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Predictive modelling approaches for compound damage occurring in composite materials PhD

   School of Aerospace, Transport and Manufacturing (SATM)

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  Mr P Addepalli  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Cranfield University is currently seeking a top class candidate to undertake fundamental research in developing theoretical models that best represent active thermography inspection data. This opportunity provides the individual to develop novel thermal simulation models that bridge the gap between data obtained from real-time inspection and its theoretical model.

Composite materials have revolutionised the industry by offering structurally superior parts with an improved strength-to-weight ratio. These materials offer improved material properties such as low density, high mechanical strength, durability and improved corrosion resistance. These properties showcase the huge offering of the material, which not such boasts of functional superiority but also provides an optimised structural and operational performance. However, they are vulnerable to damage due to their britility and significant plastic deformation. The ability to detect damage and predicting their structural integrity becomes a challenge when employing these materials as load-bearing structures. Furthermore, the repair of these materials is far more complicated and time-consuming, especially with the behaviour of these materials post repair.

This project will look at compound damage occurring in composite structures theoretically by not just detecting the sub-surface damage but also predicts its mechanical strength of the damage. Initially, an FEA model of compound sub-surface damage will be created and a pulsed thermography inspection method will be deployed on the model to detect the damage. Once the model achieves 85-90% accuracy, the material strength of the model will be recorded against the damage size. The model will then be subjected to both vibrational and environmental modelling that will accelerate the growth of damage. The damage will then be characterised through the pulse thermography inspection created at the start of the project with insights added through the estimated mechanical strength due to the model’s exposure to both mechanical and environmental cycling. This work is expected to be run using ABAQUS FEA package.

This PhD will develop NDT models by exploring the fundamental physics of the materials thermal behaviour. Initially, a thermal model will be created by building a representative composite material with internal compound damage. Once the thermal model is established, environmental and stress modelling approaches will be pursued to grow damage theoretically.

Finite Element Modelling experience is preferred with exposure to software packages not limited to ABAQAS, COMSOL, MATLAB, Python, C/C++. A strong engineering background especially in non-destructive damage characterisation is welcomed.


The aim of this PhD is to develop an integrated theoretical model to evaluate sub-surface damage quantification using thermography and extend the model to predict damage behaviour under mechanical and environmental stress application.


1. Conduct literature review to identify multiple thermal, mechanical and environmental modelling approaches in damage detection and predict damage growth;

2. Build and expand thermal model for sub-surface compound damage detection in-line with pulsed thermography inspection;

3. Carry out parametric tests on experimental parameters and compare it with the in-house real-time inspection system;

4. Create multiple [mechanical & environmental] theoretical models to study damage growth and its detection using appropriate FEA methods;

At Cranfield, the candidate will be based at the Centre for Digital Engineering and Manufacturing (CDEM), which hosts cutting-edge simulation and visualisation facilities. The student will have access to cooled and uncooled state-of-the-art infrared camera systems, high-end computers for finite element analysis modelling, integration algorithm development, in-house technologies including digital platforms to visualise digital data. The work developed will be presented to industry partners /advisory board of the centre for their validation and comments. 


Entry requirements

Candidates should have a minimum of an upper second (2.1) honours degree (or equivalent) preferably in Mechanical Engineering / Industrial Engineering / Physics but candidates in other degrees related to Engineering or related quantitative fields would be considered. Candidates with an MSc degree in these disciplines will be desirable. Experience in damage detection technologies and software competence in ABAQUS, COMSOL, MATLAB, Python, C/C++ is preferred.

Funding Notes

This is a self-funded PhD; open to UK, EU and International applicants.
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