Presentations by CMML members at USNCCM Austin
Our research group will give 5 presentations at the 15th US National Congress on Computational Mechanics in Austin. The schedule and topics of the presentations are listed below:
2019-07-29
| Minisymposium | #208 Data Assimilation in Model Order Reduction Techniques for Computational Mechanics |
| Authors | Jie Hou * ,Jun Li ,Alfa Heryudono ,Wenzhen Huang ,Jing Bi |
| Location | Room # 202 – LVL 2 |
Additive manufacturing (AM) has revolutionized the making of engineering products and relevant standards/methodologies. With more freedom in design space, one can create more design variants in geometry and material distributions. During AM process, part distortions and material defects may also lead to geometry and materials variations. Finite element analysis (FEA) is a powerful tool for physics-based high-fidelity simulations while may be time- consuming. A data-driven approach using Machine Learning has the promise to rapidly predict reliable results for real-time design evaluation and AM process quality control with improved decision-making capability. Two examples were investigated in this study: the first one considers the stress field predictions of a 3D cuboid model with varying sizes subjected to bending; the second one predicts the strain field of a 2D panel under uniaxial tension with a material defect varied in location and sizes. The model order reduction techniques of both POD (Proper Orthogonal Decomposition) and PGD (Proper Generalized Decomposition) are studied for the two examples. They both enable the representation of full FEA stress/strain field outputs with much less number of variables at an acceptable accuracy.
| Minisymposium | #803 Modeling and Simulation of Additive Manufacturing Processes |
| Authors | Osama Aljarrah * ,Wenzhen Huang ,Jun Li ,Alfa Heryudono ,Jing Bi |
| Location | Room # 301 – LVL 3 |
This paper proposes a novel integrated inductive approach for predicting and optimizing the additive manufacturing process parameters. The integrated scheme consists of three popular algorithms: (1) group method for data handling (GMDH) as the engine of neural networks, (2) autoregressive integrated moving average (ARIMA) for characterizing spatial collinearity of residual stresses in multiple layers, and (3) indirect optimization method by self-organization (IOSO) to adopt the emerged multi-response correlated optimization problem. As a numerical case study: A computer-generated fused deposition modeling (FDM) simulation data tested the introduced algorithms. The FE models consist the multi-layer residual stresses as targets, with respect to printing speeds as process parameters. The residual stresses predicted by the low order ARIMA-GMDH variant correlate well with the cuboid FE simulations. The printing speeds and their experimental simulation results were submitted into four analytical stages: the initial phase, transient phase, steady-state phase, and terminal phase, where each stage was analyzed through a low order integrated ARIMA-GMDH variants. The results in predicted output found to have a high correlation with the simulated values. This approach provides a viable alternative for computationally-based rapid prototyping and additive manufacturing processes. Limitations of the techniques were discussed.
2019-07-31
| Minisymposium | #802 Modeling and Simulation for Additive Manufacturing |
| Authors | Jun Li * |
| Location | Room # 205 – LVL 2 |
Additive manufacturing (or 3D printing) is being increasingly used in a wide range of areas including aerospace, mechanical, civil and biomedical engineering where it offers significant advantages for model prototyping. However, the reduced fracture performance often observed in 3D printed materials limits its application to end-user load-bearing components. A combination of computational and experimental investigation is performed to study 3D printed materials with various build orientations for enhanced fracture properties, including single edge notched tension (SENT) and bending (SENB) specimens made of acrylonitrile-butadiene-styrene (ABS) polymers by fused filament fabrication. The measured fracture properties were found to highly depend on layer/filament orientations and crack kinking was observed to often follow the weak planes along those directions. The extended finite element method (XFEM) using cohesive zone approach with anisotropic damage initiation and evolution criteria has been developed to capture the results measured in experiments. Numerical parametric studies further show that the inter-layer and inter-filament bonding strength could be tuned to create alternate crack paths for maximum fracture energy. Finally, toughening mechanisms using 3D printed topological patterns on the surface to deflect crack paths are explored. This study sheds light on predicting fracture of 3D printed materials for enhanced performance.
| Minisymposium | #802 Modeling and Simulation for Additive Manufacturing |
| Authors | Prosenjit Biswas * ,Sofiane Guessasma ,Jun Li |
| Location | Room # 205 – LVL 2 |
The mechanical property of 3D printed components often shows anisotropic behavior and strong dependence on printing orientations and process parameters. In this presentation, various computational models are developed using the representative volume element (RVE) to investigate the orthotropic elastic properties of 3D printed ABS polymers. Two finite element (FE) models, based on Micro-CT or periodic CAD geometry, with different raster angles, 0/90, 45/-45, 30/-30, and 60/-60 among layers are considered in this study. The Micro-CT model used the realistic geometry of a 3D printed cube reconstructed from Micro-CT scans. The periodic CAD model was specified according to the dimensional statistics from the Micro-CT model, including inter and intra layer porosity, bond width, layer height and filament width. All models are subjected to six independent load cases of macroscopically uniform boundary conditions (kinematic and mixed-orthogonal) admitted by Hill-Mandel condition to obtain full orthotropic elastic stiffness matrix. In addition, the size-dependent bounds from those BCs for periodic CAD model were investigated and verified with periodic BC. More anisotropy was found in the periodic CAD model than in the Micro-CT model. The numerical results are consistent with experiments and able to capture the dependence on raster angles. Finally, parametric studies were performed by varying the filament shapes, bond width, layer height and porosity to investigate the effect of those parameters in the determination of effective mechanical properties.
| Minisymposium | #601 Computational Mechanics for Performance and Damage of Materials |
| Authors | Rojin Ghandriz * ,Jun Li |
| Location | Room # 202 – LVL 2 |
Additive manufacturing (or 3D printing) is coming of age as a viable advanced manufacturing technology that is already serving a substantial impact on a wide variety of subdivisions, from biomedical, electronics, automotive to aerospace industries. However, the reduced fracture resistance often observed in 3D printed materials limits its application to functional components. The fracture of 3D printed polymer materials with various layer orientations and surface patterns is studied using the extended finite element method (XFEM) and phase filed fracture method (PFFM) implemented in finite element software ABAQUS [1,2]. The XFEM with cohesive segment approach is employed to model the inter-laminar fracture (fracture between layers), cross-laminar fracture (fracture through layers), as well as mixed inter-/cross- laminar fracture of 3D printed specimens made of acrylonitrile-butadiene-styrene (ABS) materials. Both elastic and elastic-plastic fracture models are developed for the inter-laminar and cross-laminar fracture, respectively. For mixed inter-/cross- laminar fracture, an anisotropic damage model is developed to predict the kinked crack propagations. The model was implemented through user-defined damage initiation subroutines with ABAQUS/XFEM to capture fracture behaviors under various layer orientations. Furthermore, various 3D printed surface patterns are studied to enhance the fracture resistance. A robust PFFM is developed to predict the complicated crack deflections in 3D printed samples with patterned surfaces. 1. J. Li, S. Yang, D. Li, V. Chalivendra. Numerical and experimental studies of additively manufactured polymers for enhanced fracture properties. Engineering Fracture Mechanics, 204 (2018) 557–569. 2. M.A. Msekh, J.M. Sargado, M. Jamshidian, P.M. Areias, T. Rabczuk. Abaqus implementation of phase-field model for brittle fracture. Computational Materials Science 96(2015) 472484.