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Identification and characterization of design fires to be used in performance-based fire design of CERN facilities

Perovic, Darko LU (2018) In LUTVDG/TVBB VBRM05 20181
Division of Fire Safety Engineering
Abstract
CERN operates the most complex particle accelerator facility built until today. As such, it consists of thousands of custom-made components spread both in upper ground facilities and in underground tunnels and caverns. Several different hazards, including fire, are present in these facilities and need to be reduced to a tolerable level; in particular, fire safety often requires the application of a scientific and engineering approach. As it would be impossible addressing each tiny component individually, envelope conservative solutions have to be developed in order to save both financial and time resources.
This thesis is aimed at characterizing and better understanding of the potential fire behaviour of most common combustible items... (More)
CERN operates the most complex particle accelerator facility built until today. As such, it consists of thousands of custom-made components spread both in upper ground facilities and in underground tunnels and caverns. Several different hazards, including fire, are present in these facilities and need to be reduced to a tolerable level; in particular, fire safety often requires the application of a scientific and engineering approach. As it would be impossible addressing each tiny component individually, envelope conservative solutions have to be developed in order to save both financial and time resources.
This thesis is aimed at characterizing and better understanding of the potential fire behaviour of most common combustible items present in CERN’s facilities. After a detailed literature review of fires in electronic cabinets, an Excel calculator for obtaining a design fire in any number of cabinets/racks is developed. As literature for small vehicles in fires is scarce, suggestions on how to address the fires in vehicles used at CERN are given.
Second part of the thesis is dedicated to exploring testing techniques suitable for CERN’s needs with the goal of characterizing smoke produced by the most common cables and insulating oils used at CERN. Particle size distribution is obtained by using DMS500 fast particle analyser (Cambusiton), coupled with cone calorimeter (FTT). Data obtained on smoke particles will in future be used to validate and further improve FDS (Fire Dynamics Simulator) code in terms of addressing this issue. CERN is particularly interested in knowing the smoke particle size distribution that can be expected, as radioactive particles could be carried around, and endanger the whole facility and the surrounding environment. (Less)
Popular Abstract
CERN operates the most complex particle accelerator facility built until today. As such, it consists of thousands of custom-made components spread both in upper ground facilities and in underground tunnels and caverns. Several different hazards, including fire, are present in these facilities and need to be reduced to a tolerable level; in particular, fire safety often requires the application of a scientific and engineering approach. As it would be impossible addressing each tiny component individually, envelope conservative solutions have to be developed in order to save both financial and time resources.
This thesis is aimed at characterizing and better understanding of the potential fire behaviour of most common combustible items... (More)
CERN operates the most complex particle accelerator facility built until today. As such, it consists of thousands of custom-made components spread both in upper ground facilities and in underground tunnels and caverns. Several different hazards, including fire, are present in these facilities and need to be reduced to a tolerable level; in particular, fire safety often requires the application of a scientific and engineering approach. As it would be impossible addressing each tiny component individually, envelope conservative solutions have to be developed in order to save both financial and time resources.
This thesis is aimed at characterizing and better understanding of the potential fire behaviour of most common combustible items present in CERN’s facilities. After a detailed literature review of fires in electronic cabinets, an Excel calculator for obtaining a design fire in any number of cabinets/racks is developed. As literature for small vehicles in fires is scarce, suggestions on how to address the fires in vehicles used at CERN are given.
Second part of the thesis is dedicated to exploring testing techniques suitable for CERN’s needs with the goal of characterizing smoke produced by the most common cables and insulating oils used at CERN. Particle size distribution is obtained by using DMS500 fast particle analyser (Cambustion), coupled with cone calorimeter (FTT). Data obtained on smoke particles will in future be used to validate and further improve FDS (Fire Dynamics Simulator) code in terms of addressing this issue. CERN is particularly interested in knowing the smoke particle size distribution that can be expected, as radioactive particles could be carried around, and endanger the whole facility and the surrounding environment.
This thesis tries to present the state of art in the mentioned fields and to use the knowledge obtained in literature and by conducting experiments with a goal of further familiarizing with hazards common for nuclear facilities. (Less)
Please use this url to cite or link to this publication:
author
Perovic, Darko LU
supervisor
organization
course
VBRM05 20181
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Fire, Design fire, Vehicle fires, DMS 500, fast particulate analyser, Cone Calorimeter, Smoke characterization, Particle size distribution, Shell Diala, Midel, Cables, cable fires, Electrical cabinets, Electrical racks, CERN
publication/series
LUTVDG/TVBB
report number
5574
other publication id
LUTVDG/TVBB-5574-SE
language
English
id
8951634
date added to LUP
2018-06-20 11:30:40
date last changed
2018-06-20 11:30:40
@misc{8951634,
  abstract     = {{CERN operates the most complex particle accelerator facility built until today. As such, it consists of thousands of custom-made components spread both in upper ground facilities and in underground tunnels and caverns. Several different hazards, including fire, are present in these facilities and need to be reduced to a tolerable level; in particular, fire safety often requires the application of a scientific and engineering approach. As it would be impossible addressing each tiny component individually, envelope conservative solutions have to be developed in order to save both financial and time resources.
This thesis is aimed at characterizing and better understanding of the potential fire behaviour of most common combustible items present in CERN’s facilities. After a detailed literature review of fires in electronic cabinets, an Excel calculator for obtaining a design fire in any number of cabinets/racks is developed. As literature for small vehicles in fires is scarce, suggestions on how to address the fires in vehicles used at CERN are given. 
Second part of the thesis is dedicated to exploring testing techniques suitable for CERN’s needs with the goal of characterizing smoke produced by the most common cables and insulating oils used at CERN. Particle size distribution is obtained by using DMS500 fast particle analyser (Cambusiton), coupled with cone calorimeter (FTT). Data obtained on smoke particles will in future be used to validate and further improve FDS (Fire Dynamics Simulator) code in terms of addressing this issue. CERN is particularly interested in knowing the smoke particle size distribution that can be expected, as radioactive particles could be carried around, and endanger the whole facility and the surrounding environment.}},
  author       = {{Perovic, Darko}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{LUTVDG/TVBB}},
  title        = {{Identification and characterization of design fires to be used in performance-based fire design of CERN facilities}},
  year         = {{2018}},
}