virtual institute i s - hzg · virtual institute improving performance and productivity of integral...
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IPSUSDr. Jorge F. dos Santos
GKSS - Forschungszentrum, Geesthacht
Institute of Materials Research
WMP – Solid State Joining Processes
Virtual Institute
Improving Performance and Productivity
of Integral Structures through
Fundamental Understanding of
Metallurgical Reactions in Metallic Joints
FSWProcesses
Materials AlLi / AlMgSc ODS Steels
Knowledge
Gap
Viscous flow and
diffusion processes in
high speed FSW and
joining by forming
Precipitation
Phenomena in
FSW of Al and Mg
Alloys
Methodology Process Simulation
Material Flow Visualisation
by Computer Tomography
In-Situ monitoring of metallurgical phenomena
using synchrotron-based diffraction techniques
Phase analysis with TEM X-Ray Diffraction
Mechanical TestingMicrostructure Analysis
Coextrusion
Artificial
Neural Networks
6060 / AZ31
Methodology for improved
productivity in high speed FSW
and hybrid extrusion profiles
Methods & procedures for
microstructure control of FSW in
Al, Mg and advanced steels
Methodology and hardware for in-situ monitoring of
metallurgical phenomena using synchrotron-based
diffraction techniques
Guidelines for design of
Al and Mg alloys with
superior weldability
Demonstrator: hybrid
extrusion profile / high speed
FSW welded component
Improved productivity in
high speed FSW and
hybrid extruded profiles
Recrystallisation
Kinetics in FSW of
Al and Mg Alloys
Phase
transformation
in FSW of steels
TWIP Steels
Motivation
Strategic Research Topics
1. In-situ synchrotron-based diffraction techniques
2. Non-Equilibrium Precipitation and Recrystallisation
Phenomena in Metallic Joints
AlLi Alloy (2198-T8)
AlMgSc
Automotive: 6082 (6181), 5457
3. Phase Transformation and Phase Formation in FSW of
Advanced Steels
Twinning Induced Plasticity Steels (TWIP)
Oxide Dispersion Strengthened Steels (ODS)
4. Coextrusion of Hybrid Al-Mg Profiles
5. FSW Process Modelling for High Production Rates
6. Artificial Neural Network
Objectives
1. To develop the methodology and hardware for in-situ
monitoring of non-equilibrium metallurgical phenomena using
synchrotron-based diffraction techniques,
2. To describe the kinetics and phenomena of precipitation and
recrystallisation in FSW and coextrusion of Al and Mg alloys
3. To describe the kinetics of phase transformation and
formation and their influence of the joint properties of friction
stir welded TWIP and ODS steels
4. To develop the methodology for coextrusion of hybrid Al-Mg
profiles
5. To develop a FSW process model for high production rates
6. To implement the use of artificial neural networks to establish
a generalised computer model for process-properties
relationships
Further Aims
1. To disseminate the work in VI-IPSUS to the public to develop and hence
establish a Centre of Expertise for In-Situ Monitoring of Physical
Phenomena in Production Processes as a medium to long-term
perspective.
2. Qualification of Post-Docs (by assigning the responsibilities of
technical work and organisation alongside of the respective experts
from HGF centres and universities)
3. Training of young scientists by dedicated trainee programmes by
adequate combination of sub-tasks to be conducted at both HGF-
centres and universities
4. Acquisition of third party funding by using the network of expertise
developed via the VI-IPSUS and hence offering a team of experts for
solving complex industrial problems.
5. Dissemination of scientific results in workshops, conferences,
publications etc. and hence contributing for enhancement of existing
scientific knowledge in the fields of the covered areas by the VI-IPSUS.
Results of analysis and testing of “as welded” an coextruded samples
(Post-mortem Results)
In-situ Diffraction
Experiments
WP2
Assembly and Commissioning of
the In-situ Experimental Equipment
WP2
Preliminary In-situ
Experiments
WP2
Processes
FSW and Coextrusion
WP1
Artificial Neural
Network
WP6
Process
Modelling
WP5
Recrystallisation and
Precipitation
WP3
Phase
Transformation
WP4
Microstructural
Analysis
WP3/WP4
Mechanical
Testing
WP1
Flow
Visualisation
WP1
Ex-situ X-Ray
Diffraction
WP4
Expertise Centre for
In-situ Monitoring of
Physical Phenomena in
Production Processes
Deliverables
and
Achievements
Work Programme: General Strategy
WP1 – Processes and Characterisation (GKSS)
Task 1.1 – Development of FSW Process Parameters
(GKSS, RUB, MPIE, FZK)
Task 1.2 – Development of Coextrusion Parameters
(TUB, GKSS)
Task 1.3 – Mechanical Testing (GKSS; MPIE; FZK)
WP2 – In-Situ Diffraction Experiments (GKSS)
Task 2.1 – Design and Fabrication of the FlexiStir
Unit (GKSS)
Task 2.2 – Installation and Commissioning of the
Experimental Set-Up (GKSS)
Task 2.3 – In-Situ Diffraction Experiments (GKSS;
TUB, MPIE, FZK)
WP3 – Precipitation and Recrystallisation (TUB)
Task 3.1 – Analysis of In-Situ Diffraction and
Tomography Experiments (TUB, GKSS)
Task 3.2 – Coextrusion Model (TUB, CU)
Task 3.3 – Microstructure Analysis (RUB, TUB,
GKSS)
Task 3.4 – Analysis of Precipitation and
Recrystallisation in Coextrusion (TUB,
GKSS, RUB)
Task 3.5 – Precipitation and Recrystallisation
Phenomena in FSW (GKSS, RUB)
WP4 – Processes Deformation Mechanisms and
Phase Transformations in Steels (RUB)
Task 4.1 – Development of FSW Process
Parameters (MPIE, FZK, GKSS)
Task 4.2 – Tomography Experiments on Similar and
Dissimilar Steel Joints Parameters
(GKSS, MPIE, FZK, CU)
Task 4.3 – Microstructure Analysis (RUB, MPIE,
FZK)
WP5 – Processes Modelling (CU)
Task 5.1 – Optimisation of the Existing FSW Model
to Higher Welding Speeds (CU)
Task 5.2 – Material Flow Experiments (GKSS; FZK,
MPIE, CU)
Task 5.3 – Application of the Model to Steels (CU)
Task 5.4 – Validation of the new Model (CU,
GKSS,MPIE, FZK)
WP6 – Artificial Neural Networks (GKSS)
Task 6.1 – Gathering of Experimental Data (GKSS,
CU)
Task 6.2 – Modelling Data with Neural Network
(GKSS)
Task 6.3 – Validation of the Model (GKSS, CU RUB)
WP7 – Management
Work Programme: General Strategy
WP1 – Processes and Characterisation
- Material procurement
- ODS: FZK
- TWIP: MPIE
- Al and Mg Alloys: GKSS
- Al / Mg Profiles (coextrusion): TUB
- Base material characterisation
- Study on the welding metallurgy of the selected base materials
- Gleeble Experiments
- Initial development of FSW process parameters (GKSS Gantry + Fixed Gap Bobbin Tool)
- Development of FSW Process Parameters with the FlexiStir
- Welding of specimens for material flow visualisation
- Welding of specimens for microstructural analysis and mechanical testing
- Development of Coextrusion Procedures for similar (Al/Al and Mg/Mg) and dissimilar
configurations
- Development of high speed FSW procedures for Al and Mg alloys
- Welding of specimens for material flow visualisation, microstructural analysis and
mechanical testing
- High temperature testing (input data for modelling)
Work Programme: Detailed Activities
Work Programme: Detailed Activities
FSW with a fixed gap bobbin tool
WP2 – In-Situ Diffraction Experiments
- Design and Manufacturing of the FlexiStir Unit
- Commissioning of the FlexiStir Unit at GKSS/WMP
- Installation and Commissioning of the experimental set-up for in-situ diffraction experiments
at DESY
- Performing in-situ diffraction experiments
- Processing of acquired data
Work Programme: Detailed Activities
WP3 – Precipitation and Recrystallisation
- Microstructural analysis of base material (base material characterisation), Gleeble samples,
welded specimens and coextruded samples (post-mortem analysis) – Al and Mg alloys
- Analysis of the in-situ diffraction experiments
- Analysis of the -computer tomography
- Correlation of the in-situ experiments with post-mortem analysis (FSW)
- Correlation of the ex-situ experiments with post-mortem analysis (Coextrusion)
- Formulation of the precipitation and recrystallisation phenomena in FSW (Al and Mg alloys)
Work Programme: Detailed Activities
WP4 – Processes Deformation Mechanisms and Phase Transformations in Steels
- Development of FSW Process Parameters (GKSS-Gantry and fixed gap bobbin tool)
- Development of FSW Process Parameters with the FlexiStir
- Welding of specimens for material flow visualisation
- Welding of specimens for microstructural analysis and mechanical testing
- Tomography Experiments on Similar and Dissimilar Steel Joints Parameters
- Microstructure Analysis
WP5 – Processes Modelling
- Optimisation of the Existing FSW Model to Higher Welding Speeds
- Material Flow Experiments
- Application of the Model to Steels
- Validation of the new Model
WP6 – Artificial Neural Networks
- Gathering of Experimental Data
- Modelling Data with Neural Network
- Validation of the Model
WP1 – Processes and Characterisation
C.W. Olea (GKSS)
WP2 – In-Situ Diffraction Experiments
Dr. R. Martins (GKSS)
WP3 – Precipitation and Recrystallisation
B. Camin (TUB)
WP4 – Processes Deformation Mechanisms and Phase Transformations in
Steels
Dr. Christoph Somsen, RUB
WP5 – Processes Modelling
Dr. P. Colegrove
WP6 – Artificial Neural Networks
R. Zettler
WP7 – Management
G. Amancio
Work Programme: WP Leaders
Work Programme: Time Schedule
Year 1 Year 2 Year 3
Activities Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
WP1 Process Task 1.1 Develop. of FSW Procedures
Task 1.2 Develop. of Coextrusion Pro Task 1.3 Mechanical Testing
WP2 In-Situ Diffraction Experiments
Task 2.1 Design and Fabrication of the FlexStir unit
Task 2.2 Installation and Commissioning of the Exp. Setup
Task 2.3 In-situ Diffraction Experim.
WP3 Precipitation and Recrystallisation
Task 3.1 In-situ Diffraction and Tomography Experiments
Task 3.2 Coextrusion Model Task 3.3 Microstructure Analysis Task 3.4 Precipitation and Recrystallisation in Coextrusio n
Task 3.5 Precipitation and
Recrystallisation in FSW
WP4 Deformation Mechanisms and Phase Transformations
Task 4.1 Ex-situ Diffraction
Experiments on Similar and Dissimilar Steel Joints
Task 4.2 Tomography Experiments on Joints of Similar and Dissimilar Steel Joints
Task 4.3 Microstructure Analysis
Milestone Description Date
1 Development FSW concluded Month 3
2 Development of Coextrusion Month 12
3 FlexStir Availability Month 9
4 Begin In-Situ Diffraction Experiments Month 13
5 Optimised FSW Process Model Month 12
6 Modell Neural Network Month 6
WP5 Process Modelling Task 5.1 Optimisation of the Existing Model to Higher Welding Speeds
Task 5.2 Material Flow Experiments Task 5.3 Application of the Model to Steels
Task 5.4 Validation of the New Model
WP6 Artificial Neural Network Task 6.1 Gathering of Experimental Data
Task 6.2 Modelling Data with Neural Network
Task 6.3 Validation of the Model WP7 Management Task 7.1 Coordination and
Management of the Research
Task 7.2 Promotion of Young Scientists
Task 7.3 Dissemination Activities REPORTING PROJECT MEETINGS
6 Month Progress Report 12 Month Project Report
Year 1 Year 2 Year 3
Activities Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4
Work Programme: Time Schedule
Deliverable (D) / Milestone (M) Due date
Development of FSW procedures concluded (M) Month 3
Weldability Report (D) Month 6
FlexiStir availability (M) Month 9
WP1
Development of Coextrusion procedures concluded (M) Month 12
Methodology and hardware for in-situ monitoring of non-equilibrium metallurgical phenomena in productionprocesses using synchrotron based diffraction technique (D)
Month 12WP2
Begin in-situ diffraction experiments (M) Month 13
Procedure and interlayer selection for coextrusion of hybrid Al-Mg profiles (D)
Process model describing thermo-mechanical phenomena in coextrusion of hybrid Al-Mg profiles (D)
WP3
Time resolved description of precipitation and recrystallisation kinetics in FSW of Al and Mg alloys as well as indissimilar joints (D)
WP4 Time resolved description of phase formation and transformation in FSW of advanced steels and dissimilar jointsthereof (D)
Literature review (D) Month 6
Optimised FSW process model (M) Month 12
Process model describing thermo-mechanical phenomena in high speed FSW, which will support the selection ofstrategy and parameters for high productivity FSW (D)
Month 24
WP5
Process model for FSW of steel materials (D) Month 36
Model Artificial Neural Network (M) Month 6WP6
Artificial neural network for the dete rmination of op timal parameters based on experimentally determined complexprocess-properties relationship. (D)
Month 36
Deliverables and Milestones
Technology Demonstrators
1. coextruded hybrid Al-Mg profile
2. high speed friction stir welded tailored blanks
3. dissimilar Al-TWIP and Mg-TWIP steel joints
4. dissimilar ODS-Steel based joints