Evidence map›Paper›PMID 37688201›Full record

ArticlePolymers2023

Topology Optimization for Digital Light Projector Additive Manufacturing Addressing the In-Situ Structural Strength Issue.

Jun Wang, Jikai Liu, Lei Li

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2023. 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
0.9field-weighted citation impact, top 29% 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, 6 citations in OpenAlex.

  1. 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.

Jun WangCenter for Advanced Jet Engineering Technologies (CaJET), Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan 250061, China.
Jikai LiuCenter for Advanced Jet Engineering Technologies (CaJET), Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan 250061, China.
Lei LiCenter for Advanced Jet Engineering Technologies (CaJET), Key Laboratory of High Efficiency and Clean Mechanical Manufacture, Ministry of Education, School of Mechanical Engineering, Shandong University, Jinan 250061, China.ORCID 0000-0002-5259-407X
Shandong University · CN

Funding

Shandong Provincial Key Research and Development Program 2021CXGC010206
6 · The paper itself

Abstract

A topology optimization approach is proposed for the design of self-supporting structures for digital light projector (DLP) 3D printing. This method accounts for the adhesion forces between the print part and the resin base during DLP printing to avoid failure of the part due to stress concentration and weak connections. Specifically, the effect of the process-related adhesion forces is first simulated by developing a design variable-interpolated finite element model to capture the intricate mechanical behavior during DLP 3D printing. Guided by the process model, a stress-constrained topology optimization algorithm is formulated with both the SIMP and RAMP interpolation schemes. The interpolations on the stress term and the design-dependent adhesion load are carefully investigated. A sensitivity result on the P-norm stress constraint is fully developed. Finally, the approach is applied to several 2D benchmark examples to validate its efficacy in controlling the process-caused peak P-norm stresses. The effects of alternating between the SIMP and RAMP interpolations and changing the stress upper limits are carefully explored during the numerical trials. Moreover, 3D printing tests are performed to validate the improvement in printability when involving the process-related P-norm stress constraint.

Indexed as

design for additive manufacturingDLP 3D printingstress constrainttopology optimization

Identifiers

PMID37688201
PMCPMC10490026
OpenAlexW4386255498

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.