Bond Graph Modelling and Simulation of Static Recrystallization Kinetics in Multipass Hot Steel Rolling

In hot rolling, the final thickness of the strip is achieved through plastic deformation of the original stock by a series of counter-rotating rollers. In this work, static recrystallization kinetics in between two stages of steel rolling has been modelled, and simulation studies have also been performed to find out the effect of entry temperature on the recrystallization kinetics. A viable bond graph model has been developed to study the kinetics of the process. Low-carbon steel has been considered for this purpose

Microstructure modelling of hot deformation of Al–1%Mg alloy

This study presents the application of the finite elementmethod and intelligent systems techniques to the prediction of microstructural mapping for aluminium alloys. Here, the material within each finite element is defined using a hybrid model. The hybrid model is based on neuro-fuzzy and physically based components and it has been combined with the finite element technique. The model simulates the evolution of the internal state variables (i.e. dislocation density, subgrain size and subgrain boundary misorientation) and their effect on the recrystallisation behaviour of the stock. This paper presents the theory behind the model development, the integration between the numerical techniques, and the application of the technique to a hot rolling operation using aluminium, 1 wt% magnesium alloy. Furthermore, experimental data from plane strain compression (PSC) tests and rolling are used to validate the modelling outcome. The results show that the recrystallisation kinetics agree well with the experimental results for different annealing times. This hybrid approach has proved to be more accurate than conventional methods using empirical equations

Self-Organising Fuzzy Logic Control and its Application to Muscle Relaxant Anaesthesia

In this paper the authors describe the use of Self-Organising Fuzzy Logic Control (SOFLC) for automated drug delivery in muscle relaxant anaesthesia. The self-elicitation of a knowledge base is shown to be robust in the presence of model uncertainty, noise contamination and parameter changes. Being computing intensive, SOFLC is considered for parallel implementation on transputers, both via use of Lisp interpreter and direct Occam coding. SOFLC in Occam code gave a fast implementation, which could be further speeded up using multiple transputers

Self-Organising Learning Control and its Applications to Muscle Relaxant Anaesthesia

Controlling systems with interacting response variables and interacting actuators has been a formidable task requiring expensive modelling to identify measure plant characteristics. These attempts often result in less than an ideal controller. With self-organising techniques the uncertainty of plant behaviour need not be an obstacle to fast, efficient and stable control. In fact they do not require a definitive course of action based on a given set of conditions.......

An Adaptive Analogue Tracker for Automatic Measurement of Time-Varying Lung Parameters

This research report describes the design and results obtained using simple electronic circuits specially designed for implementing a single lung parameter tracking algorithm for identification of the mechanical properties of the lung. Unlike the commonly used loop-flattening technique, the adaptive electronic tracker is able to monitor continuously the mechanical properties of the respiratory system. It is capable of tracking the rapid changes in lung parameters as the frequency of breathing changes. The design of the adaptive tracker is based on equation-error formulation and the global asymptotic stability of the adaptive tracking equations is guaranteed. The cheapness and simplicity of the tracker makes it suitable for clinical applications