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Queen Mary University of LondonQueen Mary University of London
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Current research funding in the Division of Mechanical Engineering, Robotics and Design

Division of Mechanical Engineering, Robotics and Design

Research Projects

The following are current funded research projects taking place within the research division:

Hierarchical optimal energy management of electric vehicles

Principal Investigator: Guang LI
Funding source: EU Commission - Horizon 2020
Start: 01-07-2019  /  End: 30-06-2021
Amount: £179,947

It has been widely recognized that vehicle electrification provides a potential way for the EU to move towards a more decarbonized transport system and sustainable circular economy. The overarching objective of this project is to develop a novel computationally efficient hierarchical adaptive optimal control framework incorporating transportation information and drivers’ habits suitable for energy management of multi-source EVs.

The National Centre for Nuclear Robotics (NCNR)

Principal Investigator: Kaspar ALTHOEFER
Co-investigator(s): Andrea Cavallaro, Lorenzo JAMONE, Ildar FARKHATDINOV, Miles Hansard and Stefan Poslad
Funding source: EPSRC Engineering and Physical Sciences Research Council
Start: 02-10-2017  /  End: 30-04-2021
Amount: £1,020,239

Nuclear facilities require a wide variety of robotics capabilities, engendering a variety of extreme RAI challenges. NCNR brings together a diverse consortium of experts in robotics, AI, sensors, radiation and resilient embedded systems, to address these complex problems. In high gamma environments, human entries are not possible at all. In alpha-contaminated environments, air-fed suited human entries are possible, but engender significant secondary waste (contaminated suits), and reduced worker capability. We have a duty to eliminate the need for humans to enter such hazardous environments wherever technologically possible. Hence, nuclear robots will typically be remote from human controllers, creating significant opportunities for advanced telepresence. However, limited bandwidth and situational awareness demand increased intelligence and autonomous control capabilities on the robot, especially for performing complex manipulations. Shared control, where both human and AI collaboratively control the robot, will be critical because i) safety-critical environments demand a human in the loop, however ii) complex remote actions are too difficult for a human to perform reliably and efficiently.

Thermal neutron distribution within a small reactor corePredictive Modelling for Nuclear Engineering (Early Career Fellowship)

Principal Investigator: Andrew BUCHAN
Funding source: E.P.S.R.C
Start: 19-06-2017  /  End: 18-12-2020
Amount: £464,161

To develop numerical models that predict the coupled neutronics-thermal hydraulics physics with nuclear reactor cores and to quantify the uncertainties in these predictions.

Launch & Recovery Enhanced Sea States

Principal Investigator: Guang LI
Funding source: E.P.S.R.C.
Start: 01-08-2017  /  End: 04-12-2020
Amount: £303,819

The project aims to develop a novel approach to predicting a suitable time instant at which to initiate an Launch and Recovery operation, together with a confidence measure, and then to control the execution of the subsequent lift operation once initiated.

Adaptive hierarchical model predictive control of wave energy converter - Stage 3

Principal Investigator: Guang LI
Funding source: WES Wave Energy Scotland
Start: 13-05-2019  /  End: 12-11-2020
Amount: £461,346

Asphalt mixture and experiment of fracture.Bimodule material in highway construction and computational study

Principal Investigator: Pihua WEN
Funding source: Changsha University of Science and Technology
Start: 01-07-2017  /  End: 30-06-2020
Amount: £90,000

Finite element method and meshless finite block method are developed to study composites with bimodule materials.


Principal Investigator: Kaspar ALTHOEFER
Funding source: Innovate UK
Start: 01-01-2018  /  End: 31-03-2020
Amount: £149,984

In this project, in collaboration with our partner, Q-bot, a London-based robotic company, we aim to design, manufacture and validate robust, soft robots to remotely apply insulation below the ground floor of domestic dwellings.

Organic Rankine Cycle

Principal Investigator: Huasheng WANG
Funding source: Royal Society
Start: 31-03-2018  /  End: 30-03-2020
Amount: £10,000

The project aims at bridging the gap between fundamental heat transfer and sustainable thermal systems by investigating expertise at both Queen Mary University of London and Guangdong University of Technology.

Newton Advanced Fellowship: Professor Wei He

Principal Investigator: Guang LI
Funding source: Royal Society
Start: 01-03-2017  /  End: 28-02-2020
Amount: £111,000

The project is on Control of Floating Wave Energy Converters with Mooring Systems. This project aims to resolve a fundamental control problem for floating wave energy converters (WEC) with mooring lines. The project will be collaboratively conducted by the UK team (lead by Dr Li) with expertise in WEC control and the Chinese team (lead by Prof He) in mooring control.

Automated remote monitoring of lower limb disorders to improve treatments and rehabilitation outcome

Principal Investigator: Aleksandra BIRN-JEFFERY
Funding source: Innovate UK
Start: 03-12-2018  /  End: 28-02-2020
Amount: £129,054

Thermally Driven Heat Pump Based on Integrated Thermodynamic Cycles for Low Carbon Domestic Heating

Principal Investigator: Huasheng WANG
Co-investigator(s): John ROSE
Funding source: E.P.S.R.C.
Start: 01-07-2016  /  End: 31-12-2019
Amount: £210,153

Schlieren image of over-expanded jet (pressure ratio of 3.2) emitting from a convergent-divergent nozzle of design Mach number 2, produced by Dr Punekar a visiting scholar in the group Jet noise: characteristics of the instantaneous emission patterns

Principal Investigator: Eldad AVITAL
Funding source: Royal Society
Start: 16-03-2018  /  End: 30-11-2019
Amount: £6,000

To develop a model which is consistent with jet noise far field measurements of both spectra measured at different angles and 2-point far field correlations of the sound pressure.