Wear in centrifugal slurry pumps

The project improves understanding of wear in slurry pumps. By measuring actual pump wear and microscopically examining worn surfaces, a clearer picture emerged of wear modes and mechanisms for different materials. This enables improved guidelines for material selection and modifications to hydraulic shape that increased pump wear life.

Role of grain boundary sliding in the anisotropy of magnesium alloys

The plastic anisotropy of magnesium alloy sheet drops rapidly with test temperature. It has previously been suggested that this may be due to an increase in the activity of (c+a) dislocations. The present note points out that the phenomenon may result, instead, from the action of grain boundary sliding. This can explain the strong effect of grain size on anisotropy. Furthermore, it points to a new avenue for alloy development.

An EM-based algorithm for clustering data streams in sliding windows

Cluster analysis has played a key role in data understanding. When such an important data mining task is extended to the context of data streams, it becomes more challenging since the data arrive at a mining system in one-pass manner. The problem is even more difficult when the clustering task is considered in a sliding window model which requiring the elimination of outdated data must be dealt with properly. We propose SWEM algorithm that exploits the Expectation Maximization technique to address these challenges. SWEM is not only able to process the stream in an incremental manner, but also capable to adapt to changes happened in the underlying stream distribution.

Incremental and adaptive clustering stream data over sliding window

Cluster analysis has played a key role in data stream understanding. The problem is difficult when the clustering task is considered in a sliding window model in which the requirement of outdated data elimination must be dealt with properly. We propose SWEM algorithm that is designed based on the Expectation Maximization technique to address these challenges. Equipped in SWEM is the capability to compute clusters incrementally using a small number of statistics summarized over the stream and the capability to adapt to the stream distribution’s changes. The feasibility of SWEM has been verified via a number of experiments and we show that it is superior than Clustream algorithm, for both synthetic and real datasets.

Modelling of tooling wear in trim dies for AHSS

Using Advanced High Strength Steels (AHSS) in forming and cutting dies generates higher loads in tools. Tool wear is an issue when applying AHSS. This study investigates the effect of process parameters such as clearance, material properties and punch/die bluntness on contact pressure values and tool wear. Some desirable process parameters that minimise wear have been found.

Tool wear analysis in sheet metal stamping

This thesis advances the understanding of die wear in sheet metal stamping. It was found that transient conditions exist at the die radius, resulting in severe contact pressures that are critical to the wear behaviour. The findings challenge applicability of traditional wear tests and models for sheet metal stamping processes.

Transition in wear performance for ionic liquid lubricants under increasing load

The effect of ionic liquid (IL) lubrication for aluminium/steel systems is highly dependant on the applied load and the IL structure. This study illustrates that a change in anion of an IL lubricant results in different physicochemical properties that will alter its performance at a given load. As the load is increased there is a shift in lubricant performance and mechanism of the IL. Up to a load of 30 N the lowest wear coefficient was achieved by a phosphonium diphenylphosphate IL, whilst above 30 N a phosphonium bis(trifluoromethanesulfonyl)amide IL was able to form a more tenacious tribolayer that resulted in the lowest wear.

Performance of first and second-order sliding mode observers for nonlinear systems

This paper presents a brief study on the design and performance comparison of conventional first-order and super-twisting second-order sliding mode observers for some nonlinear control systems. Estimation accuracy, fast response, chattering effect, peaking phenomenon and robustness are considered for nonlinear ystems under observer-based output feedback control and state feedback control.

Deformation and frictional heating in relation to wear in sheet metal stamping

In the automotive industry, press production rates often need to be reduced in order to minimize tool wear issues and successfully stamp advanced high strength steels. This indicates that heating affects may be important. This paper examines friction and deformational heating at the die radius during sheet metal stamping, using finite element analysis. The results show that high temperatures, of up to 130°C, can occur at the die radius surface. Such behavior has not been previously reported in the literature, for what is expected to be ‘cold’ sheet metal stamping conditions. It will be shown that the temperature rise is due to the increased contact stresses and increased plastic work, associated with stamping AHSS. Consequently, new insights into the local contact conditions in sheet metal stamping were obtained. The outcomes of this work may impact the wear models and tests employed for future tool wear analyses in sheet metal stamping.

Navigation of four-wheel-steering mobile robots using robust fault-tolerant sliding mode control

This paper addresses the leader-follower tracking problem of a four-wheel-steering robot subjected to nonlinear uncertainties. Two control laws have been developed, based on the adaptive sliding mode method and the adaptive input-output feedback linearization method. The proposed control schemes have been tested by means of simulations.

A new sliding mode-based learning control scheme

 A new sliding mode-based learning control scheme for a class of SISO dynamic systems is developed in this paper. It is seen that, based on the most recent information on the closed-loop stability, a recursive learning chattering-free sliding mode controller can be designed to drive the closed-loop dynamics to reach the sliding mode surface in a finite time, on which the desired closed-loop dynamics with the zero-error convergence can be achieved.