Kai Pang's research while affiliated with Lancaster University and other places

Discrete element (DE) model has great feasibility in modelling the microstructural behaviours of adhesive composite joints. However, it demands a sophisticated calibration process to determine microscale bond parameters, which involves massive efforts in both experimental and numerical investigations. This work developed a novel calibration strategy based on DE models and genetic expression programming (GEP) approach for predicting the behaviours of hybrid composite joints encompassing the material nonlinearity, large ductile deformation and multiple fracture modes. In the developed strategy, both the bulk and interlaminar-like properties of ductile adhesives were concerned to suit various joint configurations. GEP modelling was performed based on the datasets from virtual DE experiments. Symbolic regression models were subsequently developed to facilitate the parameters determination. A series lab tests were conducted to validate the numerical results. It shows that the calibrated DE model can adaptively simulate the featured behaviours of both the ductile adhesive and composite joints with different configurations well in most examined occasions. Therefore, it could be suggested to generalize the developed strategy in the development of other DE models for saving the massive efforts in the calibration process of microstructural parameters.

Micro-roughness at adhesion surface yields significant influences on the structural behaviour of adhesive joints. Investigations into the micromechanical mechanism are extremely limited. This works developed a novel particle-based model of joints with stochastic microstructural features of roughness, which can capture refined multi-scale responses as first of this kind. Aluminium adherends with mechanical surface treatments were firstly scanned using 3D laser scanning microscope. The statistical features and reconstruction method of micro-roughness profiles were determined. Single lap shear tests on joints made of epoxy adhesive (Loctite EA 9497) and treated aluminium adherends were performed to provide testing data and observations on failure modes. The refined numerical models were subsequently developed to examine the influences of the actual micro-roughness on the micromechanical behaviors and failure mechanism. The mechanical interlocking, mitigation on crack propagation due to the irregular roughness were investigated. It is followed by introducing the reconstructed roughness of various magnitudes and further numerically examining the micromechanical responses by key stochastic parameters such as root mean square roughness and correlation length. The results indicate that the mechanical interlocking contribute more to enhancing the joint strength than the increase of adhesion area by micro-roughness. A rougher surface in either horizontal or vertical directions does not exhibit a consistent improvement of joint strength, which also depends on the threshold of roughness and the surface skewness triggering the transition of failure modes.