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Discretization and adaptive approximation of fully nonlinear equations

Project description

Novel approximations enable application of powerful conventional solvers

Partial differential equations (PDEs) are fundamental to our description of the world around us, explaining mathematically how a given phenomenon changes with respect to changes in other factors. They can model dynamics related to gas exchange in the circulatory system, changes in the stock market and the propagation of X-rays in materials. Fully non-linear PDEs are a particularly tricky case for which conventional solutions may not exist or even be defined. The EU-funded DAFNE project will lay the foundations to implement solution approaches using powerful finite element methods with impact in areas from physics and geometry to transport phenomena and finance.

Objective

Fully nonlinear partial differential equations (PDE) arise in many applications ranging from physics to economy. They are different from PDEs in mechanics, and the PDE theory relies on the generalized solution concept of so-called viscosity solutions. Monotone finite difference methods (FDM) are provably convergent for approximating viscosity solutions, but are restricted to regular meshes and low-order approximations, thus having limitations in resolving realistic geometries or dealing with local mesh refinement. As viscosity solutions are lacking smoothness properties in general, adaptive approximations are desirable. In contrast to FDM, finite element methods (FEM) offer the possibility of high-order approximations with flexibility in adaptive and automatic mesh design. However, provably convergent FEM formulations for viscosity solutions to nonvariational problems are as yet unknown.

With a background in the numerical analysis of PDEs, especially the theory of FEM and adaptive algorithms, DAFNE aims at laying the theoretical and practical foundation for the application of FEM and automatic mesh-refinement algorithms to fully nonlinear equations. The focus is on the large class of Hamilton-Jacobi-Bellman (HJB) equations. They originated from stochastic control problems, but more generally comprise many classical and relevant equations like Pucci's equation or the Monge-Ampre equation
with applications in finance, optimal transport, physics, and geometry.

The novel approach is to estimate local regularity properties through the control variable in the HJB formulation. This (a) gives rise to new regularization strategies and (b) indicates where the mesh needs to be refined. Both achievements are key to the design of a new FEM formulation.

The project is at the frontiers of PDE analysis, numerical analysis, and scientific computing. The long-term goal is to establish the first convergence proofs for adaptive FEM simulations of fully nonlinear phenomena.

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Topic(s)

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Funding Scheme

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ERC-STG - Starting Grant

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Call for proposal

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(opens in new window) ERC-2020-STG

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Host institution

FRIEDRICH-SCHILLER-UNIVERSITÄT JENA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 453 937,00
Address
FÜRSTENGRABEN 1
07743 JENA
Germany

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Region
Thüringen Thüringen Jena, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 453 937,00

Beneficiaries (1)

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