G19
Generative Design

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16:05
conference time (CEST, Berlin)
Generative Design of Lattice Structures
28/10/2021 16:05 conference time (CEST, Berlin)
Room: G
J. Coronado (PTC, USA); A. Vlahinos (Advanced Engineering Solutions LLC, USA)
J. Coronado (PTC, USA); A. Vlahinos (Advanced Engineering Solutions LLC, USA)
The additive manufacturing industry continues to grow with new machines, faster processes and a large selection of materials. Design practitioners are now enabled to unleash the full potential of AM with the use of Generative Design and Lattice structures. Generative Design is the automatic process of generating optimum feasible designs from a set of performance requirements and design rules. With the use of manufacturing constraints, the generated organic designs can be printed using additive manufacturing. Generative Design is a fundamentally disruptive paradigm shift. Over the last 3000 years humans conceived a design and then built physical or virtual prototypes to evaluate the design’s performance requirements. Generative Design spawns designs that even experienced skilled practitioners couldn’t imagine. There is no preconceived geometry as a starting point. The geometric complexity of these designs can be handled by additive manufacturing. Lattice structures are topologically ordered, three-dimensional open-celled structures that are used by nature. An example of exceptional achievement of evolutionary engineering is the formation of the biphotonic gyroid material in butterfly wings. Visually stunning manifestations of light weight biological nanostructured materials are observed in insects, birds, and plants. Lattice structures are very effective for lightweight structural panels, energy absorption devices, thermal insulation, high performance heat exchangers, ballistic protection and porous implants. The combination of Generative Design tools and Lattice structures is producing a tsunami of change in the design process. This presentation will demonstrate this new design process with an example of light weighting a helicopter bell crank. The baseline component is examined for stress compliance and the design space is established without interference during the mechanism motion. The Generative Design procedure uses homogenized material properties, of the lattice structure, and establishes the optimized topology. This topology is filled with a Stochastic Lattice structure. The density and size of the struts can be driven by the three-dimensional stress field of the optimized topology. Experimental results of the optimized topology will be also presented.
Generative Design, Lattice Structures, Additive Manufacturing
16:25
conference time (CEST, Berlin)
Towards Generative Design With Improved Geometry Outcomes and Faster Performance
28/10/2021 16:25 conference time (CEST, Berlin)
Room: G
D. Weinberg (Autodesk Inc., USA); N-H. Kim (University of Florida, Gainesville, USA)
D. Weinberg (Autodesk Inc., USA); N-H. Kim (University of Florida, Gainesville, USA)
There are many challenges today in obtaining better quality outcomes in generative design using conventional tetrahedron meshes. In addition, adding more elements to obtain better shapes typically means slower performance and when running jobs on the cloud and this translates to higher costs. Also, tetrahedron meshes are not ideal for certain manufacturing constraints such as milling and extrusion. One solution is to use a voxelized mesh which approximately conforms to the input design space envelop using voxel elements. One benefit of this is the ability to use fast interpolation from a finer design space mesh to a coarser one used for FEA, resulting in a better outcome both in aesthetics and the objective function without a loss in accuracy. Our voxelized mesh concept results in a more accurate application of boundary conditions which allows using a smaller number of voxel elements to perform accurate FEA computations. The coarser FEA mesh also results in better overall performance and reduced cloud costs. The finer optimization design space results in smoother shapes especially with complex starting geometry resulting more detail yielding a more optimal design. Using a voxelized mesh also allows for faster optimization operations associated with manufacturing constraints and more compliant milling and extrude manufacturing constraints. A side benefit of using interpolation is improved multidisciplinary optimization where other FEA physics such normal modes, buckling, heat transfer, and CFD can be coupled for fully compliant design. In this presentation, we combine linear statics, normal modes, and buckling to design various structures. The linear static analysis handles the stress and displacement constrains and runs in parallel with a normal modes and buckling solution all as separate processes communicating using Inter Process Communication or IPC. The current architecture assumes that the design problem has a single objective function which is minimize compliance with multiple design and manufacturing constraints using different FEA physics. The main topology optimization engine is controlled by a fast independent GOCM optimization processor, while constraints are handled in multiple dependent FEA processes which calculate their own adjoint sensitivities and pass data to the independent process using IPC. Optimal designs are further achieved by using an adjustable volume fraction constraint which adjusts up or down to satisfy all design constraints.
topology optimzation, generative design, multidisciplinary optimization, voxelized mesh, interpolation, FEA, finite element analysis, hex meshing, Inter Process Communicatio, IPC, cloud computing
16:45
conference time (CEST, Berlin)
Multi-objective Optimization of Flat and Dished Pressure Vessel Heads With Bionic Principles
28/10/2021 16:45 conference time (CEST, Berlin)
Room: G
D. Becker, N. Kockmann, S. Gerling, T. Nissalk (Technical university Dortmund, DEU)
D. Becker, N. Kockmann, S. Gerling, T. Nissalk (Technical university Dortmund, DEU)
In order to design components that are safe and durable, material-efficient lightweight construction methods have become established in many areas of mechanical engineering. But lightweight construction methods have not yet been widely used in the design of chemical process equipment. The design goal here is dimensioning against failure and fatigue of the apparatus. Established guidelines are used, which often lead to safe but rather over-dimensioned and thus material-inefficient solutions. To analyze possible advantages of lightweight design in apparatus engineering flat and dished pressure vessel heads are designed by bionic principles, and achieved mass and resulting stresses are compared with conventional design. The sandwich comb design of diatoms is applied to pressure vessel heads as a bionic principle. The good mechanical properties of diatoms were already shown by several groups [1]. However, no technical application in the fields of apparatus engineering can be found in literature. Therefore, the concentric comb construction of diatoms was converted in a parametric CAD-Script. The essential parameters of this script influence both number and distribution of combs over the circle radius. Thus, it is possible to create models with clear different geometrical properties only with a small set of parameters. The flat pressure vessel heads are designed with a diameter of 1 m and a wall thickness of 2 mm. In linear-elastic FEM-simulations the pressure vessel heads are loaded with pressure of 1 bar and the resulting Von-Mises equivalent stresses and masses are evaluated. Subsequently a multi objective optimization takes place, which optimizes both mass and stresses using methods of artificial intelligence. For the optimization, the TSEMO algorithm was used which uses Gaussian process surrogates and genetic algorithms to evaluate the pareto front [1]. In comparison to pressure vessel heads designed by conventional guidelines, flat heads with comb sandwich structures only need 50% of mass. The results of the flat pressure vessel heads are transferred to dished components. In the high loaded knuckle region of widely used Klöpper heads a sandwich structure is inserted and a parametric CAD-Model is scripted. As in the case of the flat pressure vessel heads, optimization takes place in terms of strength and weight, for which linear-elastic simulations are performed. Compared to conventional dished heads, designed according to the AD2000 guideline [3], the equivalent stresses were reduced by 30% for the same mass. Both in flat and in curved construction, pressure vessel heads can be designed more material-economically and safely by sandwich construction methods. The use of artificial intelligence methods can significantly reduce the effort of multi-objective optimization. [1] C.E. Hamm (2005) The evolution of advanced mechanical defenses and potential technological applications of diatom shells. J Nanosci Nanotechnol 5:108–119. https://doi.org/10.1166/jnn.2005.023 [2] E. Bradford, A.M. Schweidtmann, & A. Lapkin. Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm. J Glob Optim 71, 407–438 (2018). https://doi.org/10.1007/s10898-018-0609-2 [3] AD 2000-Merkblatt B3, Gewölbte Böden unter innerem und äußerem Überdruck, Verband der Technischen Überwachungs-Vereine e.V. Essen (2000)
Bionics, FEM, AI, multi objective optimization, chemical process equipment
17:05
conference time (CEST, Berlin)
Reduce Part Count in Complex Assemblies by Combining Generative Design with Additive Manufacturing in a New Workflow
28/10/2021 17:05 conference time (CEST, Berlin)
Room: G
L. Maasjost (MSC Software GmbH, DEU)
L. Maasjost (MSC Software GmbH, DEU)
It is well known that Additive Manufacturing offers excellent potential to achieve functional integration through new levels of component complexity that would have been inconceivable before. Simultaneously, this complexity has only a minor impact on the time and costs required for the manufacturing process. Yet, the current challenge is to exploit these technical advantages not only for individual components but also for complex applications. Reducing the part count has considerable potential for higher efficiency in manufacturing and operations and often offers an improved functionality. It also comes with less assembly, a lower part number to handle, less storage and overall decreased complexity amongst the weight reductions usually gained. But it takes currently a considerable manual effort in the component's design phase to take advantage of the possible complexity for achieving function integration. Also, in-depth knowledge of this process is often required to achieve good results. This presentation will show how current design generation tools can lead to an accelerated and simplified process. For this, simulation is applied at the beginning of the product development to gain more insights early in the process. This gives the designers a fast response to how the given requirements affect the design. The steady exchange between concept decisions and Generative Design simulations throughout the whole process can prevent wrong decisions due to lack of information in early phases. This process will be demonstrated using an example assembly from industry, in which a reduction of the components is carried out with the support of Generative Design. Special attention is paid to exploit the advantages of additive manufacturing, particularly its extensive design freedom. At the same time, the targeted application of generative design improves usability and enables the user to make critical design decisions early in the process. Ultimately, both the component reduction and the presented approach avoid unnecessary errors and costs while improving manufacturability.
generative design, part consolidation, additive manufacturing, optimization, workflow, complex assembly
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