Atomistic studies of <110] screw dislocation core structures and glide in γ-TiAl

The core structure of <110] superdislocations in L10 TiAl was investigated with a view to clarifying their dissociation abilities and the mechanisms by which they may become sessile by self-locking. A detailed knowledge of the fine structure of dislocations is essential in analysing the origin of the various deformation features. Atomistic simulation of the core structure and glide of the screw <110] superdislocation was carried out using a bond order potential for ?-TiAl. The core structure of the screw <110] superdislocation was examined, starting with initial unrelaxed configurations corresponding to various dislocation dissociations discussed in the literature. The superdislocation was found to possess in the screw orientation either planar (glissile) or non-planar (sessile) core structures. The response of the core configurations to externally applied shear stress was studied. Some implications were considered of the dissociated configurations and their response to externally applied stress on dislocation dynamics, including the issue of dislocation decomposition, the mechanism of locking and the orientation dependence of the dislocation substructure observed in single-phase ?-TiAl. An unexpectedly rich and complex set of candidate core structures, both planar and non-planar, was found, the cores of which may transform under applied stress with consequent violation of Schmid's law.

The inferential monitoring of the screw disturbance torque to predict process fluctuations in polymer extrusion

Polymer extrusion is one of the major methods of processing polymer materials and advanced process monitoring is important to ensure good product quality. However, commonly used process monitoring devices, e.g. temperature and pressure sensors, are limited in providing information on process dynamics inside an extruder barrel. Screw load torque dynamics, which may occur due to changes in solids conveying, melting, mixing, melt conveying, etc., are believed to be a useful indicator of process fluctuations inside the extruder barrel. However, practical measurement of the screw load torque is difficult to achieve. In this work, inferential monitoring of the screw load torque signal in an extruder was shown to be possible by monitoring the motor current (armature and/or field) and simulation studies were used to check the accuracy of the proposed method. The ability of this signal to aid identification and diagnosis of process issues was explored through an experimental investigation. Power spectral density and wavelet frequency analysis were implemented together with a covariance analysis. It was shown that the torque signal is dominated by the solid friction in the extruder and hence it did not correlate well with melting fluctuations. However, it is useful for online identification of solids conveying issues.

A new model based approach for the prediction and optimisation of thermal homogeneity in single screw extrusion

In polymer extrusion, delivery of a melt which is homogenous in composition and temperature is important for good product quality. However, the process is inherently prone to temperature fluctuations which are difficult to monitor and control via single point based conventional thermo- couples. In this work, the die melt temperature profile was monitored by a thermocouple mesh and the data obtained was used to generate a model to predict the die melt temperature profile. A novel nonlinear model was then proposed which was demonstrated to be in good agreement with training and unseen data. Furthermore, the proposed model was used to select optimum process settings to achieve the desired average melt temperature across the die while improving the temperature homogeneity. The simulation results indicate a reduction in melt temperature variations of up to 60%.