Skip to main content
placeholder image

Curvature flow of clusters: optimal partitioning and merging fire fronts

Grant


Scheme


  • Discovery Early Career Researcher Award (DECRA)

Abstract


  • This project aims to develop the curvature flow of clusters, a new mathematical innovation that builds on methods with proven success in making new progress on difficult problems in geometry and topology. The curvature flow of clusters will allow foams - partitions of space - to be viewed dynamically. This allows long-standing problems on their structure, a key mathematical challenge in material science, to be studied in a natural context. The project is expected to produce a software suite capable of simulating the movement of merging fire fronts with better accuracy than ever before. The mathematical tools developed by the project will have broad applicability, not only to space partitioning but also notably to bushfires, especially on the dynamics of merging fire fronts.

Sponsor Award Id


  • DE190100379

Local Award Id


  • 127944

Scheme


  • Discovery Early Career Researcher Award (DECRA)

Abstract


  • This project aims to develop the curvature flow of clusters, a new mathematical innovation that builds on methods with proven success in making new progress on difficult problems in geometry and topology. The curvature flow of clusters will allow foams - partitions of space - to be viewed dynamically. This allows long-standing problems on their structure, a key mathematical challenge in material science, to be studied in a natural context. The project is expected to produce a software suite capable of simulating the movement of merging fire fronts with better accuracy than ever before. The mathematical tools developed by the project will have broad applicability, not only to space partitioning but also notably to bushfires, especially on the dynamics of merging fire fronts.

Sponsor Award Id


  • DE190100379

Local Award Id


  • 127944