Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
High-order essentially nonsocillatory schemes for Hamilton-Jacobi equations
SIAM Journal on Numerical Analysis
Lower semicontinuous solutions of Hamilton-Jacobi-Bellman equations
SIAM Journal on Control and Optimization
A level set formulation for the solution of the Dirichlet problem for Hamilton-Jacobi equations
SIAM Journal on Mathematical Analysis
A level set approach for computing solutions to incompressible two-phase flow
Journal of Computational Physics
A fast level set method for propagating interfaces
Journal of Computational Physics
A PDE-based fast local level set method
Journal of Computational Physics
Weighted ENO Schemes for Hamilton--Jacobi Equations
SIAM Journal on Scientific Computing
High Order Numerical Discretization for Hamilton–Jacobi Equations on Triangular Meshes
Journal of Scientific Computing
Contact Discontinuity Capturing Schemes for Linear Advection and Compressible Gas Dynamics
Journal of Scientific Computing
IEEE Transactions on Computers
An anti-diffusive scheme for viability problems
Applied Numerical Mathematics - Numerical methods for viscosity solutions and applications
Anti-Dissipative Schemes for Advection and Application to Hamilton-Jacobi-Bellmann Equations
Journal of Scientific Computing
Differential equation based constrained reinitialization for level set methods
Journal of Computational Physics
A Fast Marching Method for Hamilton-Jacobi Equations Modeling Monotone Front Propagations
Journal of Scientific Computing
Hi-index | 0.00 |
In this paper, we are interested in some front propagation problems coming from control problems in d-dimensional spaces, with d驴2. As opposed to the usual level set method, we localize the front as a discontinuity of a characteristic function. The evolution of the front is computed by solving an Hamilton-Jacobi-Bellman equation with discontinuous data, discretized by means of the antidissipative Ultra Bee scheme.We develop an efficient dynamic storage technique suitable for handling front evolutions in large dimension. Then we propose a fast algorithm, showing its relevance on several challenging tests in dimension d=2,3,4. We also compare our method with the techniques usually used in level set methods. Our approach leads to a computational cost as well as a memory allocation scaling as O(N nb ) in most situations, where N nb is the number of grid nodes around the front. Moreover, we show on several examples the accuracy of our approach when compared with level set methods.