Skip to main content
Log in

The flow from simulation to reality

  • Comment
  • Published:

From Nature Physics

View current issue Submit your manuscript

Fluid simulations today are remarkably realistic. In this Comment I discuss some of the most striking results from the past 20 years of computer graphics research that made this happen.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1: Two optimizations for fluid simulations.

a, reproduced from ref. 5, ACM; b, courtesy of Chris Wojtan and Eitan Grinspun.

Fig. 2: Advanced fluid simulation effects.

a, The FLIP Fluids Addon Development Team; b, reproduced from ref. 8, ACM.

References

  1. Harlow, F. & Welch, J. E. Phys. Fluids 8, 2182–2189 (1965).

    Article  ADS  MathSciNet  Google Scholar 

  2. Foster, N. & Metaxas, D. Graph. Models Im. Proc. 58, 471–483 (1996).

    Article  Google Scholar 

  3. Stam, J. Stable fluids. In SIGGRAPH ‘99: Proc. 26th Conference on Computer Graphics and Interactive Techniques 121–128 (ACM, 1999).

  4. Berger, M. J. & Colella, P. J. Comput. Phys. 82, 64–84 (1984).

    Article  ADS  Google Scholar 

  5. Ando, R., Thürey, N. & Wojtan, C. ACM Trans. Graph. 32, 103 (2013).

    Article  Google Scholar 

  6. Da, F., Hahn, D., Batty, C., Wojtan, C. & Grinspun, E. ACM Trans. Graph. 35, 78 (2016).

    Article  Google Scholar 

  7. Ihmsen, M., Akinci, N., Akinci, G. & Teschner, M. Visual Comput. 28, 669–677 (2012).

    Article  Google Scholar 

  8. Ruan, L. et al. ACM Trans. Graph. 40, 120 (2021).

    Article  Google Scholar 

  9. Lyu, C., Li, W., Desbrun, M. & Liu, X. ACM Trans. Graph. 40, 201 (2021).

    Article  ADS  Google Scholar 

  10. Huang, L., Hädrich, T. & Michels, D. L. ACM Trans. Graph. 38, 93 (2019).

    Google Scholar 

  11. Fei, Y., Maia, H. T., Batty, C., Zheng, C. & Grinspun, E. ACM Trans. Graph. 36, 56 (2017).

    Article  Google Scholar 

  12. Takahashi, T. & Lin, M. C. ACM Trans. Graph. 38, 237 (2019).

    Article  Google Scholar 

  13. Sanchez-Gonzalez, A. et al. Learning to simulate complex physics with graph networks. Proc. 37th International Conference on Machine Learning 119, 8459–8468 (2020).

    Google Scholar 

Download references

Acknowledgements

I thank C. Batty who graciously provided constructive feedback.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Károly Zsolnai-Fehér.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zsolnai-Fehér, K. The flow from simulation to reality. Nat. Phys. 18, 1260–1261 (2022). https://doi.org/10.1038/s41567-022-01788-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41567-022-01788-5

  • Springer Nature Limited

Navigation