Evidence map›Paper›PMID 27019583›Full record

ArticleApplied bionics and biomechanics2015

Design and Analysis of Bionic Cutting Blades Using Finite Element Method.

Mo Li, Yuwang Yang, Li Guo, Donghui Chen, Hongliang Sun, Jin Tong

Abstract read
In one paragraph

Article in Applied bionics and biomechanics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Motion Simulation of Ionic Liquid Gel Soft Actuators Based on CPG Control.Computational intelligence and neuroscience · 2019
    Article
  4. Article
  5. 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

6 authors.

Mo LiThe Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, 5988 Renmin Street, Changchun 130022, China.
Yuwang YangThe Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, 5988 Renmin Street, Changchun 130022, China.
Li GuoThe Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, 5988 Renmin Street, Changchun 130022, China.
Donghui ChenThe Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, 5988 Renmin Street, Changchun 130022, China.
Hongliang SunThe School of Mechanical Engineering, Xi'an Jiaotong University, Xianning Road, Xi'an 710049, China.
Jin TongThe Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, 5988 Renmin Street, Changchun 130022, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Praying mantis is one of the most efficient predators in insect world, which has a pair of powerful tools, two sharp and strong forelegs. Its femur and tibia are both armed with a double row of strong spines along their posterior edges which can firmly grasp the prey, when the femur and tibia fold on each other in capturing. These spines are so sharp that they can easily and quickly cut into the prey. The geometrical characteristic of the praying mantis's foreleg, especially its tibia, has important reference value for the design of agricultural soil-cutting tools. Learning from the profile and arrangement of these spines, cutting blades with tooth profile were designed in this work. Two different sizes of tooth structure and arrangement were utilized in the design on the cutting edge. A conventional smooth-edge blade was used to compare with the bionic serrate-edge blades. To compare the working efficiency of conventional blade and bionic blades, 3D finite element simulation analysis and experimental measurement were operated in present work. Both the simulation and experimental results indicated that the bionic serrate-edge blades showed better performance in cutting efficiency.

Identifiers

PMID27019583
PMCPMC4745428

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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.