Evidence map›Paper›PMID 40508522›Full record

ArticleMaterials (Basel, Switzerland)2025

Optimization Design and Mechanical Performance Study of Carbon Fiber-Reinforced Composite Load-Carrying Structures for Subway Driver Cabin.

Jinle Wang, Bing Yang, Honglei Tian, Wenbin Wang, Xu Sang

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Jinle WangState Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, China.ORCID 0009-0000-2432-6310
Bing YangState Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031, China.
Honglei TianCRRC Qingdao Sifang Co., Ltd., Qingdao 266111, China.
Wenbin WangCollege of Transportation, Tongji University, Shanghai 200092, China.
Xu SangCollege of Transportation, Tongji University, Shanghai 200092, China.ORCID 0009-0004-1035-7756

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study systematically investigates the optimization design and mechanical performance of carbon fiber-reinforced polymer (CFRP) load-carrying structures for subway driver cabins to meet the lightweight demands of rail transit. Through experimental testing and micromechanical modeling, the mechanical properties of CFRP and foam core materials were characterized, with predicted elastic constants exhibiting an error of ≤5% compared with experimental data. A shape optimization framework integrating mesh morphing and genetic algorithms achieved a 22% mass reduction while preserving structural performance and maintaining load-carrying requirements. Additionally, a stepwise optimization strategy combining free-size, sizing, and stacking sequence optimization was developed to enhance layup efficiency. The final design reduced the total mass by 29.1% compared with the original model, with all failure factors remaining below critical thresholds across three loading cases. The increased failure factor confirmed that the optimized structure effectively exploited the material's potential while eliminating redundancy. These findings provide valuable theoretical and technical insights into lightweight CFRP applications in rail transit, demonstrating significant improvements in structural efficiency, safety, and manufacturability.

Indexed as

CFRPcomposite layuplightweight designstructural optimizationsubway driver cabin

Identifiers

PMID40508522
PMCPMC12156311

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.