Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 874

The DOI matches its Crossref record; 103 of the 103 references it cites were found in a registry or an index.

A review of topology optimization for additive manufacturing: Status and challenges

Open access
ZHU, Jihong, ZHOU, Han, WANG, Chuang, ZHOU, Lu, YUAN, Shangqin, ZHANG, Weihong·2021·Chinese Journal of Aeronautics

Abstract

Topology optimization was developed as an advanced structural design methodology to generate innovative lightweight and high-performance configurations that are difficult to obtain with conventional ideas. Additive manufacturing is an advanced manufacturing technique building as-designed structures via layer-by-layer joining material, providing an alternative pattern for complex components. The integration of topology optimization and additive manufacturing can make the most of their advantages and potentials, and has wide application prospects in modern manufacturing. This article reviews the main content and applications of the research on the integration of topology optimization and additive manufacturing in recent years, including multi-scale or hierarchical structural optimization design and topology optimization considering additive manufacturing constraints. Meanwhile, some challenges of structural design approaches for additive manufacturing are discussed, such as the performance characterization and scale effects of additively manufactured lattice structures, the anisotropy and fatigue performance of additively manufactured material, and additively manufactured functionally graded material issues, etc. It is shown that in the research of topology optimization for additive manufacturing, the integration of material, structure, process and performance is important to pursue high-performance, multi-functional and lightweight production. This article provides a reference for further related research and aerospace applications.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.cja.2020.09.020

Cites

103 of 103 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 103 references

Cited by

See all 874

Metadata

Authors
ZHU, J., ZHOU, H., WANG, C., ZHOU, L., YUAN, S., & ZHANG, W.
Venue
Chinese Journal of Aeronautics
Publisher
Elsevier BV
Published
2021-01
Volume
34
Issue
1
Pages
91-110
ISSN
1000-9361 (ISSN-L)
OpenAlex
W3093210795
Cited by
874
References
103
FWCI
45.43
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A review of topology optimization for additive manufacturing: Status and challenges. https://app.cochat.ai/papers/10.1016/j.cja.2020.09.020
The paper
ZHU, J., ZHOU, H., WANG, C., ZHOU, L., YUAN, S., & ZHANG, W. (2021). A review of topology optimization for additive manufacturing: Status and challenges. Chinese Journal of Aeronautics. https://doi.org/10.1016/j.cja.2020.09.020

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.