Reinforced crumbed rubber concrete for residential construction. Reinforced crumbed rubber concrete for residential construction. This project aims to use crumb rubber from used tyres to replace natural sand aggregate in concrete used in housing construction. Globally, very few of the millions of tyres discarded annually are recycled, while natural sand used in concrete is being depleted. This project intends to provide the tyre industry with a viable market for end of life tyres, and the premix ....Reinforced crumbed rubber concrete for residential construction. Reinforced crumbed rubber concrete for residential construction. This project aims to use crumb rubber from used tyres to replace natural sand aggregate in concrete used in housing construction. Globally, very few of the millions of tyres discarded annually are recycled, while natural sand used in concrete is being depleted. This project intends to provide the tyre industry with a viable market for end of life tyres, and the premix concrete industry with a “green” product for the residential construction market. Expected benefits include the increased use of a waste resource (used tyres), reduced use of a scarce natural resource (sand), and the development of an economic but green alternative concrete option for residential builders and owners.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less