Advances in Additive Manufacturing and Their Applications

Berce, Petru

doi:10.3390/met14020165

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…These tools have been tested and applied to real-world components in some instances. More recent studies and reviews evidence a trend to use and develop this method for future applications in the world of part design [24][25][26][27][28][29][30] The paper conducts a comparative analysis on the structural optimization of a real part using four commercial software codes (PTC Creo Parametric 6.0.1.0, Altair HyperMesh 2023.1, Solidworks 2023, and Ansys Workbench 2023R1) and a self-implemented MATLAB code. The aim is to demonstrate the benefits of understanding and applying the core principles of the topology optimization process over the use of popular solvers, like Tosca, OptiStruct, Ansys, and PTC.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing

Vadillo Morillas,

Meneses Alonso,

Bustos Caballero

et al. 2024

Preprint

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CAD-CAE software companies have introduced numerous tools aimed at facilitating topology optimization through Finite Element Simulation, thereby enhancing accessibility for designers via user-friendly interfaces. However, the imposition of intricate constraint conditions or additional restrictions during calculations may introduce instability into the resultant outcomes. In this paper, an algorithm for updating the design variables called Adaptive Variable Design is proposed to keep the final design space volume of the optimized part always under the target value while giving the main algorithm multiple chances to update the optimization parameters and search for a valid design. This algorithm aims to producing results that are more conducive to manufacturability and potentially more straightforward in interpretation. A comparison between several commercial software and the proposed algorithm, implemented in MATLAB, is carried out to prove the robustness of the latter. By simulating identical parts under similar conditions, we seek to generate comparable results and underscore the advantages stemming from the adoption and comprehension of the proposed topology optimization methodology. Our findings reveal that the integrated enhancements within MATLAB pertaining to the topology optimization process yield favourable outcomes with respect to discretization, and the manufacturability of resultant geometries. Furthermore, we assert that the methodology evaluated within MATLAB holds promise for potential integration into commercial packages, thereby enhancing the efficiency of topology optimization processes.

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Section: Introductionmentioning

confidence: 99%

Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing

Vadillo Morillas,

Meneses Alonso,

Bustos Caballero

et al. 2024

Preprint

View full text Add to dashboard Cite

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Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing Guided Design

Vadillo Morillas,

Meneses Alonso,

Bustos Caballero

et al. 2024

Inventions

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CAD-CAE software companies have introduced numerous tools aimed at facilitating topology optimization through Finite Element Simulation, thereby enhancing accessibility for designers via user-friendly interfaces. However, the imposition of intricate constraint conditions or additional restrictions during calculations may introduce instability into the resultant outcomes. In this paper, an algorithm for updating the design variables called Adaptive Variable Design is proposed to keep the final design space volume of the optimized part consistently under the target value while giving the main algorithm multiple chances to update the optimization parameters and search for a valid design. This algorithm aims to produce results that are more conducive to manufacturability and potentially more straightforward in interpretation. A comparison between several commercial software packages and the proposed algorithm, implemented in MATLAB R2023a, is carried out to prove the robustness of the latter. By simulating identical parts under similar conditions, we seek to generate comparable results and underscore the advantages stemming from the adoption and comprehension of the proposed topology optimization methodology. Our findings reveal that the integrated enhancements within MATLAB pertaining to the topology optimization process yield favourable outcomes with respect to discretization and the manufacturability of the resultant geometries. Furthermore, we assert that the methodology evaluated within MATLAB holds promise for potential integration into commercial packages, thereby enhancing the efficiency of topology optimization processes.

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Advances in Additive Manufacturing and Their Applications

Abstract: Additive manufacturing (AM) has evolved rapidly in the last few years [...]

Cited by 2 publications

References 10 publications

Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing

Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing

Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing Guided Design

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