Decision support systems optimising effluent release in sub tropical estuarine environment - An Australian case study

Gold Coast Water is responsible for the management of the water and wastewater assets of the City of the Gold Coast on Australia’s east coast. Treated wastewater is released at the Gold Coast Seaway on an outgoing tide in order for the plume to be dispersed before the tide changes and renters the Broadwater estuary. Rapid population growth over the past decade has placed increasing demands on the receiving waters for the release of the City’s effluent. The Seaway SmartRelease Project is designed to optimise the release of the effluent from the City’s main wastewater treatment plant in order to minimise the impact of the estuarine water quality and maximise the cost efficiency of pumping. In order to do this an optimisation study that involves water quality monitoring, numerical modelling and a web based decision support system was conducted. An intensive monitoring campaign provided information on water levels, currents, winds, waves, nutrients and bacterial levels within the Broadwater. These data were then used to calibrate and verify numerical models using the MIKE by DHI suite of software. The decision support system then collects continually measured data such as water levels, interacts with the WWTP SCADA system, runs the models in forecast mode and provides the optimal time window to release the required amount of effluent from the WWTP. The City’s increasing population means that the length of time available for releasing the water with minimal impact may be exceeded within 5 years. Optimising the release of the treated water through monitoring, modelling and a decision support system has been an effective way of demonstrating the limited environmental impact of the expected short term increase in effluent disposal procedures. (PDF contains 5 pages)

Design support for turbomachinery

From the steam turbines which provide most of our electricity to the jet engines which have shrunk our World, turbomachines undoubtedly play a major role in life today. Competition in the turbomachinery industry is fiercely strong [Wisler, 1998], hence good aerodynamic design is vital. However, with efficiency levels already close to their theoretical maxima, companies are increasingly looking to reduce costs and increase reliability through improved design practice. Computational Fluid Dynamics (CFD) can make a strong contribution to assisting this process as it has the potential to increase performance while reducing cost. The situation is, however, complicated by an ever decreasing number of engineers with sufficient design experience to reap the full benefits offered by CFD. With the large risks involved, novice designers of today are increasingly confined to refining old designs rather than gaining experience, like their forebears, through 'clean sheet' exercises. Hence it is desirable to capture the knowledge and experience of older designers, before it is lost, to assist the engineers of tomorrow. It is therefore the aim of this project to produce a design support tool which will not only store the appropriate CFD codes, but also provide a dynamic signpost (based on elicited knowledge and experience) to advise the engineer in their use. The signposting methodology developed for the aerospace industry [Clarkson and Hamilton, 1997] will provide the basic framework for the tool. This paper reviews current turbomachinery design practice (including an examination of the relevant CFD) in order to establish the important issues which a support tool must address. Current design support methodologies and their propriety are then reviewed, followed by a detailed description of the signposting concept. It then sets out a clear statement of the objectives for the research and the methods proposed to meet them. The paper concludes with a timetable of the work.

A new adaptive marine policy toolbox to support ecosystem-based approach to management

4 p.

International Support of Climate Change Policies in Developing Countries: Strategic, Moral and Fairness Aspects

33 p.