Evidence map›Paper›PMID 40414925›Full record

ArticleScientific reports2025

Damage analysis of split spherical node concrete filled steel tube lattice wind turbine plane towers.

Miao Li, Jiaqing Tao, Huanbin Huang, Chengjun Peng, Yang Wen

Abstract read
PubMed Full text at PMC Publisher
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.

Miao LiSchool of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China.
Jiaqing TaoSchool of Civil Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China. 2022022156@stu.imust.edu.cn.
Huanbin HuangSchool of Civil Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China.
Chengjun PengSchool of Civil Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China.
Yang WenSchool of Mechanical Engineering, Inner Mongolia University of Science and Technology, Baotou, 014010, China.

Funding

Fundamental Research Funds for Inner Mongolia University of Science & Technology 2024RCTD004Inner Mongolia Autonomous Region University Youth Science and Technology Talents Project NJYT22068National natural science foundation 51768056
6 · The paper itself

Abstract

This study analyzes the split spherical node concrete-filled steel tube wind turbine plane towers with web member wall thicknesses of 3 mm (TJ-1) and 5 mm (TJ-2) through low-cyclic reversed load tests, comparing their hysteresis curves, skeleton curves, ductility, and stiffness degradation. The analysis is further validated using ABAQUS software simulations, exploring the impact of web member diameter ratios on the damage of the plane towers. The results indicate that the failure modes of the split spherical node concrete-filled steel tube wind turbine plane towers include weld tearing failure, web member buckling failure, and high-strength bolt pull-out failure. The yield load and peak load of specimen TJ-2 are 9% and 21% higher than those of specimen TJ-1, respectively, with a more plump hysteresis curve and better energy dissipation capacity. Increasing the web member wall thickness can enhance the initial and overall stiffness of the tower. The parametric analysis of the web member diameter ratio suggests that a ratio of 0.11-0.13 is recommended for engineering applications.

Indexed as

Bearing capacityDamage analysisLattice constructionWall thicknessWind turbine towers

Identifiers

PMID40414925
PMCPMC12104333

What OpenQuestion holds

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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.