The computational paradigm and software framework for mechanism and data-driven physical simulation

doi:10.11996/JG.j.2095-302X.2024061207

Abstract

Abstract:

As the cornerstone of modern industrial software, physical simulation encompasses various computational paradigms, including mechanism-driven, data-driven, and hybrid-driven models. Meeting the demands of diverse physical simulation requires the construction of a general framework capable of flexibly adapting to various physical simulation computational paradigms while achieving efficient coupling across various computational paradigms, presenting a critical challenge in software design and development. To address this, the Data field—Node—Module— Scene graph (FNMS) architecture was proposed, targeting multi-physics simulation computational paradigms. Its core lies in the design of a four-layer structure: Data field, Node, Module, and Scene graph. Specifically, the Data field layer provides a unified data management and access interface for the simulation process, enhancing the convenience and efficiency in data sharing for physical simulation computations. The Module layer encapsulated various physical simulation algorithms, realizing algorithm modularization and reusability while solving the asynchronous coordination of simulation computation, rendering, and interaction. Through data and algorithm decoupling, the Node layer enabled algorithm reuse across different physical simulation computational paradigms, and it facilitated the exchange and sharing within multi-physics coupling processes. The Scene graph layer supported efficient coupled computations of various physical simulation computational paradigms by organizing nodes into a directed acyclic graph. Through the combination of these four layers, the FNMS architecture not only enhanced the computational efficiency and flexibility in physical simulations but also provided strong technical support for interdisciplinary and cross-domain physical simulation research.

Key words: FNMS framework, mechanism driven, data driven, physical simulation, computing paradigm

CLC Number:

TP391

HE Xiaowei, SHI Jian, LIU Shusen, REN Lixin, GUO Yuzhong, CAI Yong, WANG Hu, ZHU Fei, WANG Guoping. The computational paradigm and software framework for mechanism and data-driven physical simulation[J]. Journal of Graphics, 2024, 45(6): 1207-1221.

Figures/Tables 18

Fig. 1 The computational paradigm of physical simulation mainly ((a) Theoretical modeling; (b) Digital modeling; (c) Numerical solving; (d) Visual analysis)

Fig. 2 Diagram of a boundary value problem

Fig. 3 Classification of computing paradigms of physical simulation

Fig. 4 Flowchart of the data-driven physical simulation

Fig. 5 Diagram of the FNMS architecture

Fig. 6 Diagram of the data domain

Fig. 7 Solid-fluid coupling scenario ((a) Visual effect;(b) Node graph)

Fig. 8 Hierarchical representation of mesh topology

Fig. 9 Multimodal representation of a jeep ((a) TextureMesh; (b) TriangleSet; (c) DiscreElements))

Fig. 10 Simulation pipeline of rigid body dynamics for a jeep

Fig. 11 Diagram of the data field synchronization mechanism

Fig. 12 Diagram of asynchronous collaboration between simulation and interaction

Fig. 13 Diffuse interface model for blood flow simulation ((a1) A two-dimensional section of the adaptive grid; (a2) Velocity field; (b) Node graph)

Fig. 14 FEM-based simulation and analysis for pump ((a) Visual effect; (b) Node graph)

Fig. 15 Fluid simulation based on a dual particle approach ((a) Visual effect; (b) Node graph)

Fig. 16 Solving transient collision problems based on graph neural networks

Fig. 17 Intelligent solving for two-dimensional dynamic problems

Fig. 18 Comparison of intelligent rapid simulation results and experiments for three-dimensional collision ((a) 0.00 ms; (b) 4.38 ms; (c) 7.29 ms; (d) 11.56 ms; (e) 18.00 ms)

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