Embed Size (px)
Citation preview
ADVANCED NUMERICAL
AND PHYSICAL SIMULATION
OF THE RING ROLLING PROCESS
S. Andrietti1, J.-L. Chenot1,2, P. Lasne1,
1 Transvalor SA, France 2 CEMEF - Mines ParisTech, France
AeroMat’2014 – S. Andrietti et al. 1
Outline
• Introduction
• Thermo-mechanical model & FE resolution
• Examples of numerical simulation with FORGE®
• Metallurgical aspects
• Conclusions
2 AeroMat’2014 – S. Andrietti et al.
Introduction • Applications of ring rolling in many industrial fields:
– Aerospace
– Automotive
– Nuclear
– Railroad, Oil & Gas
– Wind Power
• Sophisticated process:
– Due to kinematics
– Several independent rolls
– Accurate piloting is crucial
3 AeroMat’2014 – S. Andrietti et al.
Industrial issues
• Rolling mill piloting
• Process instabilities : ring climbing phenomenon, offset
• Workpiece properties : effective strain and grain flow
• Prevent defects : underfilling, folds, fishtail, …
• Prediction of the microstructure
=> Virtual factory from ingot to final ring.
4 AeroMat’2014 – S. Andrietti et al.
• Introduction
• Thermo-mechanical model & FE resolution
• Examples of numerical simulation with FORGE®
• Metallurgical aspects
• Conclusions
5 AeroMat’2014 – S. Andrietti et al.
• Constitutive equations
– Elasto-viscoplastic:
– Elasticity:
– Viscoplasticity:
Example of power law:
6
e p th
( ) (3 2 ) 2e e e e e eJdtrace T I
dt
0
2' ( , , )
3
p
T
1
' 2 ( , ) 3m
pK T
AeroMat’2014 – S. Andrietti et al.
• Friction modeling:
– Example « Coulomb viscoplastic »:
• Thermal coupling
7
1 fp
f n v v
( ( )) : 0pdTc div kgrad T r
dt
AeroMat’2014 – S. Andrietti et al.
8
• Time discretization:
– Time increments t for non-stationary processes
– Implicit formulation for the mechanical equilibrium at each
time step
• Finite element discretization:
– Use of P1+/P1 linear tetrahedral elements
– Unknows : Velocity (v) , Pressure (p) , Temperature (T)
• Equation solving:
– Iterative method for non-linear system
– Solver supports high parallel computing (up to 64 cores)
AeroMat’2014 – S. Andrietti et al.
• Arbitrary Lagrangian Eulerian (ALE) formulation:
– Use of a structured mesh with refinement in angular
sectors
– Next trends : dual-mesh technique, self-adaptive
remeshing
9 AeroMat’2014 – S. Andrietti et al.
10
• Introduction
• Thermo-mechanical model & FE resolution
• Examples of numerical simulation with FORGE®
• Metallurgical aspects
• Conclusions
Aeromat’2014 – S. Andrietti et al.
Typical industrial example
11 AeroMat’2014 – S. Andrietti et al.
Typical defect prediction
12 AeroMat’2014 – S. Andrietti et al.
Underfilling defect
Fishtail defect
Cou
rte
sy o
f M
ura
ro S
pa
Grain flow prediction
13 AeroMat’2014 – S. Andrietti et al.
Rolling mill piloting
• Ring centering :
– Use of force-driven (or torque) guide rolls
– Keep the ring’s centroid along X-axis by applying a
scalar constraint
• Piloting mode :
– « conventional » : displacements of mandrel & axial rolls
are set based on pre-defined rolling curves
– « innovative » : coupling with real-time process data 14 AeroMat’2014 – S. Andrietti et al.
15
Conventional piloting
King roll : constant rotation speed
Mandrel & axial rolls : automatic rotation speed
Standard rolling curves :
• Ring Growth Speed vs Outer Diameter
• Ring Height vs Thickness
AeroMat’2014 – S. Andrietti et al.
Ring thickness
Rin
g h
eig
ht
Conventional piloting - Results
AeroMat’2014 – S. Andrietti et al.
17
Innovative piloting
Collaborative work with Muraro Spa (Italy)
Displacements of rolls & cones are function of time
according to the real evolution of the ring’s parameters
• Diameter – Thickness – Height
• Linear velocity - Rotation speed
• Force - Torque
AeroMat’2014 – S. Andrietti et al.
General principle of the external piloting
18
Innovative piloting - Results
AeroMat’2014 – S. Andrietti et al.
Stainless steel bearing ring
Courtesy of Muraro Spa
19
Innovative piloting – Results
AeroMat’2014 – S. Andrietti et al.
Courtesy of Muraro Spa
20
• Introduction
• Thermo-mechanical model & FE resolution
• Examples of numerical simulation with FORGE®
• Metallurgical aspects
• Conclusions
Aeromat’2014 – S. Andrietti et al.
Heat treatment capabilities
21 AeroMat’2014 – S. Andrietti et al.
• Various heat treatment operations can be simulated:
– Austenitization, carburizing, nitriding
– Quenching, tempering
– Induction heating, induction hardening
• Standard outputs:
– Phase transformation (for steel), dimensional variations
– Final hardness & residual stress
• Example:
– Water+Polymer quenching of a steel ring
22 AeroMat’2014 – S. Andrietti et al.
AISI 4140 Steel - HTC conditions
Vickers hardness distribution vs Experimental measurements
Co
urt
esy
of
Fris
a Fo
rjad
os
Quenching - Results
23
Microstructure evolution
JMAK semi-empirical approach for recristallization
AeroMat’2014 – S. Andrietti et al.
Dynamic : nucleation and growth during
deformation
Meta-dynamic : nucleation during
deformation and growth after deformation
Static : nucleation and growth after
deformation
For given constant conditions
Material data for recristallization
• Low carbon steel : SAE 1035, …
• Austenitic stainless steels : 316L, …
• Ni steels / Mn steels / Cr steels
• Ni-Cr-Mo / Mn-Cr / Cr-Mo / Mn-Si steels (SAE 9310, SAE 5120, SAE 4140, SAE 1536, …)
• Nickel based alloy : Inconel718, Waspaloy
• Or User data
24 AeroMat’2014 – S. Andrietti et al.
AeroMat’2014 – S. Andrietti et al. 25
Recristallization during ring rolling
Grain size evolution with sensors Strain & Strain rate vs Time
Average grain size evolution
26 Aeromat’2014 – S. Andrietti et al.
Nu
cle
atio
n a
nd
Gro
wth
From Macroscale …
27 Aeromat’2014 – S. Andrietti et al.
… to Mesoscale modeling
28 Aeromat’2014 – S. Andrietti et al.
29
Recristallization model – Full field approach
AeroMat’2014 – S. Andrietti et al.
Adaptive anisotropic mesh
Representative Volume Element
Modelling of grain growth (left) and static recrystallization (right) in 304L austenitic stainless steel
Conclusions
• Numerical simulations of complex ring rolling process
providing reliable results (final shape, grain flow,
defects, strain-temperature-stress-hardness, …)
• An innovative & efficient new piloting method to
reproduce the industrial practice
• Intensive work for final microstructure prediction using
mesoscale modeling
• Perspectives : use multi-objective optimization engine
applicable to any sort of process design
30 Aeromat’2014 – S. Andrietti et al.
THANK YOU FOR YOUR ATTENTION
Stéphane Andrietti Director of Software Production Department
Transvalor SA
Email : [email protected]
Web site : www.transvalor.com
AeroMat’2014 – S. Andrietti et al. 31
Patrice Lasne Expert Engineering Department
Transvalor SA
Email : [email protected]
Web site : www.transvalor.com
Professor Jean-Loup Chenot Transvalor Scientific Director
Email : [email protected]
www.transvalor.com
www.cemef.mines-paristech.fr
