Dr Hafid Belaidi

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

Dr Hafid Belaidi

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

Senior Lecturer

Department of Engineering Science

Faculty of Engineering and Science

Dr Hafid Belaidi joined the University of Greenwich in February 2009. He is currently a Senior Lecturer in Thermo-Fluid and programme manager in the Department of Engineering Science. He graduated with a first-class MEng degree in Marine Engineering from the University of Science and Technology of Oran (Algeria) and was awarded a PhD in Mechanical Engineering from the University of Liverpool. Hafid has held various research positions, notably at the Universities of Bradford and Ulster. He also worked in industry for a service provider to the oil and gas industry for several years improving produced fluids separation processes and improving operator competency.

His main research interests include:

  • Experimental and numerical simulation of fluid flows through complex passages, mainly to improve aerodynamic shapes of components, such as turbine and compressor blade design and separator geometry
  • Physical separation of Liquid/liquid and solid/liquid systems using cyclonic technology
  • Energy use optimisation in manufacturing plants through simulation and modelling

Hafid also worked across 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 practices. Dr Belaidi is currently supervising three PhD students.

  • Course coordinator (4 courses)
  • Programme manager
  • Partnership manager
  • Timetabling Officer for all Engineering Departments
  • Institution of Mechanical Engineers Academic Liaison

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

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

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.


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.


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.


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.


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.

, , , and () . Process Safety and Environmental Protection. Elsevier. pp. 262-273. ISSN 0957-5820 ISSN 0957-5820

, , and () . Journal of Cleaner Production. Elsevier. pp. 266-276. ISSN 0959-6526 ISSN 0959-6526

, , , , and () . Applied Energy. Elsevier Ltd.. pp. 323-335. ISSN 0306-2619 ISSN 0306-2619

, , and () . Energy and Buildings. Elsevier B.V.. ISSN 0378-7788 ISSN 0378-7788

Browse our research at GALA

, , , and () . In: The 2017 European Simulation and Modelling Conference. Eurosis, Portugal. pp. 328-335. ISBN 978-492859-00-6

Browse our research at GALA