden, Dinu Thomas
1 / 3 shared
Shivamurthy, Basavanna
1 / 1 shared
Mohan, Mahesh
1 / 3 shared
Thimmappa, B. H. S.
1 / 1 shared
Chart of publication period
2022

Co-Authors (by relevance)

  • Mourad, Abdel-Hamid I.
  • Stephen, Clifton
  • Shivamurthy, B.
  • Behara, Sai Rohit
  • Kannan, Satish
  • Thekkuden, Dinu Thomas
  • Shivamurthy, Basavanna
  • Mohan, Mahesh
  • Thimmappa, B. H. S.
OrganizationsLocationPeople

article

Prediction of impact performance of fiber reinforced polymer composites using finite element analysis and artificial neural network

  • Thekkuden, Dinu Thomas
  • Mourad, Abdel-Hamid I.
  • Stephen, Clifton
  • Selvam, Rajiv
  • Behara, Sai Rohit
  • Shivamurthy, Basavanna
Abstract

In this study, a methodology combining finite element analysis (FEA) and artificial neural network (ANN) through multilayer perceptron architecture was utilized to predict the impact resistance behavior of hybrid and non-hybrid fabric reinforced polymer (FRP) composites. A projectile at 250 m s−1 impact velocity was considered for the high velocity impact simulations. The Kevlar, carbon and glass fabric-based epoxy composites were modelled and the impact tests were performed through finite element simulations. The residual velocity results from FEA were used as training data for the ANN prediction. The ANN predicted results were in good agreement with FEA results with a maximum variation of about 6.6%. In terms of impact resistance, composite laminates with more Kevlar layers exhibited enhanced performance compared to other samples. Neat Kevlar/epoxy (K/K/K) exhibited the best impact resistance performance in terms of lowest residual velocity and highest energy absorption of 101.84 m s−1 and 222.86 J, respectively. Whereas, neat glass/epoxy (G/G/G) specimens registered the highest projectile residual velocity (165.13 m s−1) and lowest energy absorption (158.99 J) compared to all other specimens. 2-fabric sandwich composite K/G/K exhibited a low residual velocity of 115.27 m s−1 and high energy absorption of 218.53 J, which is the second best among all specimens. Comparatively, the 3-fabric hybrid composites registered intermediate impact resistance results lower than that of Kevlar rich specimens, but significantly higher than neat G/G/G composite, thus, proving the effectiveness of hybridization in enhancement of impact performance compared to neat glass composite. Overall, the chosen methodology yielded significantly accurate results for the prediction of impact behavior of FRP composites.

Topics
  • impedance spectroscopy
  • polymer
  • Carbon
  • simulation
  • glass
  • glass
  • composite
  • impact test
  • finite element analysis