Physics-Informed Graph Neural Networks for Water Distribution Systems

arXiv:2403.18570v1 Announce Type: new
Abstract: Water distribution systems (WDS) are an integral part of critical infrastructure which is pivotal to urban development. As 70% of the world's population will likely live in urban environments in 2050, efficient simulation and planning tools for WDS play a crucial role in reaching UN's sustainable developmental goal (SDG) 6 - "Clean water and sanitation for all". In this realm, we propose a novel and efficient machine learning emulator, more precisely, a physics-informed deep learning …

abstract arxiv critical infrastructure cs.ai cs.lg development distribution environments graph graph neural networks infrastructure integral networks neural networks part physics physics-informed pivotal planning population role simulation sustainable systems tools type urban water will world