Civil engineering

Supervisor: Dr. Michael Heisel

Eligibility: Students enrolled in fluid mechanics and who have some experience programming in languages such as Python or Fortran.

Project Description: Much of the natural world and human-built environments exist within the lowest portion of the atmosphere known as the boundary layer. Wind patterns in the boundary layer significantly affect evaporation and heat exchange between the atmosphere and the Earth’s surface, which are key drivers of weather and climate change. The goal of this project is to advance our understanding of these wind patterns using a computational method known as large-eddy simulations (LES). The student will help run various LES cases using Australia’s national supercomputer Gadi. The student will also analyse and visualise outputs of the simulations. Preference will be given to students who have completed coursework in fluid mechanics and who have some experience programming in languages such as Python or Fortran.

Requirement to be on campus: Yes *dependent on government’s health advice.

Supervisor: Dr. Andres Fielbaum

Eligibility: Requires advanced programming skills

Project Description: The problem of deciding the itineraries of every vessel in a ferry public transport system is a complex one, as several constraints need to be met in order to ensure safety, efficiency, and punctuality. In this project, the student will work with a formulation of this problem as an Integer Linear Program (ILP), which they will have to program to be solved by state-of-the-art commercial solvers. They will use real-life data from the Sydney ferry system, and use this model to analyse how a potential electrification of the ferry system would impact their operations.

Requirement to be on campus: No

Supervisor: Dr. Emily Moylan; A/Prof. Somwrita Sarkar

Eligibility: WAM>75 and Undergraduate candidates must have already completed at least 96 credit points towards their undergraduate degree at the time of application

Project Description: We will develop and employ advanced machine learning methods and geo-spatial analysis for USGS LandSat imagery extending back several decades to detect the correlation and co-evolution of urban growth and urban heat island effects. The methods will be developed with the 50 biggest agglomerations of South America as an empirical case study. The results of the project will advance new knowledge and provide insights into how unplanned urban growth is contributing to the increasing intensity of urban heat islands in a developing part of the world, and the related energy, climate, and health implications. 

Requirement to be on campus: Yes *dependent on government’s health advice.

Supervisor: Dr. Ali Hadigheh

Eligibility: WAM>75 and Undergraduate candidates must have already completed at least 96 credit points towards their undergraduate degree at the time of application.

Project Description: Structures are subject to gradual and progressive deterioration over time, and are likewise prone to damage due to accident, misuse or extreme natural events. Corrosion of reinforcement is one of the main deteriorating mechanisms in reinforced concrete structures. In addition, the on-going requirement for more structurally sound infrastructures has driven the introduction and development of advanced structural health monitoring (SHM) methods. This project aims to use innovative SHM techniques for automated condition assessment and evaluation of reinforced concrete infrastructure.

Requirement to be on campus: Yes *dependent on government’s health advice.

Supervisor: Dr. Faham Tahmasebinia

Eligibility: WAM>75 and Undergraduate candidates must have already completed at least 96 credit points towards their undergraduate degree at the time of application.

Project Description: Steel–glass composite frames are advantageous compared with traditional steel frames. The combined use of steel and glass diversifies the structural design. Compared with traditional steel structures with straight members, the irregular shapes of glass–steel structures allow designers to express their design concepts in more artistic ways, which improves the aesthetic value of the designed structure.

In this research, the loading performance of the glass spindle torus in different cases will be investigated using two numerical modelling packages, Strand7 and ABAQUS. The research methodology will be exhibited high applicability on other case studies.  With these two powerful finite element modelling tools, the loading performance of other structures can also be captured by developing new structural models.

The most effective thickness and size of the stiffener to prevent local buckling will be explored. Finally, structural performance of the designed structure under serviceability limit state with vertical supports configured in the central opening will be comprehensively investigated.

Requirement to be on campus: No

Supervisor: Dr. Faham Tahmasebinia

Eligibility: WAM>75 and Undergraduate candidates must have already completed at least 96 credit points towards their undergraduate degree at the time of application.

Project Description:

The energy performance prediction of buildings plays a significant role in the design phases. Theoretical analysis and statistical analysis are typically carried out to predict energy consumption. However, due to the complexity of the building characteristics, precise energy performance can hardly be predicted in the early design stage.

This study considers both building information modelling (BIM) and statistical approaches, including several regression models for the prediction purpose. This research also highlights a number of findings of energy modelling related to building energy performance simulation software, particularly Autodesk Green Building Studio.

In this research, the geometric models were created using Autodesk Revit. Based on the energy simulation conducted by Autodesk Green Building Studio (GBS), the energy properties of number of prototype and case study models will be determined. The GBS simulation will be carried out using DOE 2.2 engine. Some key parameters will be demonstrated used in BIM, including building type, location, building area, analysis year, floor-to-ceiling height, floor construction, wall construction, and ceiling construction. The Monte Carlo simulation method will be performed to predict precise energy consumption.

Requirement to be on campus: No

Supervisor: Dr. Faham Tahmasebinia

Eligibility: WAM>75 and Undergraduate candidates must have already completed at least 96 credit points towards their undergraduate degree at the time of application.

Project Description:

A rock burst is an uncontrolled failure that releases a massive amount of kinetic energy, inducing excessive displacement of rock mass. Combined support to controlling rock dynamic failures is an essential part of the rock burst management. In the design of rock support, it is essential to consider not only the capacity of the individual elements but also their compatibility with each other and their interactions.

This research is aimed to develop a novel full-scale numerical procedure to evaluate the behaviour of individual support elements and their interactions under dynamic loads using Finite Element Commercial Package ABAQUS/Explicit. A mutual interaction relationship between two indicators, namely Cable/Rock Bolt Dissipated Energy and the Steel Mesh Dissipated Energy is also developed, and an interaction diagram will be provided.

The proposed design concept can be used for the selection of an appropriate support system for coal burst management.

Requirement to be on campus: No