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Multiscale Computational Mechanics for the Analysis of Composite Materials Failure

This special issue belongs to the section “Materials Science and Engineering“.

Special Issue Information

Dear Colleagues,

Industries in modern societies are increasingly involved in responsible consumption and production. Innovative technologies are driving interest in utilizing composite materials, as these types of materials feature interesting sets of properties. Those properties may be analyzed using computational modelling, especially in terms of failure mechanisms in them.

Composite materials are materials made up of different components combined to achieve specific properties. Understanding how and why these materials fail is crucial for engineering applications and has been one of the main interests of various research groups for several decades. From another point of view, the term "multiscale" indicates that the analysis is conducted at various levels, from the microscopic scale (e.g., individual fibers and their interactions) to the macroscopic scale (e.g., overall structural behavior). By employing computational techniques, researchers can simulate and study the behavior of composite materials under different loading conditions and identify the factors contributing to their failure. This multiscale approach helps in uncovering the underlying mechanisms that lead to failure, guiding the development of improved composite materials and design strategies.

In summary, the proposed Special Issue should bridge the gap between the world of computational mechanics, with a focus on multiple scales and investigation of the failure behavior of composite materials. It aims to enhance the understanding of composite material failure and provide that information allowing the development of more durable and efficient composite structures to wider audience of scientific world.

Dr. Magdalena Palacz
Prof. Dr. Marek Krawczuk
Guest Editors

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Keywords

  • composite materials failure
  • multiscale modelling
  • numerical analysis
Graphical abstract

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Appl. Sci. - ISSN 2076-3417