Validation of geometry modelling approaches for offshore gas dispersion simulations. (November 2016)

• Record Type: Journal Article
• Authors: Ahmed, I.; Bengherbia, T.; Zhvansky, R.; Ferrara, G.; Wen, J.X.; Stocks, N.G.
• Is Part Of: Journal of loss prevention in the process industries. Volume 44(2016:Nov.)
• Page Start: 594
• Page End: 600
• Publication Date: 2016-11
• Subjects: Gas dispersion -- Geometry modelling -- Computational fluid dynamics; Chemical industries -- Safety measures -- Periodicals; 660.2804
• DOI: 10.1016/j.jlp.2016.07.009
• Languages: English
• ISSNs: 0950-4230

Abstract

Abstract: Computational Fluid Dynamics (CFD) codes are widely used for gas dispersion studies on offshore installations. The majority of these codes use single-block Cartesian grids with the porosity/distributed-resistance (PDR) approach to model small geometric details. Computational cost of this approach is low since small-scale obstacles are not resolved on the computational mesh. However, there are some uncertainties regarding this approach, especially in terms of grid dependency and turbulence generated from complex objects. An alternative approach, which can be implemented in general-purpose CFD codes, is to use body-fitted grids for medium to large-scale objects whilst combining multiple small-scale obstacles in close proximity and using porous media models to represent blockage effects. This approach is validated in this study, by comparing numerical predictions with large-scale gas dispersion experiments carried out in DNV GL's Spadeadam test site. Gas concentrations and gas cloud volumes obtained from simulations are compared with measurements. These simulations are performed using the commercially available ANSYS CFX, which is a general-purpose CFD code. For comparison, further simulations are performed using CFX where small-scale objects are explicitly resolved. The aim of this work is to evaluate the accuracy and efficiency of these different geometry modelling approaches. Highlights: Significant savings in computational time when small-scale obstacles are represented using porosity. Resolving small-scale obstacles does not give a significant improvement in results. The porosity approach needs to be refined further.