  We present a new software package, "HybridOctree_Hex," for adaptive
all-hexahedral mesh generation based on hybrid octree and quality improvement
with Jacobian control. The proposed HybridOctree_Hex begins by detecting
curvatures and narrow regions of the input boundary to identify key surface
features and initialize an octree structure. Subsequently, a strongly balanced
octree is constructed using the balancing and pairing rules. Inspired by our
earlier preliminary hybrid octree-based work, templates are designed to
guarantee an all-hexahedral dual mesh generation directly from the strongly
balanced octree. With these pre-defined templates, the sophisticated hybrid
octree construction step is skipped to achieve an efficient implementation.
After that, elements outside and around the boundary are removed to create a
core mesh. The boundary points of the core mesh are connected to their
corresponding closest points on the surface to fill the buffer zone and build
the final mesh. Coupled with smart Laplacian smoothing, HybridOctree_Hex takes
advantage of a delicate optimization-based quality improvement method
considering geometric fitting, Jacobian and scaled Jacobian, to achieve a
minimum scaled Jacobian that is higher than $0.5$. We empirically verify the
robustness and efficiency of our method by running the HybridOctree_Hex
software on dozens of complex 3D models without any manual intervention or
parameter adjustment. We provide the HybridOctree_Hex source code, along with
comprehensive results encompassing the input and output files and statistical
data in the following repository: https://github.com/CMU-CBML/HybridOctree_Hex.
