The Brunel Composites Centre (BCC) conducts research in phenomena that take place at the interface of composites with other types of materials. Current research projects cover composites processing, composites joints, and composites performance assessment through modelling and testing.
The objective of this PhD research study is to develop a framework that can assess the reliability of adhesively bonded joints in terms of mechanical performance.
Please note that this position is intended for self-funded PhD students.
The increasing use of fibre reinforced polymer (FRP) composite materials in a wide range of applications increases the use of similar and dissimilar joints. Due to the architecture of FRPs, the use of traditional mechanical fastening joining methods is damaging, restrictive and cost-intensive. In contrast, adhesive bonding technology is one of the most widely used joining methods for composites because it allows flexibility in selecting materials, improved production efficiency, and cost reduction. Yet, because of the complex nature of their failure and the fact that not all defects can be fully verified by inspection and testing, these joints are conservatively designed, limiting the potential of composite materials in weight reduction, cost-saving, and performance.
While many studies have investigated the effect of defects on the failure of adhesive bonds and others aimed at developing non-destructive testing technologies to inspect these joints, there is a need to identify the statistical uncertainties of these defects and understand their correlation and effect when designing and analysing joining systems. Therefore, this study aims to establish a probabilistic reliability-based analysis of adhesively bonded FRPs.
The study will address the following objectives:
- Categorise the defects in adhesively bonded joints based on their location: interface, adhesive, and adherends.
- Define the statistical properties of these defects using Uncertainty quantification methods.
- Quantify the presence of defects. There is a need to investigate the influence level and degree of correlation between these different defects and uncertainties using numerical and analytical methods.
- Improve the computational efficiency of the developed stochastic strategy (for example, using a suitable surrogate model).
- Demonstrate the effectiveness of the developed framework in an application case using reliability-based analysis.
- Investigate the possibility of conducting a reliability-based design optimisation for an application case.
For any enquires, feel free to contact Dr Sadik Omairey ([Email Address Removed]).
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