Abstract
At CFD2014 in Trondheim, Norway a framework (FW) for pragmatic industrial modeling was suggested and demonstrated on industrial use cases with a process centric approach by Zoric et al. (2014). The present paper elaborates further on these concepts with focus on modeling and experimental data and metadata, their organization, syntax and semantics. This is exemplified on a new use case, related to drilling of oil & gas wells. The analytical problem is to produce a model which can predict the motion of a spherical particle embedded in laminar non-Newtonian flow. An overview of tasks, procedures, organization, structure and flow of data (to/from various modeling and experimental phases), required metadata, and technical and quality requirements is given. The uncertainty in the characterization of the fluid will impact the accuracy of the model predictions. The necessary uncertainty assessments and the corresponding metadata needed to support the entire modeling process are also discussed. Quantification of uncertainty is demonstrated using polynomial chaos to assess the effect of uncertainties in the parameters for the non-Newtonian viscosity model. Finally, we summarize the findings and discuss how the "pragmatism in industrial modeling" concept can help building more consistent industrial models, answering to customer needs for actual accuracy and delivery speed.