Exploiting Advanced Manufacturing Capabilities: Topology Optimization in Design Proceedings of a Workshop (2022) / Chapter Skim
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5 Topology Optimization of Soft Materials and Deformable Structures
5 Topology Optimization of Soft Materials and Deformable Structures
Pages 38-51
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From page 38... ...
MATERIAL EXTRUSION ADDITIVE MANUFACTURING OF MULTI-MATERIAL HYBRID STRUCTURES Brett Compton, University of Tennessee, Knoxville Compton discussed challenges and advantages of material extrusion additive manufacturing (MEAM) , stressed the importance of understanding materials science relationships, and described MEAM's effects on material properties.
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From page 39... ...
Understanding Materials Science Relationships Compton stressed that MEAM methods require an understanding of the classic materials science relationships between structure, process, and property. His work has focused on deepening the understanding of how certain materials and compos ites react to the extrusion-based printing process, for example, how composition and print parameter choices affect strength, stiffness, and functional properties in printed materials.2 In addition to the materials themselves, the extrusion hardware design affects material properties.
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From page 40... ...
Composite feedstocks show even greater complexities, and there are also significant differences when changing nozzle size or flow rate. Compton has also experimented with multi-material architectures, specifically a low-density, compliant core material encased in a stiffer shell material, similar to a porcupine quill or sunflower stalk; and with graded and multi-material honeycombs, to which MEAM is especially well suited.
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From page 41... ...
O'Masta also detailed processes for optimiz ing structures with soft materials and new metals materials his team has developed for optimizing parts. Making Optimizations Useful Optimizations will only be useful to industry if they account for design con straints, including secondary properties such as weight and loading conditions; incorporate environmental stress; offer strong cost benefits; and enable quality control, O'Masta said.
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From page 42... ...
Existing high-strength alloys crack or tear during the 3D-printing process; to make those alloys printable, the team has added inoculants that create a very fine equiaxed microstructure that is resistant to cracking.5 Their inoculant-added 7000 series aluminum alloy has strong commercial potential, and it recently was granted the material designation 7A77, a first by the Aluminum Association for a 3D-printable material.6 The inoculant process is alloy agnostic, so theoretically similar performance improvements will be achieved with other alloys systems, O'Masta said. HRL Laboratories is also seeking to create metals with properties and micro structures that can be tailored to specifications.
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ACHIEVING MORE WITH LESS: ARCHITECTING METAMATERIALS WITH ADDITIVE MANUFACTURING Xiaoyu (Rayne) Zayne, University of California, Los Angeles Zheng described present and future materials manufacturing processes, stress ing that additive manufacturing must be tailored to a material's topology, constitu ents, and feature sizes in order to achieve the ultimate goal: utilization of architected metamaterials for multifunctional devices.
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From page 44... ...
.8 These materials can be bent or twisted to harness the power of multiscale 3D architectures and size effects, includ ing stress/strain curves, expanding what is possible for additive manufacturing.9 The length-scales of unit cells with respect to the overall dimension of meta materials are also important to create successfully architected metamaterials. For example, fracture toughness is essential for effective material design and utilization.
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From page 45... ...
This methodology was used to test multiple stress/strain curves for shoe insole designs. This inverse design of mechanical behaviors required a combination of simulation and experimentation in order to create training data that machine learning algo rithms could use to capture the complete material structure behavior, including manufacturing defects, for all classification types.
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From page 46... ...
Pedersen argued that topology optimization would work for that prob lem, and in fact it is already being practiced today. Zheng said that experimentally based data acquisition could take into account all possible failures and manu facturing defect, and machine learning could eliminate the needs for nonlinear, large-scale simulations, suggesting a possible collaboration to explore this further.
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From page 47... ...
Kabaria noted that while materials and processes are important to additive manufacturing, design tools are critical to manufacturing actual working parts, accelerating product innovation, and making additive manufacturing more wide spread. To improve their design tools, Carbon developed a design parameter optimization process that takes customer inputs -- material properties, desired mechanical responses, and design constraints -- and creates an additive manufac turing-ready design.
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From page 48... ...
In addition, he suggested that real-time topology optimization capabili ties should be expanded, as they enable users to quickly visualize results, adjust parameters, and develop a more intuitive understanding of the process. Also, creating new additive manufacturing design rules would standardize results and eliminate unnecessary experimentation.
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From page 49... ...
In addition, Zok said there is great promise in multi materials printing, especially for devices and high-temperature materials such as ceramics and ceramic composites. Participants discussed the possibilities of using ceramics and other composites; designing for qualities such as elasticity, fracture toughness, defect sensitivity, and sound dynamics; and overcoming modeling difficulties.
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From page 50... ...
William Paul King, University of Illinois, Urbana-Champaign, asked if it was possible to tune the modulus for material distribution in multi-material structures to affect fracture toughness. Sigmund, who has worked on that very problem, replied that it is often a process of optimizing different material properties and working with the inevitable tradeoffs.
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From page 51... ...
A simple, linear system is much easier, but does not translate to whole systems and not always to realistic detailed modeling. Berger asked Kabaria if Carbon could eventually have enough modeling data such that a printed product would not require testing.
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