Evidence map›Paper›PMID 40271701›Full record

ArticleMaterials (Basel, Switzerland)2025

Comparative Analysis and Dynamic Size Optimization of Aluminum and Carbon Fiber Thin-Walled Structures of a Railway Vehicle Car Body.

Alessio Cascino, Enrico Meli, Andrea Rindi

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Alessio CascinoDepartment of Industrial Engineering, University of Florence, 50139 Florence, Italy.ORCID 0000-0003-0071-003X
Enrico MeliDepartment of Industrial Engineering, University of Florence, 50139 Florence, Italy.ORCID 0000-0002-0513-9242
Andrea RindiDepartment of Industrial Engineering, University of Florence, 50139 Florence, Italy.ORCID 0000-0001-7779-752X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of modern railway engineering, the demand for lighter and more reliable vehicles has become a key objective for rolling stock manufacturers. Reducing energy consumption and minimizing environmental impact are driving the adoption of advanced materials and innovative design methodologies. This research activity focuses on a comparative analysis between aluminum and carbon fiber thin-walled structures used in railway vehicle car bodies. A high-fidelity finite element model (FEM) of a complete railway vehicle was developed to evaluate structural performance in compliance with European standards. Gaining deeper insights, one of the car body structures was isolated for a detailed dynamic analysis, enabling a comparative evaluation of the two materials. A structural dynamic size optimization process was applied to specific key components, aiming to maximize mass savings while maintaining mechanical integrity. The results exhibited an increase of approximately 10% in the first 10 car body eigenvalues, despite a mass reduction per unit of volume exceeding 30%, while largely preserving the nature of the eigenvectors. From a static perspective, both materials demonstrated good performance, with percentage differences below 20%. The optimization process highlighted significant potential for weight reduction in the analyzed structures. The findings highlight the critical role of optimization processes in streamlining design choices for lightweight structures. Moreover, they underscore the significant potential of high-performance carbon fiber materials in enhancing the efficiency and sustainability of railway vehicles. This study provides valuable insights for future research and practical applications in the field of lightweight railway vehicle design.

Indexed as

carbon fiber compositesdynamic optimizationlightweight materialsrailway vehicle designstructural optimization

Identifiers

PMID40271701
PMCPMC11989826

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.