Real-Time Reconstruction of Fluid Flow under Unknown Disturbance

ACM Transactions on Graphics (SIGGRAPH Asia 2023)

Kinfung Chu¹ Jiawei Huang² Hidemasa Takana¹ Yoshifumi Kitamura¹

¹Tohoku University ²Chuzhou University and Void Dimensions

BibTeX

        
          @article{chu2024flowrecon,
          author = {Chu, Kinfung and Huang, Jiawei and Takana, Hidemasa and Kitamura, Yoshifumi},
          title = {Real-Time Reconstruction of Fluid Flow under Unknown Disturbance},
          year = {2023},
          issue_date = {February 2024},
          publisher = {Association for Computing Machinery},
          address = {New York, NY, USA},
          volume = {43},
          number = {1},
          issn = {0730-0301},
          url = {https://doi.org/10.1145/3624011},
          doi = {10.1145/3624011},
          journal = {ACM Trans. Graph.},
          month = oct,
          articleno = {4},
          numpages = {14},
          keywords = {parameter optimization, SPH, Fluid simulation, reinforcement learning, fluid tracking}
          }

Let It Flow

Through reinforcement learning, we recreate the detailed water motion from the movement of a few buoys in real time.

Side-by-side Comparison

Move cursor over the video to adjust the split position.