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Pasquale Posabella

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

2

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86

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0

Scholarly Papers (2)

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1.

From Prediction to Design: A Machine Learning Tool for Porous Mechanical Metamaterials

Downloads 46 (1,157,785)

From Prediction to Design: A Machine Learning Tool for Porous Mechanical Metamaterials

Number of pages: 48 Posted: 15 May 2025
Pasquale Posabella, Marcin Heljak, Kamil Majchrowicz, Marco Costantini and Wojciech Święszkowski
affiliation not provided to SSRN, Warsaw University of Technology - Faculty of Materials Science and Engineering, affiliation not provided to SSRN, Polish Academy of Sciences and Warsaw University of Technology
Downloads 35 (1,326,242)

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Spherical-based Porous Metamaterials, Mechanical Metamaterials, Artificial Neural Network, Genetic Algorithm, Inverse Design, Porous materials

From Prediction to Design: A Machine Learning Tool for Porous Mechanical Metamaterials

Number of pages: 35 Posted: 13 Jun 2025
Pasquale Posabella, Marcin Heljak, Kamil Majchrowicz, Marco Costantini and Wojciech Święszkowski
affiliation not provided to SSRN, Warsaw University of Technology - Faculty of Materials Science and Engineering, affiliation not provided to SSRN, Polish Academy of Sciences and Warsaw University of Technology
Downloads 11 (1,606,395)

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Spherical-based Porous Metamaterials, Mechanical metamaterials, Artificial Neural Network, Genetic algorithm, Inverse design, Porous materials

2.

Functionally Graded Spherical-Based Porous Architectures Via Low Force Stereolithography: In Silico Design and Experimental Validation

Number of pages: 26 Posted: 24 Feb 2024
Pasquale Posabella, Marcin Heljak, Marco Costantini and Wojciech Święszkowski
affiliation not provided to SSRN, Warsaw University of Technology - Faculty of Materials Science and Engineering, Polish Academy of Sciences and Warsaw University of Technology
Downloads 40 (1,183,237)

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porous architecture, functionally graded structure, 3D printing, mechanical characterisation, finite element analysis, Computational Fluid Dynamics