A Hybrid Level Set Method for the Topology Optimization of Functionally Graded Structures.

Junjian Fu, Zhengtao Shu, Liang Gao, Xiangman Zhou

Abstract read

In one paragraph

Article in Materials (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.

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2citing 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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

Biomimetic Lattice Structures Design and Manufacturing for High Stress, Deformation, and Energy Absorption Performance.Biomimetics (Basel, Switzerland) · 2025
Review
Cellular Automaton Mimicking Colliding Bodies for Topology Optimization.Materials (Basel, Switzerland) · 2022
Article

4 · The record

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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

4 authors.

Junjian FuHubei Key Laboratory of Hydroelectric Machinery Design & Maintenance, Yichang 443002, China.

Zhengtao ShuCollege of Mechanical and Power Engineering, China Three Gorges University, Yichang 443002, China.

Liang GaoState Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID 0000-0002-1485-0722

Xiangman ZhouHubei Key Laboratory of Hydroelectric Machinery Design & Maintenance, Yichang 443002, China.

Funding

Hubei Key Laboratory of Hydroelectric Machinery Design & Maintenance Open Foundation 2020KJX04National Natural Science Foundation of China 51775308Natural Science Foundation of Hubei Province 2021CFB236Science and Technology Research Project of Hubei Provincial Department of Education Q20201205

6 · The paper itself

Abstract

This paper presents a hybrid level set method (HLSM) to design novelty functionally graded structures (FGSs) with complex macroscopic graded patterns. The hybrid level set function (HLSF) is constructed to parametrically model the macro unit cells by introducing the affine concept of convex optimization theory. The global weight coefficients on macro unit cell nodes and the local weight coefficients within the macro unit cell are defined as master and slave design variables, respectively. The local design variables are interpolated by the global design variables to guarantee the C

Indexed as

functionally graded cellular structureshybrid level set methodthin-walled stiffened structurestopology optimization

Identifiers

PMID35806609

DOI10.3390/ma15134483

PMCPMC9267375

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