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Thanks to a filter that works directly with the density field using automatic algorithms, the researchers have managed to manufacture parts with optimal material distribution based on the constraints imposed, whether these were weight, volume, stress or the amount of heat that the part had to transmit or withstand. The results of the research have recently been published in the prestigious scientific journal Structural and Multidisciplinary Optimization.  

“The advantage of using topological optimization for part design is that you automatically obtain the optimal shape, instead of having to apply different iterations and calculations,” says one of the authors of the study, Abraham Vadillo Morillas, from the Department of Mechanical Engineering at UC3M, whose doctoral thesis is based on this area of research. “In addition, this process has other advantages, such as direct and indirect cost savings. For example, an airplane manufactured with a lighter part than the original will be more environmentally friendly and will make travel cheaper for the passenger,” he notes.

A world of applications to discover

Although the experimental evaluation of these advances has been focused on the manufacture of motorcycle parts, the applications of these methods are much broader, as many sectors can benefit from the reduction in weight of their components, as well as the improvement in their rigidity.

“Any part subjected to loads or vibrations can benefit from these advances: from vehicle components to industrial machinery elements, architectural structures, jewellery and even fashion,” explains another of the researchers, Cristina Castejón Sisamón, professor in the Department of Mechanical Engineering at UC3M and head of the MAQLAB research group.

The methodology used to achieve these advances consisted of adapting topological optimization to the main manufacturing processes and improving the interpretability and accuracy of the results using new algorithms. In the case of additive manufacturing, the researchers have developed specific methods for 3D printing that have already been used to manufacture motorcycle components that have significantly reduced their weight. 

Recently, the team has begun to incorporate artificial intelligence (AI) techniques in order to move toward even more autonomous optimization processes. “Our goal is to develop agents that can adjust optimization parameters themselves, in an approach we have called AVM (Adaptive Variable Modelling). In this way, we hope that the new AI-based tools will change the paradigm of mechanical design and enable the generation of optimal parts more quickly, accurately and efficiently,” concludes Castejón.

The doctoral thesis produced based on this line of research was the first related to the MotoStudent competition project in which UC3M participates with its students and the MOTO-MAQLAB-UC3M association. This line of research began more than ten years ago with the aim of supporting students participating in this competition. The results of the research are already tangible in the different prototypes that have participated in several editions of MotoStudent, some of which are on display at the entrance to the Torres Quevedo Building on the Leganés Campus. 

Bibliographic references:

Vadillo, A., Meneses, J., Bustos, A. et al. Improving performance and convergence in topology optimization for print-ready designs. Struct Multidisc Optim 68, 189 (2025). https://doi.org/10.1007/s00158-025-04090-z 

Vadillo Morillas, A (2024). Novel methods in topology optimisation for additive/subtractive manufacturing in the digital environment. Application to motorbike design. Tesis doctoral Universidad Carlos III de Madrid, Departamento de Ingeniería Mecánica. https://hdl.handle.net/10016/46241