The School of Civil, Environmental and Mining Engineering (CEME) is one of the livliest, most diverse and interesting Schools in the Faculty of Engineering, Computer and Mathematical Sciences.
If you want to design a bridge or a dam, build a football stadium, a skyscraper or a highway, organise operations in a mine, or tunnel through a mountain, CEME at the University of Adelaide can help you learn how and learn why. Our teachers and researchers are some of the best in Australia. And our graduates are some of the most outstanding engineers and contributors to the prosperity of the state and country. We invite you to join our team, and learn to engineer for the future.
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Water & Environmental EngineeringCoastal morphology and the River Murray mouth and Coorong Long-term modelling of nearshore coastal phenomena Environmental impact of man-made changes to climate change and its effect on the coast Development and application of Artificial Neural Networks in hydrology and water resources management Optimisation of the design, operation and management of water distribution systems including sustainability and water quality considerations Incorporation of uncertainty and multiple criteria in the design, operation and management of water resources and water supply systems Multi-objective optimization of total urban water management at the regional and cluster scales Development of decision support systems for natural resources management Monitoring, modelling and optimization of water quality in water distribution systems Use of artificial neural networks techniques for forecasting hydrologic and water resources variables Visit the Water & Environmental Engineering Research Group website for more information |
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Structures GroupPrevention of earthquake induced damage (including collapse) of unreinforced masonry buildings and non-seismically designed reinforced concrete frames Blast resistance of Ultra-High Performance concrete Mitigation of blast effects on Reinforced Concrete and masonry structures Characteristics of confined and partially confined blast loading Meso/micro scale model for cellular materials Rock fragmentation Behaviour and design of earthquake-resistant reinforced concrete structures Behaviour and design of fibre reinforced polymer (FRP) reinforced concrete structural members Confinement of normal- and high-strength concrete columns Design and use of concrete-filled FRP tubes as high-performance columns for new construction Repair and strengthening of reinforced concrete structures with FRP composites Reinforced concrete structures - behaviour and assessment under normal, cyclic and extreme loads Retrofitting reinforced concrete, steel and masonry structures by adhesive bonding steel or fibre reinforced polymer (FRP) reinforcement Advanced concrete material such as steel and polymer fibre concretes Composite steel and concrete structures - strength and fatigue endurance Application of three-dimensional failure criteria for the prediction of rock strength True-triaxial laboratory testing of rock materials Measurement and characterisation of discontinuities for rock engineering Rock slope stability analysis Visit the Structures Group website for more information |
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Mining and Geomechanics Early Warning System (EWS) for mine rock failure using acoustic emission Practical application of genetic programming in rock mechanics Numerical Modelling; 2D and 3D Finite Element Analysis New Austrian Tunnelling Method (NATM) Ground characterisation incorporating site investigation optimisation, in situ testing, problematic soils and ground vibrations Artificial neural networks in geotechnical engineering e-learning in geotechnical engineering Characterisation of the stratigraphy, structure and alteration associated with the Broken Hill orebody Visit the Mining and Geomechanics Research Group website for more information |
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GeostatisticsRisk and reliability in geotechnical engineering incorporating probabilistic analysis and design, spatial variability of soils, geostatistics Diagnosis and assessment of defective geotechnical structures using probabilistic approaches Incorporating spatial variability of soils in geotechnical modelling Evaluation of prediction uncertainty associated with non-linear soil models Visit the Geostatistics website for more information |
Further details are available, please contact the Faculty of Engineering, Computer & Mathematical Sciences office.