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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
£2,670,701

Division of Mechanical Engineering, Robotics and Design

Research Projects

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

Drinking Water from Rain: a standalone green energy powered rainwater purification system


Principal Investigator: Hasan SHAHEED
Co-investigator(s): PETER MCOWAN and Pankaj VADGAMA
Funding source: Royal Society
Start: 01-12-2019  /  End: 30-11-2021
Amount: £74,000

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

Electroadhesion for anchoring robots in challenging environments


Principal Investigator: Ketao ZHANG
Co-investigator(s): HAREESH GODABA
Funding source: EPSRC Engineering and Physical Sciences Research Council
Start: 01-10-2019  /  End: 30-09-2020
Amount: £77,189

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.