Designing the next generation of geosynthetic liner systems . The project aims to improve the effectiveness of geosynthetic liner systems to contain emerging contaminants such as per-and poly-fluoroalkyl substances (PFASs) for better protection of Australian groundwater resources. The project expects to experimentally validate theory to improve predictive models for performance of geosynthetic liner systems. Expected outcomes include new and updated design guidelines for effective environmental ....Designing the next generation of geosynthetic liner systems . The project aims to improve the effectiveness of geosynthetic liner systems to contain emerging contaminants such as per-and poly-fluoroalkyl substances (PFASs) for better protection of Australian groundwater resources. The project expects to experimentally validate theory to improve predictive models for performance of geosynthetic liner systems. Expected outcomes include new and updated design guidelines for effective environmental protection against PFASs and establishment of new approaches for predicting functional containment lifetimes of liner systems. These outcomes are expected to benefit the waste and remediation industries by influencing next-generation design regulations to ensure long-term environmental protection from PFAS.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