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Meeting NUMIFORM 2019: The 13th International Conference on Numerical Methods in Industrial Forming Processes
Symposium NUMIFORM Plenary Session
Presentation Title Plasticity Models for Predictive Additive Manufacturing Process Simulations
Author(s) Victor Oancea, Tyler London, Madie Alen, Qi Zhang, Yangzhan Yang, Jing Bi
On-Site Speaker (Planned) Victor Oancea
Abstract Scope Numerical methods are sought to provide insight into the process and help accelerate progress in raising the quality of AM parts, including predicting thermal evolutions, part distortions and residual stresses, melt pool sizes, metallurgical phase transformations and defects. Micro-mechanics inspired phenomenological anisotropic plasticity models are often the critical ingredient in order to obtain accurate predictions for manufacturing induced stresses and deformations of 3D-printed parts. In this presentation we highlight some of the authors’ successes and remaining challenges on the topic. A customizable general simulation finite element-based framework for a wide spectrum of additive manufacturing processes based on a thermal-stress in a general purpose finite element code (Physics Apps from DASSAULT SYSTEMES – Abaqus-based) was previously introduced [1] and is only briefly reviewed. In general, for manufacturing process simulations, one accounts for the temperature-dependent plasticity behavior of the material under consideration [2]. We present our findings with modelling metal-based laser Powder Bed Fusion and Direct Energy Deposition and discuss the influence importance of the temperature-dependence on the yield behavior vs. (typically) orthotropic plasticity on the calculated residual stress field. Based on a generic framework [3] for assessing metallurgical phase transformations, building on the general simulation framework mentioned above, we discuss the connection between solid phase transformations and mechanical properties. Experimental work was conducted to validate numerical predictions and included temperature measurements and EBSD/XRD microstructural examinations. Metallurgical phase transformations and an empirically-driven plasticity model for predicting mechanical properties are used for comparisons between experiments and numerical predictions [4] suggesting that such modeling techniques, with minimal calibration efforts, can be used to link processing conditions to microstructural features and strength behavior of printed parts. Extensive comparisons with experimental test data are summarized for validated predictive workflows. [1] V. Oancea, J. Hurtado, and T. London, “A Customizable General Framework for Additive Manufacturing Process Simulation”, Simulation for Additive Manufacturing 11th –13th October 2017 Munich, Germany. [2] S. Simunovic, A. Nycz, M. Noakes, C. Chin, and V. Oancea, “Metal Big Area Additive Manufacturing: Process Modeling and Validation”, NAFEMS World Congress 2017, June 11-14 2017, Stockholm, Sweden. [3] Q. Zhang, J. Xie, Z. Gao, T. London, D. Griffiths, V. Oancea, “A Metallurgical phase transformation framework applied to SLM additive manufacturing processes”, Materials and Design 166 (2019) 107618 [4] Q. Zhang, J. Xie, T. London, D. Griffiths, I. Bhamji, V. Oancea, “Estimates of the mechanical properties of laser powder bed fusion Ti-6Al-4V parts using finite element models”, Materials and Design 169 (2019) 107678
Proceedings Inclusion? Definite: At-meeting proceedings


Continuum Description of Anisotropic Flow and Hardening Based on Lower Scale
Numerical Methods to Design Complex Process Chains in Sheet-bulk Metal Forming
Plasticity Models for Predictive Additive Manufacturing Process Simulations
The Automotive Industry’s Perspective on Advances and Challenges in Sheet Metal Forming
Third Generation Steels – Material Characterizations and Modeling for Accurate Numerical Simulations
Toughness, Roughness and the Possibility of Microstructure Design for Improved Crack Growth Resistance

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