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Improving the regulatory acceptance and numerical performance of CFD based fire-modelling software

Improving the regulatory acceptance and numerical performance of CFD based fire-modelling software

Grandison, Angus ORCID: 0000-0002-9714-1605 (2003) Improving the regulatory acceptance and numerical performance of CFD based fire-modelling software. PhD thesis, University of Greenwich.

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The research of this thesis was concerned with practical aspects of Computational Fluid Dynamics (CFD) based fire modelling software, specifically its application and performance. Initially a novel CFD based fire suppression model was developed (FIREDASS). The FIREDASS (FIRE Detection And Suppression Simulation) programme was concerned with the development of water misting systems as a possible replacement for halon based fire suppression systems currently used in aircraft cargo holds and ship engine rooms.

A set of procedures was developed to test the applicability of CFD fire modelling software. This methodology was demonstrated on three CFD products that can be used for fire modelling purposes. The proposed procedure involved two phases.

Phase 1 allowed comparison between different computer codes without the bias of the user or specialist features that may exist in one code and not another by rigidly defining the case set-up.

Phase 2 allowed the software developer to perform the test using the best modelling features available in the code to best represent the scenario being modelled. In this way it was hoped to demonstrate that in addition to achieving a common minimum standard of performance, the software products were also capable of achieving improved agreement with the experimental or theoretical results.

A significant conclusion drawn from this work suggests that an engineer using the basic capabilities of any of the products tested would be likely to draw the same conclusions from the results irrespective of which product was used. From a regulators view, this is an important result as it suggests that the quality of the predictions produced are likely to be independent of the tool used - at least in situations where the basic capabilities of the software were used.

The majority of this work has focussed on the use of specialised proprietary hardware generally based around the UNIX operating system. The majority of engineering firms that would benefit from the reduced timeframes offered by parallel processing rarely have access to such specialised systems. However, in recent years with the increasing power of individual office PCs and the improved performance of Local Area Networks (LAN) it has now come to the point where parallel processing can be usefully utilised in a typical office environment where many such PCs maybe connected to a LAN.

Harnessing this power for fire modelling has great promise. Modern low cost supercomputers are now typically constructed from commodity PC motherboards connected via a dedicated high-speed network. However, virtually no work has been published on using office based PCs connected via a LAN in a parallel manner on real applications. The SMARTFIRE fire field model was modified to utilise multiple PCs on a typical office based LAN. It was found that good speedup could be achieved on homogeneous PCs, for example for a problem composed of-100,000 cells would run on a network of 12 PCs with a speedup of 9.3 over a single PC. A dynamic load balancing scheme was devised to allow the effective use of the software on heterogeneous PC networks.

This scheme also ensured that the impact of the parallel processing on other computer users was minimised. This scheme also minimised the impact of other computer users on the parallel processing performed by the FSE.

Item Type: Thesis (PhD)
Additional Information:
Uncontrolled Keywords: computer software, computational Fluid Dynamics, CFD, fire modelling software, Unix, SMARTFIRE
Subjects: Q Science > QA Mathematics > QA76 Computer software
Pre-2014 Departments: School of Computing & Mathematical Sciences
School of Computing & Mathematical Sciences > Centre for Numerical Modelling & Process Analysis > Fire Safety Engineering Group
School of Computing & Mathematical Sciences > Department of Mathematical Sciences
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Last Modified: 14 Feb 2017 17:13

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