The industrial sector continues to explore innovative strategies to exploit the full potential of Additive Manufacturing (AM). Among its many advantages, AM enables the fabrication of lattice structures; these are lightweight metamaterials with tunable mechanical properties and excellent energy absorption capabilities. Despite their promise, the widespread industrial use of such structures is limited by the difficulty in accurately assessing their fatigue behavior. This study presents a methodology aimed at predicting the fatigue life of polymer-based lattice components, with a specific focus on PA12 manufactured using the Multi Jet Fusion (MJF) process. This is an industrially relevant technology offering large production volumes, high printing quality and low production costs. The approach begins with fatigue testing of bulk PA12 specimens to establish baseline material behavior. Based on these results, a predictive algorithm is developed to estimate the fatigue performance of lattice structures. The model adopts an energy-based framework inspired by the Average Strain Energy Density (ASED) method, previously used for metallic materials, and adapts it to the characteristics of polymer lattices. The proposed methodology contributes to the development of efficient fatigue assessment tools, supporting the broader adoption of lattice structures in cost-sensitive industrial applications where polymer-based materials are effective.

Fatigue life prediction of multi jet fusion-manufactured polyamide12 lattice structures using the average strain energy density method / De Biasi, Raffaele; Romanelli, Lorenzo; Santus, Ciro; Perini, Matteo; Berto, Filippo; Benedetti, Matteo. - In: INTERNATIONAL JOURNAL OF FATIGUE. - ISSN 0142-1123. - 206:109452(2026). [10.1016/j.ijfatigue.2025.109452]

Fatigue life prediction of multi jet fusion-manufactured polyamide12 lattice structures using the average strain energy density method

De Biasi, Raffaele
Primo
;
Benedetti, Matteo
Ultimo
2026-01-01

Abstract

The industrial sector continues to explore innovative strategies to exploit the full potential of Additive Manufacturing (AM). Among its many advantages, AM enables the fabrication of lattice structures; these are lightweight metamaterials with tunable mechanical properties and excellent energy absorption capabilities. Despite their promise, the widespread industrial use of such structures is limited by the difficulty in accurately assessing their fatigue behavior. This study presents a methodology aimed at predicting the fatigue life of polymer-based lattice components, with a specific focus on PA12 manufactured using the Multi Jet Fusion (MJF) process. This is an industrially relevant technology offering large production volumes, high printing quality and low production costs. The approach begins with fatigue testing of bulk PA12 specimens to establish baseline material behavior. Based on these results, a predictive algorithm is developed to estimate the fatigue performance of lattice structures. The model adopts an energy-based framework inspired by the Average Strain Energy Density (ASED) method, previously used for metallic materials, and adapts it to the characteristics of polymer lattices. The proposed methodology contributes to the development of efficient fatigue assessment tools, supporting the broader adoption of lattice structures in cost-sensitive industrial applications where polymer-based materials are effective.
2026
109452
Settore ING-IND/14 - Progettazione Meccanica e Costruzione di Macchine
Settore IIND-03/A - Progettazione meccanica e costruzione di macchine
De Biasi, Raffaele; Romanelli, Lorenzo; Santus, Ciro; Perini, Matteo; Berto, Filippo; Benedetti, Matteo
Fatigue life prediction of multi jet fusion-manufactured polyamide12 lattice structures using the average strain energy density method / De Biasi, Raffaele; Romanelli, Lorenzo; Santus, Ciro; Perini, Matteo; Berto, Filippo; Benedetti, Matteo. - In: INTERNATIONAL JOURNAL OF FATIGUE. - ISSN 0142-1123. - 206:109452(2026). [10.1016/j.ijfatigue.2025.109452]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/470230
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