...” algorithm is introduced to improve the quality of particle distribution. Deep learning models for fluid flow applications typically use three primary network architectures: deep feedforward neural networks, convolutional neural networks, and graph neural networks (GNNs). When deep feedforward neural...

.../methodology/approach This study introduces the fluid efficient graph neural network simulator (FEGNS), an innovative framework that integrates an adaptive filtering layer and aggregator fusion strategy within a graph neural network architecture. FEGNS is designed to directly learn from extensive liquid...