Evidence map›Paper›PMID 41257885›Full record

ArticleScientific reports2025

Research on risk factors identification and optimization strategies for railway tunnel construction in ecologically sensitive areas.

Zhongsheng Tan, Baojin Zhang, Zhenliang Zhou, Qinglou Li, Binghong Wan

Abstract read
In one paragraph

Article in Scientific reports, 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.

Zhongsheng TanKey Laboratory of Urban Underground Engineering of Ministry of Education, Beijing Jiaotong University, Beijing, 100044, China.ORCID http://orcid.org/0000-0001-5690-1420
Baojin ZhangKey Laboratory of Urban Underground Engineering of Ministry of Education, Beijing Jiaotong University, Beijing, 100044, China. 23111326@bjtu.edu.cn.ORCID http://orcid.org/0009-0005-6268-0878
Zhenliang ZhouKey Laboratory of Urban Underground Engineering of Ministry of Education, Beijing Jiaotong University, Beijing, 100044, China.
Qinglou LiKey Laboratory of Urban Underground Engineering of Ministry of Education, Beijing Jiaotong University, Beijing, 100044, China.ORCID http://orcid.org/0009-0003-9338-0064
Binghong WanChina Railway 25th Bureau Group Co., Ltd., Guangzhou, Guangdong, 510600, China.

Funding

Fundamental Research Funds for the Central Universities 2024JBMC046
6 · The paper itself

Abstract

When constructing railway tunnels in ecologically sensitive areas, numerous risks with high interdependence exist. Current risk identification methods are often unsystematic, prone to significant omissions, and may jeopardize construction safety and the ecological environment. This study uses the Xi'ning - Huangshengguan section of the Xi'ning - Chengdu Railway as a case study to quantitatively identify and hierarchically analyze the key influencing factors of railway tunnel construction risks. Seventeen core influencing factors were first distilled through literature review and expert questionnaires. Then, a DEMATEL-AISM hybrid model was employed to analyze expert rating data from levels 0-4, constructing a five - level adversarial hierarchical structure. The results show that in terms of centrality, environmental awareness (S16), regulatory system (S17), and construction methods (S8) rank the top three with centralities of 9.48, 9.40, and 8.90, indicating their significant system - wide impact. Causality analysis reveals that climate condition (S4) and construction season (S3) are the strongest root causes, while drainage system design (S11) and pollutant handling (S13) are most susceptible to other factors. By controlling four surface - level factors (construction equipment and materials S9, drainage system design S11, spoil dump design S12, and pollutant handling S13), a risk reduction rate of 62% can be achieved. This study offers a clear prioritization of risk factors for railway tunnel construction in ecologically sensitive areas, assisting projects in more effectively reducing risks during planning and construction.

Indexed as

DEMATEL-AISM (Adversarial interpretive structure modeling method)Railway engineering constructionRisk identificationRisk identification influencing factors

Identifiers

PMID41257885
PMCPMC12630707

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.