Taste of Research Summer Scholarships

2027 Projects - School of Mechanical and Manufacturing Engineering

Mechanical & Manufacturing Engineering Research Areas

Related Projects

Projects offered by other Engineering Schools that may be of interest.

Mechanical & Manufacturing Engineering Projects

No School Research Area

Project Title:	Development of Digital Tools for Engineering Analysis, Visualisation and Decision Support for bioma
Name of Supervisor:	Prof. Gangadhara Prusty
Email of Supervisor:	g.prusty@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr. Prashanth Nagulapally
Email of Joint/Co-Supervisor:	.
School:	School of Mechanical and Manufacturing Engineering
Faculty Research Area (Theme):	Structural Engineering, Structures
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Development of Digital Tools for Engineering Analysis, Visualisation and Decision Support for biomaterials and conveyor frames - This project aims to develop and validate advanced digital tools that integrate experimental data, engineering models and artificial intelligence to support analysis, visualisation and engineering decision-making across dental and mining applications. Sub-Project 1 will develop a software platform for reconstructing and visualising the three-dimensional spatial and temporal evolution of polymerisation-induced shrinkage in dental resin composites. Building on previous CFBG-based spatial strain measurements, depth-wise and spatially distributed CFBG data will be used with AI-based modelling to reconstruct 3D shrinkage fields and provide interactive visualisation of shrinkage evolution during polymerisation. Sub-Project 2 will develop and validate a digital decision-support tool for the selection and preliminary design of composite conveyor components for mining applications. The tool will incorporate user requirements and engineering rules covering structural loads, operating conditions, component configurations, material/design options and relevant compliance requirements. It will be demonstrated across at least three representative use cases and validated against benchmark designs. The overall project will deliver functional software prototypes, associated validation and user documentation, supporting translation of research outcomes into practical digital engineering tools.
Research Environment:	You will join a top-notch Composites research laboratory in Australia (Southern Hemisphere). You will be supported by postdocs and a primary supervisor. The AMAC centre can manufacture, post-cure, test, analyse, and monitor the structural health of composites under one roof. This experience prepares the student for real life challenges and exposure to industry scale research and manufacturing. Ideal applicants should have strong programming skills in C/C++, Python or MATLAB, with foundational knowledge in composites and structures.
Novelty and Contribution:	.
Expected Outcomes:	1. A validated AI-assisted 3D visualisation tool for reconstructing spatial and temporal polymerisation-induced shrinkage in dental resin composites using CFBG sensor data. 2. Experimental datasets and modelling approaches for depth-wise and three-dimensional characterisation of polymerisation-induced strain. 3. A functional digital decision-support tool for selection and preliminary design of composite conveyor components for mining applications. 4. Validation of the mining tool against benchmark designs and demonstration through at least three representative use cases. 5. Functional software prototypes, validation methodologies and user documentation supporting future research, industry deployment and technology translation.
Reference Material Links:	https://www.unsw.edu.au/research/amac https://doi.org/10.1016/j.dental.2026.09.007. *https://www.linkedin.com/posts/gprusty_compositematerials-mininginnovation-minesafety-share-7500044972881072129-vkmA/
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Flame flashback mitigation for 100% hydrogen capable gas turbines
Name of Supervisor:	Prof Evatt Hawkes
Email of Supervisor:	evatt.hawkes@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr Jianhong Lin
Email of Joint/Co-Supervisor:	.
School:	School of Mechanical and Manufacturing Engineering
Faculty Research Area (Theme):	Energy Systems, Renewable and Non-Renewable
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Australia has massive potential for renewable electricity generation that significantly exceeds our own needs. Embodying this energy in a chemical form such as hydrogen (H2) would enable its international trade, helping to decarbonise economies elsewhere. To convert the energy in such fuels back into electricity at the point of end use, large combined cycle gas turbines offer the most efficient option; however, their ability to burn hydrogen needs to be improved, with the most important issue being boundary layer flashback. In this off-design condition, the flame propagates upstream from its design location into fuel/air mixing sections, leading to catastrophic failure. In this project, you will evaluate a measure of mitigating flashback, by injecting air at or near to the wall. This will lead to local dilution and a reduced flame speed, potentially enhancing flashback resistance. To evaluate this concept, you will carry out two-dimensional, laminar direct numerical simulations, with a highly scalable open-source computational fluid dynamics (CFD) code (PeleLMeX) using high-performance computing. Your task will be construct and analyse a series of simulations designed to understand the effectiveness of wall air injection to mitigate flashback. Applicants for this project should be very strong in mathematics, physics, and engineering thermofluids, and ideally would have basic knowledge of chemistry and some scripting experience, though the last two are not strictly necessary.
Research Environment:	You will join a thriving, highly focused group working on using supercomputers to understand turbulent, chemically reacting flows in sustainable energy applications. You will be well supported by a PhD student and postdoc as well as the primary advisor. Additionally, you will join in social activities of the group.
Novelty and Contribution:	.
Expected Outcomes:	You will learn a lot about combustion, CFD, and high-performance computing. The project outcomes will help understand the mechanisms behind flashback mitigation using wall air injection, providing useful information for industry to design more flashback resistant combustors, and ultimately an efficient way to burn renewable, zero-carbon hydrogen fuel.
Reference Material Links:	https://research.unsw.edu.au/people/professor-evatt-hawkes
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Multimodal chemical sensors: simultaneous colorimetric and chemiresistive detection using a single m
Name of Supervisor:	Dr Mohamed Kilani
Email of Supervisor:	m.kilani@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr Zifei Han, Prof. Rona Chandrawati
Email of Joint/Co-Supervisor:	.
School:	School of Mechanical and Manufacturing Engineering
Faculty Research Area (Theme):	Advanced Materials
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Most conventional gas sensors rely on a single type of signal output: they provide either a qualitative visual warning or a quantitative electronic readout. This limits their deployment in critical areas like smart food packaging for quality control or wearable badges for industrial safety. For example, while current colour-changing polymer sensors can visually indicate meat spoilage, their response cannot be easily integrated into digital systems for remote, continuous logging. This project aims to bridge that gap by building a dual-mode sensor that reports gas exposure both visually and electronically in a single package. We are using Polydiacetylenes (PDAs), a class of polymers that change from blue to red when exposed to target gases like ammonia and amines, which are common byproducts of food decomposition. Because the structural shift that causes this colour change also alters electrical conductivity, we can theoretically measure both properties simultaneously. To make the polymer sufficiently conductive for a reliable electronic reading, you will engineer a composite material by integrating conductive charge-transfer-complex (CTC) crystals into the PDA matrix. You will take this concept from materials formulation to device prototyping. Your tasks will involve depositing these composite thin films onto interdigitated microelectrodes, exposing the sensors to target analytes, and simultaneously recording real-time electrical and optical data. This project provides hands-on experience in thin-film fabrication, microelectronics, and sensor characterisation, delivering proof-of-concept data for a new class of smart sensors.
Research Environment:	The student will be co-supervised across two complementary areas of expertise: Prof. Rona Chandrawati's NanoFAM Laboratory (specialising in colorimetric nanosensors for food, health, and environmental monitoring) and Dr Mohamed Kilani's research focus on electrocrystallised nanomaterials and chemiresistive devices. The student will have hands-on access to materials synthesis facilities, patterned microelectrode platforms, and an automated gas-sensor testing bench equipped for controlled analyte concentration, humidity, and temperature. The combined supervisory team will provide day-to-day mentoring, ensuring a supportive cross-disciplinary environment ideal for a first research experience.
Novelty and Contribution:	.
Expected Outcomes:	• Demonstration of a single PDA material transducing a gas signal both colorimetrically and electrically. • Evaluation of whether PDA/CTC composite films improve the baseline chemiresistive response. • Characterisation of a set of films with paired optical and electrical response data for a target analyte. • Generation of preliminary results to seed a journal publication featuring the student as a contributor.
Reference Material Links:	Tjandra, Angie Davina, and Rona Chandrawati. "Polydiacetylene/copolymer sensors to detect lung cancer breath volatile organic compounds." RSC Applied Polymers 2.6 (2024): 1043-1056. Wang, Ren, et al. "Electrocrystallization of Copper 7, 7, 8, 8?Tetracyanoquinodimethane Charge?Transfer Complex on Flexible Substrates for Real?Time Ammonia Gas Sensing." Advanced Sensor Research 4.3 (2025): 2400167.
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Optical diagnostics and machine learning of gaseous fuel combustion in a heavy-duty diesel engine
Name of Supervisor:	Prof. Shawn Kook
Email of Supervisor:	s.kook@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Mechanical and Manufacturing Engineering
Faculty Research Area (Theme):	Energy Systems, Renewable and Non-Renewable
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	A selected student will perform high-speed imaging diagnostics in a running optical diesel engine to which a new gaseous main fuel is injected. The engine is compatible with both hydrogen and natural gas, two most promising candidates for industrial decarbonisation. The student will post process the obtained high-speed flame images to obtain flame shape parameters as well as in-flame flow fields. These quantified info will be used to develop new flame features for machine learning with which crucial flame parameters responsible for high efficiency engine operation are found for enhanced fundamental understanding. The student is not expected to hold high academic score but needs to be passionate about engines, optical diagnostics and image post processing. Previous experience in optical engines and high-speed flame imaging is preferred. The student needs to demonstrate excellent communication skills - both spoken and written - and that s/he work effectively in a team environment. The student is expected to have a sincere interest in MPhil or PhD study.
Research Environment:	The student will work with an experienced PhD candidate or Research Associate to operate a research engine with optical access. The student will lead the design change required to achieve gaseous fuel injection, and actual running of the engine and high-speed imaging.
Novelty and Contribution:	.
Expected Outcomes:	The student will be fully trained to conduct a higher degree research (HDR) study - either MPhil or PhD - towards affordable and reliable industrial decarbonisation. The student will engage with global industry partners with the results presented to the industry engineers and receive feedback on future tasks.
Reference Material Links:	Visit the research website https://research.unsw.edu.au/projects/engines and read papers such as https://www.sciencedirect.com/science/article/pii/S2666352X25000639?via%3Dihub https://journals.sagepub.com/doi/10.1177/14680874251330681
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Satellite manoeuvre detection
Name of Supervisor:	Dr Yang Yang
Email of Supervisor:	yang.yang16@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Mechanical and Manufacturing Engineering
Faculty Research Area (Theme):	Intelligent & Autonomous Systems
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	This project aims to enhance space safety by developing a system that leverages optical data and optimal control theory to accurately model, detect, and analyse the behaviours of manoeuvring space objects in near Earth orbits. Given the increasing number of satellite constellations and the complexity of proximity operations, accurate monitoring is essential to avoid collisions. This initiative will yield an add-on to the existing in-house orbit dynamics tool for satellite monitoring and manoeuvre analysis, aligning with the Australian Space Agency's commitment to space sustainability. It will be of significant benefit to satellite operators and will contribute to global efforts to maintain space as a safe and sustainable environment.
Research Environment:	This project offers a unique opportunity to develop advanced expertise in orbital dynamics. You will begin by mastering an in?house high?fidelity orbit propagator, then explore classical optimal control theories and apply them to satellite manoeuvre detection using optical tracking data from a ground?based telescope. The project also involves using a Lambert solver to define admissible regions for hypothetical space object orbits. This experience prepares you to contribute to global space?domain awareness and space?traffic management. Ideal applicants have strong programming skills in C/C++, Python or MATLAB, with foundational knowledge of control theory and orbit dynamics.
Novelty and Contribution:	.
Expected Outcomes:	Verified codes for simulations and detections of satellite manoeuvres. A summary of experimental results using both synthetic and real-life satellite tracking datasets. A manuscript draft to summarise the research output.
Reference Material Links:	https://www.sciencedirect.com/science/article/pii/S0094576521000291 Yang Yang, Zhenwei Li, Han Cai, Yan Zhang, SINGLE-/MULTIPLE-REVOLUTION LAMBERT’S PROBLEM CONSTRAINTS FOR OPTICAL TRACK-TO-TRACK ASSOCIATION, AAS 21-671
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Project Title:	Understanding mechanisms of ammonia slip in zero-carbon gas turbine combustors
Name of Supervisor:	Prof Evatt Hawkes
Email of Supervisor:	evatt.hawkes@unsw.edu.au
Name of Joint/Co-Supervisor:	Dr Jianhong Lin
Email of Joint/Co-Supervisor:	.
School:	School of Mechanical and Manufacturing Engineering
Faculty Research Area (Theme):	Energy Systems, Renewable and Non-Renewable
Applicable to other Engineering schools/disciplines:
Terms:	Summer
Abstract:	Australia has massive potential for renewable electricity generation that significantly exceeds our own needs. Embodying this energy in a chemical form such as ammonia (NH3) would enable its international trade, helping to decarbonise economies elsewhere. To convert the energy in such fuels back into electricity at the point of end use, large combined cycle gas turbines offer the most efficient option; however, their ability to burn ammonia needs to be improved, with the key outstanding issue being emissions of oxides of nitrogen (NOx), a regulated pollutant. Much progress has been made using rich-lean staged combustion systems, where the fuel is burned first in a fuel-rich stage, which is followed by a fuel-lean stage. However, if any ammonia bypasses combustion in the first stage (ammonia slip), it will cause large emissions of NOx in the second stage. In this project, you will evaluate one of two mechanisms of NH3 slip: flame extinction by interaction with a wall, or flame extinction by aerodynamic strain. Your evaluation will be carried out using two-dimensional, laminar direct numerical simulations, carried out with a highly scalable open-source computational fluid dynamics (CFD) code (PeleLMeX) using high performance computing. Your task will be construct and analyse a series of simulations designed to understand the extinction mechanisms and the resulting ammonia slip. Applicants for this project should be very strong in mathematics, physics, and engineering thermofluids, and ideally would have basic knowledge of chemistry and some scripting experience, though the last two are not strictly necessary.
Research Environment:	You will join a thriving, highly focused group working on using supercomputers to understand turbulent, chemically reacting flows in sustainable energy applications. You will be well supported by a PhD student and postdoc as well as the primary advisor. Additionally, you will join in social activities of the group.
Novelty and Contribution:	.
Expected Outcomes:	You will learn a lot about combustion, CFD, and high performance computing. The project outcomes will help unravel the mechanisms of ammonia slip, providing crucial information for industry in the design of improved rich-lean staged combustion systems, and ultimately an efficient way to burn renewable, zero-carbon fuels.
Reference Material Links:	https://research.unsw.edu.au/people/professor-evatt-hawkes
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No

Projects offered by other Engineering Schools that may be of interest are:

Graduate School of Biomedical Engineering

School of Computer Science and Engineering

Project Title:	Combination Therapy with Antimicrobial Peptides to Combat Multidrug-Resistant Bacteria
Name of Supervisor:	Edgar Wong
Email of Supervisor:	edgar.wong@unsw.edu.au
Name of Joint/Co-Supervisor:	.
Email of Joint/Co-Supervisor:	.
School:	School of Chemical Engineering
Faculty Research Area (Theme):	Health & Medical Technologies
Applicable to other Engineering schools/disciplines:	Biomedical Engineering Computer Science & Engineering Mechanical & Manufacturing Engineering Photovoltaic and Renewable Energy Engineering
Terms:	Summer
Abstract:	Antimicrobial resistance (AMR) is now considered a critical global healthcare challenge and urgently requires new therapeutic strategies to overcome this issue. Antimicrobial peptides (AMPs) and mimics thereof have been shown to effectively synergise and revive the 'lost' activity of antibiotics against multidrug-resistant bacteria. This approach is promising in combating AMR and we aim to build upon our initial work and develop further. The project will look at testing more combinations and against wider panel of bacteria including priority pathogens such as Klebsiella pneumoniae and Acinetobacter baumannii.
Research Environment:	Very biofocussed project and hence the scholar will be mainly working in a PC2 microbiology lab to perform antimicrobial assays. Scholar needs to have good attention to detail.
Novelty and Contribution:	.
Expected Outcomes:	Tested various combinations of AMPs and antibiotics against different bacteria strains. The results are expected to lead to high impact publication and also further in vivo testing in animal models with collaborators, which would form the basis of preclinical work for future translation. The scholar will learn/enhance technical skills at working in a biolab and also develop deep knowledge in the AMR field.
Reference Material Links:	https://www.edgarwonglab.com/ https://pubs.acs.org/doi/full/10.1021/acsinfecdis.2c00087 https://pubs.acs.org/doi/full/10.1021/acs.biomac.4c01137 General reading on antimicrobial peptides (AMPs) and combination therapy
Will the student visit the premises of an industry partner, or undertake any activity on premises external to UNSW?	No