Mapping the global flow of steel: from steelmaking to end-use goods.

Our society is addicted to steel. Global demand for steel has risen to 1.4 billion tonnes a year and is set to at least double by 2050, while the steel industry generates nearly a 10th of the world's energy related CO₂ emissions. Meeting our 2050 climate change targets would require a 75% reduction in CO₂ emissions for every tonne of steel produced and finding credible solutions is proving a challenge. The starting point for understanding the environmental impacts of steel production is to accurately map the global steel supply chain and identify the biggest steel flows where actions can be directed to deliver the largest impact. In this paper we present a map of global steel, which for the first time traces steel flows from steelmaking, through casting, forming, and rolling, to the fabrication of final goods. The diagram reveals the relative scale of steel flows and shows where efforts to improve energy and material efficiency should be focused.

A Stochastic Model for Electron Multiplication Charge-Coupled Devices - From Theory to Practice

Electron multiplication charge-coupled devices (EMCCD) are widely used for photon counting experiments and measurements of low intensity light sources, and are extensively employed in biological fluorescence imaging applications. These devices have a complex statistical behaviour that is often not fully considered in the analysis of EMCCD data. Robust and optimal analysis of EMCCD images requires an understanding of their noise properties, in particular to exploit fully the advantages of Bayesian and maximum-likelihood analysis techniques, whose value is increasingly recognised in biological imaging for obtaining robust quantitative measurements from challenging data. To improve our own EMCCD analysis and as an effort to aid that of the wider bioimaging community, we present, explain and discuss a detailed physical model for EMCCD noise properties, giving a likelihood function for image counts in each pixel for a given incident intensity, and we explain how to measure the parameters for this model from various calibration images. © 2013 Hirsch et al.

The high strain rate response of Ultra High Molecular-weight Polyethylene: From fibre to laminate

The effect of strain rate upon the uniaxial response of Ultra High Molecular-weight Polyethylene (UHMWPE) fibres, yarns and laminates of lay-up [0/90]48 has been measured in both the 0/90 and ±45 configurations. The tensile strength of the matrix-dominated ±45 laminate is two orders of magnitude less than that of the fibre-dominated 0/90 laminate, and is more sensitive to strain rate. A piezoelectric force sensor device was developed to obtain the high strain rate data, and this achieved a rise time of less than 1 μs. It is found that the failure strength (and failure strain) of the yarn is almost insensitive to strain rate within the range (10 -1-103 s-1). At low strain rates (below 10 -1 s-1), creep of the yarn dominates and the failure strain increases with diminishing strain rate. The tensile strength of the dry yarn exceeds that of the laminate by about 20%. Tests on single fibres exceed the strength of the yarn by 20%. © 2013 Elsevier Ltd. All rights reserved.

Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo.

Action Potential (APs) patterns of sensory cortex neurons encode a variety of stimulus features, but how can a neuron change the feature to which it responds? Here, we show that in vivo a spike-timing-dependent plasticity (STDP) protocol-consisting of pairing a postsynaptic AP with visually driven presynaptic inputs-modifies a neurons' AP-response in a bidirectional way that depends on the relative AP-timing during pairing. Whereas postsynaptic APs repeatedly following presynaptic activation can convert subthreshold into suprathreshold responses, APs repeatedly preceding presynaptic activation reduce AP responses to visual stimulation. These changes were paralleled by restructuring of the neurons response to surround stimulus locations and membrane-potential time-course. Computational simulations could reproduce the observed subthreshold voltage changes only when presynaptic temporal jitter was included. Together this shows that STDP rules can modify output patterns of sensory neurons and the timing of single-APs plays a crucial role in sensory coding and plasticity.DOI:http://dx.doi.org/10.7554/eLife.00012.001.

Initial phase modelling in numerical explosion applied to process safety

The utilisation of computational fluid dynamics (CFD) in process safety has increased significantly in recent years. The modelling of accidental explosion via CFD has in many cases replaced the classical Multi Energy and Brake Strehlow methods. The benefits obtained with CFD modelling can be diminished if proper modelling of the initial phase of explosion is neglected. In the early stages of an explosion, the flame propagates in a quasi-laminar regime. Proper modelling of the initial laminar phase is a key aspect in order to predict the peak pressure and the time to peak pressure. The present work suggests a modelling approach for the initial laminar phase in explosion scenarios. Findings are compared with experimental data for two classical explosion test cases which resemble the common features in chemical process areas (confinement and congestion). A detailed analysis of the threshold for the transition from laminar to turbulent regime is also carried out. The modelling is implemented in a fully 3D Navier-Stokes compressible formulation. Combustion is treated using a laminar flamelet approach based on the Bray, Moss and Libby (BML) formulation. A novel modified porosity approach developed for the unstructured solver is also considered. Results agree satisfactorily with experiments and the modelling is found to be robust. © 2013 The Institution of Chemical Engineers.