Simulation-driven design and optimisation tools for additive manufacturing applications

Additive manufacturing technologies such as laser powder bed fusion have been widely adopted in various industries. A core reason for this adoption is the design freedom which allows for more complex designs than conventional manufacturing methods. While design for additive manufacturing includes restrictive aspects to ensure parts are manufactured successfully and at high quality, there is also an opportunistic aspect where the designer can improve performance by consolidating assemblies, reducing weight, and improving performance with new fabrication capabilities. Engineering design and analysis tools have also advanced greatly, with simulation being a core part of engineering design and iteration. To take full advantage of these new additive design freedoms new simulation-driven-design tools are required which optimise complex designs based on state-of-the-art in-service simulations and for additive manufacturing. This thesis develops and demonstrates a simulation-driven-design framework which automates the geometry generation, simulation and design iteration/optimisation steps to speed up design iteration and optimise part design. Knowledge of additive manufacturing limits are encoded in the framework to ensure the final designs are manufacturable and of acceptable quality. This is applied to develop and demonstrate three problem-specific design tools which advance the state of the art in the demonstrator topics: lattice structures, conformal cooling for injection moulding, and thermal stability of space optics. First an inverse design tool is developed for lattice structures which designs lattices to exhibit a target compressive stress-strain curve based on beam-element finite element analysis and accounts for large deformations and contact. This is supported by validation of the model with experimental testing with an average error in plateau stress of 12.6%, and X-ray micro-computed tomography to measure lattice dimensions. The tool is applied to design lattices with five distinct stress-strain curves, which are manufactured, tested, and compared to the target curves, achieving errors in plateau stress of 4.5–14.5% for four of the five test cases. Lattice structures are studied further via multi-material powder bed fusion, exploring another dimension of design freedom offered by the latest developments in multi-material additive manufacturing. Bi-metallic 17-4PH/316L stainless steel lattices are manufactured and the material interface is studied in lattice and bulk specimens. The material interface was found to be robust under the compressive loading, with no failure or cracking initiating at the interface. The compressive behaviour of two contrasting unit cells and two loading orientations are studied, with bi-metallic samples found have a greater energy absorption than single-material samples. A finite element model is developed to predict the response, including as-built dimensions informed by computed tomography. Finite element model predictions of the first maximum strength differ by a range of 3.2–96.6% to experimental values. To improve cooling time and cooling uniformity in injection moulding, an automated design tool is created to automatically design and optimise conformal cooling channels. The tool is demonstrated in a generic case study as well an industrial problem to design cooling channels for a real mould tool featuring multiple inserts. Channels are designed in a two-step process where first a candidate design is selected from a parameter study, and this candidate proceeds for further optimisation to improve the temperature uniformity. Analysis is performed with a MATLAB-based thermal model which is compared to industry-standard software Moldflow. In both demonstrators, the temperature uniformity and cooling time are improved via the MATLAB-based optimisation, however due to some of the assumptions in the MATLAB model improvements in temperature uniformity do not carry over to Moldflow in scenarios where some channels increase in temperature up more than others. To improve the thermal stability of optics in space applications, a custom shape optimisation method is developed and applied to minimise the optical wavefront error resulting from thermal gradients. An initial design is first created with topology optimisation to optimise the structural performance and find a lightweight design, which is directly followed by a custom shape optimisation step to optimise the optical performance measured based on a ray tracing simulation before and after thermally-induced deformations. This shape optimisation step reduced the wavefront error by up to 79%, and multi-objective optimisation resulted in simultaneous reductions in wavefront error by 60% and in volume by 20%. This custom method allows for further optimisation directly on the output of topology optimisation, and enables shape optimisation to improve on optical performance under a prescribed thermal load. This project has demonstrated the design framework across structural, thermal, and coupled thermomechanical and optical problems, producing a series of design tools offering fast design iteration and optimisation for additive manufacturing applications. This work has also produced a number of findings for design and design methods for each topic as a result of the large batches of simulations that are run with this method, showing its value as a research tool as well as for simulation-driven-design.

Funder

College of Science and Engineering, University of Galway

Publisher

University of Galway

Rights

CC BY-NC-ND

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Collections

University of Galway Theses (PhD Theses)