Evidence map›Paper›PMID 38676120›Full record

ArticleSensors (Basel, Switzerland)2024

A Concrete Core Void Imaging Approach and Parameter Analysis of Concrete-Filled Steel Tube Members Using Travel Time Tomography: Multi-Physics Simulations and Experimental Studies.

Wenting Zheng, Bin Xu, Zongjun Xia, Jiang Wang, Jingliang Liu, Yudi Yao, Yifei Wang

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. 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
2.1field-weighted citation impact, top 16% of its field
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, 4 citations in OpenAlex.

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

7 authors at 4 institutions in 1 country.

Wenting ZhengCollege of Civil Engineering, Huaqiao University, Xiamen 361021, China.
Bin XuCollege of Civil Engineering, Huaqiao University, Xiamen 361021, China.ORCID 0000-0001-8336-3306
Zongjun XiaChina Railway 15th Bureau Group City Construction Company Ltd., Luoyang 471000, China.
Jiang WangResearch Institute of Urbanization and Urban Safety, School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Jingliang LiuCollege of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou 350108, China.ORCID 0000-0001-5508-158X
Yudi YaoChina Railway 15th Bureau Group City Construction Company Ltd., Luoyang 471000, China.
Yifei WangChina Railway 15th Bureau Group City Construction Company Ltd., Luoyang 471000, China.
China Railway Construction Corporation (China) · CNHuaqiao University · CNFujian Agriculture and Forestry University · CNUniversity of Science and Technology Beijing · CN

Funding

National Natural Science Foundation of China (NSFC) 51608122National Natural Science Foundation of China (NSFC) 51878305National Natural Science Foundation of China (NSFC) 52378301
6 · The paper itself

Abstract

Concrete-filled steel tube (CFST) members have been widely used in civil engineering due to their advanced mechanical properties. However, internal defects such as the concrete core voids and interface debonding in CFST structures are likely to weaken their load-carrying capacity and stiffness, which affects the safety and serviceability. Visualizing the inner defects of the concrete cores in CFST members is a critical requirement and a challenging task due to the obvious difference in the material mechanical parameters of the concrete core and steel tube in CFST members. In this study, a curved ray theory-based travel time tomography (TTT) with a least square iterative linear inversion algorithm is first introduced to quantitatively identify and visualize the sizes and positions of the concrete core voids in CFST members. Secondly, a numerical investigation of the influence of different parameters on the inversion algorithm for the defect imaging of CFST members, including the effects of the model weighting matrix, weighting factor and grid size on the void's imaging quality and accuracy, is carried out. Finally, an experimental study on six CFST specimens with mimicked concrete core void defects is performed in a laboratory and the mimicked defects are visualized. The results demonstrate that TTT can identify the sizes and positions of the concrete core void defects in CFST members efficiently with the use of optimal parameters.

Indexed as

concrete-filled steel tubecurved ray theory-based travel time tomographydefect imagingexperimental studyleast square iterative linear inversion algorithmnumerical studyparameter analysispiezoelectric lead zirconate titanate

Identifiers

PMID38676120
PMCPMC11054418
OpenAlexW4394820991

What OpenQuestion holds

Textmetadata
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.