Modelling and visualisation of material flow in friction stir spot welding

Abstract The material flow in friction stir spot welding of aluminium to both aluminium and steel has been investigated, using pinless tools in a lap joint geometry. The flow behaviour was revealed experimentally using dissimilar Al alloys of similar strength. The effect on the material flow of tool surface features, welding conditions (rotation speed, plunge depth, dwell time), and the surface state of the steel sheet (un-coated or galvanized) have been systematically studied. A novel kinematic flow model is presented, which successfully predicts the observed layering of the dissimilar Al alloys under a range of conditions. The model and the experimental observations provide a consistent interpretation of the stick-slip conditions at the tool-workpiece interface, addressing an elusive and long-standing issue in the modelling of heat generation in friction stir processing.

Manufacturing at double the speed

The speed of manufacturing processes today depends on a trade-off between the physical processes of production, the wider system that allows these processes to operate and the co-ordination of a supply chain in the pursuit of meeting customer needs. Could the speed of this activity be doubled? This paper explores this hypothetical question, starting with examination of a diverse set of case studies spanning the activities of manufacturing. This reveals that the constraints on increasing manufacturing speed have some common themes, and several of these are examined in more detail, to identify absolute limits to performance. The physical processes of production are constrained by factors such as machine stiffness, actuator acceleration, heat transfer and the delivery of fluids, and for each of these, a simplified model is used to analyse the gap between current and limiting performance. The wider systems of production require the co-ordination of resources and push at the limits of human biophysical and cognitive limits. Evidence about these is explored and related to current practice. Out of this discussion, five promising innovations are explored to show examples of how manufacturing speed is increasing—with line arrays of point actuators, parallel tools, tailored application of precision, hybridisation and task taxonomies. The paper addresses a broad question which could be pursued by a wider community and in greater depth, but even this first examination suggests the possibility of unanticipated innovations in current manufacturing practices.

Effect of Single and Double Austenitization heat treatments on the Microstructure and Hardness of AISI D2 Tool Steel

This investigation is concerned with the study of effect of Double Austenitization (DA) and Single Austenitization (SA) heat treatment processes on microstructure and mechanical property of AISI D2type cold worked tool steel. To maximize hardness, tool steels are used in a quenched and tempered condition. This involves heating the material to the austenitizing temperature (∼850−1100 °C), quenching at an appropriate rate to form martensite, and tempering to reduce the retained austenite content and induce toughness. The merits of DA treatment isto promote dissolution of carbides at the same time proscribe grain coarsening significantly was attempted in D2 tool steel. The study has found that DA treatment has induced high hardness with insignificant growth in grains. The increase in hardness is attributed to increase in carbon content in matrix due to dissolution of carbides; whereas finer grains due to role of inclusions.

Processing, microstructure and mechanical properties of air plasma-sprayed ceria-yttria co-stabilized zirconia coatings

Thermal barrier coatings (TBCs) are widely adopted to protect mechanical components in gas turbine engines operating at high temperature. Basically, the surface temperature of these components must be low enough to retain material properties within acceptable bounds and to extend component life. From this standpoint, air plasma-sprayed (APS) ceria and yttria co-stabilized zirconia (CYSZ) is particularly promising because it provides enhanced thermal insulation capabilities and resistance to hot corrosion. However, essential mechanical properties, such as hardness and Young's modulus, have been less thoroughly investigated. Knowledge of Young's modulus is of concern because it has a significant effect on strain tolerance and stress level and, hence, on durability. The focus of the present study was to determine the mechanical properties of APS CYSZ coatings. In particular, X-ray diffraction (XRD) is adopted for phase analysis of powders and as-sprayed coatings. In addition, scanning electron microscopy (SEM) and image analysis (IA) are employed to explore coating microstructure and porosity. Finally, the Young's modulus of the coating is determined using nanoindentation and a resonant method. The results obtained are then discussed and a cross-check on their consistency is carried out by resorting to a micromechanical model. © 2010 Blackwell Publishing Ltd.

Numerical modelling of low temperature laser produced magnesium plasma

The two-dimensional laser-plasma-interaction hydrodynamic code POLLUX has been used to simulate the ablation of a magnesium target by a 30-ns, 248-nm KrF excimer laser at low laser fluences of ≤10 J cm2. This code, originally written for much higher laser intensities, has been recently extended to include a detailed description of the equation of state in order to treat changes of phase within the target material, and also includes a Thomas Fermi description of the electrons. The simulated temporal and spatial evolution of the plasma plume in the early phase of the expansion (≤100 ns) is compared with experimental interferometric measurements of electron density. The expansion dynamics are in good agreement, although the simulated electron number density is about 2.5 times higher than the experimental values.

Olefin / Paraffin separation using Task-Specific Materials based on Ionic Liquids: Advances in Gas Processing

In this work, 1-hexene was extracted from its mixtures with n-hexane in varying ratios using a task specific ionic liquid. Herein, the ionic liquid (IL) 1-butyl-3-methylimidazolium nitrate, [BMIM][NO3], was used and examined with and without the addition of a metal salt. The impact of water on both selectivity and distribution coefficient was also tested. Four potential metal salts were investigated, the results of which demonstrate that the dissolution of transition-metal salts in the IL improves the separation of 1-hexene from n-hexane through metal-olefin complexation. Additionally, the presence of water in IL solutions containing metal salt enhances this selectivity. Finally, UNIFAC was used to correlate the experimental LLE data with good accuracy.

Software Products for Modelling and Simulation in Materials Science

Models and software products have been developed for modelling, simulation and prediction of different correlations in materials science, including 1. the correlation between processing parameters and properties in titanium alloys and ?-titanium aluminides; 2. time–temperature–transformation (TTT) diagrams for titanium alloys; 3. corrosion resistance of titanium alloys; 4. surface hardness and microhardness profile of nitrocarburised layers; 5. fatigue stress life (S–N) diagrams for Ti–6Al–4V alloys. The programs are based on trained artificial neural networks. For each particular case appropriate combination of inputs and outputs is chosen. Very good performances of the models are achieved. Graphical user interfaces (GUI) are created for easy use of the models. In addition interactive text versions are developed. The models designed are combined and integrated in software package that is built up on a modular fashion. The software products are available in versions for different platforms including Windows 95/98/2000/NT, UNIX and Apple Macintosh. Description of the software products is given, to demonstrate that they are convenient and powerful tools for practical applications in solving various problems in materials science. Examples for optimisation of the alloy compositions, processing parameters and working conditions are illustrated. An option for use of the software in materials selection procedure is described.

Germanium MOS Capacitors with Hafnium Dioxide and Silicon Dioxide Dielectrics

Germanium (Ge) does not grow a suitable oxide for MOS devices. The Ge/dielectric interface is of prime importance to the operation of photo-detectors and scaled MOSTs. Therefore there is a requirement for deposited or bonded dielectric materials. MOS capacitors have been formed on germanium substrates with three different dielectric materials. Firstly, a thermally grown and bonded silicon dioxide (SiO2) layer, secondly, SiO2 deposited by atmospheric pressure CVD ‘silox’, and thirdly a hafnium oxide (HfO2) high-k dielectric deposited by atomic layer deposition (ALD). Ge wafers used were p-type 1 0 0 2 O cm. C–V measurements have been made on all three types of capacitors to assess the interface quality. ALD HfO2 and silox both display acceptable C–V characteristics. Threshold voltage and maximum and minimum capacitance values closely match expected values found through calculation. However, the bonded SiO2 has non-ideal C–V characteristics, revealing the presence of a high density of interface states. A H2/N2 post metal anneal has a detrimental effect on C–V characteristics of HfO2 and silox dielectrics, causing a shift in the threshold voltage and rise in the minimum capacitance value. In the case of hafnium dioxide, capacitor properties can be improved by performing a plasma nitridation of the Ge surface prior to dielectric deposition.

Modelling the correlation between processing parameters and properties of maraging steels using artificial neural network

An artificial neural network (ANN) model is developed for the analysis and simulation of the correlation between the properties of maraging steels and composition, processing and working conditions. The input parameters of the model consist of alloy composition, processing parameters (including cold deformation degree, ageing temperature, and ageing time), and working temperature. The outputs of the ANN model include property parameters namely: ultimate tensile strength, yield strength, elongation, reduction in area, hardness, notched tensile strength, Charpy impact energy, fracture toughness, and martensitic transformation start temperature. Good performance of the ANN model is achieved. The model can be used to calculate properties of maraging steels as functions of alloy composition, processing parameters, and working condition. The combined influence of Co and Mo on the properties of maraging steels is simulated using the model. The results are in agreement with experimental data. Explanation of the calculated results from the metallurgical point of view is attempted. The model can be used as a guide for further alloy development.