Boxstructured

Boxstructured is a term used in computational methods to describe a grid or mesh arrangement in which a domain is subdivided into a regular, axis-aligned array of boxes (rectangular prisms in 3D). Each box has a uniform size and neighbors are arranged in a predictable, grid-like topology. This contrasts with unstructured meshes where cells may have arbitrary shapes and connectivity.

Box-structured grids are common in finite difference and finite volume solvers because they enable simple indexing, efficient memory access, and straightforward stencil computations. They are typically implemented as two- or three-dimensional arrays, where each cell stores field values and connectivity is determined by fixed offset patterns.

Block-structured or box-structured grids extend the idea by partitioning the domain into several non-overlapping blocks that are individually structured. This supports scalable parallelism and domain decomposition, and blocks can be refined independently in adaptive schemes or distributed across processors for parallel simulations.

Advantages of boxstructured grids include simplicity, speed, and ease of boundary condition implementation. Limitations involve difficulty in representing complex geometry and curved boundaries, and potential inefficiency for highly irregular domains. Hybrid approaches may combine boxstructured grids with local mesh refinement or embed unstructured regions where needed.

Boxstructured grids are used across fields such as computational fluid dynamics, heat transfer, groundwater modeling, volume rendering, and voxel-based image processing. Related concepts include structured grids, Cartesian grids, block-structured grids, and adaptive mesh refinement.