: The research presented in this work focuses on the structural optimization of a multilayer CFRP (carbon fiber reinforced polymer) laminate integrated within a railway carbody frame. The primary objective is to implement a systematic design methodology aimed at achieving significant mass reduction while preserving the mechanical performance and safety margins required by railway standards. To this end, a multi-stage optimization framework was developed to explore the sensitivity of fiber orientation on the laminate's failure behavior, directly coupled with high-fidelity finite element models for objective performance extraction. The investigation was initially conducted using an asynchronous optimization strategy, where the orientation of each individual ply was decoupled and analyzed independently. This phase revealed that a tailored, ply-specific approach is essential to address the varying structural requirements across the laminate thickness. Through this methodology, an optimal sequence of 36°/54°/126° was identified, achieving a significant 40.83% reduction in the Tsai-Wu failure index compared to a standard 0°/0°/0° baseline. Subsequently, a synchronous rotation analysis was performed to compare these results against conventional single-orientation design strategies. While the synchronous optimum was identified at 54°, it yielded a lower failure index reduction of 24.81%. The comparison highlights a further 16% performance gain enabled by the asynchronous method. Finally, the validation confirmed that these in-plane improvements were achieved without compromising interlaminar integrity, as the interlaminar shear stress (ILSS) remained constant and safe. This framework provides an objective and rigorous tool for the railway industry, replacing empirical design methods with a high-performance, data-driven approach.

Optimal Design of CFRP Railway Carbody Laminates via Multi-Criterion Fiber Orientation Sensitivity / Cascino, Alessio; Meli, Enrico; Rindi, Andrea. - In: MATERIALS. - ISSN 1996-1944. - ELETTRONICO. - 19:(2026), pp. 0-0. [10.3390/ma19071355]

Optimal Design of CFRP Railway Carbody Laminates via Multi-Criterion Fiber Orientation Sensitivity

Cascino, Alessio
;
Meli, Enrico;Rindi, Andrea
2026

Abstract

: The research presented in this work focuses on the structural optimization of a multilayer CFRP (carbon fiber reinforced polymer) laminate integrated within a railway carbody frame. The primary objective is to implement a systematic design methodology aimed at achieving significant mass reduction while preserving the mechanical performance and safety margins required by railway standards. To this end, a multi-stage optimization framework was developed to explore the sensitivity of fiber orientation on the laminate's failure behavior, directly coupled with high-fidelity finite element models for objective performance extraction. The investigation was initially conducted using an asynchronous optimization strategy, where the orientation of each individual ply was decoupled and analyzed independently. This phase revealed that a tailored, ply-specific approach is essential to address the varying structural requirements across the laminate thickness. Through this methodology, an optimal sequence of 36°/54°/126° was identified, achieving a significant 40.83% reduction in the Tsai-Wu failure index compared to a standard 0°/0°/0° baseline. Subsequently, a synchronous rotation analysis was performed to compare these results against conventional single-orientation design strategies. While the synchronous optimum was identified at 54°, it yielded a lower failure index reduction of 24.81%. The comparison highlights a further 16% performance gain enabled by the asynchronous method. Finally, the validation confirmed that these in-plane improvements were achieved without compromising interlaminar integrity, as the interlaminar shear stress (ILSS) remained constant and safe. This framework provides an objective and rigorous tool for the railway industry, replacing empirical design methods with a high-performance, data-driven approach.
2026
19
0
0
Cascino, Alessio; Meli, Enrico; Rindi, Andrea
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1464792
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