Fire and Gas detectors are commonly installed in manufacturing and production facilities utilising hazardous processes to automatically alarm and trigger safety measures in response to hazardous events. Without effective detection, installations can be susceptible to three main hazards: (1) accumulation of toxic gases to levels that exceed given exposure threshold limits, (2) accumulation of flammable gases to levels that can cause fires or explosions and (3) various types of fire events.
The design of gas detection systems is currently based on fairly simple, often company-specific standards or rules, and carried out with ‘mapping’ software. It maps each detector within a defined volume of specified size, in which the detector is assumed to detect all possible leaks. This method, while simple and robust, can lead to excessive detector numbers if the hazards are not well understood, and the parameters to be used in design (such as the cloud size required to cause damaging overpressures) are selected poorly. Also, this approach is not based in any way on the typical wind fields or actual flow patterns in the facility.
Based on its computational fluid dynamics software FLACS, Gexcon suggested the development of a new application in gas detection system optimization, based on running many different gas dispersion scenarios. While experienced with traditional ‘mapping software’, Micropack’s intention to join the experiment has been to be involved in the development of the next generation gas detection system optimisation methodology, based on CFD simulation.
The objective of this experiment has been to improve the installation design process by using advanced CFD simulation and modelling techniques in a cloud-based framework, which exceeds standard modern ‘mapping programs’ for gas detection purposes. The solution provides a firm and repeatable base upon which complex reasoning for designing detector systems should be based. It provides improved safety and reduced detector installation and operating cost in a vast number of industrial/manufacturing facilities that incur risks of gas releases, explosions, fire, etc.
Since the computational requirements of this system are considerable (simulation of many different scenarios), the solution is provided as an HPC-cloud based simulation and modelling service.
