Evidence map›Paper›PMID 35009168›Full record

ArticleMaterials (Basel, Switzerland)2021

Inverse Determination of Johnson-Cook Parameters of Additively Produced Anisotropic Maraging Steel.

Rocco Eisseler, Daniel Gutsche, Clemens Maucher, Hans-Christian Möhring

Open access · goldAbstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 44% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

Rocco EisselerInstitute for Machine Tools, University of Stuttgart, Holzgartenstrasse 17, 70174 Stuttgart, Germany.
Daniel GutscheInstitute for Machine Tools, University of Stuttgart, Holzgartenstrasse 17, 70174 Stuttgart, Germany.
Clemens MaucherInstitute for Machine Tools, University of Stuttgart, Holzgartenstrasse 17, 70174 Stuttgart, Germany.
Hans-Christian MöhringInstitute for Machine Tools, University of Stuttgart, Holzgartenstrasse 17, 70174 Stuttgart, Germany.
University of Stuttgart · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In powder bed-based additive manufacturing (AM), complex geometries can be produced in a layer-wise approach. Results of material science experiments regarding material property identification, e.g., tensile strength, show interdependencies between the test load direction and the layer orientation. This goes hand-in-hand with the measured cutting force, changing with the relative angle between cutting direction and layer orientation in orthogonal cutting tests. However, due to the specific process characteristics, the layer orientation results in anisotropic material properties. Therefore, during machining, the material behaves depending on the buildup direction, which influences the cutting process. To predict this behavior, a simplified inverse approach is developed to determine the buildup direction-dependent parameters of a modified Johnson-Cook model for cutting simulation. To qualify these cutting models, mainly the cutting force and additionally the chip formation examined during orthogonal cuts are used. In the present paper, the influence of the laser-powder-bed-fusion (LPBF) process parameters on subtractive post-processing are shown. A good agreement between verification experiments and simulations is achieved.

Indexed as

additive manufacturinginverse parameter identificationmachining simulationmaraging steelmaterial property

Identifiers

PMID35009168
PMCPMC8746021
OpenAlexW4200163312

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.