This document summarizes a study that used finite element model updating (FEMU) to identify Swift law parameters for DP600 steel. Synthetic images and digital image correlation (DIC) were used to generate virtual experimental strain fields. Two identification approaches were compared: direct comparison of FEA results to reference data, and using DIC-levelled FEA data. The DIC-levelled approach improved identification accuracy, achieving near-zero error for the parameters, but required significantly more computational time than the direct comparison approach. The authors conclude the DIC-levelled FEMU method shows promise for identifying parameters of more complex constitutive models in future work.
Parameter Identification of Swift law using a FEMU-based approach and an inno...vformxsteels
ESAFORM 2022
M. Conde1, J. Henriques1,
S. Coppieters2, A. Andrade-Campos1
1 TEMA, Department of Mechanical Engineering, University of Aveiro, Portugal
2 Department of Materials Engineering, Ghent Technology Campus, KU Leuven, Belgium
Parameter Identification of Swift law using a FEMU-based approach and an inno...vformxsteels
ESAFORM 2022
M. Conde1, J. Henriques1,
S. Coppieters2, A. Andrade-Campos1
1 TEMA, Department of Mechanical Engineering, University of Aveiro, Portugal
2 Department of Materials Engineering, Ghent Technology Campus, KU Leuven, Belgium
Identification of orthotropic elastic properties of wood by a synthetic image...Vform Xsteels
This work aims to identify orthotropic linear elastic constitutive parameters of Pinus pinaster Ait. wood through the Finite Element Model Updating (FEMU) methodology. The approach is validated using both FE and synthetic image data. In the latter, digital image correlation is carried out on synthetic images deformed according to a 2D FE model. A systematic comparison is carried out. The identifiability for the four orthotropic material parameters on the radial-tangential (RT) plane is discussed regarding robustness and relative errors.
Identification of orthotropic elastic properties of wood by a synthetic image...Vform Xsteels
This work aims to identify orthotropic linear elastic constitutive parameters of Pinus pinaster Ait. wood through the Finite Element Model Updating (FEMU) methodology. The approach is validated using both FE and synthetic image data. In the latter, digital image correlation is carried out on synthetic images deformed according to a 2D FE model. A systematic comparison is carried out. The identifiability for the four orthotropic material parameters on the radial-tangential (RT) plane is discussed regarding robustness and relative errors.
Recommendation engine and uncertainty techniques for the efficient calibratio...Vform Xsteels
Nowadays, digitalisation and virtualisation are the keys for companies’ success and competitiveness. Thus, numerical simulation tools are essential for engineering analysis and development. The success of a simulated material behaviour prediction depends on the chosen complex constitutive model and the correctness of its parameter identification. These days, it is used several classical mechanical tests to identify the model’s parameters.
Virtual materials testing: come funziona e i benefici sulla produzioneCompositi
Webinar 29 settembre 2020
Connettendo il mondo reale con il virtuale, il processo di sviluppo di virtual materials testing permette di accelerare i tempi e ridurre i costi della filiera.
Parameter Identification of Swift law using a FEMU-based approach and an inno...vformxsteels
ESAFORM 2022
M. Conde1, J. Henriques1,
S. Coppieters2, A. Andrade-Campos1
1 TEMA, Department of Mechanical Engineering, University of Aveiro, Portugal
2 Department of Materials Engineering, Ghent Technology Campus, KU Leuven, Belgium
Parameter Identification of Swift law using a FEMU-based approach and an inno...vformxsteels
ESAFORM 2022
M. Conde1, J. Henriques1,
S. Coppieters2, A. Andrade-Campos1
1 TEMA, Department of Mechanical Engineering, University of Aveiro, Portugal
2 Department of Materials Engineering, Ghent Technology Campus, KU Leuven, Belgium
Identification of orthotropic elastic properties of wood by a synthetic image...Vform Xsteels
This work aims to identify orthotropic linear elastic constitutive parameters of Pinus pinaster Ait. wood through the Finite Element Model Updating (FEMU) methodology. The approach is validated using both FE and synthetic image data. In the latter, digital image correlation is carried out on synthetic images deformed according to a 2D FE model. A systematic comparison is carried out. The identifiability for the four orthotropic material parameters on the radial-tangential (RT) plane is discussed regarding robustness and relative errors.
Identification of orthotropic elastic properties of wood by a synthetic image...Vform Xsteels
This work aims to identify orthotropic linear elastic constitutive parameters of Pinus pinaster Ait. wood through the Finite Element Model Updating (FEMU) methodology. The approach is validated using both FE and synthetic image data. In the latter, digital image correlation is carried out on synthetic images deformed according to a 2D FE model. A systematic comparison is carried out. The identifiability for the four orthotropic material parameters on the radial-tangential (RT) plane is discussed regarding robustness and relative errors.
Recommendation engine and uncertainty techniques for the efficient calibratio...Vform Xsteels
Nowadays, digitalisation and virtualisation are the keys for companies’ success and competitiveness. Thus, numerical simulation tools are essential for engineering analysis and development. The success of a simulated material behaviour prediction depends on the chosen complex constitutive model and the correctness of its parameter identification. These days, it is used several classical mechanical tests to identify the model’s parameters.
Virtual materials testing: come funziona e i benefici sulla produzioneCompositi
Webinar 29 settembre 2020
Connettendo il mondo reale con il virtuale, il processo di sviluppo di virtual materials testing permette di accelerare i tempi e ridurre i costi della filiera.
eMDC 2017 Reath Weber Device Scaling v Process Control ScalingKimberly Daich
Device Scaling vs. Process Control Scaling: Advanced Sensorization Closes the Gap. A presentation by Mark Reath at Global Foundries and Alan Weber of Cimetrix Inc.
On the power of virtual experimentation in MT2.0: a VFORM-xSteels outlookvformxsteels
Sam Coppieters, A. Gil Andrade-Campos et al.
MatchID Global User Meeting
On the power of virtual experimentation in MT2.0 : a VFORM outlook
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Identification of orthotropic elastic properties of wood by digital image cor...Vform Xsteels
Wood and wood-based products have been gathering relevance across the globe due to policies of sustainability and green economy. Wood can be modelled as a hierarchical material. Despite the mechanical characterization of several major species at the macro and structural scales, information addressing material properties at the mesoscale of the annual growth rings is still very scarce in the literature.
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Plastics manufacturing can be unpredictable. Deviations in material batches, moisture content, machine calibration, among other variables, lead to issues in manufacturing quality and final part properties.
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Finite Element Analysis of PVC window profile &aluminium window profile with ...IJERA Editor
Examine a thermal analysis .Numerous analogies exist between thermal and structuralanalysis for PVC window
profile &aluminium window profile with and without thermalbreak ,Finite Element Analysis, commonly called
FEA, is a method of numerical analysis. FEA isused for solving problems in many engineering disciplines such
as machine design,acoustics, electromagnetism, soil mechanics, fluid dynamics, and many others.
Inmathematical terms, FEA is a numerical technique used for solving field problemsdescribed by a set of partial
differential equations. In mechanical engineering, FEA iswidely used for solving structural, vibration, and
thermal problems. However, FEA is notthe only available tool of numerical analysis. Other numerical methods
include the FiniteDifference Method, the Boundary Element Method, and the Finite Volumes Method tomention
just a few. However, due to its versatility and numerical efficiency, FEA has cometo dominate the engineering
analysis software market, while other methods have beenrelegated to niche applications. When implemented
into modern commercial software,both FEA theory and numerical problem formulation become completely
transparent tousers.
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Index Terms—Area overhead, data recovery, error detection, reliability, residue-and-quotient (RQ) code, Xilinx ISE
On the topology design of an innovative heterogeneous mechanical test for mat...vformxsteels
RS 2022
On the topology design of an innovative
heterogeneous mechanical test for material
mechanical characterization
Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, University of Aveiro,
Portugal
Univ. Bretagne Sud, UMR CNRS 6027, IRDL, F-56100 Lorient, France
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On the topology design of an innovative heterogeneous mechanical test for mat...vformxsteels
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Mafalda Gonçalves, Sandrine Thuillier, António Andrade-Campos
Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, University of Aveiro,
Portugal
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Mafalda Gonçalves, Sandrine Thuillier, António Andrade-Campos
1
A nonlinear topology-based optimization approach for the design of a heteroge...vformxsteels
TechMA 2022
Mafalda Gonçalves, Sandrine Thuillier, António Andrade-Campos
Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro, Portugal
Univ. Bretagne Sud, UMR CNRS 6027, IRDL, F-56100 Lorient, France
A nonlinear topology-based optimization approach for the design of a heteroge...vformxsteels
TechMA 2022
Mafalda Gonçalves, Sandrine Thuillier, António Andrade-Campos
Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro, Portugal
Univ. Bretagne Sud, UMR CNRS 6027, IRDL, F-56100 Lorient, France
Robust Algorithm Development for Application of Pinch Analysis on HENIJERA Editor
Since its genesis, Pinch Analysis is continuously evolving and its application is widening, reaching new horizons. The original concept of pinch approach was quite clear and, because of flexibility of this approach, innumerable applications have been developed in the industry. Consequently, a designer gets thoroughly muddled among these flexibilities. Hence, there was a need for a rigorous and robust model which could guide the optimisation engineer on deciding the applicability of the pinch approach and direct sequential step of procedure in predefined workflow, so that the precision of approach is ensured. Exploring the various options of a novice hands-on algorithm development that can be coded and interfaced with GUI and keeping in mind the difficulties faced by designers, an effort was made to formulate a new algorithm for the optimisation activity. As such, the work aims at easing out application hurdles and providing hands-on information to the Developer for use during preparation of new application tools. This paper presents a new algorithm, the application which ensures the Developer does not violate basic pinch rules. To achieve this, intermittent check gates are provided in the algorithm, which eliminate violation of predefined basic pinch rules, design philosophy, and Engineering Standards and ensure that constraints are adequately considered. On the other side, its sequential instruction to develop the pinch analysis and reiteration promises Maximum Energy Recovery (MER).
Identification of anisotropic yield functions using an information-rich tensi...vformxsteels
Yi Zhang1, António Andrade-Campos2, Sam Coppieters1
1 Department of Materials Engineering, KU Leuven
2 Department of Mechanical Engineering, University of Aveiro, 3810-193
Aveiro, Portugal
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into modern commercial software,both FEA theory and numerical problem formulation become completely
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IDENTIFICATION OF SWIFT LAW PARAMETERS USING FEMU BY A SYNTHETIC IMAGE DIC-BASED APPROACH
1. IDENTIFICATION OF SWIFT LAW PARAMETERS USING
FEMU BY A SYNTHETIC IMAGE DIC-BASED APPROACH
J. Henriquesa,*, M. Condea, A. Andrade-Camposa, J. Xavierb
*Corresponding author: joaodiogofh@ua.pt
aTEMA, Department of Mechanical Engineering, University of Aveiro, Campus Universitário de Santiago,
3810-193 Aveiro, Portugal
bUNIDEMI, Department of Mechanical and Industrial Engineering, NOVA School of Science and Technology,
NOVA University Lisbon, 2829-516 Caparica, Portugal
25th International Conference on Material Forming
Braga, Portugal, 27-29 April 2022
2. 2
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
Finite element model
updating technique
4
Material and numerical
model
2 Synthetic images and
digital image correlation
3
Results and discussion
5 Conclusions
6
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
3. Conclusions
6
Results and discussion
5
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
Finite element model
updating technique
4
2 Synthetic images and
digital image correlation
3
Material and numerical
model
3
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
4. 4
Motivation and goals
1
CAE Systems Manufacturing processes
- Reduced costs;
- Reduced time-waste;
- Increased quality.
Why?
▪ Computer-aided engineering systems play a key role in the simulation of
manufacturing processes.
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
5. 5
Motivation and goals
1
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
▪ Given the recent advancements in image-based technology, there has been an
increase in the use of novel optical methodologies.
- Full-field measurements
coupled to inverse identification
methods and heterogeneous
testing.
- Reducing the number of
experimental tests required to
identify material parameters.
6. 6
Motivation and goals
1
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
▪ The goal of this work is to identify the Swift hardening law parameters of the
DP600, using two approaches:
(i) Directly comparing the reference
with the FEA results;
(ii) Using DIC-levelled FEA data in the
comparison with the reference;
7. Conclusions
6
Results and discussion
5
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
Finite element model
updating technique
4
2 Synthetic images and
digital image correlation
3
Material and numerical
model
7
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
8. 8
Material and numerical model
2
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
- The material used in this study is the DP600 steel;
- FEA under plane stress conditions using ABAQUS;
- Mesh is composed by 858 four-node plane stress
elements (CPS4R);
- The material behaviour is modelled using the
UMMDp[1].
[1] H. Takizawa, T. Kuwabara, K. Oide, and J. Yoshida. Development of the subroutine library ‘UMMDp’ for anisotropic
yield functions commonly applicable to commercial FEM codes. Journal of Physics: Conference Series, 734:032028, 2016.
9. 9
Material and numerical model
2
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
The constitutive model chosen assumes the following considerations:
▪ Isotropic linear elastic behaviour according to
Hooke’s Law;
▪ Isotropic hardening described by Swift law;
▪ Anisotropic behaviour described by Yld2000-2d
criterion[2].
[2] F. Barlat et. al. Plane stress yield function for aluminum alloy sheets—part 1: theory. International Journal of Plasticity,
19: 1297-1319, 2003.
10. [3] F. Ozturk, S. Toros, and S. Kilic. Effects of anisotropic
yield functions on prediction of forming limit diagrams of
dp600 advanced high strength steel. Procedia
Engineering, 81:760–765, 2014.
10
Material and numerical model
2
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Hooke’s Law
E (GPa) ν
210 0.3
Yld2000-2d criterion
α1 α2 α3 α4 α5 α6 α7 α8 α
1.011 0.964 1.191 0.995 1.011 1.018 0.977 0.935 6
Swift Law
K [MPa] ε0 n
979.46 5.35×10-3 0.194
Reference parameters considered for the DP600 steel[3,4]:
[4] M. G. Oliveira, S. Thuillier, and A. Andrade-Campos.
Analysis of heterogeneous tests for sheet metal mechanical
behavior. Procedia Manufacturing, 47:831–838, 2020.
11. Conclusions
6
Results and discussion
5
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
Finite element model
updating technique
4
2 Synthetic images and
digital image correlation
3
Material and numerical
model
11
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
12. 12
Synthetic images and digital image correlation
3
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Reference image with FE mesh
Reference
synthetic image
Set of deformed
synthetic images
13. 13
Synthetic images and digital image correlation
3
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
2D DIC settings
Correlation criterion: ZNSSD
Interpolation: Bicubic spline
Shape function: Quadratic
Subset size: 21 px
Step Size: 5 px
Image pre-filtering: Gaussian, 5 px kernel
Strain window size: 11
Strain interpolation: Bilinear Q4
Strain convention: Green-Lagrange
Displacement noise-floor: 0.009 px
Strain noise-floor: 1.246×10-4
Hardware settings
Camera: Flir Blackfly BFS-U3-51S5M-C
Focal length: 12.5 mm
Image resolution: 2448×2048 px2
Camera noise: 0.48% of range
Working distance: 251 mm
Image conversion factor: 0.05039 mm/px
Speckle pattern: Numerically generated
Average speckle size: 3 px
14. Conclusions
6
Results and discussion
5
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
Finite element model
updating technique
4
2 Synthetic images and
digital image correlation
3
Material and numerical
model
14
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
15. 15
Finite element model updating technique
4
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Time steps
Measurement points
Optimization method:
• Levenberg-Marquardt algorithm.
K [MPa] ε0 n
Lower bound 500.00 1.00×10-6 1.00×10-6
Upper bound 1500.00 1.00×10-2 4.00×10-1
16. 16
Finite element model updating technique
4
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Generation of the reference virtual experimental strain fields and load data.
17. 17
Finite element model updating technique
4
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Direct comparison (FEA Methodology) Virtual experiment (VE Methodology)
18. Conclusions
6
Results and discussion
5
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
Finite element model
updating technique
4
2 Synthetic images and
digital image correlation
3
Material and numerical
model
18
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
19. 19
Results and discussion
5
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
K [MPa] ε0 n CF
FEA methodology
Run 2 – CPU time: 36 minutes (1.06 rel. time)
Identified parameters 968.83 3.80×10-3 1.87×10-1 1.57×10-4
Relative error [%] 1.09 28.48 3.81 -
VE methodology
Run 2 – CPU time: 287 minutes (8.44 rel. time)
Identified parameters 979.15 5.34×10-3 1.94×10-1 1.68×10-8
Relative error [%] 0.03 0.16 0.00 -
20. 20
Results and discussion
5
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
21. Conclusions
6
Results and discussion
5
Time steps
Measurement points
Optimization method:
- Levenberg-Marquardt algorithm.
Finite element model
updating technique
4
2 Synthetic images and
digital image correlation
3
Material and numerical
model
21
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
Outline
CAE Systems Manufacturing processes
Motivation and goals
1
22. 22
Conclusions
6
J. Henriques, M. Conde, A. Andrade-Campos, J. Xavier - ESAFORM 2022 Conference, April 2022, Braga, Portugal
▪ This study compared the identification results for the swift hardening law by
using the traditional FEMU approach and by using a DIC-levelling approach.
▪ The results show a significant improvement in the identification accuracy
when using the DIC-levelled FEA data at the expense of increased
computational time.
▪ In future work, the VE methodology can be used to identify the constitutive
parameters of more complex constitutive models.
23. THANK YOU!
J. Henriquesa,*, M. Condea, A. Andrade-Camposa, J. Xavierb
* joaodiogofh@ua.pt
25th International Conference on Material Forming
Braga, Portugal, 27-29 April 2022
This project has received funding from the Research Fund for Coal and Steel under grant agreement No 888153.
The authors also gratefully acknowledge the financial support of the Portuguese Foundation for Science and
Technology (FCT) under the projects CENTRO-01-0145-FEDER-029713, POCI-01-0145 FEDER-031243 and
POCI-01-0145-FEDER-030592 by UE/FEDER through the programs CENTRO 2020 and COMPETE 2020, and
UIDB/00481/2020 and UIDP/00481/2020-FCT under CENTRO-01-0145-FEDER-022083. Authors also
acknowledge Fundação para a Ciência e a Tecnologia (FCT - MCTES) for its financial support via the projects
UIDB/00667/2020 (UNIDEMI). J. Henriques is also grateful to the FCT for the PhD grant 2021.05692.BD.
Acknowledgements
