NVIDIA GVDB Voxels is ideally suited for 3D Printing design, prototyping and embedded applications where both performance and memory footprint are critical. Voxels enable a nextgeneration approach to the 3D Printing workflow as they represent complex, connected microstructures and heterogeneous materials more easily than polygons. Supporting very high resolution volumes with massive parallelism on GPUs, the sparse data structure of NVIDIA GVDB Voxels allows for geometric operations, simulation and rendering of complex models with fine detail. GVDB Voxels is ideally suited as core representation for 3D Printing Design applications, Generative Design,Process Engineering, Materials Simulation or print PreVisualization.
- Sparse storage allows for high-resolution models
- Runs on embedded hardware such as the Jetson TK1, TX1 and TX2
- Open source, so developers can adopt and modify to suit their needs
- Compute operations allow for process customization, including simulation
- Built-in high quality rendering supports raytraced pre-visualization
- GVDB SDK includes a g3DPrint sample which demonstrates slicing
Process Engineering with HP Labs
NVIDIA worked closely with HP Labs in 2017 to explore the potential for Process Engineering on GPUs. Generative design takes the approach of simulating the stresses, strains and energy on a part to reconfigure the part itself with user guidance.
Dr. Jun Zeng , Principal Scientist at HP Labs, was interested in solving novel problems in Process Engineering , which considers the generation and design of complex microstructures for infilling after the part shape is complete. Bringing NVIDIA GVDB Voxels to the Pascal GP100 was an ideally match for this exploration since the microstructures are generated at a finer detail than the part, requiring significantly more memory and computing power.
GVDB Voxels generates in-filling structures interactively
With NVIDIA GVDB Voxels we were able to generate variations in the infilling structures interactively , in response to simulated part strains and user manipulation. Generated structures respond dynamically to desired changes in foam density. NVIDIA GVDB Voxels achieves a level of responsiveness with fine structures that would be difficult to achieve using polygons alone. The output data can be directly used in slicebased printing.
To generate adaptive infilling, HP Labs computed a strain simulation using their Material Capture software to determine the areas of the part with greater strain energy. With forces applied to the wingtips, greater density is needed in the lower back (right image). An adaptive voronoi foam was then generated to match that density requirement (above, left). NVIDIA GVDB Voxels also produced the interactive render previews and the crosssections for printing. The result is a method of Process Engineering where a given printed part uses selective, adaptive infilling to reduced weight while meeting the force constraints (above, right).
The VOX3 DLP 3D Printer on the Jetson TX2
The VOX3 is a DLP/SLA 3D Printer with an entirely voxel-based workflow running NVIDIA GVDB Voxels on the Jetson TX2. The Lead Architect of NVIDIA GVDB Voxels, Dr. Rama Hoetzlein , developed an entirely voxel-based 3D Printer to prototype the combination of novel NVIDIA hardware and software.
“By running GVDB Voxels on the Jetson TX2, we are able to develop embedded devices with advanced processing atthedevice. VOX3 is an experimental prototype for a liquid resin DLP/SLA 3D Printer with an entirely voxel-based workflow. With dual video outputs, the Jetson TX2 runs both the slice projector and a preview monitor. The TX2’s 8GB of memory, combined with sparse storage of GVDB software, allows large models to reside entirely onboard. The 256 cuda cores of the Jetson TX2 enable compute and simulation with GVDB. This means we can send, process, infill and slice volumetric data directly on the printer without any intermediate polygonal representation. Dr. Rama Hoetzlein, NVIDIA GVDB Voxels Lead Architect.