Evidence map›Paper›PMID 40732422›Full record

ArticleSensors (Basel, Switzerland)2025

Visualization Monitoring and Safety Evaluation of Turnout Wheel-Rail Forces Based on BIM for Sustainable Railway Management.

Xinyi Dong, Yuelei He, Hongyao Lu

Abstract read
In one paragraph

Article in Sensors (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

3 authors.

Xinyi DongCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201600, China.
Yuelei HeCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201600, China.
Hongyao LuCollege of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai 201600, China.

Funding

The National Natural Science Foundation of China 51978393The National Natural Science Foundation of China 52178430
6 · The paper itself

Abstract

With China's high-speed rail network undergoing rapid expansion, turnouts constitute critical elements whose safety and stability are essential to railway operation. At present, the efficiency of wheel-rail force safety monitoring conducted in the small hours reserved for the construction and maintenance of operating lines without marking train operation lines is relatively low. To enhance the efficiency of turnout safety monitoring, in this study, a three-dimensional BIM model of the No. 42 turnout was established and a corresponding wheel-rail force monitoring scheme was devised. Collision detection for monitoring equipment placement and construction process simulation was conducted using Navisworks, such that the rationality of cable routing and the precision of construction sequence alignment were improved. A train wheel-rail force analysis program was developed in MATLAB R2022b to perform signal filtering, and static calibration was applied to calculate key safety evaluation indices-namely, the coefficient of derailment and the rate of wheel load reduction-which were subsequently analyzed. The safety of the No. 42 turnout and the effectiveness of the proposed monitoring scheme were validated, theoretical support was provided for train operational safety and turnout maintenance, and technical guidance was offered for whole-life-cycle management and green, sustainable development of railway infrastructure.

Indexed as

4D construction simulationBuilding Information Modelingdata analysishigh-speed railwaysustainable operation and maintenanceturnout wheel–rail force monitoring

Identifiers

PMID40732422
PMCPMC12300579

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.