Flow Gym
This toolkit addresses the need for standardized tools in fluid dynamics research, but it is incremental as it builds on existing frameworks like OpenAI Gym.
The authors introduced Flow Gym, a toolkit for developing and deploying flow-field quantification methods, providing a unified interface for testing, training, and integrating algorithms using synthetic image generation.
Flow Gym is a toolkit for research and deployment of flow-field quantification methods inspired by OpenAI Gym and Stable-Baselines3. It uses SynthPix as synthetic image generation engine and provides a unified interface for the testing, deployment and training of (learning-based) algorithms for flow-field quantification from a number of consecutive images of tracer particles. It also contains a growing number of integrations of existing algorithms and stable (re-)implementations in JAX.