Impact of nanodiffusion on the stacking fault energy in high-strength steels

A key requirement of modern steels – the combination of high strength and high deformability – can best be achieved by enabling a local adaptation of the microstructure during deformation. A local hardening is most efficiently obtained by a modification of the stacking sequence of atomic layers, resulting in the formation of twins or martensite. Combining ab initio calculations with in situ transmission electron microscopy, we show that the ability of a material to incorporate such stacking faults depends on its overall chemical composition and, importantly, the local composition near the defect, which is controlled by nanodiffusion. Specifically, the role of carbon for the stacking fault energy in high-Mn steels is investigated. Consequences for the long-term mechanical properties and the characterisation of these materials are discussed.

The association between attributions of responsibility for motor vehicle accidents and patient satisfaction: a study within a no-fault injury compensation system

This study set out to test the relationship between attributions of responsibility for motor vehicle accidents and satisfaction with personal injury compensation systems.

Sleeping at work: not all about location, location, location

Working arrangements in industries that use non-standard hours sometimes necessitate an 'onsite' workforce where workers sleep in accommodation within or adjacent to the workplace. Of particular relevance to these workers is the widely held (and largely anecdotal) assumption that sleep at home is better than sleep away, particularly when away for work. This narrative review explores the idea that sleep outcomes in these unique work situations are the product of an interaction between numerous factors including timing and duration of breaks, commute length, sleeping environment (noise, movement, vibration, light), circadian phase, demographic factors and familiarity with the sleep location. Based on the data presented in this review, it is our contention that the location of sleep, whilst important, is secondary to other factors such as the timing and duration of sleep periods. We suggest that future research should include measures that allow conceptualisation of other critical factors such as familiarity with the sleeping environment.

Approach to fault detection of time-delay systems using functional observers

A new methodology is reported for designing functional observers to detect actuator faults of a class of time-delay systems where the matrix pair (A, C) is not observable. First, a generalised state transformation is used to transform the system into new coordinates where the delay term associated with the state vector is injected into the system's output and input. Then, a minimum-order functional observer is designed to construct a residual function that can trigger system faults. The finding is significant as it is now possible to detect faults of time-delay systems where the pair (A, C) is not required to be observable. A numerical example is given to illustrate the effectiveness of the proposed design approach. © The Institution of Engineering and Technology 2014.

The correlation between stacking fault energy and the work hardening behaviour of high-mn twinning induced plasticity steel tested at various temperatures

High-Mn Twinning Induced Plasticity (TWIP) steels have superior mechanical properties, which make them promising materials in automotive industry to improve the passenger safety and the fuel consumption. The TWIP steels are characterized by high work hardening rates due to continuous mechanical twin formation during the deformation. Mechanical twinning is a unique deformation mode, which is highly governed by the stacking fault energy (SFE). The composition of steel alloy was Fe-18Mn-0.6C-1Al (wt.%) with SFE of about 25-30 mJ/m2 at room temperature. The SFE ensures the mechanical twinning to be the main deformation mechanism at room temperature. The microstructure, mechanical properties, work hardening behaviour and SFE of the steel was studied at the temperature range of ambient ≤T[°C]≤ 400°C. The mechanical properties were determined using Instron tensile testing machine with 30kN load cell and strain rate of 10-3s-1 and the work hardening behaviour curves were generated using true stress and true strain data. The microstructure after deformation at different temperatures was examined using Zeiss Supra 55VP SEM. It was found that an increase in the deformation temperature raised the SFE resulting in the deterioration of the mechanical twinning that led to decrease not only in the strength but also in the total strain of the steel. A correlation between the temperature, the SFE, the mechanical twinning, the mechanical properties and the work hardening rate was also found. © (2014) Trans Tech Publications, Switzerland.

Incidental physical activity in Melbourne, Australia: health and economic impacts of mode of transport and suburban location.

Using the known health impacts of physical activity (PA), levels of incidental PA in Melbourne were analysed, and after determining key behavioural associations, economic modelling estimated potential long-term health and economic benefits of changes in active transport (AT) patterns.

AUV location detection in an enclosed environment

Normally, experiments are done in a controlled environment so that different systems under test can be isolated. The added benefit is that the sensors used are a lot more accurate under controlled conditions. In the experiments perform on underwater robot localization, this was not the case. The sonar localization equipment use perform flawlessly in open water as it was designed to do, but poorly in an indoor pool. It is believed that the sonar had too much power causing too many reflections in the enclosed space. Unfortunately the experiments are better done in a pool so as to control the elements under test. This paper is the search to improve the equipment's accuracy in an enclosed environment by attempting to reduce the power of the sonar via mechanical means.

Motor fault detection and diagnosis using a hybrid FMM-CART model with online learning

In this paper, a hybrid online learning model that combines the fuzzy min-max (FMM) neural network and the Classification and Regression Tree (CART) for motor fault detection and diagnosis tasks is described. The hybrid model, known as FMM-CART, incorporates the advantages of both FMM and CART for undertaking data classification (with FMM) and rule extraction (with CART) problems. In particular, the CART model is enhanced with an importance predictor-based feature selection measure. To evaluate the effectiveness of the proposed online FMM-CART model, a series of experiments using publicly available data sets containing motor bearing faults is first conducted. The results (primarily prediction accuracy and model complexity) are analyzed and compared with those reported in the literature. Then, an experimental study on detecting imbalanced voltage supply of an induction motor using a laboratory-scale test rig is performed. In addition to producing accurate results, a set of rules in the form of a decision tree is extracted from FMM-CART to provide explanations for its predictions. The results positively demonstrate the usefulness of FMM-CART with online learning capabilities in tackling real-world motor fault detection and diagnosis tasks. © 2014 Springer Science+Business Media New York.