Bridge performance assessment through advanced sensing and modelling. Bridge performance assessment through advanced sensing and modelling. This project aims to create cyber infrastructure to manage and maintain civil infrastructure, specifically bridges. Current sensor data interpretation approaches are not good at assessing the performance of civil infrastructure or evaluating the reserve capacity; in particular, they do not adequately account for high levels of systematic modelling uncertaint ....Bridge performance assessment through advanced sensing and modelling. Bridge performance assessment through advanced sensing and modelling. This project aims to create cyber infrastructure to manage and maintain civil infrastructure, specifically bridges. Current sensor data interpretation approaches are not good at assessing the performance of civil infrastructure or evaluating the reserve capacity; in particular, they do not adequately account for high levels of systematic modelling uncertainties. This project intends to ease the current scientific data interpretation bottleneck. Expected outcomes are better infrastructure management and maintenance planning, fewer redundant interventions, modified infrastructure and improved future design.Read moreRead less
AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in d ....AI Assisted Probabilistic Structural Health Monitoring with Uncertain Data. This project aims to develop an advanced Artificial Intelligence (AI) assisted probabilistic structural health monitoring approach for civil engineering structures. The developed approach applies novel deep learning techniques with a large amount of data measured from uncertain and complex environment, for reliable structural condition monitoring and performance prediction. This project expects to make a step change in data mining and interpretation. Expected outcomes of the project include novel AI assisted approaches to conduct probabilistic structural condition monitoring with sensitive features and future structural performance prediction. This will provide significant benefits to infrastructure asset owners to reduce maintenance costs.Read moreRead less
Mitigating the risk of cyanobacterial blooms in wastewater ponds. Cyanobacterial blooms in wastewater treatment plants impact on effluent quality and the utility of recycled water, posing a significant risk to the economy, the environment and public health. To understand the causes of cyanobacterial blooms in pond-based wastewater treatment plants and the risk they pose, this project will use the latest molecular techniques to examine how the microbial communities within these systems interact w ....Mitigating the risk of cyanobacterial blooms in wastewater ponds. Cyanobacterial blooms in wastewater treatment plants impact on effluent quality and the utility of recycled water, posing a significant risk to the economy, the environment and public health. To understand the causes of cyanobacterial blooms in pond-based wastewater treatment plants and the risk they pose, this project will use the latest molecular techniques to examine how the microbial communities within these systems interact with each other and their surrounding environment to form blooms and produce toxins and other harmful metabolites. Such knowledge will inform risk assessment and provide strategies for the mitigation of future bloom events, improving the security of our increasingly valuable recycled water resources.Read moreRead less