Physics-based and Data-driven Models for Additive Manufacturing

Call for Papers

Physics-based and Data-driven Models for Additive Manufacturing

Journal: Virtual and Physical Prototyping
Publisher: Taylor & Francis Group
Article Collection: Open Access
Manuscript Submission Deadline: 31 October 2026

Virtual and Physical Prototyping invites high-quality submissions for its Open Access Article Collection on Physics-based and Data-driven Models for Additive Manufacturing.

About the Article Collection

Additive Manufacturing (AM) has evolved from rapid prototyping to the production of certified, high-value industrial components. However, broader industrial adoption remains challenged by process variability arising from complex multi-physics phenomena such as heat transfer, fluid flow, powder dynamics, phase transformation, and thermo-mechanical effects.

This Article Collection aims to showcase cutting-edge research that combines physics-based simulations with data-driven and AI-enabled modeling to improve predictive capability, reduce experimental costs, optimize manufacturing processes, and accelerate qualification workflows. Contributions focusing on hybrid modeling, digital twins, scientific machine learning, uncertainty quantification, and intelligent process control are particularly encouraged.

Topics of Interest

Submissions may include, but are not limited to:

• High-fidelity multi-physics simulations (DEM, CFD, SPH, coupled thermo-mechanics)

• Reduced-order and surrogate models for process optimization

• Scientific Machine Learning (SciML) and physics-informed AI for Additive Manufacturing

• Multi-scale and multi-fidelity modeling frameworks

• Powder, melt pool, microstructure, and part-scale performance modeling

• Uncertainty quantification, sensitivity analysis, and robust optimization

• Digital twins for Additive Manufacturing

• In-situ monitoring integration and model-based process control

• Computational modeling across the material-process-structure-performance chain

Preferred Article Types

The journal welcomes:

• Original Research Articles

• Review Papers

Submission Information

• Submission Deadline: 31 October 2026

• Manuscripts will undergo a full peer-review process.

• Select "Physics-based and Data-driven Models for Additive Manufacturing" from the Article Collection dropdown menu during submission.

• Authors should carefully follow the journal's official Instructions for Authors before submission.

Guest Advisors

• Dr. Mohamadreza Afrasiabi, ETH Zurich, Switzerland

• Prof. Zhilang Zhang, Peking University, China

• Posted on ServiceSetu Academics — Premier Platform for Academic Opportunities & Research Collaboration

Visit official website of the publisher