Inverse Modelling of Incompressible Gas Flow in Subspace

• Main Authors: Zhai, Xiao, Hou, Fei, Qin, Hong, Hao, Aimin
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2016
• Subjects: Model reduction; EMD
• Online Access: https://hdl.handle.net/10356/84715; http://hdl.handle.net/10220/41918
• Institution: Nanyang Technological University

This paper advocates a novel method for modelling physically realistic flow from captured incompressible gas sequence via modal analysis in frequency-constrained subspace. Our analytical tool is uniquely founded upon empirical mode decomposition (EMD) and modal reduction for fluids, which are seamlessly integrated towards a powerful, style-controllable flow modelling approach. We first extend EMD, which is capable of processing 1D time series but has shown inadequacies for 3D graphics earlier, to fit gas flows in 3D. Next, frequency components from EMD are adopted as candidate vectors for bases of modal reduction. The prerequisite parameters of the Navier–Stokes equations are then optimized to inversely model the physically realistic flow in the frequency-constrained subspace. The estimated parameters can be utilized for re-simulation, or be altered toward fluid editing. Our novel inverse-modelling technique produces real-time gas sequences after precomputation, and is convenient to couple with other methods for visual enhancement and/or special visual effects. We integrate our new modelling tool with a state-of-the-art fluid capturing approach, forming a complete pipeline from real-world fluid to flow re-simulation and editing for various graphics applications.