5. Plasticity and Fracture Prediction Under Nonlinear Loading

Transcription

1 5. Plasticity and Fracture Prediction Under Nonlinear Loading Wing Kam Liu, Walter P. Murphy Professor, Northwestern University President of the International Association for Computational Mechanics Past Chair of National Committee on Theoretical & Applied Mechanics of US National Academies Member of the Board of International Scientific Organizations of US National Academies Member of Center for Hierarchical Materials Design (CHiMaD) Member of Northwestern Initiative on Manufacturing Science and Innovation (NIMSI) Project PIs: Wing Kam Liu a, Greg Wagner a, Jian Cao a, Brad Kinsey b, Marko Knezevic b, Amine Benzerga c a Northwestern University b University of New Hampshire c Texas A&M

2 5. Plasticity and Fracture Prediction Executive Summary: Objective/Industrial Need: The capability of quickly predicting macroscale properties based on microstructure evolution Approach: Data-driven multiscale modeling using reduced order Self-consistent Clustering Analysis (SCA) [1000x faster in 3D sim.] Deliverable: Experimentally-validated simulation tools Budget and Timeline: $500K for 3 years; supports 3 RAs (micro/meso-scale modeling, meso/macro-scale modeling, experimental characterization) NSF I/UCRC Planning Meeting Slide 2

3 Industrial Needs and Relevance: Plasticity and fracture lead to failure of metallic material during processing and service High-fidelity simulation tools can: Predict part s behavior under nonlinear loading Improve understanding of material s properties Reduce number of experiments and cost Double-side Incremental Forming Simulation Malhotra, R., Xue, L., Belytschko, T. and Cao, J., 2012, Mechanics of Fracture in Single Point Incremental Forming, Journal of Materials Processing Technology, Vol. 212 (1), pp NSF I/UCRC Planning Meeting Slide 3

4 Plasticity and Fracture Prediction Under Nonlinear Deformation Paths Industrial Needs and Relevance: Save development time and less iteration in product and process design (a) Strain reversal in a punching process (b) Edge crack of Advanced High- Strength Steel sheets (c) Forming to crash simulation in car bodies (a) (b) (c) NSF I/UCRC Planning Meeting Slide 4

5 Project Objectives: Develop data compression and data analysis methods to accelerate computations Combine data processing techniques and multiscale simulation methods to establish a data-driven multiscale simulation framework Use such framework to reduce computational cost while keeping accuracy in modeling Extend this framework to plasticity and fracture prediction Under this common goal, the project objectives include, but are not limited to: 1. Simulate different metal forming processes 2. Predict macroscale properties based on microstructure evolution 3. Increase computational efficiency by data-driven multiscale modeling Plastic Strain CP SCA picture Vernerey, Liu and Moran, Multiscale Micromorphic Theory for Hierarchical Materials, JMPS, 2007 Vernerey, Liu, et al., A Micromorphic Model for the Multiple Scale Failure of Heterogeneous Materials, JMPS, McVeigh & Liu, Multiresolution modeling of ductile reinforced brittle composites. JMPS, Tian & Liu et al., A Multiresolution Continuum Simulation of the Ductile Fracture Process, JMPS, NSF I/UCRC Planning Meeting Slide 5

6 Approach/Methodologies: The group has many technologies ready to use or in development stage. Selected technologies are listed below: a) Multiresolution Continuum Theory (MCT) b) Self-consistent Clustering Analysis (SCA) c) Experiments for fracture calibration NSF I/UCRC Planning Meeting Slide 6

7 Multi-resolution Continuum Theory Too expensive to model microstructure explicitly Captures size effects Mesh independent Low computational cost Captures only one scale Cannot capture size effects Mesh dependent Low computational cost Captures multiple scales of localization Captures size effects Mesh independent NSF I/UCRC Planning Meeting Slide 7

8 Reduce Order Modeling by SCA Offline or training stage (SCA) Reduced order model 2-Dimension 1) Domain decomposition (k-means clustering): find material clusters. Strain concentration tensor is used for characterizing the responses. 2) Compute the interaction tensors based on Green s function FEM 3D- 16 clusters 1420 s 16 clusters: 1 s 256 clusters 20 s 3-Dimension Online or predictive stage (SCA) Self-consistent clustering analysis based on Lippman-Schwinger equation. 2D- 16 clusters Computational time drastically reduced O. Goury, D. Amsallem, SP. Bordas, WK. Liu, P. Kerfriden, Automatised selection of load paths to construct reduced-order models in computational damage micromechanics: from dissipation-driven random selection to Bayesian optimization, Comput Mech (2016) Z. Liu, MA. Bessa, WK. Liu, Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials, Comput. Methods Appl. Mech. Engrg. (2016) Z. Liu, JA Moore, WK Liu, An Extended Micromechanics Method for Probing Interphase Properties in Polymer Nanocomposites, Journal of the Mechanics and Physics of Solids, 2016, NSF I/UCRC Planning Meeting FEM 25.7 hours on 24 CPUs 16 clusters: 2 s 256 clusters 50 s Slide 8

9 Numerical modeling of ductile fracture mechanisms Remeshing algorithm Large plastic strain Ductile matrix Void growth & coalescence Composite with brittle particles Cracks modeled with Level-Sets & remeshing Plastic localization and void coalescence Particle debonding & fragmentation Loading condition: Forming Shakoor, M. "Three-dimensional numerical modeling of ductile fracture mechanisms at the microscale". PhD thesis, Mines ParisTech, NSF I/UCRC Planning Meeting Slide 9

10 Concurrent Simulation Based On SCA Same microscale SCA database is used for materials with hard and soft inclusions The SCA reduced order module is implemented as a VUMAT in ABAQUS under 2D plane strain condition. Microscale model (SCA) NSF I/UCRC Planning Meeting Slide 10

11 Evolution of The Macroscale Effective Plastic Strain Field NSF I/UCRC Planning Meeting Slide 11

12 Damage Parameter Comparison: 1-step vs. 3-step homogenization One-step homogenization elastoplastic material without damage Three-step homogenization

13 SCA Concurrent simulation: Damage evolutions (Hard Inclusions) Point 1: Damage field Point 2: Damage field Point 1: Mises stress field Point 2: Mises stress field Hard inclusions help to carry the load and increase the overall stiffness. The damage initiation is sensitive to the shear loading.

14 Relation to A/SP Projects Numerical models developed here can be used as numerical experiments to simulate loading paths that are impossible or hard to obtain in physical tests Provide more realistic deformation mechanisms at the microstructure level Use microstructure and fracture data already generated from A/SP projects as a starting point to build up and validate the multi-scale model NSF I/UCRC Planning Meeting Slide 14

15 Experimental Characterization Microstructure characterization Tests for determining fracture models In-situ damage evolution using ANL facilities Proposed testing efforts under monotonic and multiaxial loadings Most tests can be done in one universal testing machine. NSF I/UCRC Planning Meeting Slide 15

16 5. Plasticity and Fracture Prediction Under Nonlinear Loading Deliverables: An experimentally-verified computational platform for evaluating fracture and material damage of advanced materials while incorporating micromechanical effects with macrostructural models. A multiscale software interface and integration tool for fracture prediction in existing commercial CAE tools (e.g., ABAQUS, LS- DYNA), with documentation Training and consulting services for new software interface. NSF I/UCRC Planning Meeting Slide 16

17 5. Plasticity and Fracture Prediction Under Nonlinear Deformation Paths Budget and Timeline: Estimated cost of the project is $500K for three years, including 3RAs and experimentation cost. Task / Milestone Material characterization Multi-scale theory Tool integration Model validation and Doc Year 1 Year 2 Year 3 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 NSF I/UCRC Planning Meeting Slide 17

18 5. Plasticity and Fracture Prediction Under Nonlinear Loading Discussions: Are the industrial need and relevance accurately captured? Are the objectives realistic and complete? Are the approaches technically sound and appropriate? Are there alternative implementation paths or better approaches? Are the deliverables impactful to industrial partners? Are the budget and timeline reasonable? Are there conflicts with intellectual property or trade secrets? List additional project specific questions are appropriate. NSF I/UCRC Planning Meeting Slide 18