Computational Approaches for Manufacturing

Dear Colleagues,

Manufacturing, such as additive manufacturing, welding, and casting, is a complex process for fabricating material and building parts, which involves heat transfer, fluid flow, evaporation, phase changes, and solidification. Computational methods have played a key role in obtaining a deep understanding of how manufacturing processes affect material microstructure, mechanical properties, and parts performance. The development of multi-physics models and data-driven models in manufacturing offers efficient ways to explore the fundamental science and findings related to the manufacturing process.

The aim of this Special Issue is to highlight the technologies and progress in simulations and data-driven models for manufacturing. Specific fields and topics of interest include, but are not limited to, the following:

• Multiscale and multiphysics modeling;
• Data-driven modeling;
• Model calibration;
• Reduced order modeling;
• Uncertainty quantification;
• Optimization and design;
• Experimental image processing;
• Image segmentation and analysis;
• Heat transfer;
• Alloy design;
• Solidification modeling;
• Process–structure property.

Dr. Lichao Fang
Guest Editor

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• multiphysics modeling
• data-driven modeling
• additive manufacturing
• welding
• casting
• image processing
• process–structure property

Title: Statistical Modeling of Defects in Metal 3D Printing from a Simplified Finite Element Method

Authors: Antonio Martínez Raya 1,*, Martín Nicolás Braun 2, Cristina Carrasco-Garrido 3, and Vicente González Albuixech 4

Affiliations: 1 Department of Organizational Engineering, Business Administration and Statistics, Technical University of
Madrid—Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; [email protected]
2 Universidad Politécnica de Madrid (UPM), Department of Fluid Mechanics and Aerospace Propulsion,
Technical University of Madrid—Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; matias.
[email protected]
3 Department of Business Administration, Rey Juan Carlos University—Universidad Rey Juan Carlos
(URJC), Madrid, 28032, Spain; [email protected]
4 Department of Physics Applied to Aeronautical and Naval Engineering, Technical University of Madrid—
Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain; [email protected]
* Correspondence: [email protected]; Tel.: +34‐91‐0676046

Abstract: The additive manufacturing of metals has emerged as a revolutionary technology for fabricating high‐complexity components. However, this technique presents unique challenges related to the structural integrity and final strength of the produced parts due to inherent defects such as porosity, cracks, and geometric deviations. These defects significantly impact the fatigue life of the material by acting as stress concentrators that accelerate failure under cyclic loading. This paper presents a simplified finite element method combined with a statistical approach to model the presence of porosity in metal components produced by additive manufacturing. The proposed model considers a two‐dimensional square plate subjected to tensile stress, with randomly introduced defects characterized by their size, shape, and orientation. The mechanical properties of the finite elements are adjusted under the percentage of porosity affecting each element. A series of simulations were conducted, resulting in the generation of multiple models with random defect distributions, to estimate the maximum stress values. This approach demonstrates that complex models are not always necessary for a preliminary practical estimation of the effects of new manufacturing techniques. Furthermore, it demonstrates the potential for the extension of frugal computational techniques, which aim to minimize computational and experimental costs, to the field of engineering. Finally, in addition to existing limitations to the study carried out, future research directions are
discussed in the last part of the paper, particularly those relating to potential business applications, including commercial uses.

Keywords: Additive Manufacturing; Porosity; Defects; Finite Element Methods; Fatigue Life; Frugal Computational Techniques.