ADVANCED NUMERICAL AND PHYSICAL SIMULATION OF THE RING ROLLING PROCESS

Transcription

1 ADVANCED NUMERICAL AND PHYSICAL SIMULATION OF THE RING ROLLING PROCESS S. Andrietti 1, J.-L. Chenot 1,2, P. Lasne 1, 1 Transvalor SA, France 2 CEMEF - Mines ParisTech, France 1

2 Outline Introduction Thermo-mechanical model & FE resolution Examples of numerical simulation with FORGE Metallurgical aspects Conclusions 2

3 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

4 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

5 Introduction Thermo-mechanical model & FE resolution Examples of numerical simulation with FORGE Metallurgical aspects Conclusions 5

6 Constitutive equations Elasto-viscoplastic: e p th Elasticity: Viscoplasticity: d J e trace( e ) (3 e 2 e ) T I 2 e e dt p 2 ' 0(,, T ) 3 Example of power law: m 1 ' 2 K(, T) 3 p 6

7 Friction modeling: Example «Coulomb viscoplastic»: Thermal coupling 1 p f f n v v dt p c div( kgrad( T )) r : 0 dt 7

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) 8

9 Arbitrary Lagrangian Eulerian (ALE) formulation: Use of a structured mesh with refinement in angular sectors Next trends : dual-mesh technique, self-adaptive remeshing 9

10 Introduction Thermo-mechanical model & FE resolution Examples of numerical simulation with FORGE Metallurgical aspects Conclusions Aeromat 2014 S. Andrietti et al. 10

11 Typical industrial example 11

12 Typical defect prediction Courtesy of Muraro Spa Fishtail defect Underfilling defect 12

13 Grain flow prediction 13

14 Ring centering : Rolling mill piloting 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

15 Ring height 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 Ring thickness 15

16 Conventional piloting - Results

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 General principle of the external piloting 17

18 Innovative piloting - Results Stainless steel bearing ring Courtesy of Muraro Spa 18

19 Innovative piloting Results Courtesy of Muraro Spa 19

20 Introduction Thermo-mechanical model & FE resolution Examples of numerical simulation with FORGE Metallurgical aspects Conclusions Aeromat 2014 S. Andrietti et al. 20

21 Heat treatment capabilities 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 21

22 Courtesy of Frisa Forjados Quenching - Results AISI 4140 Steel - HTC conditions Vickers hardness distribution vs Experimental measurements 22

23 Microstructure evolution JMAK semi-empirical approach for recristallization 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 23

24 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

25 Recristallization during ring rolling Grain size evolution with sensors Strain & Strain rate vs Time 25

26 Nucleation and Growth Average grain size evolution Aeromat 2014 S. Andrietti et al. 26

27 From Macroscale Aeromat 2014 S. Andrietti et al. 27

28 to Mesoscale modeling Aeromat 2014 S. Andrietti et al. 28

29 Recristallization model Full field approach Representative Volume Element Adaptive anisotropic mesh Modelling of grain growth (left) and static recrystallization (right) in 304L austenitic stainless steel 29

30 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 Aeromat 2014 S. Andrietti et al. 30

31 THANK YOU FOR YOUR ATTENTION Stéphane Andrietti Director of Software Production Department Professor Jean-Loup Chenot Transvalor Scientific Director Patrice Lasne Expert Engineering Department Transvalor SA stephane.andrietti@transvalor.com Web site : jean-loup.chenot@mines-paristech.fr Transvalor SA patrice.lasne@transvalor.com Web site : 31