Ontology-based metrics computation for business process analysis

Business Process Management (BPM) aims to support the whole life-cycle necessary to deploy and maintain business processes in organisations. Crucial within the BPM lifecycle is the analysis of deployed processes. Analysing business processes requires computing metrics that can help determining the health of business activities and thus the whole enterprise. However, the degree of automation currently achieved cannot support the level of reactivity and adaptation demanded by businesses. In this paper we argue and show how the use of Semantic Web technologies can increase to an important extent the level of automation for analysing business processes. We present a domain-independent ontological framework for Business Process Analysis (BPA) with support for automatically computing metrics. In particular, we define a set of ontologies for specifying metrics. We describe a domain-independent metrics computation engine that can interpret and compute them. Finally we illustrate and evaluate our approach with a set of general purpose metrics

Reynolds-averaged Navier-Stokes simulation of turbulent flow in a circular pipe using OpenFOAM®

A RANS simulation of flow through a pipe is performed and validated against experimental data and previous DNS results. A mesh refinement study is performed to illustrate the near wall mesh size needed to correctly predict mean flow characteristics. In addition, aspects of the model are changed to study their impact on the results as well as the computational requirements. Comparisons are made between a two-dimensional analysis with axisymmetric boundary conditions, a one-eighth axisymmetric model, a one-fourth axisymmetric model, and a full three-dimensional pipe. The two-dimensional model provides the best match to past data; however, it is noted that the model may not be well tuned for a three-dimensional mesh. The simulation is also performed using three different turbulence models and the results of each model are compared. The purpose of the model is to create a tool that can be used for design iterations. While the model does not fully capture the complexities of turbulent flow, it is able to predict the mean flow accurately enough to be useful in a design setting. The goal of this work is to create a foundation upon which further studies of pipe flow with internal obstructions can build. The overall results show the model is able to predict the mean flow well for the validation case. However, the model does not perform well when certain aspects are changed. Increasing the robustness of the model and the determination of more usable boundary conditions remains a subject for future studies