Dr Hafid Belaidi

Dr Hafid Belaidi PhD, MEng, Cert HE, CEng, MIMechE, SFHEA

Associate Professor and Deputy Head of Engineering

Key details

Dr Hafid Belaidi

Associate Professor and Deputy Head of Engineering


Hafid joined the University of Greenwich in February 2009 as a Senior Lecturer in the areas of Thermo-Fluids and Numerical Simulation. He graduated with a first-class MEng degree in Marine Engineering from U.S.T.O and read for a PhD in Mechanical Engineering at the University of Liverpool. Before joining the University of Greenwich, he spent many years working in industry for a service provider to the oil and gas industry developing systems to enhanced oil and gas recovery. Prior to that, he held several research positions, notably at the Universities of Bradford and Ulster.

Hafid has responsibilities spanning several levels. As a deputy head, he has full operational responsibility of the school of engineering and oversees the day to day running of its activities. He also manages a programme of study and leads four mechanical engineering modules across three different stages. He was behind the development of successful partnerships with international partners which he currently manages.

Hafid worked on major research projects sponsored by multinational oil and gas players and manufacturers. His research outputs are disseminated through journal papers and conference proceedings and is currently supervising two PhD students. His research interests are in the areas of:

  • Produced fluid treatment for enhanced oil and gas recovery.
  • Wet and dry separation and filtration processes.
  • Energy optimisation in large and complex manufacturing environments.

Hafid worked cross disciplines, using engineering tools to investigate physiological problems, and was the first to publish a paper on the use of FEA in the investigation of stress distribution in the human eye lens to improve medical diagnosis and intervention.

Awards

Best Graduating Student and award of a scholarship to study for a PhD.

Recognition

  • Chartered Engineer registered with the Engineering Council
  • Member of the Institution of Mechanical Engineers
  • Senior Fellow of the Higher Education Academy

Research / Scholarly interests

Main research areas

  • Experimental Fluid Dynamics
  • Computational Fluid Dynamics
  • Cyclonic Separation
  • Energy Optimisation
  • Heat Storage

Current projects

Energy Optimisation in Complex Manufacturing Environments – EPSRC Industrial CASE Award with Ford Motor Company (HSSMI)

Energy used in manufacturing is generally quantified as overall usage and with a history of low energy costs the need to optimise or breakdown this cost was not a priority. With the rising cost of energy it has become rather significant operating cost of manufacturing industry. In order to optimise energy consumption, its actual usage must be quantified and the correlations with operation procedures, practices and scheduling must be investigated.

Aim

To develop a modelling framework and associated techniques to optimise the usage of energy in manufacturing.

Optimisation of Ancillary and Support Systems in Large Factories to Lower Energy Usage – VC s Scholarship and co-funded by Ford motor company and the HSSMI

Manufacturing in a large factory is an expensive operation, with both direct and indirect costs. A significant indirect cost is the running of ancillary and support machines. Recent research work with HSSMI/Ford has shown a significant amount of energy and resources being used in supporting direct operations. Some of these energy/resources are used in running compressors, coolant pumps, chillers and a host of electronic systems. The relationship between resources used for indirect operations and the number of items produced is hard to correlate, unless a complex simulation is used to replicated measured data and algorithms created to establish this complex inter-relationship.

Aim

The aim of this project is to optimise the running of all ancillary and support systems used in large factories to lower energy/resource consumption.

Lowering Cost and Carbon Footprint via Energy Modelling and Management – funded by Ford Motor Company

Large quantities of energy (~ 5MW) are used to run a manufacturing plant, most of which is lost via extraction of fumes from machines and through the ventilation of the factory in addition to losses through open doors and windows. Other losses are through the roof and walls of the factory and from the transport of steam via pipes. In order to maintain air quality, positive pressure has to be maintained whilst fumes and particles have to be extracted from the machines. These two conflicting requirements can lead to a lack of positive air pressure being maintained which is further exacerbated by leakage from open doors and windows. Lack of positive air pressure compromises the clean room requirements needed for optimal quality.

Aim

To reduce the overall energy consumption at the Ford Dagenham plant whilst increasing air quality and comfort as well as evaluating and lowering the environmental impact of processes in the plant.

Predicting concentrations of fine particles in enclosed vessels using a camera based system

Biomass is generating an increased interest as a renewable fuel and as a consequence, industries handling biomass have experienced a fast level of growth over the past ten years. This, however, comes with challenges, especially when handling, transporting and storing materials such as wood pellets. One of the issues with pelletised biomass is the breakage of pellets that lead to fine particles smaller than 500 micron that can form dust clouds in the handling and storing equipment. These dust clouds present potential health and safety hazards as well as dust explosion hazards to plant and operator if dust explosive limits are reach during the filling process of silos. To eliminate or reduce such hazards a profound understanding of fine particle dynamics in the dust cloud circulation in the silo is required.

Aim

The aim of the project is to develop a camera based system to predict fine dust concentration in silos and help improve silo design to avoid dust explosive concentration envelop.

Recent publications

Lulbadda, L.L., S. Zigan & A. Belaidi (2016), 'Predicting Concentration of Fines in Enclosed Vessels Using a Camera System', With Publishers for review. Farnish, R., A. Belaidi & S. Zigan, "The Effects of Reverse Jet Pulse Over-Pressurisation on Dust Filter Performance", (2019), 13th International Conference on

Bulk Materials Storage, Handling and Transportation, 9 -11 July 2019, Mantra on View, Queensland, Australia.

Farnish, R., A. Belaidi & S. Zigan, "Investigation into the effects of Cyclic Particle Loading onto Filter Media", (2019), 13th International Conference on Bulk Materials Storage, Handling and Transportation, 9 -11 July 2019, Mantra on View, Queensland, Australia.

Mulvany, R., A. Arokiam, A. Belaidi, J. Ladbrook & M. Higgins, (2017) "Optimisation of Compressed Air System's Energy Usage Through Discrete Event Simulation: Compressor Performance". ESM 2017 at IST – Instituto Superior Tecnico Lisbon, Portugal.

Skarvelis-Kazakos, S., T. Gorman, A. Belaidi & S. Zegan (2015), 'Multiple Energy Carrier Optimisation with Intelligent Agents', Journal of Applied Energy (2015).

Wilson, J., A. Arokiam, A. Belaidi, & J. Ladbrook (2015), 'A simple Energy Usage Toolkit from Manufacturing Simulation Data', Journal of Cleaner Energy (2015).