John Ewer

Dr John Ewer PhD, MSc, BSc.

Associate Professor in Applied Fire Safety Engineering

Dr John Ewer (he/him) is the Fire Research Team Leader for fire modelling research and the SMARTFIRE commercial software development in the Fire Safety Engineering Group (FSEG).

Dr Ewer is currently working on a number of fire safety and general safety related projects, including:

  • September 2022-ongoing: Healthy Sailing EU Horizon Project: developing a scientific evidence base, modelling tools and guidance in support of the Prevention, Mitigation, and Management (PMM) of disease outbreaks on passenger vessels.
  • 2018-ongoing: Leading a ‘buildingSMART’ project to develop standards focusing on the incorporation of FSE into BIM standards in support of preserving the ‘Golden Thread of Information’.
  • 2018-ongoing: The development of an Integrated Ship Survivability Assessment Capability (ISSAC) for the Australian DSTG (Defence Science & Technology Group),
  • 2020-ongoing: Research and development of a Virtual Training Environment (VTE) for aircraft crew training for emergency evacuation in survivable crashes.

2020-ongoing: During the Covid pandemic, Dr Ewer was awarded University of Greenwich Proof of Concept Innovation funding, and led the research team to develop modelling capabilities for indoor aerosol dispersal and infection risk modelling. This project included features such as moving sources, targets, and wake flows – based on scalar-gas and droplet dispersion using a localised ‘Wells-Riley’ method to determine infection risk.

Current Doctoral Supervisions:

  • Dr Ewer is currently supervising two VC Scholarship PhD researchers in their investigation of the fire dynamics in baled waste; and fire safety issues of high-rise buildings.

He has successfully supervised three PhD researchers in:

  • A Knowledge Based System supported control of fire modelling simulations;
  • Research into geometry optimisation of building evacuation;
  • Developing a data sharing strategy for Building Information Modelling (BIM) and Fire Safety Engineering (FSE).

Key Research, Enterprise, and Academic Activities:

  • 2012-ongoing: Dr Ewer is a co-ordinator and lecturer on the annual ‘Principles and Practice of Fire Modelling’ CPD (continuing Professional Development) short course, held online and face-to-face at the University of Greenwich.
  • 2015-ongoing: Dr Ewer has developed a strand of consultative work to review third party fire strategy submissions to Building Control services.
  • 2021-ongoing: Dr Ewer leads the Software Engineering BEng.  module COMP1714: ‘Software Engineering Management’ and tutors as well as supervises undergraduate and postgraduate project students.
  • 2008, 2014, 2021: Dr Ewer was included in three highly successful FSEG Research Excellence Framework (REF) submissions with significant contributions to the fire modelling related impact studies.

Awards and Achievements:

  • 2021: Dr Ewer attained a Gold/HEA (Higher Education Academy) Fellowship.
  • His research and publications have received numerous awards.

Publications:

  • Since 1997 Dr Ewer has authored and co-authored over fifty publications.

Qualifications

PhD in re-engineering and development of an object-oriented, interactive, event-driven CFD code from a legacy FORTRAN code. University of Greenwich, 2020.

MSc in Scientific and Engineering Software Technology. University of Greenwich, 1991.

BSc in Physics. Reading University, 1989.

Responsibilities within the university

  • Associate Professor in Applied Fire Safety Engineering.
  • Team leader for Fire Safety Research and SMARTFIRE software development in FSEG.
  • Coordinator and Lecturer for the CPD Short Course, titled: ‘Principles and Practice of Fire Modelling’.
  • Module Leader for the Level 6 COMP1714: ‘Software Engineering Management’ course.
  • Lecturer and Tutor in undergraduate and postgraduate Software Engineering subjects.
  • Undergraduate and postgraduate project supervisor.
  • PhD supervisor.

Awards

2022: Dr Ewer received the 2022 Student Led Teaching Award for best postgraduate research supervisor in FES.

2021: Awarded funding for VC Scholarship (VCS-FLAS-01-21) for High Rise Cladding Fire Research.

2020: Awarded University of Greenwich Innovation funding as Principal Investigator for project to develop a Covid-19 Aerosol Dispersion Modelling capability in SMARTFIRE.

2020: Awarded HEIF funding as Principal Investigator for a project to develop a prototype VR Virtual Training Environment for aircraft crews to manage emergency evacuation in survivable crashes involving fire.

2014: EU FP7 Research Project: “GETAWAY” (Intelligent Active Dynamic Signage Systems) was awarded the prestigious Research Impact Award as part of The Guardian University Awards.

2011: Co-authored journal paper: “Fire and evacuation analysis in BWB aircraft configurations: computer simulations and large-scale evacuation experiments”, won the award by the Royal Aeronautical Society for best paper in The Aeronautical Journal, 2010.

2006: Co-authored journal papers: “CFD Fire Simulation of the Swissair Flight 111 In-Flight Fire - Parts 1 & 2”, which appeared in the Aeronautical Journal 2006, won the Royal Aeronautical Society's Gold Award and George Taylor Prize.

Research / Scholarly interests

  • Dr Ewer leads research and development for the commercialisation of modelling capabilities related to SARS-CoV-2/Covid-19 aerosol and droplet dispersion and infection risk assessment (Innovation Fund for Proof of Concept);
  • He leads a research team developing a VR based Virtual Training Environment for Aircraft Crew (HEIF, 2019);
  • Dr Ewer leads the SMARTFIRE software development and research to develop a fully coupled Fire and Evacuation VR based framework, Integrated Ship Survivability Assessment Capability (ISSAC), for the Australian DSTG (2013 – Date);
  • He has collaborated on a HEIF funded review project concerning the fire safety risks and regulation of Green/Living Walls;
  • He also coordinates and lectures on the annual Principles and Practice of Fire Modelling (PPFM) CPD short course for fire professionals, with optional Master of Science by Research. A distance learning version of the course was created for deployment during the Covid-19 pandemic.

Dr Ewer has contributed to a number of past major projects, including:

2017-2020: Supported research for the Grenfell Tower Inquiry, examining factors that influenced the disaster’s severity;

2011-2014: EU ‘Getaway’ project (EU FP7) researching the use of active dynamic signage in evacuation emergencies;

2011-2014: EU ‘Aircraft Fire’ (EU FP7) investigating fire safety impacts of modern composite aircraft materials;

2015-2018: EU ‘AUGGMED’ (EU HORIZON) a VR first responder training system; and

2009, 2010: CBRN (Chemical, Biological, Radiological and Nuclear) related modelling capability development and technology review projects for the UK Home Office.

Among his research interests are:

Computational Fluid Dynamics (CFD), Object Oriented Programming, Indoor Air Quality (IAQ), C++ Programming, Fire Field Modelling (FFM), Fire Strategy Reviews, Fire Safety Consultancy, Optimization techniques, Knowledge Based Solution Control, Human Computer Interaction techniques, User Experience Design, Visualization, VR/AR and Mixed Reality, Serious Gaming, Building Information Modelling (BIM), Software Re-engineering & Re-use and Algorithm development.

Recent publications

Article

Stettler, Marc E. J. , Nishida, Robert T., de Oliveira, Pedro M., Mesquita, Léo C. C. , Johnson, Tyler J. , Galea, Edwin , Grandison, Angus , Ewer, John , Carruthers-Jones, David , Sykes, David (2022), Source terms for benchmarking models of SARS-CoV-2 transmission via aerosols and droplets. The Royal Society - Royal Society of Chemistry (RSC). In: , , , . The Royal Society - Royal Society of Chemistry (RSC), Royal Society Open Science, 9: 212022 (5) 2054-5703 (Online) (doi: https://doi.org/10.1098/rsos.212022).

Wang, Zhaozhi , Galea, Edwin R., Grandison, Angus, Ewer, John , Jia, Fuchen (2021), A coupled computational fluid dynamics and Wells-Riley model to predict COVID-19 infection probability for passengers on long-distance trains. Elsevier. In: , , , . Elsevier, Safety Science, 147: 105572 ISSN: 0925-7535 (Print), (doi: https://doi.org/10.1016/j.ssci.2021.105572) NB Item availability restricted.

Siddiqui, Asim A. , Ewer, John A., Lawrence, Peter J., Galea, Edwin R. , Frost, Ian R. (2021), Building information modelling for performance-based fire safety engineering analysis – a strategy for data sharing. Elsevier. In: , , , . Elsevier, Journal of Building Engineering, 42: 102794 2352-7102 (Online) (doi: https://doi.org/10.1016/j.jobe.2021.102794).

Wang, Zhaozhi , Galea, Edwin R., Grandison, Angus, Ewer, John , Jia, Fuchen (2021), Inflight transmission of COVID-19 based on experimental aerosol dispersion data. Oxford University Press. In: , , , Inflight Transmission of COVID-19 Based on Aerosol Dispersion Data. Oxford University Press, Journal of Travel Medicine, 28: taab023 (4) ISSN: 1195-1982 (Print), 1708-8305 (Online) (doi: https://doi.org/10.1093/jtm/taab023).

Woolley, Anthony , Ewer, John, Lawrence, Peter, Deere, Steven , Travers, Anthony , Whitehouse, Tom , Galea, Edwin Richard (2020), A naval damage incident recoverability toolset: Assessing naval platform recoverability after a fire event. Elsevier. In: , , , . Elsevier, Ocean Engineering, 207: 107351 ISSN: 0029-8018 (Print), (doi: https://doi.org/10.1016/j.oceaneng.2020.107351) NB Item availability restricted.

Galea, E.R. , Wang, Z., Jia, F., Lawrence, P.J. , Ewer, J. (2016), Fire safety assessment of open wide gangway underground trains in tunnels using coupled fire and evacuation simulation. Wiley. In: , , , . Wiley, Fire and Materials, 41 (6) . pp. 716-737 ISSN: 0308-0501 (Print), 1099-1018 (Online) (doi: https://doi.org/10.1002/fam.2413) NB Item availability restricted.

Monograph

Ewer, J. , Galea, E., Grandison, A., Patel, M. (2017), SMARTFIRE v4.4: technical reference manual. University of Greenwich. In: , , , . University of Greenwich, Greenwich, London, UK (doi: ).