Deutsche Nationalbibliothek
metadata only
Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach / Giacomo Rizzieri, Jörg F. Unger, Annika Robens-Radermacher, Saif-Ur-Rehman
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach#987845
- Influence of Extruded Filament Shape on Buildability in 3D Concrete Printing: A Geometry-Informed Deep Learning-FEM Approach#639665
- ADVANCED ADDITIVE MANUFACTURING ACROSS MATERIAL, SCALE, DIMENSIONS TOWARDS HIGH-PERFORMANCE STRUCTURE#929138
- Structural Optimization under Self-Weight for Extrusion-Based Additive Manufacturing : a Path-Oriented Modeling and Optimization Framework#337545
- Machine learning models for predicting the hardness of additively manufactured Polymethyl Methacrylate (PMMA) parts for biomedical applications.#455526
Record · ID 983262
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive