Integrated modelling of cost-effective siting and operation of flow-control infrastructure for river ecosystem conservation

Wetland and floodplain ecosystems along many regulated rivers are highly stressed, primarily due to a lack of environmental flows of appropriate magnitude, frequency, duration, and timing to support ecological functions. In the absence of increased environmental flows, the ecological health of river ecosystems can be enhanced by the operation of existing and new flow-control infrastructure (weirs and regulators) to return more natural environmental flow regimes to specific areas. However, determining the optimal investment and operation strategies over time is a complex task due to several factors including the multiple environmental values attached to wetlands, spatial and temporal heterogeneity and dependencies, nonlinearity, and time-dependent decisions. This makes for a very large number of decision variables over a long planning horizon. The focus of this paper is the development of a nonlinear integer programming model that accommodates these complexities. The mathematical objective aims to return the natural flow regime of key components of river ecosystems in terms of flood timing, flood duration, and interflood period. We applied a 2-stage recursive heuristic using tabu search to solve the model and tested it on the entire South Australian River Murray floodplain. We conclude that modern meta-heuristics can be used to solve the very complex nonlinear problems with spatial and temporal dependencies typical of environmental flow allocation in regulated river ecosystems. The model has been used to inform the investment in, and operation of, flow-control infrastructure in the South Australian River Murray.

Current distribution and Lorentz field modelling using cathode designs : a parametric approach

A mathematical model of magnetohydrodynamic (MHD) effects in an aluminium cell using numerical approximation of a finite element method is presented. The model predicts the current distribution in the cell and calculates the Lorentz force from the external magnetic field in molten metal for cathode blocks with different surface inclinations.

The findings indicated that the cathode surface inclinations have significant influence on cathode current density and Lorentz field distribution in the molten metal. The results establish a trend for the current density and associated MHD force distributions with increase in cathode inclination angle, φ. It has been found that cathode with φ = 5^o inclination could decrease 16 to 20 % of Lorentz force in the molten metal.

Enhanced thermal stability and lifetime of epoxy nanocomposites using covalently functionalized clay: Experimental and modelling

The present work aims at finding a relationship between kinetic models of thermal degradation process with the physiochemical structure of epoxy-clay nanocomposites in order to understand its service temperature. In this work, two different types of modified clays, including clay modified with (3-aminopropyl)triethoxysilane (APTES) and a commercial organoclay, were covalently and non-covalently incorporated into epoxy matrix, respectively. The effect of different concentrations of silanized clay on thermal behaviour of epoxy nanocomposites were first investigated in order to choose the optimum clay concentration. Afterwards, thermal characteristics of the degradation process of epoxy nanocomposites were obtained by TGA analysis and the results were employed to determine the kinetic parameters using model-free isoconversional and model-fitting methods. The obtained kinetic parameters were used to model the entire degradation process. The results showed that the incorporation of the different modified clay into epoxy matrix change the mathematical model of the degradation process, associating with different orientations of clay into epoxy matrix confirming by XRD results. The obtained models for each epoxy nanocomposite systems were used to investigate the dependence of degradation rate and degradation time on temperature and conversion degree. Our results provide an explanation as to how the life time of epoxy and its nanocomposites change in a wide range of operating temperatures as a result of their structural changes.

Characterising an ECG signal using statistical modelling: a feasibility study

For clinical use, in electrocardiogram (ECG) signal analysis it is important to detect not only the centre of the P wave, the QRS complex and the T wave, but also the time intervals, such as the ST segment. Much research focused entirely on qrs complex detection, via methods such as wavelet transforms, spline fitting and neural networks. However, drawbacks include the false classification of a severe noise spike as a QRS complex, possibly requiring manual editing, or the omission of information contained in other regions of the ECG signal. While some attempts were made to develop algorithms to detect additional signal characteristics, such as P and T waves, the reported success rates are subject to change from person-to-person and beat-to-beat. To address this variability we propose the use of Markov-chain Monte Carlo statistical modelling to extract the key features of an ECG signal and we report on a feasibility study to investigate the utility of the approach. The modelling approach is examined with reference to a realistic computer generated ECG signal, where details such as wave morphology and noise levels are variable.