Interfaces | Services | Mesh Geometry | Mesh Curving | Mesh Smoothing | Mesh Swapping | Adaptive Loops | Front Tracking | Dynamic Services | Search and Sort | Visit Plugins | iMeshIO | IPComMan | Mesh Adapt Service | Petascale Meshing | Shape Optimization | AMR Front Tracking | Solution Transfer
An ITAPS/TOPS/ SLAC collaboration focuses on optimizing the shape of accelerator cavities for the International Linear Collider (ILC). At various optimization stages, the code a) generates a cavity geometry based on a set of design parameters, b) projects a mesh onto that geometry and smooths it to improve quality, c) computes the derivative of surface vertex positions with respect to design parameters, and d) passes these results to the function evaluation (an electro-magnetic analysis) through the mesh interface. These capabilities use implementations of the geometry, mesh, and relations interfaces, along with Mesquite mesh improvement services, and are packaged in the DDRIV code library and executable driver.
Figure: The steps needed to modify the geometry and mesh as part of the design optimization procedure. First the new geometry is determined and the boundary nodes of the mesh are projected to the geometrical surface. This can results in a poor quality mesh, so the curves, surface, and volume of the mesh are then improved using smoothing techniques. The derivative information associated with the mesh motion is then computed for use in the optimization technique.
We will continue construction and application of a higher-level shape optimization component along two specific fronts. First, we will continue the collaboration with SLAC to apply shape optimization to accelerator cavities used in the International Linear Collider (ILC). Second, we propose generalizing and enhancing this capability, so that this work can be leveraged in future optimization efforts.
Since function evaluations in the optimization for SciDAC applications are highly parallelized, driving them as part of an optimization loop requires all software components in the optimization process be parallel as well. Furthermore, these components should be automated such that no manual intervention is required. DDRIV will be parallelized to facilitate automation of the optimization loop. We will investigate whether to use the same partition for DDRIV functions as that used by the application or a different partition. In the longer term, methods for treating larger parameter variations, leading to topological changes to the underlying geometric model, will be investigated. This may require the introduction of re-meshing and/or local mesh topological changes to the process to improve mesh quality. This research will use the dynamic mesh services, parallel mesh generation, and parallel deforming mesh capabilities discussed in this proposal. DDRIV will be released as open source early in this process, and we will seek other applications of this technology.