Generative Design Of Light-weight Structural Systems
Creators: name: Watson, Marcus
Publisher: name: RMIT University
Year: 2025
Subjects: classificationCode: 401499
subject: Manufacturing engineering not elsewhere classified
classificationCode: 401799
subject: Mechanical engineering not elsewhere classified
classificationCode: 400202
subject: Automotive engineering materials

description: Light-weighting for vehicle design is an important consideration and is often achieved through structural optimisation. Light-weight component geometries which were previously not manufacturable through subtractive means, are now manufacturable using additive manufacturing technologies. Additionally, tools such as topology optimisation allow designers to generate novel light-weight component designs with improved performance characteristics.
Opportunities exist, in the integration of these light-weighting tools into automated workflows. This approach to design is known as generative design; an algorithmic approach to the design process which can generate and evaluate solutions to a design problem in an automated fashion. The application of generative design principles has the potential to provide several important improvements to the design process, including reduced lead times, reduced effect of designer fixation, increased size of solution space exploration, and redundancy provided through parallel design.
Key challenges exist in the creation of successful generative design workflows for application in light-weighting: a means to utilise algorithmic form generation tools in an efficient, low computational cost manner, for the exploration of potential problem solutions must be developed; parameterisation techniques are required to connect form generation tools to performance evaluating models; structural optimisation techniques need to be incorporated into automated workflows, to define and refine solution geometry.
This research addressed these challenges through the development of novel generative design workflows for three distinct structural light-weighting design cases: truss, frame, and shell structures respectively. Within this generative design approach, topology optimisation is utilised as a form generation tool. Novel parameterisation methods are developed utilising image processing algorithms to parameterise topology optimisation solutions into low-fidelity representations which are suitable as inputs to performance evaluating computer-aided engineering tools. Shape and sizing optimisation algorithms are then successfully applied to determine optimal geometry of parameterised solutions.
The generative design techniques proposed within this research were developed first for the design of trusses in two dimensions. Form generation is conducted utilising topology optimisation. The solution space is explored through alteration of topology optimisation control variables, whose solutions are then parameterised into connectivity definitions. An algorithm is proposed which can transform parameterised solutions into statically determinate representations of pin-jointed truss structures. Performance of the parameterised solutions is evaluated using the method of joints. Shape optimisation is then conducted using gradient descent algorithms for solution search, with constraints on stress and buckling, as well as a bounding on member cross-section size. A case study was conducted for three loading scenarios: Simply supported beam, Messerschmidt-Bölkow-Blohm beam, and cantilever beam. A set of high-performing solutions was generated for each of the loading cases. The capability of the generative design method to produce high-performing solutions was confirmed through the generation of known optimal Michell structures.
The generative design method was developed further in three-dimensions for the design of space frame structures. The parameterisation method developed for trusses was expanded to three dimensions successfully. Performance evaluation was conducted using a finite element method beam model. Shape optimisation solution search was conducted with a gradient descent algorithm. This was constrained using the method of gradient summation, with regards to maximum stress, critical buckling stress, and a bounding on maximum and minimum frame member cross-section. An experimental case study was conducted, applying the generative design method to an industry type problem, through the light-weighting of an aerospace bracket. Through this case study, the effect of topology optimisation resolution on design outcomes, as well as the performance of the parameterisation method, was assessed. A resolution threshold was identified at which point parameterisation performance is compromised. Six high-performing topologies were identified and found to be generated many times using low resolution topology optimisation. This finding confirms that reductions in computational cost within generative design workflows can be achieved through low resolution simulation, while still generating high-performance outcomes. The method was benchmarked against solutions generated with Autodesk’s Fusion and were found to outperform these commercial software outcomes.
The generative design approach was applied to the light-weighting of a shell component. A novel approach was developed, whereby two-dimensional topology optimisation simulations are conducted on slices taken through the span-wise length of the incumbent shell geometry. A novel parameterisation technique was created which translates structures within these solutions into trajectories which are used to generate surfaces running through the the incumbent geometry span. Four solutions to a constant external pressure loading problem were generated by altering topology optimisation simulation resolution. Sizing optimisation was conducted on three of the generated solutions, alongside a control, using a shell finite element model, evaluating deflection with regards to surface thickness. Pareto fronts of deflection-to-mass were created from sizing optimisation results, and solutions were selected from the Pareto front for a target deflection. Each selected component was manufactured out of Acrylonitrile-butadiene-styrene using fused filament fabrication, and compressively tested to evaluate the components stiffness. The generated components were found to have improved stiffness-to-weight ratio when compared to the incumbent component. The solutions were also benchmarked against open-source topology optimisation software, top3D for runtime, showing a marked improvement in time required for simulation. The performance of solutions under compressive loading was also benchmarked against a solution generated using commercial software Fusion by Autodesk, and all solutions generated using the proposed method were found to outperform the Fusion solution with regards to stiffness and stiffness-to-mass ratio.
The findings of this research contribute to the field of generative design through discussion of the field’s history, the tools required, and approaches for successful application of generative design in light-weighting. Additionally, through the implementation of generative design strategies for the design of light-weight truss, frame and shell structures, this research proposes novel generative design approaches that can successfully achieve design outcomes utilising low computational cost. Application of the proposed methods for two industry type problems within Chapter 4 and Chapter 5 shows the potential for improvements in lead times and performance within the embodiment design phase, while allowing for redundancy that can improve the light-weighting design process. These research contributions improve on the understanding of generative design processes and their implementations, providing opportunities to improve the uptake and effectiveness of generative design use within industry.