Evidence map›Paper›PMID 37834596›Full record

ReviewMaterials (Basel, Switzerland)2023

A Review of Computational Approaches to the Microstructure-Informed Mechanical Modelling of Metals Produced by Powder Bed Fusion Additive Manufacturing.

Olga Zinovieva, Varvara Romanova, Ekaterina Dymnich, Aleksandr Zinoviev, Ruslan Balokhonov

Abstract readReview
In one paragraph

Review in Materials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Advances in Metal Microstructure Simulation and Analysis.Materials (Basel, Switzerland) · 2026
    Review
  2. Review
  3. 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

5 authors.

Olga ZinovievaSchool of Engineering and Technology, University of New South Wales Canberra, Campbell, ACT 2612, Australia.ORCID 0000-0002-9373-8711
Varvara RomanovaInstitute of Strength Physics and Materials Science, 634055 Tomsk, Russia.ORCID 0000-0001-8693-3810
Ekaterina DymnichInstitute of Strength Physics and Materials Science, 634055 Tomsk, Russia.
Aleksandr ZinovievSchool of Engineering and Technology, University of New South Wales Canberra, Campbell, ACT 2612, Australia.ORCID 0000-0002-3387-3727
Ruslan BalokhonovInstitute of Strength Physics and Materials Science, 634055 Tomsk, Russia.ORCID 0000-0001-9994-5685

Funding

Government research assignment for ISPMS SB RAS FWRW-2021-0002Russian Science Foundation 20-19-1096 00600University of New South Wales Canberra Start-up grant PS66347
6 · The paper itself

Abstract

In the rapidly evolving field of additive manufacturing (AM), the predictability of part properties is still challenging due to the inherent multiphysics complexity of the technology. This results in time-consuming and costly experimental guess-and-check approaches for manufacturing each individual design. Through synthesising advancements in the field, this review argues that numerical modelling is instrumental in mitigating these challenges by working in tandem with experimental studies. Unique hierarchical microstructures induced by extreme AM process conditions- including melt pool patterns, grains, cellular-dendritic substructures, and precipitates-affect the final part properties. Therefore, the development of microstructure-informed mechanical models becomes vital. Our review of numerical studies explores various modelling approaches that consider the microstructural features explicitly and offers insights into multiscale stress-strain analysis across diverse materials fabricated by powder bed fusion AM. The literature indicates a growing consensus on the key role of multiscale integrated process-structure-property-performance (PSPP) modelling in capturing the complexity of AM-produced materials. Current models, though increasingly sophisticated, still tend to relate only two elements of the PSPP chain while often focusing on a single scale. This emphasises the need for integrated PSPP approaches validated by a solid experimental base. The PSPP paradigm for AM, while promising as a concept, is still in its infantry, confronting multifaceted challenges that require in-depth, multidisciplinary expertise. These challenges range from accounting for multiphysics phenomena (e.g., advanced laser-material interaction) and their interplay (thermo-mechanical and microstructural evolution for simulating Type II residual stresses), accurately defined assumptions (e.g., flat molten surface during AM or purely epitaxial solidification), and correctly estimated boundary conditions for each element of the PSPP chain up to the need to balance the model's complexity and detalisation in terms of both multiphysics and discretisation with efficient multitrack and multilayer simulations. Efforts in bridging these gaps would not only improve predictability but also expedite the development and certification of new AM materials.

Indexed as

crystal plasticitymetal additive manufacturingmicromechanicsmicrostructure-based simulationmicrostructure modellingpowder bed fusion

Identifiers

PMID37834596
PMCPMC10573704

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.