TY  - JOUR
  - Cronin, K, Davis, M
  - 2008
  - August
  - Proceedings of The Institution of Mechanical Engineers Part E-Journal of Process Mechanical Engineering
  - Analysis of The Variability In Collapse Time of A Process Storage Vessel Due to Internal Steam Condensation
  - Validated
  - ()
  - 222
  - E3
  - 171
  - 181
  - An expression to predict the time taken for a storage vessel to collapse because of the development of a net external pressure was obtained in a previous paper. Steam condensation inside the vessel was the mechanism chosen to produce this mode of failure. There is considerable natural dispersion in the causes of this phenomenon, meaning that collapse times are unpredictable in practice. An experimental arrangement to obtain data on dispersion in this phenomenon was devised. A large series of replicate tests were conducted to quantify the statistics describing the dispersion. Two probabilistic modelling techniques, the perturbation method and the Monte-Carlo, Simulation, were employed to analyse this variation. Good agreement was found between the predictions of the modelling techniques and the experimentally obtained results..
  - DOI 10.1243/09544089JPME170
DA  - 2008/08
ER  - 

@article{V722548,
   = {Cronin,  K and  Davis,  M },
   = {2008},
   = {August},
   = {Proceedings of The Institution of Mechanical Engineers Part E-Journal of Process Mechanical Engineering},
   = {Analysis of The Variability In Collapse Time of A Process Storage Vessel Due to Internal Steam Condensation},
   = {Validated},
   = {()},
   = {222},
   = {E3},
  pages = {171--181},
   = {{An expression to predict the time taken for a storage vessel to collapse because of the development of a net external pressure was obtained in a previous paper. Steam condensation inside the vessel was the mechanism chosen to produce this mode of failure. There is considerable natural dispersion in the causes of this phenomenon, meaning that collapse times are unpredictable in practice. An experimental arrangement to obtain data on dispersion in this phenomenon was devised. A large series of replicate tests were conducted to quantify the statistics describing the dispersion. Two probabilistic modelling techniques, the perturbation method and the Monte-Carlo, Simulation, were employed to analyse this variation. Good agreement was found between the predictions of the modelling techniques and the experimentally obtained results..}},
   = {DOI 10.1243/09544089JPME170},
  source = {IRIS}
}