Deliverables – ExaQUte

Deliverableslopez2021-09-28T15:18:48+00:00

Deriverables

WP 1 Embedded methods

WP 2 Mesh generation and adaptivity

D 1.1: Solvers “stub” implementation of the capabilities to be delivered
D 1.2: First internal release of the solvers
D 1.3: First public Release of the solvers
D 1.4: Final public Release of the solvers

D 2.1: Meshing “stub” implementation of the capabilities to be delivered
D 2.2: First release of the octree mesh-generation capabilities and of the parallel mesh adaptation kernel
D 2.3: Adjoint-Based error estimation routines
D 2.4: Second Release of the mesh generation/adaptation capabilities
D 2.5: Final Release of the mesh generation/adaptation capabilities

WP 3 Space-time parallelization

WP 4 Dynamic scheduling for MLMC

D 3.1: Report on nonlinear domain decomisition preconditioners and release of the solvers
D 3.2: Report on parallel in time methods and release of the solvers
D 3.3: Release of a 4D embedded mesh generation library
D 3.4: Report on adjoint-based space time error estimators
D 3.5: Report on the calibration of parallel space time algorithms for turbulent flows

D 4.1: Working, common python API to schedule MLMC routines
D 4.2: Profiling report of the partner’s tools
D 4.3: Benchmarking report as tested on the available infrastructure
D 4.4: API and runtime for IO using persistent storage
D 4.5: Framework development and release

WP 5 Algorithmic extensions of MLMC (UQ)

WP 6 Optimization under uncertainties

D 5.1: Release of ExaQUte API for MLMC
D 5.2: Release of ExaQUte MLMC python engine
D 5.3: Report on theoretical work to allow the use of MLMC with adaptive mesh refinement
D 5.4: Report on MLMC for time dependent problems
D 5.5: Report on the application of MLMC to wind engineering applications

D 6.1: Deterministic Optimization Software
D 6.2: Report on the calculation of stochastic sensitivities
D 6.3: Report on stochastic optimization for simplified problems
D 6.4: Report on stochastic optimization for unsteady problems
D 6.5: Report on stochastic optimization for wind engineering

WP 7 Application to robust shape optimization of structures under wind loads

WP 8 Dissemination and exploitation

D 7.1: Delivery of geometry and computational model
D 7.2: Finalization of “deterministic” verification and validation tests
D 7.3: Report on UQ results and overall user experience
D 7.4: Final report on Stochastic Optimization results

D 8.1: Data Management Plan
D 8.2: Report on dissemination activities
D 8.3 : Exploitation plan
D 8.4 : Report on dissemination activities

WP 9 Project management

D 9.1: Periodic technical, administrative and financial report
D 9.2: Periodic technical, administrative and financial report