(180ai) Toxic/Flammable Gas Detectors Allocation: Multi-Grid Treatment | AIChE

(180ai) Toxic/Flammable Gas Detectors Allocation: Multi-Grid Treatment

Authors 

Gimenes, G. B. C. - Presenter, Chemtech - A Siemens Company
Neto, A. T. P. - Presenter, Chemtech - A Siemens Company
Souza, I. R. D. - Presenter, Chemtech - A Siemens Company
Delgaudio, C. V. P. - Presenter, Chemtech - A Siemens Company
Souza, V. C. D. - Presenter, Chemtech - A Siemens Company
Waltz, F. - Presenter, Chemtech - A Siemens Company


Computational fluid dynamics (CFD) and mechanical systems optimization concepts are currently quite important tools for engineering problems analysis. A typical application of such tools is gas dispersion studies, a theme of great importance for the oil and gas industry. An important safety item for oil and gas production installations (especially oil rigs) is the use of flammable and/or toxic gas sensors to detect gas leaks. The importance of these sensors relies on potential costs compensations and the reduction of environmental impacts, life loss, and profit loss.The methodology for positioning gas sensors uses CFD tools. Associating simulation results with coherent mathematical treatment, this methodology presents improvements in relation to other studies of gas dispersion and sensor positioning. The methodology output is a probability profile that shows the most probable areas to find the gas, which allows one to define the best location for the sensors. This methodology was already presented during the 2008 AIChE Spring Meeting, which took place in New Orleans, LA (USA).This work presents an upgrade in the methodology: the possibility of multi grid treatment, allowing one to create the probability profiles using simulations with different grids as inputs, which was not possible before. The strategy was implemented using interpolation tools and concerns the migration of every different grid to a standard one to be interpreted by the methodology mechanisms. This module makes the methodology more flexible while allows the engineer to adopt grids which fits better in each of his cases.

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