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EPSRC Reference: GR/L68346/01
Title: IMPROVING PREDICTIVE CAPABILITY OF POROSITY/ DISTRIBUTED RESISTANCE MODELS FOR CONFINED EXPLOSIONS
Principal Investigator: Cant, Professor R
Other Investigators:
Savill, Professor AM Dawes, Professor WN
Researcher Co-Investigators:
Project Partners:
Shell
Department: Engineering
Organisation: University of Cambridge
Scheme: Standard Research (Pre-FEC)
Starts: 30 March 1998 Ends: 29 September 2001 Value (£): 152,366
EPSRC Research Topic Classifications:
Combustion
EPSRC Industrial Sector Classifications:
No relevance to Underpinning Sectors
Related Grants:
Panel History:  
Summary on Grant Application Form
Accurate predictions of confined explosions that may occur in oil and gas installations are important to assess hazards and make safety cases, particularly in the light of the Piper-Alpha offshore platform disaster. It is widely recognized that Computational Fluid Dynamics (CFD) has an important role to play; as representative experiments are difficult, expensive and dangerous. Unfortunately the several hundred or thousands of obstacles that need to be considered in real rigs make it impossible to perform sufficiently resolved computations in most cases. Instead no attempt is made to resolve all of these and their influence is accounted for by introducing Porosity an Distributed Resistance (PDR) corrections based on geometrical considerations and empirical input from experiment and resolved computations for at most order 10 obstacles. Although such approximate methods have been tuned to predict some simple cases, a number of serious deficiencies have emerged from more rigorous evaluation on representative rig module explosions. Taking advantage of the need for detailed resolution only when flames interact with obstacles, the proposes have adopted a novel, adaptive, unstructured mesh CFD approach with complete geometrical flexibility which allows resolved computations to be performed very efficiently for simple geometries and extended to of order 100 obstacles (or more using latest Supercomputers). This provides the capability to improve PDR model handling of various close obstacle groups, floor gratings, and ignition locations encountered in practice and will thus be used to improve reliability of and confidence in hazard assessment.
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Organisation Website: http://www.cam.ac.uk