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Design of a computational model for 3D concrete printed geometry using machine learning and genetic optimization
ID
Ličen, Jurij
(
Author
),
ID
Chen, Taole
(
Author
)
URL - Presentation file, Visit
https://journals.bilpubgroup.com/index.php/jbms/article/view/13096/7818
URL - Source URL, Visit
https://journals.bilpubgroup.com/index.php/jbms/issue/view/862
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Abstract
3D Concrete Printing (3DCP) is an emerging technology with well-established benefits and the potential to dramatically change the construction industry. While research in material and process optimization is gaining traction, the architectural application of 3DCP remains relatively underdeveloped. Among many challenges, a lack of suitable computational modelling techniques is often identified as a major obstacle, resulting in simplistic design solutions that do not take full advantage of 3DCP technology. This study proposes a fabrication-aware design model using machine learning (ML), specifically genetic optimization, to address the research gap. 3DCP is used to produce sacrificial formwork for freeform reinforced concrete shell structures. The model conceptualizes a module-based approach to establish interlinked feedback loops across the various stages of a project, enabling fabrication and assembly considerations in the early design phase. Structural behaviour, printability, and segmentation constraints are translated into evaluative criteria within a unified computational workflow implemented in Rhino/Grasshopper, using the Galapagos genetic optimization solver. The framework enables iterative exploration of design options while accounting for both geometric and fabrication-related constraints. Three shell typologies are used to demonstrate the method, including a cantilever, a bridge, and a wall element, supported by a full-scale 3D printed segment for initial validation. This approach enables designers to develop geometries that are specifically tailored to the constraints and opportunities of 3DCP, opening new possibilities for meaningful interaction with the design-to-fabrication pipeline of complex 3DCP geometries.
Language:
English
Keywords:
3D concrete printing
,
computational design
,
evolutionary optimization
,
fabrication constraints
,
reinforced concrete shells
,
digital fabrication
,
early-stage design
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FA - Faculty of Architecture
Publication status:
Published
Publication version:
Version of Record
Publication date:
01.06.2026
Year:
2026
Number of pages:
Str. 77-92
Numbering:
Vol. 8, iss. 2
PID:
20.500.12556/RUL-185081
UDC:
004.925.84:72:691.32
ISSN on article:
2630-5216
DOI:
10.30564/jbms.v8i2.13096
COBISS.SI-ID:
285678083
Publication date in RUL:
22.07.2026
Views:
175
Downloads:
60
Metadata:
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Record is a part of a journal
Title:
Journal of building material science
Shortened title:
J. build. material sci.
Publisher:
Bilingual Publishing Co.
ISSN:
2630-5216
COBISS.SI-ID:
285552131
Licences
License:
CC BY-NC 4.0, Creative Commons Attribution-NonCommercial 4.0 International
Link:
http://creativecommons.org/licenses/by-nc/4.0/
Description:
A creative commons license that bans commercial use, but the users don’t have to license their derivative works on the same terms.
Secondary language
Language:
Slovenian
Keywords:
3D tiskanje betona
,
računalniško podprto načrtovanje
,
evolucijska optimizacija
,
omejitve izdelovanja
,
armirane betonske lupine
,
digitalno izdelovanje
,
zgodnja faza načrtovanja
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