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May 2016: Journey to the 3DEXPERIENCE Platform

Considering Topology Optimization For Additive Manufacturing Applications

Sakya Tripathy, SIMULIA Additive Manufacturing Senior Technical Consultant

Future Outlook

Figure 1. The general goal of topology optimization is the distribution of

Additive Manufacturing (AM), known by the more popular moniker of 3D Printing, is giving designers freedom like never before to dream, innovate, and realize their concepts. Iconic companies in the aerospace, automotive, and life sciences industries have embraced this paradigm shift in manufacturing while others are following suit. Jet engine nozzles with complex ducts, light-weighted brackets in airplanes, porous medical implant surfaces for osseo-integration, latticed parts for race cars—among many others— have moved beyond functional prototypes to in-service usage. This adoption is being aided, in no small measure, by the rapid advances in simulation technology for multiphysics optimization and predictive analytics. With design no longer constrained by the subtractive manufacturing restrictions, a part designer can answer relevant questions. What is the functional objective of the part? Can we design a part with the same functional characteristics but use less material? Can we obtain the cost-savings from optimized additive parts? These parts are becoming increasingly complex, organic and lighter, while meeting their performance requirements.

Figure 2. Topology optimization for a 3D printed circuit box. Rocket payload image credit NASA.

A key simulation technology being leveraged in the shortened design cycle for AM is Topology Optimization, a nonparametric optimization technique that identifies and removes areas of a design space not contributing to the stiffness of the part or to the force flow in it. This method determines an optimum material distribution in a defined design area while accounting for existing constraints to the design space: boundary conditions, fixations and pre-tensions, and loads. With reduced manufacturing constraints, more organic structures with ‘holes’ and ‘openings’ are now possible with Tosca Structure, a robust general purpose tool for non-linear topology optimization.

As shown in Figure 1, Tosca Structure can be used to create organic designs that use less material while satisfying all the functional requirements and constraints. We start with a larger design space (the gray area) and based on iterative non-linear finite element analyses using Abaqus, the locations of design space where the material is required is computed as shown in the right frame. In addition, Tosca can be also be used with other 3rd-party FEA solvers.

Figure 3. (a) Tosca Outputs (Raw) in CATIA Imagine and Shape; (b) Using tube drawing to sketch sections on raw solid to create surfaces joined at T-junctions; (c) Mesh grid drawing on raw solid allows for fast creation of subdivision surfaces; (d) Final circuit box CAD.

Now, Tosca already accounts for constraints used in conventional manufacturing such as casting and injection molding. So, are there any special considerations before using Tosca for AM? Let’s review with an illustrative circuit box (shown in Figure 2) for space vehicles and satellites. A typical launch vehicle hosts dozens of these boxes and with the estimates for sending a single 1lb to space close to $10,000, costs can add up. Hence, light-weighting these enclosures can be a good design objective. In collaboration with Stratasys, we conducted a topology optimization design study with the intent of printing these new concepts with the Fused Deposition Modeling (FDM) process.

It is very likely that an AM part will co-exist in an assembly with traditionally manufactured parts. Such regions or interfacial areas can be frozen (including pre-stresses) in Tosca and removed from the design space. Next, it is important to set a minimum member size for the optimization to account for the print resolution. For instance, for FDM processes, the member size should be larger than the bead size so that the optimized surfaces can be realized in the real print. Now, for a metal printing process, the minimum member size can be much smaller. However, choosing a conservative limit can help avoid any manufacturing related defects (voids or cracks). Taking the above into account, we conducted a design study with multiple volume reduction constraints on the original design volume and settled on the optimization results that offered a 30% reduction while proving most suitable for print, from a time, quality and material-cost perspective. Another critical point to note is that most AM processes require support structures either to prop the layers, anchor the part or provide heat conduction paths during the printing process. These supports add to the cost of material and print overhead. While a nontrivial task, employing ways to minimize the use of support structures by reducing the overhang angles, build orientations optimization, and the use of parametric or non-parametric simulations to optimize support placement, will ensure that you realize the cost benefits from topology optimization.

With the optimized shape obtained and a final simulation conducted to functionally validate the new design, it is time to print the part. However, the optimized results will often contain sharp edges, disjoint islands of material and highly tessellated facets. A smoothing step helps, but the obtained STL output will require cleanup for a 3D printer to handle and produce a desirable part. Moreover, we have lost the associativity with the original design. CAD reconstruction addresses these concerns but it is a highly time-consuming manual process, often a bottleneck to wider adoption of optimization technology. In the latest release of Tosca, we’ve taken a significant step to addressing this issue. Here, using subdivision surfaces, a technique originally developed in the animation industry, Tosca outputs are transferred via points and face inputs in to a CAD environment such as CATIA, no longer requiring the use of STL files. This step drastically simplifies the reconstruction process, providing significant cost benefits as advanced surface modification tools in the CAD environment (shown in Figure 3) can be used to create organic shapes with vastly simplified facet information (reduced file size), true geometric features and parameters which lend themselves well to further parametric shape optimization studies. We are now print ready!

Additive Manufacturing is propelling the next manufacturing revolution with topology optimization at the core of enabling designers to harness the freedom from design constraints. Our powerful tools of non-linear and non-parametric topology optimization through Tosca are well-suited for this shift and we continue to improve our offerings to enable your requirements. Another key area for additive manufacturing is the use of lattice structures. Stay tuned for a future article to learn more on what we have to offer in this area or follow the authors’ LinkedIn blogs.

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