Evidence map›Paper›PMID 35458988›Full record

ArticleSensors (Basel, Switzerland)2022

Hypervelocity Impact Detection and Location for Stiffened Structures Using a Probabilistic Hyperbola Method.

Sunquan Yu, Chengguang Fan, Yong Zhao

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
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 at 1 institution in 1 country.

Sunquan YuCollege of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China.ORCID 0000-0002-9818-6063
Chengguang FanCollege of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China.
Yong ZhaoCollege of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China.
National University of Defense Technology · CN

Funding

National Natural Science Foundation of China 61601489
6 · The paper itself

Abstract

Hyper-velocity impact (HVI) caused by a collision between orbital debris and spacecraft exists widely in outer space, and it poses a threat to spacecraft. This paper proposes a probabilistic hyperbola method based on Lamb waves analysis to detect and locate the impact in stiffened aluminum (Al) plates. A hybrid model using finite element analysis (FEA) and smoothed particle hydrodynamics (SPH) was developed to gain an insight into characteristics of HVI-induced acoustic emission (AE) and shock wave propagation. In addition, an experimental validation was carried out with a two-stage light gas gun, giving an aluminum projectile a velocity of several kilometers per second. Then a quantitative agreement is obtained between numerical and experimental results, demonstrating the correctness of the hybrid model and facilitating the explanation of received AE signals in experiments. Signal analysis shows that the shock wave quickly converts to a Lamb wave as it propagates from the HVI spot, and the zeroth-order symmetric wave mode (S0) dominates wave signal energy. The S0 wave is dispersive and shows a wide frequency range, with dominant magnitudes below 500 kHz. Finally, the HVI experiment results obtained with a light gas gun showed that the average location error could be less than 1 cm with only four sensors for a 1-square-meter stiffened metal plate.

Indexed as

acoustic emissionimpact detectionpassive sensingstiffened aluminum plate

Identifiers

PMID35458988
PMCPMC9031354
OpenAlexW4224225082

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.