Feature-based intelligent system for steam simulation using computational fluid dynamics

Abstract

In the development of products involving fluids, computational fluid dynamics (CFD) has been increasingly applied to investigate the flow associated with various product operating conditions or product designs. The batch simulation is usually conducted when CFD is heavily used, which is not able to respond to the changes in flow regime when the fluid domain changes. In order to overcome this defect, a rule-based intelligent CFD simulation system for steam simulation is proposed to analyze the specific product design and generate the corresponding robust simulation model with accurate results. The rules used in the system are based on physical knowledge and CFD best practices which make this system easy to be applied in other application scenarios by changing the relevant knowledge base. Fluid physics features and dynamic physics features are used to model the intelligent functions of the system. Incorporating CAE boundary features, the CFD analysis view is fulfilled, which maintains the information consistency in a multi-view feature modeling environment. The prototype software tool is developed by Python 3 with separated logics and settings. The effectiveness of the proposed system is proven by the case study of a disk-type gate valve and a pipe reducer in a piping system.