Evidence map›Paper›PMID 38667260›Full record

ArticleBiomimetics (Basel, Switzerland)2024

Morphological Reconstruction for Variable Wing Leading Edge Based on the Node Curvature Vectors.

Jie Zeng, Qingfeng Zhu, Yueqi Zhao, Zhigang Wang, Yu Yang, Qi Wu, Jinpeng Cui

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Review
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 2 institutions in 1 country.

Jie ZengState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Qingfeng ZhuState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Yueqi ZhaoState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Zhigang WangAircraft Strength Research Institute of China, National Key Laboratory of Strength and Structural Integrity, Xi'an 710065, China.
Yu YangAircraft Strength Research Institute of China, National Key Laboratory of Strength and Structural Integrity, Xi'an 710065, China.
Qi WuAircraft Strength Research Institute of China, National Key Laboratory of Strength and Structural Integrity, Xi'an 710065, China.
Jinpeng CuiState Key Laboratory of Mechanics and Control of Mechanical Structures, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Nanjing University of Aeronautics and Astronautics · CNBeihang University · CN

Funding

the Fund of Aeronautics Science 20220028052002the National Key Laboratory of Helicopter Rotor Dynamics Fund project 61422202207the National Key Research and Development Program of the Ministry of Science and Technolo-gy 2021YFC2802300the National Natural Science Foundation of China 52275536the National Natural Science Foundation of China 62273179
6 · The paper itself

Abstract

Precise morphology acquisition for the variable wing leading edge is essential for its bio-inspired adaptive control. Therefore, this study proposes a morphological reconstruction method for the variable wing leading edge, utilizing the node curvature vectors-based curvature propagation method (NCV-CPM). By establishing a strain-arc curvature function, the method fundamentally mitigates the impact of surface curvature angle on curvature computation accuracy at sensing points. We introduce a technique that uses high-order curvature fitting functions to determine the curvature vectors of arc segment nodes. This method reduces cumulative errors in curvature computation linked to the linear interpolation-based curvature propagation method (LI-CPM) at unattached sensor positions. Integrating curvature-strain functions aids in wing leading-edge strain field reconstruction, supporting structural health monitoring. Additionally, a particle swarm algorithm optimizes the sensing point distribution, reducing network complexity. This study demonstrates significantly enhanced morphological reconstruction accuracy compared to those obtained with conventional LI-CPM.

Indexed as

curvature propagation methodmorphological reconstructionnode curvature vectorsstrain–curvature functionvariable wing leading edge

Identifiers

PMID38667260
PMCPMC11048124
OpenAlexW4395000199

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.