Bainite and second-phase engineering for improved formability (BaseForm) : final report.
Date: 2021-01-18
Institutions: Directorate-General for Research and Innovation
Subjects: applied research, innovation, iron and steel product, metalworking, research report, steel, technological process

Bainite and second-phase 
engineering for improved 
formability 
(BaseForm)

EUR 30536 EN 

EUR [25330] EN 

 
 
 
 
 
Bainite and second-phase engineering for improved formability (BaseForm) 
European Commission 
Directorate-General for Research and Innovation 
Directorate D – Clean Planet 
Unit D.3 — Low Emission Future Industries 
Contact   Andrea Gentili 
E-mail  

rtd-steel-coal@ec.europa.eu 
RTD-PUBLICATIONS@ec.europa.eu 

European Commission 
B-1049 Brussels 

Manuscript completed in 2019. 

This  document  has  been  prepared  for  the  European  Commission  however  it  reflects  the  views  only  of  the  authors,  and  the 
Commission cannot be held responsible for any use which may be made of the information contained therein. 

More information on the European Union is available on the internet (http://europa.eu). 

Luxembourg: Publications Office of the European Union, 2020 

PDF  

ISBN 978-92-76-27841-2 

ISSN 1831-9424 

doi: 10.2777/1301 

KI-NA-30-536-EN-N 

© European Union, 2020. 
Reuse is authorised provided the source is acknowledged. The reuse policy of European Commission documents is regulated by 
Decision 2011/833/EU (OJ L 330, 14.12.2011, p. 39). 

For any use or reproduction of photos or other material that is not under the EU copyright, permission must be sought directly 
from the copyright holders. 
All pictures, figures and graphs © Materials Innovation Institute - M2i, RFSR-CT-2014-000017 BaseForm  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EUROPEAN COMMISSION 

Research Fund for Coal and Steel 

Bainite and second-phase 
engineering for improved 
formability 

(BaseForm) 

Or. ir. Viktoria Savran  
(Project coordinator) 

Materials Innovation Institute - M2i  

Van der Burghweg 1 - 2628 CS Delft - The Netherlands 

Grant Agreement RFSR-CT-2014-000017 

1/07/2014 to 30/06/2018 

Final Report 

2019                      Directorate-General for Research and Innovation                     EUR 30536 EN 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table of Contents 
Summary ............................................................................................................................................................ 5 
Introduction ....................................................................................................................................................... 5 
1.  Materials and experimental procedure ..................................................................................................... 7 
1.1.  Materials production ................................................................................................................................. 7 
Casting of laboratory steels/Material purity ....................................................................................... 7 
1.1.1. 
Hot rolling and cold rolling/ Laboratory set-up for hot/cold rolling ................................................... 8 
1.1.2. 
Dilatometry ....................................................................................................................................... 10 
1.1.2. 
Vatron Annealing Simulator .............................................................................................................. 11 
1.1.3. 
1.1.4. 
Experimental procedure and material analysis ................................................................................. 12 
Processing-microstructure relationship ................................................................................................... 15 
2. 
2.1.  Experimental ............................................................................................................................................ 15 
2.1.1. 
Isothermal bainite transformation kinetics ....................................................................................... 15 
2.1.2.  Microstructural evolution as a function of process parameters ....................................................... 16 
2.2.  Modeling (transformation models) ......................................................................................................... 27 
Extension of Azuma model ................................................................................................................ 27 
2.2.1. 
2.2.2. 
Iso-work flow curve model ................................................................................................................ 29 
2.3.  Conclusions .............................................................................................................................................. 31 
3.  Microstructure-properties relationship ................................................................................................... 33 
3.1.  Experimental ............................................................................................................................................ 33 
3.1.1.  Mechanical tests ............................................................................................................................... 33 
3.1.2.  Microstructural observations and properties relationship ............................................................... 39 
3.2.  Modeling .................................................................................................................................................. 42 
Additional information and production of specific microstructures for modeling ........................... 42 
3.2.1. 
3.2.2.  Mean field approach ......................................................................................................................... 44 
3.2.3. 
Crystal plasticity models .................................................................................................................... 47 
3.2.4.  Models integration (transformation models will be coupled to micro-mechanical and 

crystallography based models) ................................................................................................................ 52 
3.3.  Conclusions .............................................................................................................................................. 55 
4.  Damage .................................................................................................................................................... 57 
4.1.  Experimental ............................................................................................................................................ 57 
Crystallographically resolved damage initiation ............................................................................... 57 
4.1.1. 
4.1.2. 
Effect of topology on damage initiation ............................................................................................ 58 
4.2.  Modeling of damage ................................................................................................................................ 62 
4.3.  Conclusions .............................................................................................................................................. 64 
Final conclusions and guidelines .............................................................................................................. 65 
5. 
Conclusions ....................................................................................................................................... 65 
5.1.1. 
5.1.2. 
Guidelines.......................................................................................................................................... 67 
Exploitation and impact of the research results ...................................................................................... 69 
6. 
Actual applications ............................................................................................................................ 69 
6.1.1. 
Technical and economic potential for the use of the results ............................................................ 69 
6.1.2. 
Publications / conference presentations resulting from the project ................................................ 70 
6.1.3. 
Symposium “Nano and Micro Scale Damage in Metals” .................................................................. 71 
6.1.4. 

List of figures ................................................................................................................................................ 73 

List of tables ................................................................................................................................................. 79 

List of acronyms and abbreviations .............................................................................................................. 81 

List of references .......................................................................................................................................... 83 

Page 3 of 112 

 
 
Page 4 of 112 

 
 
Summary 

The goal of RFCS project BaseForm is to optimize the microstructures with a bainitic matrix in order 
to improve the cold formability and edge-cracking behaviour of advanced high-strength steels with 
high  yield  strength.  Two  alloy  compositions  (low  alloyed  low  carbon  alloys  with  low  and  high  Si 
content) were designed with the aim to produce cold-rolled annealed microstructures consisting of a 
bainitic  matrix  with  small  fraction  of  second-phase  constituents  (martensite  and/or  retained 
austenite). Systematic studies were performed first on the small dilatometer samples to identify the 
transformation  kinetics  and  heat  treatment  cylces  that  can  provide  necessary  varietions  in 
microstructures (chapter 1). In the second stage (chapters 2-5), the lab scale samples were produced 
and  extensive  mechanical  testing  program  was  applied  together  with  the  detailed  microstructural 
characterization.  The  focus  was  on  materials  in  the  cold  rolled  condition,  only  limited  amount  of 
testing was performed on the hot rolled material. In the last stage, defined optimal heat treatment 
cycles constrained by typical industrial process conditions of continuous annealing and galvanizing 
lines were performed (samples marked with CAL and CGL). Parallel to the extensive testing program, 
simulations  using  phase  transformation,  crystal  plasticity  and  mean  field  models  were  conducted. 
Attempt was made to link thermo-dynamic based transformation models with micro-mechanical and 
crystallography based models. Special attention was given to the material damage. All the collected 
data  were  used  to  generate  guidelines  for  the  production  of  this  kind  of  Advanced  High  Strength 
Steel  with  an  optimum  combination  of  strength,  elongation  and  other  forming  parameters,  in 
particular hole expansion. 

Introduction 

Despite a tremendous development in the past years, the potential of Advanced High-Strength Steels 
(AHSS)  is  not  yet  fully  explored.  Further  optimization  requires  a  systematic  approach  combining 
state-of-the-art experimental characterization and physically-based model simulations. A lot of work 
has been dedicated to the correlation between process parameters, bainite microstructure features 
and specific mechanical properties, but present models can only predict the bainite transformation 
kinetics during processing and not yet the microstructure morphology. Moreover, a microstructure 
based model to handle bainite mechanical behavior is still missing. In addition, very little attention 
has been paid to the impact of a low volume fraction of martensite or martensite/austenite islands 
in the bainitic matrix on the strength and formability. Nevertheless, recent internal results suggested 
that even a few percent of martensite can strongly affect the mechanical and damage properties of 
the bainitic steels.  

BaseForm project focusses on control and optimization of the very promising combination of steel 
phases: bainite, martensite and retained austenite. Bainite has since long been known to form a very 
beneficial,  very  fine  matrix  structure,  which  can  further  be  optimized  by  controlling  martensite 
inclusions  for  enhanced  strength  and  retained  austenite  for  enhanced  formability.  By  means  of 
experimental characterization and physical understanding of the evolution of microstructures and the 
relation between microstructures and mechanical properties, this project contributes significantly to 
the further development of this most promising class of Advanced High-Strength Steels. 

The  bainitic  steel  grades  with  second-phase  constituents  in  this  project  are  optimized  aiming  at 
automotive  applications,  requiring  an  increase  of  yield  (and  tensile)  strength  while  maintaining 
adequate press formability. The focus is on just two chemical compositions, varying only in silicon 
content to control carbide formation. This approach, contrary to scanning a broad composition range, 
allows developing profound insight into the evolution, morphology, stability and behavior of these 
microstructures.  The  role  of  non-equilibrium  phases  in  steel  microstructures  has  recently  gained 
renewed attention in research, more specifically with the newly developed Quenching & Partitioning 
process  exhibits  a  martensitic  matrix  with  embedded  retained  austenite  particles.  In  the  current 
project the microstructure matrix under study is bainitic, which is a constituent that allows better 
and  more  flexible  control  than  martensite  and  which  shows  an  improved  balance  of  strength  and 
ductility. The bainitic structure is enriched by both martensite and austenite for optimum properties. 

For  the  design  of  high  strength  bainitic  AHSS  with  high  elongation  and  hole  expansion,  detailed 
analysis  of  texture  and  microstructure,  its  formation  and  damage  mechanisms  are  fundamental. 
BaseForm  project  aims  to  give  detailed  analysis  of  these  properties  by  modern,  high  resolution 
techniques and its correlation to the mechanical properties. To the purpose of modeling the process-
microstructure  relations,  existing  knowledge  on  phase-transformation  (thermo-dynamically  based 
phase transformation models) are combined with micro-mechanical transformation models that allow 
simulating the texture of the cold-rolled product. Also, structure-property relations is addressed. In 
modeling the formability properties of the material, current crystal plasticity models are used, which 
may be derived from texture data and by which the yield locus of the metal sheet can be modeled. 
This allows obtaining a more solid relation between formability and texture. 

The  most  added  value  of  this  proposal  is  that  it  combines  the  results  obtained  by  microstructure 
analysis, forming and damage behavior in order to create basic guidelines for European steel industry 

Page 5 of 112 

 
to produce a high strength bainitic AHSS with high elongation and hole-expansion behavior under 
industrial constrictions. 

The project objectives are: 

• 

• 

• 

• 
• 

to  improve  the  understanding  of  the  process-microstructure  and  the  microstructure-
properties  relations,  in  particular,  what  are  the  preferred  fraction,  carbon  content, 
morphology  and  distribution  of  second-phase  constituents  (martensite  and/or  retained 
austenite) in bainitic matrix; 
to  integrate  physical  models  allowing  to  simulate  the  thermo-mechanical  process  and  the 
material performance in press forming operations; 
to understand the mechanical behavior of bainite can be extended to many industrial AHSS 
grades containing bainite; 
to understand the mechanisms of the damage process in these microstructures; 
to  develop  guidelines  for  producing  bainitic  AHSS  with  high  elongation  and  high  forming 
capacity (bending, hole expansion) which can be used to the design of new products (3rd 
Generation AHSS like carbide-free bainite alloys).   

Page 6 of 112 

1. Materials and experimental procedure 

At the start of the project two alloy compositions, LoSi and HiSi alloys, were designed with the aim 
to produce cold-rolled annealed microstructures consisting of a bainitic matrix with a small fraction 
of second-phase constituents (martensite and/or retained austenite). After casting of the ingots and 
the subsequent hot and cold rolling (at Tata Steel), the materials were shipped to thyssenkrupp Steel 
Europe  AG  (TKSE)  for  Vatron  annealing  experiments  which  were  based  on  dilatometry  tests 
performed by both partners.  

1.1. Materials production 

1.1.1.  Casting of laboratory steels/Material purity 

Alloys for cold rolled annealed substrates 

The  design  of  the  alloys  was  aimed  to  make  cold  rolled  and  annealed  laboratory  substrates  with 
strength levels comparable to those of advanced or ultra-high strength steels (> 950MPa). Moreover, 
it was decided to design two steels in such a way that both the low Si (LoSi) and the high Si (HiSi) 
alloys will deliver comparable strength levels for similar processing. This meant that the difference 
in Si needed to be counter-balanced by varying other alloying elements, e.g. Mn or Cr. 

Table 1 shows that the realized compositions of the ingots are in good agreement with the target 
compositions. It is worth mentioning that the alloy compositions were re-confirmed by the chemical 
analysis  of  the  hot  rolled  (HR)  material  conducted  by  TKSE.  This  analysis  shows  comparable 
compositions  as  measured  for  the  ingots;  the  small  differences  could  be  well  explained  by 
uncertainties in the measurement methods. It can, thus, be concluded that all ingots have adequate 
homogeneous chemical compositions and satisfy the target values as specified in the proposal. The 
levels of P, S and N are representative for the conventional production of steels in industry.   

Table 1. Chemical composition of the material as determined by Tata Steel and TKSE. 

Alloy 

amount 

C 

Mn 

Si 

Cr 

Al 

P 

S 

N 

Aim LoSi 

120 kg 

0.22 

2.00 

0.10 

0.60 

0.02 

0.008 

0.003 

0.004 

VS5510 

2 x 30 

0.22 

1.96 

0.10 

0.61 

0.020 

0.007 

0.0027 

0.005 

VS5511 

2 x 30 

0.21 

1.98 

0.10 

0.61 

0.025 

0.007 

0.0027 

0.007 

TKSE 238821 

0.22 

2.0 

0.11 

0.61 

0.020 

0.006 

0.002 

0.0053 

Aim HiSi 

120 kg 

0.22 

2.00 

1.30 

0.02 

0.008 

0.003 

0.004 

VS5508 

2 x 30 

0.21 

1.96 

1.24 

<0.005 

0.027 

0.007 

0.0026 

0.005 

VS5509 

2 x 30 

0.22 

2.00 

1.26 

<0.005 

0.026 

0.007 

0.0025 

0.005 

TKSE 238822 

0.21 

2.0 

1.27 

0.002 

0.026 

0.006 

0.002 

0.0051 

Alloys for hot rolled substrates (extra activity) 

In  2015  it  was  decided  to  design  a  new  steel  with  a  high  alloying  content  of  both  Si  and 
Cr since literature, patents and in-house data of AMMR indicated that such an alloy (CrSi) can deliver 
differentiated microstructure and properties as compared to the HiSi alloy. It is emphasized here that 
this  CrSi  alloy  with  target  composition  0.22C-2.00Mn-1.30Si-0.60Cr  has  only  been  produced  to 
assess  its  hot  rolled  properties  for  comparison  to  the  properties  of  LoSi  and  HiSi  after  equal  hot 
rolling simulations. Furthermore, a recalculation indicated that the material feedstock available for 
hot rolling of LoSi and HiSi was limited, and therefore it was decided to make new casts of LoSi and 
HiSi alloys. The compositions of these new ingots are shown in Table 2. 

Table 2. Chemical composition of high Cr high Si alloy as determined by Tata Steel. 

Alloy 

amount 

C 

Mn 

Si 

Cr 

Al 

P 

S 

N 

CrSi (15049) 

2 x 30 kg 

0.209 

1.99 

1.25 

0.63 

0.01 

0.009 

0.004 

0.005 

LoSi (15048) 

2 x 30 kg 

0.215 

2.00 

0.10 

0.62 

0.02 

0.009 

0.004 

0.005 

HiSi (15050) 

2 x 30 kg 

0.221 

2.03 

1.29 

0.01 

0.01 

0.009 

0.003 

0.005 

Page 7 of 112 

 
 
 
 
 
 
 
 
Determination of material purity 

The characteristics and classification of the non-metallic inclusions in the HiSi and LoSi alloys were 
evaluated using two different methods:  

−  According to DIN 50602 [1] light optical microscopy (LOM) was employed to analyze an area 
of  at  least  100mm²  to  measure  the  sizes  of  inclusions.  Four  main  groups  could  be 
distinguished  on  the  basis  of  their  shape:  sulphides  in  line  (SS),  oxides  in  solution  (OA), 
oxides in line (OS), and globular oxides (OG), see Table 19 and Table 20 in Appendix 1. 
−  The second method, the PSEM (Personal Scanning Electron Microscope) was carried out to 
analyse the distribution of inclusions and their chemical compositions, see Figure 78-Figure 
80 in Appendix 1. No alignment of the inclusions was found, also not at the sample surface. 
Based on these results it was concluded that the detected inclusions (types, sizes, number density 
and distribution) should not have influence on forming and damage parameters of LoSi and HiSi. 

1.1.2.  Hot rolling and cold rolling/ Laboratory set-up for hot/cold rolling  

Roughing and Hot rolling 

Figure  1  shows  a  schematic  of  the  hot  rolling  piloting  line  at  Tata  Steel  R&D  in  IJmuiden.  The 
temperature of the block/slab is monitored with pyrometers at various locations: entry & exit of the 
single stand mill, and entry & exit of the Run-Out-Table (ROT). The 30 kg ingots with a thickness of 
70 mm were reheated to a furnace temperature of 1250 ºC for half an  hour  and thereafter got a 
roughing mill step down to 40 or 30 mm thickness followed by cooling to room temperature.  

l
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p
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cooling table
cooling table

furnace
furnace

Tin
Tin

Tout
Tout

FRT:
FRT:
+/- 20ºC
+/- 20ºC

ROT-entry
ROT-entry

ROT-exit
ROT-exit

“Coiling”
“Coiling”

e
e
r
r
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t
t
a
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p
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ROT-exit:
ROT-exit:
+/- 30ºC
+/- 30ºC

Furnace:
Furnace:
+/- 5ºC
+/- 5ºC

~ 3 sec
~ 3 sec

cooling
cooling

~ 5 sec
~ 5 sec

time
time

Figure 1. Schematic of the laboratory set-up for hot rolling at Tata Steel in Ijmuiden. 

Then each roughed ingot was cut into blocks with lengths of 80-120 mm, which were subsequently 
reheated  to  a  furnace  temperature  of  1230  ºC  for  half  an  hour.  After  reheating  of  the  blocks  to 
1230ºC for half an hour, the blocks were manually de-scaled and cooled in air down to about 1150 
ºC.  Then the  hot rolling with the single stand mill started at about 1150 ºC. The blocks were  hot 
rolled  in  several  passes  to  their  aimed  final  thickness  with  a  finish  rolling  temperature  (FRT)  of 
approximately  880  ºC.  Then  the  hot  rolled  slabs  were  transported  to  the  Run-Out-Table  (ROT) 
simulator in which slabs were cooled with a cooling rate in the range of 20-25 ºC/s to arrive at a 
coiling  temperature  (CT)  of  about  630  ºC.  Thereafter,  the  slabs  were  put  in  the  furnace  and  a 
standard coiling simulation programme was applied which approximates the cooling rate of a 25 ton 
coil made in conventional industrial production; this effectively means an exponentially decreasing 
temperature and the total cooling time is about 20 hours. Due to this slow cooling the duration of 
holding at coiling temperature is several minutes. 

Production of HR material for dilatometry and PSC samples 

For this purpose, blocks were hot rolled via three passes from 30 to 15 mm thickness with the process 
parameters as described above, i.e with a coiling temperature of about 630 ºC. The materials were 

Page 8 of 112 

 
 
 
 
 
 
dispatched to AMMR and CEIT where samples were made for further investigations with respectively 
dilatometry, torsion and plain strain compression (PSC) tests.  

Production of the Cold Rolled material 

For producing colled rolled (CR) feedstock, the blocks were hot rolled in 6 steps from 40 to 4 mm 
thickness and the coiling simulation was at a temperature of 630 ºC. The hot rolled slabs were pickled 
and thereafter, cold rolled to a final thickness of 1 mm. These sheets were cut to appropriate sizes 
for annealing with the Vatron at TKSE (WP2 and WP5).  

Production of 3 mm Hot Rolled material 

The settings for hot rolling were determined on the basis of results obtained with dilatometry and 
torsion tests:  

-  2 aimed finish rolling temperatures (FRT): 860 and 940 ºC; 
- 
-  3 target coiling temperatures (CT): 390, 420 and 450 ºC.  

a fast cooling rate in the range of 70-110 ºC/s in the ROT simulator to retard ferrite;  

Hot  rolling  started  at  about  1170  ºC  and  the  blocks  were  hot  rolled  in  5  steps  from  30  to 
approximately 3 mm thickness. The reduction schedule was approximately 30 - 20 - 12 - 8 - 5 - 3. 
The realized hot rolling parameters are listed in Table 3.  

Table 3. Hot rolling parameters. 

Alloy 

FRT, ºC 

ROT  
entry, ºC 

Cooling 
rate, 
ºC/s 

ROT 
exit, ºC 

CT 
furnace, 
ºC 

LoSi 

HiSi 

CrSi 

925 

870 

930 

870 

940 

935 

860 

930 

855 

930 

940 

865 

935 

940 

970 

800 

760 

820 

800 

830 

810 

760 

820 

770 

810 

820 

760 

820 

830 

870 

95 

90 

100 

80 

75 

100 

80 

90 

75 

75 

100 

90 

80 

80 

110 

420 

415 

400 

470 

530 

380 

430 

450 

440 

500 

410 

400 

490 

490 

380 

390 

390 

420 

420 

450 

390 

390 

420 

420 

450 

390 

390 

420 

450 

450 

After the slow cooling down to room temperature, the slabs were pickled and, subsequently, cut to 
appropriate  sizes  for  various  mechanical  tests,  see Figure  2.  The  tensile geometry  was  chosen  as 
A25 (= conventional A50/2) since this allows testing also in the transverse direction. Furthermore, 
from each slab one micro sample of 100 mm x 20 mm and two HEC samples (90 mm x 90 mm) were 
cut  from  the  head  and  tail  of  the  slabs.  The  remaining  material,  if  any,  was  used  for  bending 
experiments. 

HEC-1 

30 x 80

A25-L1
A25-L2
A25-L3
A25-L4

1
T
-
5
2
A

2
T
-
5
2
A

3
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5
2
A

4
T
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A

0
0
1

x
0
2

HEC-2 

g
n
i
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n
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B

0
0
1

x
5
3

Figure 2. Schematic of a HR slab and samples for various tests. 

Page 9 of 112 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
 
 
 
 
 
1.1.2.  Dilatometry 

Determination of the general transformation behaviour  

Dilatometry tests to determine CCT and TTT were conducted using a Bähr dilatometer type DIL 805 
in  accordance  with  the  procedures  described  in  SEP  1680  [2].  To  obtain  various  bainitic 
microstructures thermal cycles (CAL TA,°C/ CR, °C/s /TOA,°C/tOA,s)  were performed on flat (colled 
rolled)  and  cylindrical  (hot  rolled)  samples.    Flat  dilatometer  specimen  with  a  dimension  of 
4mm*9mm*sheet thickness (Figure 3a) and cylindrical samples Ø 4mm x 10mm (Figure 3b) were 
produced by spark erosion.  

Ø 4±0,1 

a) 

b) 

10±0,1 

Figure 3. Dilatometer samples: a) flat, b) cylindrical. 

Dilatometer  samples  of  LoSi  and  HiSi  were  used  for  determination  Ac1  and  Ac3  (TKSE),  and  the 
martensite-start temperature (Ms). In these experiments the samples were heated with 2 ºC/s. The 
results together with calculated values are shown in Table 4. 

Table 4. Measured and calculated values of Ac1, Ac3 and Ms for LoSi and HiSi (°C). 

Designation 

Measured 
(Dilatometer) 

Calculated 
(ThermoCalc) 
[3] 

Calculated 
(empirical eq.) 

Calculated 
(empirical)  

[4], [5] 

[6] 

LoSi 

HiSi 

Ac1 

718 

715 

Ac3 

805 

881 

MS 

365 

370 

Ae1 

675 

682 

Ae3 

779 

820 

Ae1 

715 

739 

Ae3 

804 

853 

BS 

556 

569 

MS 

388 

378 

Determination of critical cooling rates and CCT diagrams 

In the dilatometry experiments for determination of the continuous-cooling-transformation (CCT)-
diagrams the samples were austenitized at 920 °C for 5 minutes. For LoSi alloy experiments were 
also  performed  with  a  lower  austenitization  temperature,  however,  no  significant  change  in  the 
transformation behaviour was observed. After austenitizing, the samples were cooled using hydrogen 
gas with cooling rates (CR) between 0.3-100 °C/s (t8/5 between 3 s and 1000 s). The microstructures 
of the as-annealed dilatometry samples were analysed using light optical metallography to determine 
the  fractions  of  ferrite  (F),  bainite  (B),  pearlite  (P)  and  martensite  (M).  The  measurement  of  the 
retained austenite was based on the XRD results. The residual austenite is incorporated in the other 
phases, mainly bainite and martensite. Therefore, the sum of M+B+P+F =100%. The phase fractions 
and the hardness values (HV10) are listed in Table 5.  

Table 5. Quantification of microstructures [vol.%] and hardness values of HiSi and LoSi samples for 
various cooling rates. MA: Martensite-Austenite; B: Bainite; P: Pearlite; F: Ferrite; RA: residual 
austenite; M+B+P+F=100%; RA is determined by X-Ray diffraction. 

Material 

Cooling rate, 
(°C/s) 

90 
30 
15 
10 
6 
3 
1,5 
1 
0,6 
0,3 
115 
30 
20 
15 
6 
3 
0,3 

LoSi 

HiSi 

Phase fraction (uncertainty is ~5%) 

MA  
100 
95 
70 
50 
30 
10 
5 
<5 
<5 
<5 
100 
70 
60 
30 
30 
10 
Bit 

B 
- 
5 
30 
45 
60 
55 
40 
45 
40 
35 
<5 
30 
35 
55 
45 
35 
10 

P 
- 
- 
- 
<5 
traces 
5 
10 
10 
15 
20 
- 
- 
- 
traces 
5 
15 
40 

F 
- 
- 
<5 
5 
10 
30 
45 
45 
45 
45 
<5 
<5 
5 
15 
20 
40 
50 

RA 
1,5 
2,5 
3 
3,5 
3,5 
2,5 
2 
2 
1,5 
1 
2,0 
6,5 
8,0 
8,5 
7,5 
6,0 
<1 

Hardness 
HV 10 

449 
436 
369 
322 
305 
277 
250 
254 
229 
222 
463 
392 
356 
337 
291 
245 
202 

Page 10 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
Critical cooling rates can be deduced from the data from Table 5. The evaluated CCT diagrams are 
shown  in  the  Appendix  2.  Furthermore,  the  determined  Time-Temperature-Transformation  (TTT) 
diagrams with cooling rates between austenitising and isothermal holding of ~130 K/s ( to avoid any 
ferrite and perlite formation) of both alloys can be found in the Appendix 2. To save time, the phase 
fractions and transformation kinetics here have been evaluated from dilatometry data with the Lever 
rule  applied  to  the  data  using  the  non-linear  equations  for  the  thermal  contraction  of  bcc  and  fcc 
lattices derived in Ref. [7], as described in Appendix 8. Fraction of bainite as a function of time during 
bainitic transformation for HiSi (a) and LoSi (b) in the temperature range 370 – 570 ºC are shown 
in Figure 4. 

Figure 4. Fraction of bainite as a function of time during bainitic transformation for HiSi (a) and 
LoSi (b) in the temperature range 370 – 570 ºC. 

1.1.3.  Vatron Annealing Simulator 

The  annealing  of  the  cold  rolled  material  (cold  reduction  of  75  %)  was  performed  on  a  Vatron 
Annealing Simulator at thyssenkrupp Steel Europe Ag. Compared to the above described dilatometer 
test, the equipment makes it possible to conduct annealing cycles on the used larger flat samples 
(110-115mm*450mm)  by  conductive  heating.  High  cooling  rates  (CR>70  °C/s)  were  achieved  by 
cooled  copper  sheets,  in  which  the  samples  were  clamped  during  cooling,  in  order  to  assure  a 
constant and fast cooling rate to the whole sample. Two different kind of annealing treatment were 
used,  see  Figure  5,  CAL  (continuous  annealing  line)  and  CGL  (continuous  galvanizing  line).  The 
Annealing and all folowing steps have been performed into two phases.  

Figure 5. Scheme of annealing performed annealing cycles, CAL (continuous annealing line) and 
CGL (continuous galvanizing line). 

Page 11 of 112 

 
 
 
 
 
 
 
Main differences of the two cycles are the shorter annealing time tA of the CGL, the limited overaging 
time tOA and the Zink-bath (T~460 °C). From now  on, the cycles will be named as follows: cycle 
TA,°C/CR,°C/s /TOA,°C/tOA,s , wheras TA is the annealing temperature, CR is the cooling rate, TOA 
is  the  overaging  temperature  (not  the  Zn-bath  temperature)  and  tOA  is  the  overaging  time.  For 
example, CGL 920 °C/50 °C/s/420 °C/120s means Continuous Galvanizing Line TA=920 °C, TOA=420 
°C tOA=120 s and CR=50 °C/s. If the line speed of the line is changed from 100 m/min to another 
one, it will be mentioned additionally. 

In  the  first  stage  of  the  project,  the  main  influencing  factors  to  develop  bainitic  steels  with  2ry-
phases  under  ideal  conditions  are  analyzed  (Table  7)  and,  in  the  second  stage,  these  results  and 
industrial restrictions (limited time, limited speed, limited cooling rates) are taken into account (Table 
8) for creating and performing new annealing cycles. 

1.1.4.  Experimental procedure and material analysis 

Optical microscopy 

The optical microscopy was applied to characterize the mesoscale structure of the sheets, in addition 
to  any  microstructural  heterogeneity  in  the  RD-ND  plane.  It  was  also  useful  to  know  if  the  non-
desirable ferrite formed along the process. In this line, different reagents were used: LePera, Nital 
1%,  Picral  4%,  Klemm  III  and  picric  acid  2%  dissolved  in  water  to  determine  their  different 
capabilities to reveal the microstructure features of interest. In general, LePera etching is the best 
option to characterize the mesoscale structure, whose main feature was the development of banding. 
LePera, Nital 1% and Picral 4% was used to detect the likely presence of ferrite in the microstructure. 
Klemm III  has  not been successful in any case and  was discarded from the earliest stages of the 
project for LOM characterization. Finally, picric acid 2% in water was suitable to measure the prior 
austenite grain size when applied to structures obtained through water quenching or overaging at 
390ºC for long times, typically 120s.   

SEM/ FEG-SEM 

Due to the fineness of the microstructure, SEM microscopy was discarded from the earliest stages of 
the project and FEG-SEM imaging was preferred to analyse the obtained complex microstructures. 
The HiSi and LoSi steels were etched differently. On the one hand, Klemm III etching was applied to 
the HiSi steel whereas, on the other hand, Picral 4%/LePera etchings were chosen for showing the 
microstructure of  the  LoSi  steel.  The  use  of  such  reagents  reveals  unambiguously  the 2ry  phases. 
The quantitative metallography carried out on those steels was based on the  acquisition of 10-15 
micrographs  per  location  at  ¼  and  ½  of  the  thickness  of  the  material  on  the  RD-ND  section  at  a 
magnification  of  x5000  to  X10000  in  a  JEOL  JSM  7100F  micrsoc.  After  Picral/LePera  etching,  SE 
imaging allows distinguishing in a much clearer manner the carbides and MA phase in LoSi steels. 
Instead, the HiSi steel did not show carbides, thus, only MA islands, film-like austenite and low-C 
martensite like features were measured in such specimens with the help of the BSE imaging after 
etching with Klemm III. Even though the methodology was robust in general, it was needed to tune 
the magnifications and/or to increase the number of images to be analysed to get more accurate and 
reliable  results  in  some  cases,  due  to  the  difference  in  the  size  of  the  2ry  phases  among  the 
specimens. The images were automatically processed for the characterization and quantification of 
MA phase/low-C martensite. However, some specimens showed a rather complex microstructure that 
needed to be reassessed more critically. In particular, the distinction of low-C martensite and  MA 
phase was difficult in the specimens overaged for intemediate times. In those cases, the comparison 
of the quantitative results and the visual inspection of the micrographs led to some mismatch. Thus, 
the  measurement  of  the  volume  fraction  of  the  phases  was  carried  out  through  a  preliminary 
detection  of  the  phases  and  subsequent  contouring  by  an  experienced  operator  (semi-automatic 
procedure). After this essential step, the rest of the image analysis was performed in the same way 
as for only automatic analysis. 

EPMA/WDS 

Electron  probe  microanalysis  (EPMA)  was  performed  with  a  JEOL  JXA  8900R®  using  an  electron 
beam with energy of 10 keV and current of 50 nA with step size of 0.5 µm employing Wavelength 
Dispersive  Spectroscopy  (WDS)  to  validate  the  presence  of  banding  phenomenon  within  the 
microstructure. The composition at each analysed location of the sample was determined using X-
ray  intensities of  constituent’s  elements  after  background  correction  relative  to  the  corresponding 
intensities  of  reference  samples.  The  obtained  intensity  ratios  were  processed  with  the  matrix 
correction program CIRZAF®. 

Page 12 of 112 

 
 
 
 
 
EBSD 

The EBSD technique was employed for two reasons: to estimate bainite lath size and to determine 
the amount of retained austenite, even though X-ray diffraction was chosen for the reporting of the 
RA  volume  fraction.  The  scan  step  was  set  at  50  nm.  This  short  step  size  was  intended  for  the 
accurate measurement of the above-mentioned parameters. The scans were performed in the center 
of the sheets. The lath size was measured by means of the linear intercept method as a function of 
the  misorientation  that  was  ranged  from  2º  to  20º.  Both  horizontal  and  vertical  directions  were 
considered for the lath size measurement. Before the lath size was determined, a threshold of three 
pixels was established to dismiss likely artificial grains and the austenite grains were removed. In 
spite  of  the  fact  that  EBSD  can  be  used  for  the  phase distinction  based  on  the  pattern  quality  or 
misorientation related parameters, they were ruled out to calculate the amount of secondary phases 
since the various involved phases do not lead to distinctly different values of such EBSD parameters. 

X-rays diffraction (XRD) 
The  measurement  of  the  retained  austenite  was  based  on  the  XRD  results.  X-ray  scans  were 
performed on RD-ND section according to ASTM E975-13 for 4 diffraction peaks: {200} and {220} 
for austenite and, {200} and {211} for ferrite. The carbon content (C) was determined through the 
lattice parameter according to the next equation [8]: 

aγ=3.572+0.033wt%C+0.0012wt%Mn-0.00157wt%Si 

which takes into account the main elements present in the composition of the steel. The angular step 
size was of 0.02º in order to estimate the position of the peaks accurately. The methodology used 
to transform the position of the peaks into the lattice parameter relied on modified Cohen´s method 
along with the minimum-squared method [9]. 

The amount of high-C martensite, within MA phase, has been considered as the difference between 
the amount of MA phase measured by FEG-SEM imaging and the amount of RA determined by X-ray 
diffraction. 

Taking 
(bainite)+%Carbide has been set as the fraction to balance the whole equation below: 

into  account  all  the  volume 

fractions  of  the  measured  microconstituents,  %B 

%B+%Carbides=100%-%RA-%High-C martensite-%Low-C martensite-%F 

The microconstituents as well as the techniques and methods used in this work are gathered in Table 
6. 

Table  6.  Overview  of  the  microconstituent  and  the  techniques  and  methods  applied  for  the 
characterization of their volume fractions. 

Microconstituent 

Quantification technique 
(fraction) 

MA phase 

FEG-SEM imaging 

Retained austenite RA  X-rays 

Method 

(Semi)Automatic 
detection 

ASTM E975-13 

High-C martensite 

MA  fraction  (FEG-SEM)–RA 
fraction (X-rays) 

By difference 

Number of 
fields/scans 

≅20 fields 

2 scans 

≅20 fields 

Low-C martensite 

FEG-SEM imaging 

Ferrite F 

Pearlite 

Optical 

FEG-SEM imaging 

(Semi)Automatic 
detection 
Manual point counting  ≅20 fields 

≅20 fields 

Semi-automatic 
detection 

5 scans 

The  volume  fraction  of  carbides  was  not  taken  into  account  in  the  measurement  of  the  volume 
fraction of 2ry phases along this final report. For HiSi steel, its amount is negligible as observed in 
the FEG-SEM micrographs and for LoSi, it remains below 3-4% in all cases. Thus, all through this 
work, 2ry phases exclude bainitic phases and carbides. The interest in the quantification of the 2ry 
phases lies in that it can be regarded as a measurement of the bainitic transformation degree. 

Texture analysis was carried out by XRD on as hot rolled (HR) and cold rolled (CR) materials with 
their initial ferritic and pearlitic microstructures in order to investigate their texture before annealing. 
For the HiSi-HR batch, through 4 mm thickness of the sheet, X-ray analysis was conducted at three 
RD-TD sections (surface, 15 and 50 % away from surface). Data derived from XRD were processed 
using MTM-FHM software in order to plot Orientation Distribution Functions (ODFs). 

Page 13 of 112 

 
 
 
 
 
 
Mechanical testing (bending, hole expansion, tensile tests) 

Tensile tests were performed according to DIN EN ISO 6892-1 but with flat samples half of sample 
form 1 having a gauge length of 25 mm and a thickness of 1,0 mm for cold rolled and 3,5 mm for 
hot  rolled  material  (Figure  6).  All  tests  were  conducted  longitudinal  and  transverse  to  the  rolling 
direction. 

In order to characterize bending behaviour, tests according to VDA 238-100 [10] (Figure 6) were 
carried out. The bending angle was continuously determined in situ by an optical measurement [11]. 
All tests were performed transverse to the rolling direction (bending angle longitudinal to RD). The 
difference to the specification of the VDA 238-100 was the width of the samples which was chosen 
to be 20 mm instead of 60 mm for cold rolled material and 35 mm for hot rolled material due to the 
limited amount of material available.  

Another  important  test  to  automotive  industry  is  the  hole-expansion  test  (HET)  according  to  ISO 
16630 (Figure 6) on 90*90 mm² samples. The punched hole was expanded by conical punch with a 
tip angle of 60° (Figure 6) until fracture through the sheet thickness, t, occurred at the punched hole 
edge.  Failure  is  defined  by  a  crack  through  the  entire  sheet  thickness,  t.  The  hole-expansion 
coefficient  (HEC)  is  defined  by  HEC=(D-D0)/D0, where  D0  is  the  initial  diameter  and  D  is  the  hole 
diameter at end of the test. 

t

D

l

α

Figure 6. Bending test (in dependence on VDA 238-100[13]), Hole-Expansion test (ISO 16630) and 
Tensile test in dependence of DIN EN ISO 6892 [12], p. 6892, (here with Lt=83mm, Lc=37,5mm, 
L0=25mm, b0=6,25mm). t is the material thickness. 

Split Hopkinson bar tests 

High strain rate tensile tests are performed using the Split Hopkinson Tensile Bar (SHTB) machine 
at Ghent University [13]. Incident, reflected and transmitted signals captured from the dynamic tests 
are translated to engineering stress and strain curves by the conventional Hopkinson bar equations 
[14]. GL5 specimens, with gage length of 5 mm, used for the SHTB experiments are loaded along 
the RD at strain rates ranged between 400 and 1000 s-1 at room temperature [15]. The SHTB results 
are shown in the Appendix 10. 

Page 14 of 112 

 
 
 
 
 
 
 
 
 
2. Processing-microstructure relationship 

Dilatometry and torsion tests, together with metallography observations using optical microscopy, 
SEM  and  hardness  measurements,  were  carried  out  to  study  the  bainite  transformation  kinetics, 
microstructure  and  hardness  evolution  as  a  function  of  prior  austenite  grain  size  (Dγ),  austenite 
deformation temperature, bainitic holding temperature and time. According to the preliminary results 
measured on dilatometry samples, processing conditions were selected to produce large samples of 
both cold rolled and hot rolled products. These samples were provided to characterize mechanical 
properties and formability in §3, as well as to study damage mechanisms in §4. The microstructures 
of these large samples were thoroughly characterized to establish the relationship between process 
and microstructure.  

2.1. Experimental 

2.1.1.  Isothermal bainite transformation kinetics 

To  estimate  the  transformation  kinetics  during  hot  rolling  addintional  isothermal  bainitic 
transformation  cycles  have  been  performed  on  a  Bähr  DIL805  dilatometer  on  cylindrical  samples 
machined  from  hot  rolled  steels,  see  Figure  3b.  Since  the  critical  cooling  rate  to  avoid  ferrite 
transformation is about >30°C/s for LoSi and HiSi steels after a soaking at 920°C for 5min (Table 
5),  soaking  temperatures  ≥920°C  and  a  maximum  achievable  cooling  rate  using  helium  gas 
(~100°C/s)  were  selected  to  avoid  any  phase  transformation  before  reaching  the  bainitic  holding 
temperatures.  

A series of dilatometric tests were then carried out under different isothermal conditions in the bainitic 
domain for the LoSi, HiSi and CrSi steels. Three soaking temperatures, i.e. 920°C, 1000 °C and 1150 
°C were chosen to study the influence of prior austenite grain size on bainite transformation kinetics. 
Microstructural  characterization  was  performed  using  light  optical  microscopy  (LOM)  and  Field 
Emission Gun scanning electron microscope (FEG-SEM). The mean prior austenite grain size obtained 
after  soaking  at  920,  1000  and  1150°C  for  5min  lies  in  6-10µm,  20-30µm  and  100-120µm 
respectively  for  the  three  steels.  Figure  7  gives  an  example  of  bainite  transformation  kinetics  at 
different isothermal holding temperatures after a soaking at 1000 °C for 5 min for the three steels. 
The bainite fraction after 30min bainitic holding has been quantified semi-manually using FEG-SEM 
by  removing  the  secondary  phases  (pearlite,  martensite,  MA  islands  and  retained  austenite).  The 
dilatometry curves were then corrected with the hypothesis that the dilatation increase is propotional 
to  the  formed  bainite.  The  bainite  transformation  reaches  its  stasis  before  300s,  so  the  bainite 
transformation kinetics are compared for the first 300s holding for the different steels at different 
temperatures (Figure 7). It is found that HiSi steel has globally a more rapid bainite transformation 
kinetics, especially at higher holding temperature (for example at 530°C), but it has a less complete 
bainite  transformation,  i.e.  less  fraction  of  bainitic  ferrite  in  the  microstructure.  The  combined 
addition of Cr and Si in CrSi steel retards greatly the bainite transformation kinetics, especially at 
higher bainitic transformation temperatures. In addition, the bainite transformation is significantly 
less  complete  in  CrSi  steel,  which  is  consistent  with  the  thermodynamic  calculation  of  T0  carbon 
concentration using the program of Bhadeshia [16], showing that the addition of Cr in HiSi steel will 
result in a decrease of T0 carbon concentration thus a higher volume fraction of retained austenite 
at all bainitic transformation temperatures. It is also worth mentioning that the combined addition 
of Cr and Si leads to a significant decrease in Bs temperature (Bs~500°C), which is more pronounced 
than the calculation using the Van Bohemen empirical law of Bs [6] taking into account the single 
addition effect of alloying elements.  

The prior austenite grain size has a significant effect on the bainite transformation kinetics for both 
HiSi and LoSi steels, as shown in Figure 8. For both HiSi and LoSi steels, a decrease in austenitization 
temperature or prior austenite grain size leads to an acceleration in bainite transformation kinetics, 
especially  at  higher  holding  temperature.  It  seems  that  the  prior  austenite  grain  size  has  a  more 
pronounced effect for the low Si grade at higher holding temperatures (≥530°C). This acceleration 
effect  can  be  explained  by  an  increase  in  grain-boundary  nucleation  sites  due  to  the  increase  in 
austenite grain boundary area. 

Page 15 of 112 

 
 
 
a) 

b) 

c) 

d) 

Figure 7. Bainite transformation kinetics at (a) 380 °C, (b) 430 °C, (c) 480 °C, (d) 530 °C for HiSi 
(red curves) and LoSi (black curves) and CrSi (blue curves) steels after austenitization at 1000 °C 
for 5 min. 

a) 

b) 

Figure 8. Dilatometry curves showing bainite transformation kinetics for HiSi and LoSi steels after 
an austenitization at 1000°C or 1150°C for 5min followed by a bainitic holding at different 
temperatures. a) HiSi and b) LoSi alloys. 

2.1.2.  Microstructural evolution as a function of process parameters 

Hot rolled products 

As shown in Table 3, hot rolling tests were performed at different finish rolling temperature (FRT), 
run-out-table (ROT) cooling rate, exit temperature and coiling temperature (CT) on the three steel 
grades. The microstructures of all the samples are then characterised using FEG-SEM-EBSD and XRD 

Page 16 of 112 

 
 
 
 
 
 
 
 
in order to establish the relationships between process parameters and microstructure (see Appendix 
3, Table 21 - Table 23). 

Effect of alloying elements 
In HiSi steel, a small volume fraction of ferrite (<10%) is formed during run-out-table cooling when 
the cooling rate is lower than 100°C/s. LoSi and CrSi steels have an obviously higher hardenability 
than HiSi due to the Cr addition. No ferrite has been detected in the microstructure for all the LoSi 
and CrSi samples. 
The retained austenite fraction and the C content in austenite have been measured using XRD (see 
Appendix  3  Table  21).  Figure  9  shows  the  retained  austenite  fraction  for  the  three  different  steel 
grades. It can be seen that, it remains almost no retained austenite in LoSi steel, a small fraction 
(0.5-2%) of austenite in HiSi steel and a significant fraction (4-10%) of austenite in CrSi after coiling, 
indicating  that  the  combined  addition  of  Cr  and  Si  is  more  efficient  to  maintain  austenite  during 
coiling.  
The  microstructural  investigations  using  FEG-SEM  are  in  good  agreement  with  the  results  of  XRD 
analysis. At lower CT (≤420°C), the microstructure is composed of bainitic ferrite laths + inter- and 
intra-lath carbides in LoSi steel. For HiSi steel, a small fraction of retained austenite (<1%) can be 
found in the microstructure, and the carbides are mainly located at the grain/lath boundaries, which 
should be the consequence of the decomposition of retained austenite into carbides + ferrite during 
coiling. As for CrSi steel, an important fraction of MA islands is present in the microstructure, and 
only a small amount of carbides can be observed. Therefore, the combined addition of Cr and Si in 
CrSi  steel  is  more  efficient  to  resist  the  decomposition  of  austenite  into  carbides  during  lower  CT 
(≤420°C). At higher CT (≥ 450°C), most of the retained austenite has been decomposed into pearlite 
in HiSi steel (Figure 10a), whereas only a small fraction of austenite has been decomposed in CrSi 
steel  (Figure  10b),  suggesting  that  CrSi  steel  is  also  more  efficient  to  resist  the  decomposition  of 
austenite into pearlite at higher CT. In addition, it is revealed from both FEG-SEM and EBSD analyses 
that CrSi steel has a finer bainitic lath structure at CT of 420-450°C. 

Figure 9. Retained austenite fraction obtained with XRD for different steels irrespective of the 
applied experimental conditions. 

a) HiSi-4, γ=2% 

b) CrSi-4, γ=10% 

Figure 10. Microstructures of (a) HiSi and (b) CrSi at FRT = 935°C and CT= 450°C.  

Effect of finish rolling temperature (FRT) 
The hot rolled sheets were mainly produced at two distinct FRT ranges, 855-870°C and 925-940°C.  
The prior austenite grain  size is (7-8)±3µm  for FRT= 855-870°C, and (10-12)±5µm for FRT=925-
940°C respectively for the three steels. For the three steels, when FRT= 925-940°C, the austenite 
grains are equiaxed, indicating the austenite is in recrystallized state before bainite transformation 
upon cooling. However, when the FRT=855-870°C, the prior austenite is slightly pancaked, indicating 
the austenite is not fully recrystallized before phase transformations upon cooling. Thus, there is a 
significant  fraction  of  ferrite  forms  in  the  HiSi  samples  at  FRT=855-870°C  due  to  the  lower 

Page 17 of 112 

 
 
 
 
  
    
 
 
hardenability of this steel, the study of the effect of FRT on microstructure and mechanical properties 
has  been  mainly  focused  on  LoSi  and  CrSi  steels,  as  HiSi  did  not  produce  interesting  results. 
According to the microstructural characterisation using FEG-SEM and EBSD (see Appendix 3 Table 
22Table 23), the decrease in FRT (or prior austenite grain size) has no influence on the bainitic ferrite 
and carbides morphology but induces a refinement of bainite lath structure in LoSi steel. With regard 
to the CrSi steel, the decrease in FRT not only leads to a slight decrease in bainitic lath size, but also 
has a significant effect on the morphology of secondary phases, as shown in Figure 11. When the 
FRT is 940°C, after a coiling at 390°C, a lot of thin austenite films still present in the microstructure 
(Figure 11a), whereas much less austenite films but more blocky MA islands are present when the 
FRT  is  decreased  to  865°C  (Figure  11b).  This  is  consistent  with  the  XRD  analysis,  showing  the 
presence of 9% retained austenite at FRT=940°C while only 4% at FRT=865°C.  It seems that most 
of  the  thin  austenite  films  at  FRT=865°C  has  been  decomposed  into  carbides  during  coiling.  One 
hypothesis is that this may be related to the thinner geometry of austenite film, since the thinner 
austenite film has the tendency to have a locally higher C content. More in-depth analysis is needed 
to answer the question. After the microstructure quantification, it is found that the volume fraction 
of austenite films + MA islands is almost equivalent for these two FRT conditions, implying a higher 
fraction of martensite at FRT=865°C.  

a) CrSi-8: FRT=940 ºC, γ=9% 

a) CrSi-7: FRT=865 ºC, γ=4% 

Figure 11. FEG-SEM images of CrSi steel hot rolled at (a) FRT=940°C and (b) FRT=865°C followed 
by a coiling at 390°C. 

Effect of run-out-table (ROT) exit temperature 

The ROT exit temperature, i.e. the temperature before entering the coiling furnace, turns out to be 
an  important  parameter  to  change  the  microstructure  morphology  and  thus  the  mechanical 
properties. It is observed that, when the ROT exit temperature (for example 380°C) is well below 
the coiling temperature (for example 450°C), as in the case of Figure 12a, it is very probably that 
most of the bainite transforms before reaching the coiling temperature, considering the rapid bainite 
transformation kinetics at a temperature between 380-430°C in CrSi steel (Figure 7). By contrast, 
when the ROT exit temperature is well above the coiling temperature (for example 490°C), as in the 
case of Figure 12b, the bainite transformation can begin at a temperature above coiling temperature 
(450°C), but most of the bainite forms near 450°C since the bainite transformation kinetics is very 
slow at a temperature around 480°C in CrSi steel. EBSD analysis (see Appendix 3 Table 23) reveals 
that  the  bainitic  lath  size  is  much  finer  for  ROT  exit=380°C  than  that  for  ROT  exit=490°C,  which 
gives  indirect  evidence  for  the  aforementioned  hypothesis.  According  to  the  dilatometry  study 
coupled  with  metallography  analysis,  the  lower  the  bainite  transformation  temperature,  the  more 
complete the bainite transformation for CrSi steel. Consequently, the austenite films are finer and 
the C content in retained austenite is higher, which gives a higher driving force for the decomposition 
of austenite into carbides. Moreover, the bainite transformation at lower temperatures gives rise to 
more dislocations in both bainite and retained austenite, while the defects in austenite favour the 
decomposition  of  austenite  by  easy  ferrite  nucleation  [17].  This  may  explain  the  FEG-SEM 
observations in Figure 12: most of the retained austenite films have been decomposed into ferrite 
and  carbides  during  coiling  at  ROT  exit  =  380°C  whereas  very  few  austenite  films  have  been 
decomposed at ROT exit=490°C. In addition, the XRD analysis of the austenite fraction and C content 
in austenite demonstrates that the fraction of austenite is 3% and the C content in austenite is 0.43% 
at the ROT exit = 380°C, which is much lower than that at ROT exit = 490°C (10% austenite with C 
content of 0.95%). This suggests that the first step of austenite decomposition is the precipitation 
of cementite from supersaturated austenite, which dilutes the C content in retained austenite and 
decreases the stability. Then the second stage involves the transformation of austenite at the coiling 
temperature into ferrite and further quantities of carbides, as proposed in the work of A. Saha Podder 

Page 18 of 112 

 
 
 
 
and H.K.D.H. Bhadeshia after the study on the thermal stability of austenite retained in bainitic steels 
[12].  

a) CrSi-1 : γ=3% (C=0.43%) 

b) CrSi-4 : γ=10% (C=0.95%) 

Figure 12. FEG-SEM images of CrSi steel hot rolled at a FRT of 940-980°C, ROT exit temperature at 
(a) 380°C and (b) 490°C followed by a coiling at 450°C. 

Effect of coiling temperature (CT) 
The coiling is simulated by furnace cooling with a cooling rate of around 30°C/h. Besides ROT exit 
temperature,  CT  is  another  key  parameter  that  controls  the  bainite  morphology.  In  LoSi  steel,  at 
CT=390°C, the microstructure is a fully lower bainite structure with intra-lath carbides. When the CT 
is  increased  to  420°C,  almost  50%  of  lath  bainitic  structure  contains  only  inter-lath  carbides, 
indicating the evolution of microstructure into a mixture of lower bainite and upper bainite. As the 
CT continues to increase to 450°C, a mixture of granular bainite, upper bainite and pearlite islands 
appears. It stems from the EBSD analysis (see Appendix 3 Table 22) that the increase in CT leads to 
a very significant increase in bainite lath size, which is well-known in the literature.  
In CrSi steel, the increase in CT not only leads to an increase in bainite lath size, but also results in 
an  increase  in  the  volume  fraction  of  secondary  phases  and  the  decomposition  of  austenite  into 
pearlite, as shown in Figure 13. It is known from dilatometry study and metallography analysis that 
the bainite transformation becomes more incomplete when the bainite transformation temperature 
increases, therefore leading to a higher volume fraction of secondary phases. This is in accordance 
with the FEG-SEM observation in Figure 13: at lower CT (390°C), mainly retained austenite films and 
small MA islands are present in the microstructure as secondary phases (Figure 13a), when CT is 
increased  to  450°C,  a  significantly  higher  fraction  of  secondary  phases  including  large  martensite 
and MA islands and smaller fraction of retained austenite films is present. In addition, some of the 
austenite islands begin to decompose into pearlite (Figure 13b).  

a) CrSi-8: γ=9% 

b) CrSi-4: γ=10% 

P  

M  

Figure 13. Microstructures obtained at FRT= 940°C and (a) ROT exit =410°C, CT=390°C, (b) ROT 
exit =490°C, CT=450°C for CrSi steel. P – Pearlite, M – martensite. 

Cold rolled products 

Since the CrSi steel has a too slow bainite transformation kinetics to adapt to continuous annealing 
line  (Figure  7  and  Figure  8),  the  study  on  the  cold  rolled  and  annealed  bainitic  products  only 
concentrates on HiSi and LoSi steels with cold rolled parallelepiped samples. The main phase fractions 
after cooling at specific cooling rates to determine the CCT curves for both steels were summarized 

Page 19 of 112 

 
 
 
 
 
 
 
 
in Table 5. In addition to the continuous cooling tests, isothermal bainitic tests were performed on 
cold rolled flat samples (Figure 4) to determine the transformation kinetics in HiSi and LoSi (Figure 
14). To get fully austenitisation the annealing temperature (TA) should be higher than Ac3. For LoSi, 
this temperature was ~805°C and for HiSi ~881°C. Especially for HiSi, Ac3 is quite high (industrial 
TA<880°C+low temperatures are preferable because of CO2 emission). Therefore, dilatometry tests 
with flat cold rolled samples (chapter § 1.1.2) to determine the effective Ac3 were performed at Tata 
Steel. Here, the effective Ac3 is defined as the temperature for which ferrite is fully transformed to 
austenite after 1 minute of constant annealing, Figure 15. 

Figure 14. Several examples of the transformed volume fraction vs. time during bainitic reactions 
for different overaging temperatures, TOA. a) LoSi and b) HiSi. 

a) 

b) 

Figure 15. Dilatometry method for effective Ac3 (a) and ferrite fraction vers. time at TA=830°C. 

The  range  of  austenitizing  temperatures  analysed  was  from  820°C  to  860°C  in  the  HiSi  alloy.  At 
temperatures lower than 840°C, Figure 15b  (830°C), there was no full transformation to austenite 
after  1min.  Since  temperature  fluctuations  in  the  industrial  process  can  never  be  eliminated,  a 
temperature of 850°C slightly above 840°C was chosen for the effective Ac3. Besides this parameter, 
additional  main  influencing  parameters  on  bainitic  transformation  (overaging  temperatures, 
overaging  times  and  cooling  rates)  were  varied.  Therefore,  dilatometry  tests with  TA=  820-920°C 
(industry<880°C),  cooling  rates  CR=  -30  to  -100  °C/s  (industry  <50°C/s)  and  overaging 
temperature TOA=390-540°C for tOA=13s-240s were performed. First the main influencing factors to 
develop  bainitic  steels  with  2ry-phases  under  ideal  conditions  and  main  influencing  factors  are 
analyzed (Table 7) in order to get different bainitic steels with nearly precisely adjusted 2ry phase 
fractions (WP 2-4). Second industrial restrictions (limited time, limited speed, limited cooling rates) 
were taken into account (Table 8) in order to emerge the main problematic parameters and/or to 
adjust these favourable steels to industrial products (WP5). 

Two types of microstructures were generated that correspond to about 60% bainitic transformation 
(shortly  overaged  samples)  and  to  the  quasi-stagnation  of  the  bainitic  reaction  (120s  overaging 
time).  The  project  goal  was  to  optimize  the  microstructures  in  order  to  improve  the  mechanical 
properties  of  these  kinds  of  steels.  The  dilatation  experiments  were  mainly  performed  to  get 
information of production parameter-microstructure relationship. Here indications to most interesting 
annealing cycles should be detected. Therefore, estimation of microstructure was performed more 
qualitatively. It showed that high overaging temperatures (480ºC-540ºC) and long overaging times 
(120s) may give rise to the formation of pearlite in HiSi steel (see Figure 16). The interruption of the 
bainitic  transformation  through  shorter  annealing  times  induced  high  variability  of  the  amount  of 
secondary phases. The presence of ferrite is, in general, very low or almost negligible in the range 

Page 20 of 112 

 
 
 
 
 
 
of studied overaging temperatures for both steels when the annealing temperature and cooling rate 
are sufficiently high (Figure 16). Additional examples can be found in the Appendix 4. 

Table  7.  Selected  thermal  cycles  to  be  applied  in  Vatron  annealing  simulator  for  model 
microstructures (CAL: Continuous Annealing Line). 

TA (ºC) 

860/820 
860/820 
860 
920 
920 
920 
920 
920 
920 

tA (s) 

CR (°C/s) 

TOA (ºC) 

120 
120 
120 
120 
120 
120 
120 
120 
120 

100 
100 
100 
100 
100 
100 
100 
30 
100 

390 
450 
480 
390 
390 
450 
420 
450 
480 

tOA (s) 

120 
14-120 
120 
24 
120 
14-120 
120 
120 
120 

CR (°C/s) 

Steel 

20 
20 
20 
20 
20 
20 
20 
20 
20 

HiSi/LoSi 
HiSi/LoSi 
HiSi 
LoSi 
HiSi/LoSi 
HiSi/LoSi 
HiSi 
HiSi/LoSi 
HiSi/LoSi 

Table  8.  Additional  thermal  cycles  closer  to  the  industrial  lines  conditions  (CGL:  Continuous 
Galvanizing Line and CAL: Continuous Annealing Line). 

Line 

TA (ºC) 

tA (s) 

CR (°C/s) 

TOA (ºC) 

tOA (s) 

CR (°C/s) 

CAL 

CAL 

CAL 

CAL 

CGL 

CGL 

CGL 

CGL 

CGL 

CGL 

CGL 

850 

850 

850 

850 

850 

850 

850 

850 

850 

850 

920 

120 

120 

120 

120 

80 

80 

80 

80 

66,7 

80 

80 

50 

100 

50 

20 

50 

50 

100 

50 

50 

20 

50 

420 

450 

450 

450 

390 

420 

450 

450 

450 

450 

450 

116,1 

120,7 

116,7 

104,7 

35,8 

43,9 

56 

1.8 

2 

2 

2 

2.1 

2.1 

2.1 

52-80 

2.1-2.4 

41,6 

40 

50,6 

2.5 

2.1 

2.1 

Steel 

HiSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

HiSi/LoSi 

(a) 

Pearlite 

(b) 

(c) 

Figure 16. Optical micrographs of several HiSi dilatometry samples, a) HiSi 920°C/-
100°C/s/540°C/120s - pearlite formation, b) HiSi 920°C/-100°C/s/450°C/14s - high fraction of 2ry 
phases and c) HiSi 920°C/-100°C/s/390°C/120s - homogeneity. Nital etching. 

As  explained  in  §1.1.3,  the  experiments  in  Vatron  annealing  simulator  were  also  performed  to 
produce large samples with different bainitic microstructures for mechanical and damage properties 
as well as edge formability characterization. Bearing all these data in mind, a selection of the thermal 
cycles for generating large specimens was done based on several specifications: 

•  hardness difference in mechanical properties. This is readily achieved through variations in 

• 

• 

• 

the overaging temperature. Mechanical contrast among micro-constituents; 
“fully” transformed and partially transformed microstructures through varying tOA. Influence 
on mechanical properties due to large differences in the volume fraction of 2ry phases; 
influence of the microstructural homogeneity with very little amount of secondary phases. 
This could help to obtain better hole expansion, worse elongation etc.; 
the  role  that  carbides  may  have  on  reducing  elongation,  enhancing  tensile  strength  and 
probably enhancing hole expansion, which could be probably detected in LoSi steel.  

Page 21 of 112 

 
 
 
 
 
 
 
 
All in all, the selected tests carried out in the Vatron simulator are gathered in Table 7. Additionally 
to  Vatron  simulations,  semi-industrial  tests  closer  to  the  industrial  restrictions  were  performed, 
according to Table 8. The results stemming from both tests were used for developing the guidelines. 

In order to rationalize the effect of the processing parameters on the microstructure, the focus was 
put on their influence on bainite lath size, MA volume fraction, retained austenite fraction and low 
carbon (Low-C) “martensite” fraction. In order to distinguish the martensite in the MA phase (high-
C  martensite)  and  the  likely  “martensite”  with  a  lower  C  content,  this  last  was  called  Low-C 
martensite. Within the MA phase, the contribution of the high-C martensite and the retained austenite 
to the volume fractions was adequately separated. In Figure 17, the different second phases detected 
in the samples are named on a couple of FEG-SEM micrographs (B: bainite, MA: martensite-austenite 
phase, L-C martensite: low carbon martensite). 

(a) 

(b) 

Film-like austenite 

MA 

Carbides 

Figure 17. Microstructures corresponding to a) HiSi and b) LoSi after the same thermal cycle 
(920ºC/-100°C/s /450ºC/120s). 

Effect of the alloying elements 

The effect of the composition on the final microstructure is decisive. The main differences lie in the 
second phase nature and their fractions. For LoSi steel, the presence of MA phase can be assumed 
as almost residual for most conditions analyzed, below 5%, and the retained austenite was confirmed 
to be low both by X-rays and by EBSD analysis. Carbides are the most relevant secondary phase. 
Besides, for the highest overaging temperature 480ºC and longest overaging time 120s, LoSi steel 
shows that some austenite begins to decompose into pearlite. On the contrary, HiSi steel does not 
develop carbides in its structure, except for some specific cases in which its volume fraction is very 
low. Si is known to be a strong inhibitor of the cementite due to its low solubility in it. This composition 
is prone to maintain a large amount of austenite after the overaging time-temperature sets applied 
in this work, around 20%. This remaining austenite can give rise to film-like austenite or MA islands 
in different amounts, depending on the specific experimental conditions.  

Effect of the overaging temperature (TOA) 

The range of overaging temperatures in which the analysis was carried out is 390-480°C. According 
to  dilatometry  analysis,  bainitic  transformation  almost  levels  off  after  tOA=120s,  time  used  as  the 
reference  for  the  following  analysis.  The  effect  of  this  parameter  on  the  microstructure  is  highly 
relevant, as detailed in Figure 18.  

a) 

b) 

c) 

Figure 18. Evolution of the a) volume fraction of 2ry phases, b) RA and c) lath size (2º) for HiSi 
and LoSi steels as a function of the overaging temperature. 

Page 22 of 112 

 
 
 
 
 
 
 
 
The increase of the overaging temperature brings about the rise in the volume fraction of secondary 
phases as well as the coarsening of the lath size (Figure 18a and c). Instead, the behaviour of the 
RA thermal stability depends on the material. For HiSi, the maximum locates in the range 420ºC-
450ºC, reaching a value of about 14%, and decreases as long as the temperatures applied separate 
from this range (Figure 18b). LoSi does not own a large amount of RA, below 5%, and RA volume 
fraction goes up with TOA. The film-like morphologies corresponding to lath-like upper bainite, more 
preponderant at the lowest temperatures, give way to the formation of large MA islands at the highest 
temperature,  typically  in  granular  type  bainite,  also  observed  elsewhere  [18].  In  LoSi  steel,  the 
carbide fraction diminishes progressively at higher temperatures, probably due to the presence of C-
rich phases such as the MA phase and the low-C martensite phase (Figure 19). Pearlite is observed 
for 480°C-120s. Carbides at prior austenite grain boundaries (PAGB) are also observed after 120s 
overaging time at 480ºC (Figure 19).  

The effect of the overaging temperature on the nature of bainite shows a common pattern in both 
materials.  For  the  highest  temperature,  the  granular  type  bainite  is  more  prominent  whereas,  at 
390°C the lath like bainite is clearly the most relevant morphology.  

(a) 

(b) 

(c) 

(d) 

(e) 

(f) 

L-C martensite 

MA 

MA 

Carbides at PAGB 

Figure 19. FEG-SEM images for TA=920°C. Overaging temperatures TOA = a) 390ºC, b) 450ºC, c) 
480ºC (HiSi steel) and d) 390ºC, e) 450ºC and f)480 ºC (LoSi steel). 

Effect of the overaging time (tOA) 

When  shorter  overaging  times  are  considered,  partially  transformed  microstructures  are  expected 
before final cooling. Thus, the overaging time exerts a profound effect on the microstructure. As a 
result  of  prolonging  the  overaging  time  (the  fraction  of  2ry  phases)  shrink  and  the  bainite 
transformation progresses (Figure 20 and Figure 21a). Large untransformed austenite regions are 
favoured  for  short  overaging  times.  On  final  cooling,  these  zones  give  rise  to  the  so-called  low-C 
martensite phase. The appearance of such regions is related to the distribution and diffusion of C 
during the bainitic transformation. 

Looking at the fraction of MA, it seems that there is a slighly decrease with the time (Figure 21b). 
Instead, the prolongation of time enhances RA stability, leading to an increase in fraction that doubles 
the value for shorter times, from 6-7% to 12-14% in HiSi steel (Figure 21c). The opposite is observed 
in LoSi, where RA decreases from 5-6% to 2-3%. The enhancement of the carbide formation with 
time is evident for austenitization temperature of 820°C (see Figure 20c and d). Quantitative results 
distinctly show that the lath size is significantly controlled by the overaging time in both steels and, 
increases as time gets longer, Figure 21d. 

Page 23 of 112 

 
 
 
 
 
 
 
 
 
(a) 

(b) 

L-C martensite 

MA 

MA 

(c) 

(d) 

MA 

L-C martensite 

Figure 20. Microstructures after tOA=14s at TOA=450°C for a) HiSi (TA=860°C) and c) LoSi 
(TA=820°C) and after 120s at 450°C for b) HiSi (TA=860°C) and d) LoSi (TA=820°C). Klemm III 
etching. 

a) 

b) 

c) 

d) 

Figure 21. Evolution with overaging time of the volume fraction of a) 2ry phases, b) MA phase, c) 
RA and d) bainite lath size for various TOA. 

Page 24 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
Effect of the annealing temperature (TA) 

Two temperatures were selected for HiSi and LoSi steels to analyze the effect of the austenitizing 
temperature on the microstructural development during overaging: 860ºC-920ºC for HiSi steel and 
820ºC-920ºC  for  LoSi.  These  temperatures  as  well  as  the  full  thermal  cycle  before  the  overaging 
stage are exactly the ones applied for the CCT determination of the cold rolled products. However, 
an additional temperature of 850ºC, closer to the industrial conditions, was also taken into account 
in the analysis. The measurements of the prior austenite grain size, Table 9, manifest that there is 
little  change  in  the  austenite  grain  size  between  the  austenitizing  temperatures  in  both  steels, 
probably due to the control exerted by the observed AlN precipitates. 

Table 9. Prior austenite grain size (in µm). 

TA (°C) 

820°C 

860°C 

920°C 

HiSi 

LoSi 

- 

7.3±0.5 

4.2±0.2 

- 

9.8±0.6 

4.9±0.3 

In  general,  the  effect  of  TA  on  the  bainitic  lath/packet  is  not  meaningful,  attributable  to  the  low 
difference in austenite grain size. On the other hand, the austenitization temperature has a slight 
influence on the MA fraction for a fixed TOA, as this last one increases faintly with TA. The change in 
the  fraction  is  lower  than  2-3%  irrespective  of  the  steel  and  overaging  temperature  (Figure  22). 
Concerning  retained  austenite,  there  is  not  a  clear  relationship  between  TA  and  the  amount  of 
retained austenite fraction. Specifically, for LoSi, the carbide fraction seems to increase with TA as 
detailed in the Appendix 6. Thus, the microstructures are not distinctly different if the same overaging 
conditions  (TOA  and  tOA)  are  applied,  and  here  TA  has  a  limited  impact  on  the  microstructure 
development. 

Figure 22. Evolution of the volume fraction of 2ry phases with TA (tOA≅120s). 

Effect of the cooling rate (CR) between TA and TOA 

Different cooling rates between -20°C/s and -100°C /s were applied from TA to TOA=450°C and then, 
the materials were held at that temperature for more than 100 s. The micrographs in Figure 23 show 
that at -20°C/s (Figure 23a and d), both steels develop a significant amount of ferrite (59% in HiSi 
sample and 48% in LoSi sample), in accordance to the ferrite critical cooling rate derived from Table 
5. For cooling rates of -30°C/s and -100°C/s (Figure 24), the amount of ferrite is low or negligible. 
However, there are other clear differences between these two cooling rates. The film like morphology 
of bainite is readily observed at faster cooling rates, whereas more granular structures are promoted 
at -30°C/s. Quantitative results in Figure 24a shows that the secondary phases are enhanced when 
slower cooling rates between TA and TOA are applied. Instead, the RA stability in HiSi steel impairs 
drastically when the cooling rate decreases (Figure 24b). Regarding the lath size, the acceleration of 
the CR generally appears to refine the microstructure, more markedly in LoSi steel (Figure 24c). 

The increase in the TA from 850ºC to 920ºC enlarge the size of the secondary phase islands whereas 
higher cooling rates, like -100°C/s, induces larger regions of lath-like bainitic structures with respect 
to sample cooled down at -50°C/s. 

Page 25 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
a) 

F 

Pearlite 

F 

F 

b) 

MA

c) 

MA

Film-like austenite 

MA 

d) 

e) 

f) 

L C martensite 

MA 

Figure 23. Micrographs corresponding to: CR=-20°C/s (a,d) -30°C/s (b, e) and -100°C/s (c, f) 
cooling rates from TA down to 450°C. From a) to c) HiSi steel and from d) to f) LoSi steel. 

a) 

b) 

c) 

Figure 24. Evolution of volume fraction of 2ry phase a), RA b) and bainite lath size c) for various 
cooling rates between TA and TOA. 

Effect of the CGL line 

The CGL simulations are characterized by shorter overaging (tOA) times with regard to CAL (Figure 
5), which may impact on the microstructure development and mechanical parameters. However, the 
other processing parameters may also influence the microstructure evolution. The full quantification 
of the microstructural parameters in Figure 25 (volume fraction of 2ry phases/RA and lath size) shows 
that there is little drop in the amount of 2ry phases as TOA decreases in both steels. The higher the 
TOA, the higher the amount of 2ry phases. This drop is about 4%. The lath size also holds such an 
observation for HiSi alloy, in which only the sample overaged at 390ºC-420ºC developed a smaller 
lath/packet size (Figure 25e). Conversely, the stability of the retained austenite shows a decreasing 
trend as longer overaging times are applied in the time interval 40s-80s in both steels (Figure 25 c 
and  d).  The  changes  due  to  TOA  are  negligible.  Nevertheless,  in  HiSi  steel  all  samples  develop  a 
volume fraction of RA higher than 10%, even though 390ºC temperature was applied. Compared to 
CAL  results,  this  seems  to  imply  that  CGL  may  be  enhancing  RA  stability  and  the  amount  of  2ry 
phases, up to a certain extent. 
The banding is the most remarkable feature in the LoSi CGL samples (Figure 26). Multiple bands are 
detected in white contrast for almost all samples, except for the one overaged at 390ºC, Figure 26. 
The  bands  are  always  aligned  with  the  rolling  direction  (RD)  and  have  a  high  fraction  of  MA  type 
phases, as observed by FEG-SEM imaging. The banding extent depends on the specific experimental 
conditions and appears to be favored by shorter annealing and overaging times. Longer overaging 
times and lower temperatures are beneficial for the avoidance of the banding structure. 

Page 26 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Max. CAL 

Max. CAL 

Min. CAL 

a) 

b)

c)

Max. CAL 

Max. CAL 

d)

e) 

f)

Figure 25. Change in the volume fraction of 2ry phases in a) HiSi, d)  LoSi, volume fraction of RA in 
b) HiSi, e) LoSi and lath size (2º and 15º) of c) HiSi f) LoSi for varying overaging time (tOA) and 
temperature (TOA) of CGL simulations. 

a) CGL 850°C/-
50°C/s/420°C/43,9s 

b) CGL 850°C/-
50°C/s/390°C/35.8s 

c) CGL 850°C (66.7)/-
50°C/s/450°C/41.6s 

Figure 26. Micrographs etched with LePera corresponding to LoSi steel after different CGL 
simulations. (CAL TA,°C/ CR,K/s/TOA, °C/tOA, s). 

2.2.  Modeling (transformation models) 

2.2.1.  Extension of Azuma model 

On the basis of the obtained volume fraction curves performed in the dilatometer experiments, efforts 
were put into the optimization and validation of an existing transformation model. Different models 
were  assessed  in  terms  of  their  significance  for  the  observed  microstructures  and  transformation 
products, see Appendix 7. Many of the considered kinetic models of bainitic transformation lack an 
explicit  consideration  of  carbides  that  enable  a  classification  of  bainitic  morphologies  into  upper 
(cementite at interface between baintic ferrite and austenitic regions) and lower bainite (cementite 
within  the  bulk  of  baintic  ferrite).  An  example  is  the  model  proposed  by  van  Bohemen  for  which 
calculations  have  been  compared  to  experimental  data,  see  Appendix  8.  In  contrast,  the  Azuma 
model [19] (see Appendix 9) allows for the differentiation of upper and lower bainite by incorporating 
volume fractions of cementite in either bainitic ferrite or spaces between baintic ferrite and austenite. 
The  potential  to  differentiate  bainitic  morphologies  and  in  particular  the  consideration  of  carbide 
transformation which is crucial for the characterization of incomplete bainitic transformation in HiSi 
and the redistribution of carbon into carbide rich regions in LoSi lead to the decision to especially 
focus on the enhancement and validation of the Azuma model. 

In order to validate the model, the results of the isothermal dilatometry experiments described in 
section  2.1.1  have  been  compared  to  the  model  predictions.  The  dilatation  signals  occurring  at 
holding temperatures between 390°C and 480°C were converted to bainitic volume fractions. These 
fractions were directly compared to the simulated volume fractions. As a result, it was found that the 
model had to be extended to be able to adapt it to the measured results. The complex kinetics of 
bainite transformation affected by chemical composition and transformation temperature could not 
be completely grasped by the defined nucleation rate 
. Therefore, we decided to extend the model 
and include a temperature and alloy composition dependent fitting factor 

 such that 

𝛼𝛼𝐵𝐵
𝐼𝐼𝑜𝑜

𝛿𝛿 = 𝛿𝛿(𝑇𝑇)

Page 27 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
𝛾𝛾
−𝑄𝑄𝐶𝐶

∗
−∆𝐺𝐺𝛾𝛾→𝛼𝛼𝐵𝐵,𝑜𝑜

𝛼𝛼𝐵𝐵

𝑅𝑅𝑇𝑇⁄

𝑘𝑘𝑇𝑇
𝛼𝛼𝐵𝐵
ℎ ∗ �1 + 𝛽𝛽𝑓𝑓𝑜𝑜
𝐼𝐼𝑜𝑜
= 𝑁𝑁0 ∗
 takes into consideration various corrections of assumptions made for e.g. the activation 
The factor 
. In addition, the autocatalysis factor was used as a fitting factor 
energy of bainite nucleation 
𝛿𝛿
that depends on chemical composition and transformation temperature as well. These factors were 
fitted on the phase volume fraction curves of Time Temperature Transformation (TTT) experiments 
on the dilatometer reported in section 2.1.1, cf. Figure 27. 

∗
∆𝐺𝐺𝛾𝛾→𝛼𝛼𝐵𝐵,𝑜𝑜

� ∗ 𝑒𝑒

∗𝛿𝛿 𝑅𝑅𝑇𝑇⁄  

∗ 𝑒𝑒

Eq. 1 

a) 

c) 

e) 

g) 

b) 

d) 

f) 

h) 

Figure 27. Evolution of experimental (1-f_γ  DIL) and simulated (1-f_γ,…) phase volume fractions 
and carbon mole fractions obtained from the transformation simulation for HiSi and LoSi variant at 
overaging temperature of 480°C (a, b), 450°C (c, d), 420°C (e, f) and 390°C (g, h). 

Page 28 of 112 

   
 
 
 
 
 
 
 
 
 
 
 
 
 
The obtained parameters for 
displayed as data points in Figure 28. 

 and 

 for every fitted temperature and the LoSi and HiSi variants are 

𝛽𝛽

𝛿𝛿

550

HiSi

LoSi

HiSi

LoSi

)
C
°
(
e
r
u
t
a
r
e
p
m
e
T

500

450

400

)
C
°
(
e
r
u
t
a
r
e
p
m
e
T

350

1000

100

10
β

1

0,1

0

0,2

0,4

0,6

0,8

1

δ

Figure 28. Parameters β and δ and the effect of alloy composition and temperature. 

550

500

450

400

350

Following the temperature trend of data points parabolic functions were fitted for 

 and 

: 

2

+ 𝛽𝛽0

𝛽𝛽(𝑇𝑇) = 𝛼𝛼𝛽𝛽�𝑇𝑇 − 𝑇𝑇𝛽𝛽�
2
𝛿𝛿(𝑇𝑇) = 𝛼𝛼𝛿𝛿(𝑇𝑇 − 𝑇𝑇𝛿𝛿)
That resulted in the parameters shown in Table 10 and Table 11. 

+ 𝛿𝛿0

𝛽𝛽(𝑇𝑇)

Eq. 2 

𝛿𝛿(𝑇𝑇)

Eq. 3 

Table 10. Parameters for β(T). 

Table 11. Parameters for δ(T). 

LoSi 

HiSi 

(°C) 

(°C) 

𝜶𝜶𝜷𝜷

𝑻𝑻𝜷𝜷

𝜷𝜷𝟎𝟎

𝜶𝜶𝜹𝜹

𝑻𝑻𝜹𝜹

𝜹𝜹𝟎𝟎

−0.0429

440.77

146.298

−0.0008

432.91

2.042

LoSi 

HiSi 

−4.62 ∗ 10

−5

−5

413.78

0.256

−3.68 ∗ 10

421.89

0.557

In  addition  to  the  effort  on  the  Azuma  transformation  model,  the  validity  of  the  iso-work  mixing 
model for flow curve characterization of the mixed microstructures was tested. Thus, a link between 
the mechanical model and the transformation model of bainitic/martensitic microstructures has been 
enabled. 

2.2.2.  Iso-work flow curve model 

The scope to model the flow curve of microstructures with varying volume fractions and properties 
of  bainite  and  martensite  was  achieved  by  applying  the  iso-work  model.  In  contrast  to  the  other 
complex mechanical property models in the project, the iso-work or ISO-E model utilizes a simplified 
mixing approach [20], [21], [22]. Multi-phase microstructure flow curves 
 are computed from 
single phase stress strain curves 
 under the assumptions that every microstructure constituent 
 absorbs the same mechanical energy: 

𝜎𝜎𝑚𝑚𝑚𝑚𝑚𝑚(𝜖𝜖)

𝑖𝑖

𝜎𝜎𝑚𝑚(𝜖𝜖)

𝜖𝜖1
0

= ∫ 𝜎𝜎𝑚𝑚(𝜖𝜖)𝑑𝑑𝜖𝜖

𝜖𝜖1
∫ 𝜎𝜎𝑚𝑚𝑚𝑚𝑚𝑚(𝜖𝜖)𝑑𝑑𝜖𝜖
Therefore,  single  phase  strain  hardening  models  are  needed  in  order  to  obtain  the  mixed 
0
microstructure curves. As the TRIP effect adds complexity to the modelling of mechanical properties, 
the focus was put on the  LoSi variant which does not contain fractions of retained austenite after 
thermal  treatment  and  cooling.  The  produced  microstructures  (see  Table  12)  were  tested 
mechanically (Figure 57) and the results of the obtained tensile curves are the base for this modelling 
work.  

Eq. 4 

Page 29 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Table 12. Considered microstructures of the LoSi variant. 

TA, ºC 

CR, Ks-1 

TOA, ºC 

tOA, s 

High 
Carbon 
Mart, % 

Low 
Carbon 
Mart., % 

Carbides, 
% 

Type of 
model 

-100 

920 

950 

450 

390 

480 

420 

14 

120 

24 

120 

120 

25 

5 

3.5 

2.5 

0.5 

3 

- 

21 

- 

24 

- 

11 

33 

2 

3.6 

3.5 

4.5 

2 

- 

B+M 

100%B 

B+M 

100%B 

B+M 

B+M 

In order to describe the stress strain curve of the microstructure constituents, equations of the form 

Eq. 5 

 represents the friction term depending on the contribution from solid solution 

 represents the work hardening. 

were used, where 
𝜎𝜎(𝜖𝜖) =   𝜎𝜎0 + 𝜎𝜎𝜖𝜖(𝜖𝜖)
strengthening and where 

𝜎𝜎0

𝜎𝜎𝜖𝜖(𝜖𝜖)

For martensite, the definition of friction stress was based on the RFCS MEPMO project [23]: 

Similarly, the work hardening term for martensite is taken from the MEPMO project such that: 
𝜎𝜎0𝑀𝑀 = 77 + 3065 𝑤𝑤𝑤𝑤. %(𝐶𝐶) + 80 𝑤𝑤𝑤𝑤. %(𝑀𝑀𝑀𝑀) + 750 𝑤𝑤𝑤𝑤. %(𝑃𝑃) + 60 𝑤𝑤𝑤𝑤. %(𝑆𝑆𝑖𝑖) + 11 𝑤𝑤𝑤𝑤. %(𝑀𝑀𝑜𝑜) − 161

Eq. 6 

 a constant, 
with 
𝜎𝜎𝜖𝜖𝑀𝑀(𝜖𝜖) = 𝛼𝛼𝑀𝑀𝛼𝛼√𝑏𝑏�(1 − 𝑒𝑒𝑒𝑒𝑒𝑒(−𝑀𝑀 𝑘𝑘2 𝜖𝜖)) (𝑘𝑘2𝐿𝐿)
the Burgers vector. 

⁄

 the Taylor factor, 

 are constants. 

 and 
𝑀𝑀 = 3

𝛼𝛼 = 0.33

𝑚𝑚
For bainite, the same definition of friction stress given in Eq. (6) was used. In the MEPMO project 
[23] an equation for strain hardening in bainite is provided as well: 

𝑏𝑏 = 2.5 ∗ 10

𝛼𝛼 = 80 𝐺𝐺𝑃𝑃𝐺𝐺

𝐿𝐿 = 4 ∗ 10

𝑘𝑘2 = 44

−8

 the shear modulus and 

Eq. 7 

−10

with 
𝜎𝜎𝜖𝜖𝜖𝜖(𝜖𝜖, 𝑇𝑇) = 1.36 ∗ 10

 and 

∗ 𝑇𝑇

11
 as defined above and 

−3.205

+ 𝛼𝛼𝑀𝑀𝛼𝛼√𝑏𝑏�1 − 𝑒𝑒𝑒𝑒𝑒𝑒(− 38 𝜖𝜖)

 being the temperature in °C. 

Eq. 8 

The resulting model curves in comparison to the measured tensile curves are shown in Figure 29. 

𝛼𝛼, 𝑀𝑀 , 𝛼𝛼

𝑏𝑏

𝑇𝑇

Figure 29. Single constituent flow curve models (dashed) compared to experimentally measured 
results (solid). 

The ISO-E model was then applied to validate the resulting flow curves. In Figure 30 the results of 
the iso-work model are compared to the obtained experimental results. 

Page 30 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
Figure 30. Mixed microstructures flow curves computed with the ISO-E model (dotted) compared to 
experimentally measured results (solid). 

Evidently,  the  predicted  stress-strain  curves  demonstrate  the  correct  trend  and  an  overall  good 
agreement. However, deviations between the measured and computed stresses are noticeable and 
in line with a recent study of the iso-work mixing rule for bainitic microstructures with martensite as 
the second phase [24]. For higher overaging temperatures (450°C/480°C) the stress deviation for 
larger plastic strains (>0.03) increases. A possible increased work hardening of the softer bainite in 
the mixed microstructure by the influence of martensite is not included in the iso-work framework 
which  could  explain  the  difference  in  measured  and  computed  stresses.  Additionally,  increased 
martensite strength through carbon enrichment during bainite formation could not be captured by 
the iso-work method. For lower overaging temperatures (390°C/420°C) a better agreement is found 
due to more similar mechanical properties of the constituents of the microstructure.  

2.3.  Conclusions 

The microstructural characterization on the hot rolled and cold rolled products, elaborated at different 
process conditions, together with dilatometry study shows that, 

a)  The combined addition of Cr and Si in CrSi steel is more effective to maintain austenite after 
long  bainitic  holding  during  coiling  due  to  the  strong  retardation  effect  in  bainite 
transformation kinetics, and a more efficient resistance to pearlite and carbides formation. 
The CrSi steel is therefore favourable to produce hot rolled bainitic Trip steels whereas HiSi 
steel is more adapted to produce cold rolled and annealed bainitic Trip steels, in which the 
effect of the Si in the stability of the retained austenite is crucial.  

b)  The decrease in FRT or a decrease in TA leads to a refinement of bainite lath size. It leads to 
also an increase in MA fraction for hot rolled CrSi steel. But no significant difference in MA 
fraction can be observed in cold rolled annealed steels.  

c)  The ROT exit temperature may have a strong effect when it is significantly lower than the 
coiling  temperature.  The  bainite  transformation  before  coiling  may  facilitate  the 
decomposition of austenite during coiling. 

d)  The increase in overaging temperature or coiling temperature results in: (1) an evolution of 
bainite morphology in LoSi, from lower bainite to upper bainite to granular bainite; (2) an 
increase in lath size; (3) much higher tendency to form pearlite and (4) an increase in MA 
fraction for CrSi hot rolled steel.  

e)  In  CR  products,  the  overaging  time  exerts  a  great  influence  in  the  microstructural 
development when very short times are applied. Along with the promotion of the amount of 
2ry  phases,  short  overaging  time  brings  about  the  formation  of  large  islands  of  likely 
autotempered  martensite  in  the  HiSi  and  LoSi  steels.  At  the  same  time,  the  RA  stability 
impairs.  

f)  The CR affects the microstructure morphology, leading to more granular bainite at low CR 

and a more lath-like bainite for high CR.  

g)  In LoSi steel, more significant banding can be observed in CGL type cycles than in CAL ones, 
which is chiefly related to shorter austenitization and overaging times. HiSi has no significant 
banding structure in the two types of cycle. 

Page 31 of 112 

 
 
 
 
 
 
 
Page 32 of 112 

 
 
3. Microstructure-properties relationship 

Establishing  the  relationships  between  the  microstructures  (characterized  in  Chapter  §2)  and  the 
mechanical properties (tensile/bending/hole expansion tests) is the main objective of this chapter, 
e.g. the results of the mechanical behaviour are present and analysed, subsequently, with regard to 
different  microstructural  parameters.  The  modelling  task  focusses  on  the  development  of  self-
consistent  and  crystal  plasticity  models  for  the  predictions  of  the  stress-strain  curves.  For  model 
development and validation a wide range of microstructures was needed. Thus, additional new tests 
that broaden the microstructural variability were set to fulfil such needs. 

3.1. Experimental 

3.1.1.  Mechanical tests 

Hot rolled products 
Tensile, bending and HEC tests have been performed on the hot rolled substrates with variations in 
process setting as listed in Figure 31-35. Table 23 (Appendix 3) shows the tensile (L) and HEC data 
of  the  three  alloys  for  the  variation  in  hot  rolling  processing  conditions.  The  tensile  results  of  the 
specimens machined in the T-direction are listed in Table 23 (Appendix 3).  

Figure 31 shows the total elongation (A25) as a function of the ultimate tensile strength (UTS) for 
the longitudinal (L) and transverse (T) specimens. Each data point represents the average value of 
two  tensile  bars  and the  standard  deviation  calculated  on  the basis  of two  results  is  taken  as  the 
uncertainty (error bars). The dashed line in Figure 31 represents an arbitrary trend line denoting the 
ductility-strength decay which helps the cross-comparison between L- and T-data.  

Unfortunately, for approximately 10% of all the tensile tests the fracture did  not occur within the 
gauge length of 25 mm, and thus the total elongations recorded with the extensometer are too low. 
It  is  well  known  that  AHSS  and  UHSS  are  more  susceptible  to  this  kind  of  complications  due  to 
fracture outside the gauge length. Nevertheless, the strength values, (YS and UTS) are trustworthy, 
and therefore it was decided not to omit these data. The corresponding A25 elongations have been 
marked with a question mark (?) and in all the figures with A25 data the error bars have been made 
extra large (+/- 4%). 

Comparison of data for A25-T and A25-L in Figure 31 indicate that T-specimens are more susceptible 
to fracture outside the gauge length. Therefore, the analysis of tensile data is primarily focused on 
the data of L-specimens. The data, excluding the A25 data with fracture outside the gauge length, 
show that:  

(1)  for all alloys the total elongations in the T-direction are smaller than in the L-direction; 

(2)  the CrSi alloy delivers the highest UTS levels of 1100-1200 MPa, which can be attributed to 
the extra Cr addition as compared to HiSi. The UTS levels of LoSi and HiSi are similar at 800-
1000 MPa; 

(3)  the alloys with high Si, HiSi and CrSi, have a better strength-ductility balance than the LoSi 

substrates for equal processing; 

(4)  for LoSi, there is one peculiar data point (red square) with a much higher strength than the 
other  data  found  for  this  alloy.  It  falls  within  the  data  collective  for  CrSi.  It  cannot  be 
elucidated whether this is a true material property or due to a mistake in the sample coding.   

Figure 32 shows the total elongation as a function of the yield strength, and in Figure 33 the yield 
strength is plotted against the ultimate tensile strength. The data show that: 

(1)  lowest yield ratios (YR ~ 0.7) are found for CrSi with CT = 420 – 450ºC. The YR appears to 

increase with decreasing CT for both HiSi and CrSi; 

(2)  the LoSi alloy delivers the highest YR of about 0.90 for all processing conditions.  

The lower YR found for CrSi can be explained by the significant fraction of MA islands present in the 
microstructure as discussed earlier, see for example Figure 11, and Figure 13. 

Page 33 of 112 

 
 
Figure 31. Total elongation against ultimate tensile strength for L (left) and T (right) direction. 

Figure 32. Total elongation against yield strength for L (left) and T (right) direction. 

Figure 33. Yield strength against ultimate tensile strength. 

Figure 34 (left) shows the HEC as a function of UTS. For the purpose of cross-comparison between 
the figures the (arbitrary) trend line with inverse dependence is shown (dashed line) to indicate that 
in general the HEC performance is known to decrease with increasing UTS. It is widely known that 
for AHSS the HEC performance does not correlate with the tensile ductility (A25) as seen in the plot 
on  the  right-hand  side  of  Figure  34.  This  is  related  to  the  fact  that  local  differences  in  hardness 
deteriorate the HEC performance, but do not have a negative influence on the global formability as 
measured in a tensile test. This is in qualitative agreement with the data set of this study (Figure 

Page 34 of 112 

 
 
 
 
 
 
 
 
 
34) which shows that at a specific strength level the substrates with the highest YR have a relatively 
high HEC. This is illustrated by some examples Figure 34 (left) for which the YR values are given. 

Figure 35 shows the bending angles of Q-samples (left) and L-samples (right) as a function of UTS. 
Analogous to the HEC data also in this figure an arbitrary trend line with inverse dependence is shown 
(dashed line) because for AHSS the bending performance is known to decrease with increasing UTS.  

In general, the bending angles of HiSi and CrSi substrates seem better than found for LoSi. This is 
in qualitative agreement with the tensile results discussed above. However, the bending performance 
does not correlate with the tensile ductility (A25). This is widely known and in broad agreement with 
the  observations  of  the  HEC  performance  discussed  above.  Both  deformation  tests  are  mainly 
governed by the damage tolerance of the material. Despite this qualitative similarity, the deformation 
states  involved  in  HEC  and  bending  are  certainly  not  identical.  Both  property  data  do  not  exactly 
correlate.  

The 15 results for Q-samples (bending line perpendicular to RD) are in general better than found for 
the  9  L-samples  (bending  line  parallel  to  RD).  This  difference  is  usually  found  in  bending 
investigations. Damage is postponed to higher strains when the bending strains are parallel to the 
rolling direction (Q) instead of perpendicular (L). 

Figure 34. HEC performance against tensile strength (left) and total elongation (right). 

Figure 35. Bending angle (Q) (left) and bending angle (L) (right) against tensile strength. 

Cold rolled products 

For cold rolled material, tension tests were performed on the material listened in Table 7 and Table 
8. Here also only tests 0° to RD (L) are demonstrated. The table with all data can be found in the 
Appendix 5.  

Page 35 of 112 

 
 
 
 
 
 
 
 
 
 
Effect of the alloying elements 

Both alloys, HiSi and LoSi, show the same level of strength, see Figure 36a. The LoSi material exhibits 
higher  YS  and  lower  elongation  (for  the  content  of  residual  austenite  see  Figure  18b)  at  same 
strength  levels  (Figure  36).  Also,  HEC  values  are  in  the  same  range  of  order,  see  Figure  36b 
(triangles). Similar to HR material, HEC performance does not correlate with tensile ductility (Figure 
37a). A closer look to Figure 37b shows that there is a positive correlation of HEC*TS on YS/TS (yield 
ratio) and a slight negative correlation of A25 on YS/TS. Yield ratio is taken to get an estimation of 
strain hardening within the steels.  

Where  not  named,  only  cooling  rates  (CR)  =-50  to  -100°C/s  were  taken  into  account  for  further 
discussion. 

Figure 36. Overview of tension tests (a) and HEC (b) results measured on HiSi and LoSi according 
to Tensile strength (TS). 

Figure 37. Overview of a) HEC to A25 (total elongation) and b) HEC (hole expansion coefficient) 
and A25 to YS/TS (yield strength ratio) measured on HiSi and LoSi. 

The above-mentioned correlations of HEC*TS and A25 to YS/TS underline the above assumption that 
hardness  differences  between  the  phases  or  inclusions  play  a  dominant  role  in  HEC  and  total 
elongation  [25].  The  higher  the  hardness  differences  (here  deduced  from  the  low  YS/TS)  is,  the 
higher is the strain hardening potential, the higher is the elongation. But the more shear stresses 
are available, the lower is the HEC. Indeed, there are many more influencing factors, for instance 
retained  austenite  content  which,  leads  to  higher  elongation,  but  not  directly  to  worse  HEC, 
martensite content, bainite grain size, C- content of RA etc. may play a noticeable role. These factors 
will be analyzed in more detail in the next chapter. Inclusions in these melts play a minor role (§ 
1.1.1). 

In  addition  to  tension  and  hole  expansion  properties,  bending  is  also  an  interesting  parameter, 
especially  for  bending  operations  or  roll  forming  operations.  Because  of  same  loading  direction, 
bending  angles  are  compared  to  mechanical  parameters  90°  to  RD.  HiSi  shows  better  bending 
properties  than  LoSi  (Figure  38a),  probably  due  to  the  higher  total  elongation  in  these  steels.  In 
Figure 38b, α to A25*HEC is plotted. The strong correlation could result in the effect that bending is 
dominated by local damage (void formation) or by necking [25]. There is also a good correlation of 
α to A25, but higher scatter was observed than for A25*HEC. Therefore, these results will not been 
shown here. The diagram of α vers. HEC is also not shown, because direct correlation has not been 
detected. Both diagrams could be found in the Appendix 5 (Figure 84). 

Page 36 of 112 

 
 
 
 
 
 
 
Figure 38. Bending angle a to a) TS and b) A25*HEC. 

Effect of the overaging temperature 

Overaging temperature (TOA) and times (tOA) are the main influencing parameter on hole-expansion 
and tensile behavior [26]. The higher the overaging temperature, the lower are the YS, TS and HEC 
and the higher is A25, see Figure 39.  

Figure 39. Mechanical properties to overaging temperature TOA (CAL TA=920°C; CR=-100 °C/s; 
tOA=120s). 

The  above-described  dependencies  are  probably  due  to  different  amount  2ry  phases  within  the 
microstructures and transformations during testing. The above-found correlation is underlined by the 
mechanical  parameters  measured  after  annealing  with  different  annealing  temperatures  (TA)  and 
cooling rates, see Figure 40. 

Figure 40. Mechanical properties a) YS,TS and b) A25,HEC to overaging temperature TOA (CAL 
TA=850°C; CR=-50 °C/s; tOA~120s). 

Effect of the overaging time 

As  mentioned  in  §  2.1.2,  the  overaging  time  exerts  a  profound  effect  on  the  microstructure. 
Therefore, the influence on mechanical parameters is quite interesting. As already demonstrated in 

Page 37 of 112 

 
 
 
 
 
 
 
 
 
 
 
Figure 21 for the microstructure, here a big influence of tOA on the mechanical parameters could be 
observed  (Figure  41).  This  is  due  to  the  fact  that  longer  overaging  times  ensure  mostly  ful 
transformation  to  bainite,  whereas  with  shorter  tOA,  higher  fractions  of  2ry  phases  could  be  found 
within the microstructure, see Figure 21a.  

Figure 41. Mechanical properties a) YS, TS and b) A25, HEC to overaging temperature tOA (CAL 
TA=920°C; CR=-100°C/s; TOA=450°C). 

Effect of the austenitizing temperature 

The microstructures analysed in §2.1.2 seem to be minimally influenced by TA. Therefore, a detailed 
analysis  of  the  mechanical  parameters  as  a  function  of  TA  makes  no  sense  and,  thus,  was  not 
performed.  

Effect of cooling rate (CR) between TA and TOA 

As demonstrated in §2.1.2 only microstructures with cooling rates below -20°C/s show differences 
in the microstructure, this could not be seen directly on the mechanical behaviour, see Figure 42. 
Here higher YS and TS and lower elongations could be observed at higher cooling rates. This could 
be a consequence of ferrite formation with lower cooling rates and higher bainite fractions for higher 
cooling  rates.  Also  stability  of  austenite  could  have  an  influence.  This  is  not  fully  understood.  A 
tendency  of  lowering  the  HEC  could  be  observed  for  HiSi  with  lower  cooling  rate.  This  could  be  a 
consequence of the presence of ferrite within the microstructure below CR=-20°C/s, see Figure 23a 
and d.  

Figure 42. Mechanical properties a) YS,TS and b) A25,HEC to cooling rate CR (CAL TA=850°C; 
TOA=450°C; tOA~120s). 

Effect of the CGL line and line speed 

As described in chapter 2.1.2 CGL is characterized by shorter overaging (tOA) times with regard to 
CAL.  Also  banding  is  a  prominent  feature  in  the  LoSi  CGL  samples.  Latest  could  have  a  negative 
effect on HEC [27]. This was analysed and is presented in Figure 43. 

Page 38 of 112 

 
 
 
 
 
 
 
 
 
Figure 43. Mechanical properties a) YS,TS and b) A25,HEC to cooling line speed v with different 
lines (TA=850°C; TOA=450°C; tOA~long). 

In Figure 43 only a slight influence on tensile properties could be observed with different line speeds 
(v,  m/min).  For  standard  simulations  a  line  speed  of  100m/min  was  chosen.  Additional 
measurements  with  80m/min  and  120m/min  were  analysed  as  well  to  show  the  effect  of  the  line 
speed variation. 

3.1.2.  Microstructural observations and properties relationship 

Hot rolled products 

After  the  characterisation  of  both  microstructure  and  mechanical  properties  of  hot  rolled  steels, a 
dataset is available (Appendix 3) allowing the set-up of the relationship between microstructure and 
mechanical  properties.  Figure  44a  presents  globally  linear  relationship  between  (YS  -  σ0)  and  the 
inverse of lath size (1/l) defined with 2-5° misorientation for the hot rolled products, except that the 
point  containing  a  significant  fraction  of  ferrite  is  far  away  from  this  linear  relationship.  σ0  is  the 
friction  stress  caused  by  the  lattice  incorporating  the  effect  of  solid  solution:  σ0  is  assumed  to  be 
248,  360  and  341  MPa  for  hot  rolled  LoSi,  HiSi  and  CrSi  steels  respectively.  These  values  are 
calculated using literature data of solid solution hardening of each alloying element [28]. Precipitation 
hardening by carbides has not been taken into account in this first attempt. It is found that there is 
also  a  linear  relationship  between  the  fraction  of  secondary  phases,  i.e.  martensite  +  retained 
austenite,  and  the  hole  expansion  ratio  in  hot  rolled  steels,  as  demonstrated  in  Figure  44b.  The 
higher the fraction of secondary phases, the lower the hole expansion ratio. However, it should be 
noted that, not only the fraction of secondary phases, but also the morphology of carbides play an 
important  role  in  the  hole  expansion  ratio  control.  For  instance,  when  the  carbides  are  fine  and 
distributed uniformly in the microstructure, as the case for the LoSi steel coiled at 390°C after hot 
rolled at FRT=925°C (Figure 45a), the hole expansion ratio is high (HER=48%). The carbides begin 
to  segregate  on  the  lath  boundaries  and  form  carbides  films  in  LoSi  steel  after  coiling  at  420°C 
(Figure 45b), which leads to a decrease in HER (HER=36%). When the cementite carbides are present 
in the form of films on the grain/lath boundaries, as the case in HiSi steel after the decomposition of 
austenite films into cementite films at grain or lath boundaries during coiling (Figure 45c), the HER 
is reduced dramatically (HER=12%). 

Figure 44. Relationship between (a) YS and lath size defined with 2-5° misorientation and (b)  hole 
expansion ratio (HER) and secondary phases fraction (martensite + austenite + MA) fraction for 
hot rolled products. 

Page 39 of 112 

 
 
 
 
 
 
 
Figure 45. Observation of carbides distribution and localisation in the microstructure using FEG-
SEM: (a) LoSi steel coiled at 390°C, (b) LoSi steel coiled at 420°C and (c) CrSi steel with a ROT 
exit temperature at 390°C then a coiling at 450°C. 

Cold rolled products 

Quantitative  results  of  2ry  phases  vers.  overaging  temperatures  TOA  and  overaging  times  tOA  are 
gathered  in  Figure  18  and  Figure  21  for  the  continuous  annealing  treatments  (CAL  and  CGL) 
performed in the Vatron simulator. As mentioned in §2.1.2, overaging temperatures and times are 
the most relevant parameters in engineering bainitic steels. An increase in overaging temperature 
leads  to  a  rise  in  the  volume  fraction  of  secondary  phases  as  well  as  in  coarsening  the  lath.  The 
increase of overaging time leads to lower fractions of secondary phases and coarsening of lath. In 
Figure 39-Figure 41 the influence of TOA and tOA on mechanical parameters is presented. The mostly 
linear correlation of TOA/tOA and bainite lath size (Figure 18c and Figure 21d) and that of lath size 
and  YS/TS  leads  to  the  conclusion,  that  TOA  and  tOA  have  a  dominant  effect  on  the  two  latter 
mechanical parameters, see Figure 46.  

Figure 46. YS and TS (0° to RD) as a function of bainite lath size (2°). 

In HiSi, also the fraction of secondary phases could play a major role on YS/TS and A25 (Figure 18 
and Figure 21). This has been analysed in Figure 47. Here a clear correlation of austenite content in 
HiSi steel to YS and A25 could be detected. Such a clear correlation could not be found for TS (Figure 
86). 

Page 40 of 112 

  
 
 
 
 
 
 
 
 
 
Figure 47. YS and A25 (0° to RD) vers. phase contents. 

For HEC, the correlation with bainite lath size seems to be less obvious (Figure 48a). It is sure that 
there is a relationship of bainite lath size and TS (Figure 46). Here the content of secondary phases 
seems to play the major role (Figure 48b) alone. Moreover, the most deteriorating phase seems to 
be martensite, Figure 49a. The residual austenite may also have a negative influence, if it transforms 
to martensite during forming. The higher TOA the lower the C-content in RA and the lower HEC in HiSi 
(Figure  39b  and  Figure  49b).  Figure  49b  shows  that  the  carbon  concentration  in  the  austenite  is 
enhanced  at  450°C,  which  could  result  in  the  detected  improved  stability  (Figure  52).  The  most 
obvious reason for that is, it got the fastest transformation kinetic to bainite (Figure 14). 

Figure 48. HEC vers. bainite lath size (a) and fraction of secondary phases (b) for all performed 
cycles (Cr ≤50K/s). 

Figure 49. HEC vers. M/Carbide/RA-content and C-content of residual austenite vers. TOA. 

Page 41 of 112 

 
 
 
 
 
 
 
 
 
 
 
Figure 50. Volume fraction of M vers. TOA (tOA>60s) and tOA (TOA=450°C). 

Martensite content can be controlled mainly by controlling TOA and tOA (Figure 50). Because volume 
fraction of martensite is not linear correlated to TOA (Figure 50), but HEC is (at high tOA of 120s-Figure 
39b), residual austenite (Figure 18b) could probably be a deteriorating phase for HEC, mainly if it is 
not stable. 

3.2.  Modeling 

3.2.1.  Additional information and production of specific microstructures 

for modeling 

After the analysis of the previous microstructure obtained from the Vatron simulator, Chapter §2, it 
was detected that new microstructures were needed to comply with the modelling requirements. In 
particular, there was no information about the mechanical behaviour of: 

• 
• 

fully martensitic material; 
large fraction of martensitic type phases (higher than, typically, 50%). 

In addition, the stability of the retained austenite with overaging time was a subject of analysis, since 
retained  austenite  is  a  key  feature  to  understand  the  mechanical  behaviour  of  TRIP  assisted 
multiphase steels [29]. Due to the lack of a large amount of material, a dilatometry study similar to 
that explained in § 2.1.1 was performed to set the specific thermal conditions for the generation of 
tensile tests specimens. The main change with regard to previous analyses was the rise in the TA 
temperature to 950ºC, whereas the rest of parameters was unchanged (even the final cooling rate -
20ºCs-1).  
The evolution of the fraction of 2ry phases (non-bainitic ferrite phases or carbides) with overaging 
temperature is shown on Figure 51. From those data, it can be concluded that: 

• 

• 

times  shorter  than  10s  are  required  to  obtain  large  fractions  (above  50%)  of  secondary 
phases; 
times as long as 1800s are needed to get volume fractions of secondary phases lower than 
10% for HiSi steel. 

a) 

b) 

Vatron-HiSi 

Vatron-LoSi 

Figure 51. Evolution of the amount of secondary phases with the overaging temperature tOA a) 
HiSi, b) LoSi for all the applied overaging temperatures. 

Page 42 of 112 

 
 
 
 
 
 
  
 
 
 
 
 
The effect of the overaging time and temperature on the stability of the RA is shown in Figure 52 for 
HiSi. The RA amount does show a maximum for intermediate times that is followed by a net decline 
for  very  long  overaging  times,  Figure  52a.  The  fraction  of  RA  is,  for  short  to  intermediate  tOA, 
promoted by the overaging temperature, TOA. Finally, the austenitizing temperature also affects the 
amount of RA attainable: the higher the TA, the lower the RA fraction, Figure 52b. 
As a consequence of the analysis of the microstructural results, the thermal conditions detailed in 
Table 13, in addition to water quenching, were applied in a continuous annealing vertical simulator 
at CEIT, from which specimens with proper sizes machined out to run the tensile tests. 

a) 

b) 

Figure 52. a) Retained austenite fraction as a function of the overaging temperature TOA and time 
tOA. HiSi steel TA=950ºC (Dilatometry samples). b) Evolution of the retained austenite as a function 
of the overaging temperature and austenitizing temperature (tOA=120s). 

Overaging temperature (ºC)

Table 13. Selected new temperature-time overaging conditions for the modelling requirements.   

Steel grade 

HiSi 

LoSi 

Temperature (ºC) 

390 

450 

420 

450 

480 

Time (s) 

1800 

5-45-600-1800 

25 

5-12 

5 

Some of the produced samples contain athermal martensite that was formed during the final cooling. 
The carbon content of this martensite needs to be determined to formulate a suitable work hardening 
model for this phase, required by the modelling task. The dilatometry tests did not allow determining 
accurately  the  Ms  for  small  volume  fractions  of  martensite.  Consequently,  the  martensite  carbon 
content has been estimated according to the following sequence: 

• 

• 
• 

production  of  specific  microstructures  for  modelling:  martensite  in  steels  with  different 
carbon contents; 
definition of the calibration curve between C content and martensite nanohardness; and 
estimation of the carbon content from nanoindentation for the AHSS microstructures. 

Taking  advantage  of  the  nanoindentation  work,  the  evolution  of  the  nanohardness  (through  cube 
corner tip) of the various phases with the overaging temperature and time was determined to get 
insight  into  the  mechanical  behaviour  of  each  phase,  Figure  53.  The  nanohardness  in  bainite 
decreases with the overaging temperature and, for long overaging times, declines more significantly 
as TOA rises, Figure 53a. The low-C martensite exhibits a similar nanohardness to the ones for the 
as-quenched specimens and short overaging times, whereas for longer ones, it increases remarkably, 
Figure 53b. As for high-carbon martensite, the hardest phase, the hardness grows with the overaging 
time  at  different  rates  depending  on  the  material  and  TOA,  Figure  53c.  The  nanohardness  of  the 
retained austenite does not evolve clearly with the experimental conditions, Figure 53d.  

Due to modelling requirements for the mechanical behaviour of the martensite phase, as described 
above,  some  extra  work  was  performed  on  new  steel  grades,  out  of  the  project,  with  martensitic 
structures and varying C  contents (0.06-1.0%), to determine the nanohardness calibration curve, 
Figure 54a that links the nanohardenss with the effective C percentage. The results show that, for 
short  overaging  times  and  regardless  of  the  temperature,  the  nanohardness  of  low-C  martensite 
does not vary and keeps at a level close to the nominal. Instead, only when the fraction of low-C 
martensite is below 10%, there is a significant increase in the C content, Figure 54b. Regarding high-
C martensite in MA phase, the amount of effective carbon ranges between 0.45% and 0.75% for the 
HiSi steel and 0.45% and 0.55% for the LoSi steel. It must be noted that some data corresponding 

Page 43 of 112 

 
 
 
 
 
 
 
 
 
 
to high-C martensite display very high nanohardness values, out of the range of the validity, which 
correspond to C contents above 0.75, Figure 54b. 

a) 

b) 

c) 

d) 

Figure 53. Evolution of the nanohardness of the various micro-constituents with the overaging time 
and temperature a) Bainite, b) Low-C martensite, c) High-C martensite in MA, d) RA. 

a) 

b) 

Figure 54. a) Evolution of the nano-, micro- hardness with the carbon content, b) Evolution of the 
effective carbon content with the amount of low-C martensite. 

3.2.2.  Mean field approach  

This modelling part corresponds to the application of a self-consistent mean-field model to model the 
tensile  curve  and  the  strain  hardening  of  the  bainite-based  AHSS  microstructures.  Existing 
microstructure-based  work  hardening  models  developed  in  previous  RFCS  projects  [30],  [31]  for 
single  and  two-phase  microstructures  have  been  the  base  for  this  modelling  work.  This  work 
addresses the following aspects: 

• 

• 
• 
• 

definition of the homogenization strategy to extend a previous mean-field micromechanical 
secant  method  formulation,  applicable  to  two  ductile  phases,  to  a  multicomponent 
microstructure; 
assessment of a pre-existing bainite work hardening model on the project steels; 
implementation of the TRIP effect into the mixed microstructure model; 
validation of the model. 

Page 44 of 112 

 
 
 
 
 
 
 
 
 
Definition of the homogenization strategy  

The selected homogenization approach based on micro-mechanisms proposed by Weng [32] applies 
to two-phase materials. Its generalization to microstructures containing more than 2 phases needs 
a stepwise method together with some strategy to be defined, implemented and validated. Assuming 
the steel microstructure is constituted by n phases, the stepwise method follows the next stages: 

1.  out  of  the  n  components,  select  2,  based  on  the  microstructural  distribution  and  relative 

strength; 

2.  select which one of these two is the soft (S) and which one is the hard (H) component; 
3.  select  the  characteristic  microstructural  parameters  of  H  and  S  that  are  needed  into  their 

respective microstructure-based work hardening models; 

4.  consider, if required, the interaction between H and S; 
5.  apply the Weng´s model using as input values the volume fraction of H and S and the individual 

microstructure-based work hardening models; 

6.  obtain the work hardening behavior for S+H mixed microstructure; 
7.  come back to point 1 and select a new micro-constituent to be taken together with (S+H); 
8.  define which one of these two becomes the soft and the hard constituent and go through points 

3 and 6 until all the n components have been incorporated. 

In Figure 55, the scheme of the strategy applied to the most complex structure, which consists of 
bainite, low-C martensite, high-C martensite in MA phase and retained austenite, is detailed. 

• Steel composition 
• Retained austenite (Dγ, %C, Fγ ) 
• High-Carbon martensite (FHα´ ) 
• Low carbon martensite (%C, FLα´ ) 
• Bainite (TOA, FB ) 

Figure  55.  Schematic  representation  of  the  multiphase  model  strategy  for  a  microstructure 
constituted by a bainitic+ thermal low-C martensite matrix and a dispersion of MA (austenite+high 
carbon martensite). 

The validation of such an approach requires a robust formulation of the mechanical behaviour of each 
micro-constituent. In particular, the bainite model was revisited and the TRIP model for the austenite 
to martensite transformation was also taken into account. 

Bainite model 

The bainite model developed in [31] has been applied with small variations. When confronted to the 
experimental bainite curves obtained in this project, it was observed that the work hardening was 
conveniently described, but the yield strength was too high. The analysis of these results indicated 
that the coefficient assigned to the solution strengthening due to the Mn (80MPa per 1%Mn) was too 
high. A lower coefficient similar to that one in Pickering´s equation seems more appropriate, leading 
to the following equation accounting for the friction stress and solution strengthening contribution 
(σ0) [33], [34]: 

=σ
0
B

77

+

32

Mn

+

678

P

+

83

Si

+

11

Mo

Eq. 9 

For the estimate of the yield strength of martensite, in addition to Eq.8, the contribution of the initial 
dislocation density  ρ0  has  been included as in [31].  The carbon content is connected to the initial 
dislocation density through the Ms temperature, according to Eq. 9 

Page 45 of 112 

 
 
 
 
 
 
 
 
 (T=Ms in Kelvin)  

         Eq. 10  

log(𝜌𝜌0) = 8.9372 +
TRIP model  

6880.3

𝑇𝑇 −

1780360
2

𝑇𝑇

The equations describing the strain hardening of austenite and the TRIP effect were taken from the 
work of Bouquerel et al. [35]. This model takes into consideration: 

• 
• 

the evolution of the fraction of strain induced martensite (fM); 
the evolution of the austenite grain size with applied strain (Dγ(ε)) due to the subdivision as 
a result of the martensite formation.  

The modelling of the strain induced austenite transformation to martensite applies the formulation 
proposed by Olson–Cohen [36] that leads to the following evolution expression: 

Mf

−=
ε
1)(

exp

[
−

(
β
1

−

exp(

−
εδ
)

]n
)

Eq. 11 

where  the  parameters β, δ  and  n  define  the  stability  of  the  retained  austenite.  The  expressions 
proposed in Ref. [31] relating β and δ to the steel composition for Si containing TRIP steels has been 
applied here and n has been taken equal to 2.   

The formation of strain induced martensite subdivides the retained austenite islands and modifies 
their effective grain size according to [31]: 

D
γ

ε
)(

=

3

D
γ
o

1

−

f

M

ε
)(

Eq. 12 

in which Dγo is the initial retained austenite grain size before deformation, leading to a deformation 
dependent austenite grain size. The change in the austenite grain size involves the shrinkage of the 
dislocation mean free path L in the Mecking-Kocks-Estrin work hardening formulation [31]: 

=−
1
L

1
εγ
D
)(

+

k

1

ρ

Eq. 13 

The strain dependent fraction of martensite, fM, also contributes to the strengthening of the mixed 
microstructure.  According  to  the  results  in  Ref.  [37],  it  can  be  assumed  that  this  high  carbon 
martensite deforms elastically and most of the strain partitions to the austenite. The graph in Figure 
56 shows an example of the predictions of this model for the data in [31]. 

Figure 56. Stress-strain curves of austenite and 
austenite plus TRIP and of the evolution of the 
strain induced martensite volume fraction. 

When applying the TRIP model to the BaseForm HiSi Vatron samples, it results that the yield strength 
used in Ref. [31] for austenite (220 MPa) was too low, leading to a large deviation at low strains 
between  the  model  predictions  and  the  experimental  curves.  Consequently,  the  equation  was 
modified taking into consideration the equation proposed by Pickering [38]: 
[
Mo
94.0

4.4(5.15

[
Si
3.1

MPa

46.0

[ ]
C

23

D

+

=

+

+

+

5.0

]

]

)

)

(

−

γσ

%2.0,

Eq. 14 

Using  the  same  solid  solution  contribution  than  in  Eq.  14  and  the  same  work  hardening  term  for 
austenite than that reported in Ref. [31] leads to more consistent results. 

In addition to the MA phase and bainite, athermal martensite has formed during the cooling. Results 
from  nano-indentation  indicate  that  for  microstructures  with  ≅  20%  low  carbon  martensite  (to 
distinguish it from the high carbon martensite in MA islands), is in the range of 0.22 to 0.28%. Higher 
fractions  of  martensite  lead  to  carbon  concentrations  not  far  from  the  nominal,  Figure  54b.  The 

Page 46 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
possibility of some additional hardening of the bainitic matrix due to the martensitic transformation 
has been also analysed and the conclusion has been that it is negligible.  

The  model  has  been  applied  to  both  steels,  Figure  57,  and  the  predictions  show  a  fairly  good 
agreement  with  the  experimental  curves,  even  though  complex  microstructures,  as  the  one 
corresponding  to  Figure  57b  (19%  Low-C  martensite,  8%  High-C  martensite  and  12%  RA),  are 
regarded.  

a) 

b) 

Figure  57.  Comparison  between  model  predictions  (dashed  lines)  and  experimental  curves 
(symbols)  for  a)  several  CAL  Vatron-LoSi  samples  and  b)  CAL  Vatron-HiSi  920°C/-
100°C/s/450°C/14s sample. 

3.2.3.  Crystal plasticity models 

At difference of the self-consistent models previously presented, crystal plasticity models describe 
material behaviour based on its microstructure, incorporating the effect of crystallographic texture 
and grain morphology, for example, and making possible to extrapolate previous results to different 
microstructures based on physical principles. However, because of this generality, crystal plasticity 
models  can  hardly  achieve  the  accuracy  of  phenomenological  models  in  specific  cases.  Moreover, 
crystal plasticity models are orders of magnitude more complicated, making much more difficult to 
implement  additional  aspects  of  material  behaviour  (for  instance,  the  plasticity  induced 
transformation of austenite  is easier to include in mean-field than in crystal plasticity models). 

Different  models  have  been  used  to  study  the  relationship  between  material  microstructure  and 
mechanical behaviour. While simpler models based on the Taylor-Bishop-Hill theory have been used 
for the study of the formability dependence on crystallographic texture and develop an optimization 
algorithm to find the optimal texture for deep-drawing applications, the Visco-Plastic Self-Consistent 
(VPSC) model has been used to study how microstructural parameters affect the strain hardening of 
the material. Additionally, the VPSC model was used for the study of damage initiation, as explained 
in section 4.2. 

Texture optimization has been performed first developing an incremental optimization method, based 
on the gradient descent algorithm. The method works finding the ODF which optimizes the q-values 
predicted by Taylor-based models. More precisely, the objective of the method is to find the set of 
C-coefficients  [39]  for  which  the  average  of  the  q-values  in  different  on-sheet  directions  (
) 
)  approaches  zero,  which  correspond  to  optimal 
approaches  one  and  their  standard  deviation  (
deep-drawing  formability properties.  The q-values  are  calculated  using the  full-constraint  (Taylor) 
𝜎𝜎𝑞𝑞
and relaxed constraints (“pancake”) versions of the harmonic method by Van Houtte [40], [41]. 

𝛼𝛼𝑞𝑞

After asserting the validity of the method with typical BCC and FCC textures [42], it has been applied 
to the optimization of two textures of LoSi and HiSi steels studied in the project. The optimization is 
performed for the BCC texture of the material, without making any distinction between the different 
BCC phases (bainite and martensite). The evolution of the average and standard deviation of the q-
values with respect to the variation of the initial ODF after 500 optimization steps is presented in 
Figure 58. It is observed that both textures show a significant formability improvement from initial 
values between 0.450 and 0.500 to almost 0.800. Moreover, the standard deviation is reduced below 
the specified tolerance of 0.001. 

Page 47 of 112 

 
 
 
 
Figure 58. Average and standard deviation of the q-values with respect to the variation of the initial 
ODF using the Taylor and pancake models. 

Some of the textures obtained at different points of the optimization process, as well as the initial 
textures considered, are displayed in Figure 59. The initial textures show the typical alpha-gamma 
fibre texture characteristic of cold-rolled products, with a maximum intensity lower than 3 random 
units. However, as the optimization progresses, the alpha-fibre gradually disappears and the texture 
becomes dominated by a much stronger gamma fibre, with intensities close to 18 random units in 
the last optimization steps. 

In order to obtain the textures in Figure 59, each optimization step, the gradient of the average and 
standard deviation of the q-values is calculated and used to find an increment with respect to the 
original texture. Figure 60 shows these gradients (
) for the orientations in the 
),  after  one  and  five  optimization  steps.  The 
section,  as  well  as  the  corresponding  increment  (
∘
gradients show the texture components for which the highest variation is obtained, and therefore 
will affect formability in a higher degree. The calculated increments clearly show that, in these first 
steps, the optimal increment does not exactly correspond with a reinforcement of the gamma-fibre. 
Instead, it is a better strategy to diminish the components which are having a negative influence on 
the formability of the material. These components subtly vary from one material to another and also 
between different optimization steps, even although all the textures are relatively similar. 

∇𝛼𝛼𝑞𝑞
∆𝑔𝑔

𝜑𝜑2 = 45

 and 

∇𝜎𝜎𝑞𝑞

The optimal textures found (Figure 59) prove an already well-known fact: that optimal formability 
properties  are  obtained  with  a  strong  gamma  fibre  texture.  However,  as  shown  in  Figure  60,  the 
optimization method provides additional information about how to reach this optimum incrementally 
in  the  most  efficient  way.  Therefore,  the  value  of  the  method  is  that  it  can  be  useful  to  provide 
indications to steel producers in order to obtain materials with better forming properties. Moreover, 
it  sets  a  basis  for  the  development  of  more  complicated  optimization  schemes  directed  towards 
optimizing specific materials and forming processes. 

In addition to using Taylor models to optimize crystallographic texture, the VPSC model [43], [44] 
was employed to study the effect of several microstructural parameters on the mechanical response 
of the material. The original VPSC model has been extended with a physical hardening law that takes 
into  account  chemical  composition,  dislocation  density,  grain  size,  the  presence  of  carbides,  and 
other  microstructural  parameters  to  determine  the  resolved  shear  stress  in  each  slip  plane.  This 
extended model was then used to simulate the behavior of LoSi materials. 

Page 48 of 112 

 
 
 
 
Figure 59. Initial textures (at left) and optimized textures using the Taylor and pancake models 
after, respectively, 5, 50, 200 and 500 optimization steps. 

Figure 60. Gradients of the average and standard deviation of the q-values and increment of 
texture for the first and the fifth optimization steps for LoSi and HiSi materials. 

The  VPSC  model  offers  a  solution  to  the  simulation  of  deformation  processes  in  polycrystalline 
materials under an arbitrary set of loading conditions using a multiscale approach. It also predicts 
what will be the microstructural evolution resulting from the process. Using a homogenization scheme 
based in the solution of an Eshelby inclusion problem for each grain, the model takes into account 
the influence of phase fraction, crystallographic texture and grain morphology. At the grain level, the 
behavior  is  determined  by  its  crystal  structure  and  a  hardening  law  for  each  slip  system.  The 
hardening law used in this work is based in the model by Leon-Garcia [45], which is an extended 
version of the model by Pantleon [46]. 

The critical resolved shear stress (CRSS) of each slip system, 
terms: a static yield stress 
between dislocations on all slip systems. 

, is expressed as the addition of two 
 and a second component related to the flow stress due to the interaction 

(𝑠𝑠)

𝜏𝜏

𝜏𝜏0

(𝑠𝑠)

𝜏𝜏

= 𝜏𝜏0 + 𝛼𝛼𝛼𝛼𝑏𝑏�∑

𝑁𝑁𝑁𝑁𝑁𝑁
𝑠𝑠′=1

(𝑠𝑠)

′

𝜌𝜌

ℎ𝑠𝑠𝑠𝑠

Eq. 15 

Page 49 of 112 

 
 
 
 
 
 
 
 
 
 
 
While the first term is correlated with solid solution hardening and therefore chemical composition, 
the second one depends on the evolution of dislocation density 
, which is calculated integrating 
the expression: 

(𝑠𝑠)

(𝑠𝑠)

𝜌𝜌

Eq. 16 

(𝑠𝑠)

�
𝑦𝑦𝜆𝜆

𝜋𝜋

(𝑠𝑠)

�
𝜆𝜆

(𝑠𝑠)

=

1
(𝑠𝑠)

𝑏𝑏 −

2𝑦𝑦
𝑏𝑏 𝜌𝜌

𝑑𝑑𝜌𝜌
𝑑𝑑𝛾𝛾
The  three  terms  at  the  right-hand  side  of  this  equation  account  for  dislocation  storage,  dynamic 
recovery  and  the  evolution  of  geometrically  necessary  dislocations  (GNDs),  respectively.  Both 
dislocation storage and GNDs evolution depend on the mean free path 

, calculated as: 

�𝐶𝐶2 − 2𝜎𝜎𝑚𝑚𝑚𝑚𝑏𝑏

+

(𝑠𝑠)

2𝑏𝑏

𝛾𝛾

�

2

2

1
(𝑠𝑠)

1
𝑑𝑑𝑔𝑔 +

1
𝑁𝑁𝑁𝑁𝑁𝑁
′
𝑠𝑠
=1
𝛽𝛽 �∑

′

(𝑠𝑠)

𝑐𝑐𝑝𝑝
𝑣𝑣𝑝𝑝𝑑𝑑𝑝𝑝

ℎ′𝑠𝑠𝑠𝑠
Which in addition to dislocation density, depends on grain size and the amount and size of carbides 
present in the phase [47]. 

+

=

𝜌𝜌

�
𝜆𝜆

(𝑠𝑠)

�
𝜆𝜆

Eq. 17 

The material has been modeled assuming that it is composed of two different phases: bainite and 
martensite.  Both  phases  are  assumed  to  have  the  same  BCC  crystal  structure,  although  their 
behaviors  differ  because  of  the  different  microstructural  parameters  (carbon  content,  lath  width, 
amount and size of carbides, crystallographic texture, etc.). Since the amount of austenite present 
in the LoSi steel grades studied is very low, it was neglected. This is very convenient since, although 
the  model  can  effectively  simulate  the  behavior  of  austenite  when  it  is  deformed,  the  plasticity 
induced  transformation  into  martensite  has  not  been  incorporated  (this  is  the  reason  for  HiSi 
materials not being modelled with the VPSC approach). The microstructural parameters used in the 
simulations are shown in Table 14, together with the source where they were taken from. 

Table 14. Physical parameters used in the VPSC model. 

Parameter 

Source 

Chemical composition 

Section 1.1.1 

Phase fraction 

LOM/SEM/EBSD (Section 3.1.2) 

Grain size 

Lath width 

Carbides size and volume fraction 

Carbon content 

Phase diagram 

Initial dislocation density 

EBSD (Section 4.1.3) 

The parameters that cannot be directly measured from experimental observations were fitted using 
a Levenberg–Marquardt algorithm (LMA) and tensile curves from experiments (section 3.1.1). Two 
quasi-static  tensile  experiments  in  the  rolling  direction  of  the  sheet,  and  two  in  the  transversal 
directions,  were  used  for  the  fitting.  The  parameters  obtained  are  shown  in  Table  15,  while  the 
obtained  tensile  curves  are  compared  with  the  experimental  data  in  Figure  61.  Fitting  of  model 
parameters using experimental data from tensile tests at two different directions for four different 
LoSi bainitic steels. Data points from two different experiments for each material and direction are 
shown  with  dots,  while  the  result  of  the  model  is  displayed  using  continuous  lines.  The  R-square 
value obtained from the fitting was of approximately 0.88 for the material with TA of 920°C, and of 
0.96 for the one with TA of 820°C. 

Table 15. Fitted model parameters: 
fixed to 0.5, 
 and 
constants 
𝑦𝑦
present in the bainite phase). 

 is the annihilation distance, 

𝐶𝐶1

 to stage IV hardening and 

𝛽𝛽

𝐶𝐶2

2
𝜎𝜎𝑚𝑚𝑚𝑚𝑏𝑏

 is related with yield stress, 

, from the Taylor equation, is 

 is related to the structure of the dislocations, the 
 depends on the shape of the carbides (only 

𝛼𝛼

920°C/-
𝐜𝐜𝐜𝐜𝐜𝐜𝐜𝐜𝐜𝐜
100°C/s/450°C/120s  
820°C/-
100°C/s/450°C/120s 

Phase 
Bainite 
Martensite 
Bainite 
Martensite 

5.610 
𝐂𝐂𝟏𝟏(−)
8.286 
5.120 
6.347 

𝐶𝐶𝑝𝑝
0.5 
𝛂𝛂(−)
0.5 
0.5 
0.5 

8.382 
𝐜𝐜(𝐧𝐧𝐧𝐧)
15.907 
6.423 
14.762 

129.96 
𝛃𝛃(−)
203.55 
80.33 
147.49 

−𝟐𝟐

0.01239 
𝐂𝐂𝟐𝟐(𝛍𝛍𝐧𝐧
)
0.05813 
0.01449 
0.01398 

0.00000 
𝟐𝟐
−𝟐𝟐
𝛔𝛔𝐢𝐢𝐧𝐧𝐢𝐢
)
(𝛍𝛍𝐧𝐧
0.69308 
0.00000 
0.30120 

3.361 
𝐂𝐂𝐩𝐩(−)
- 
3.130 
- 

Once  the  model  parameters  were  properly  fitted,  it  was  possible  to  use  the  model  to  make 
predictions. With the goal of finding how different microstructural parameters affect the behaviour 

Page 50 of 112 

 
 
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
of  the  material  according  to  the  model,  different  simulations  were  run  in  which  the  value  of 
microstructual  parameters  varied.  More  precisely,  the  parameters  studied  were  the  fraction  of 
martensite present in the material, the dislocation density and lath width of bainite, and the fraction 
of carbides present or its size (both parameters have exactly the same effect). Figure 62 shows how 
each of these parameters influence the tensile behaviour of one of the LoSi materials. In each of the 
figures, the fitted curve is compared with the results of two other simulations: in one of them, the 
value of a microstructural parameter is doubled (200 %). In the other one, it is halved (50 %). 
The obtained simulation results can be compared with the experimental results analysed in section 
3.1.1.  It  is  seen  that  increasing  the  amount  of  martensite  produces  an  increment  of  strength,  as 
expected.  However,  the  effect  of  grain  size  is  not  so  well  captured.  While  it  is  observed  in  the 
experiments that yield stress increases with lower grain sizes, it only has influence on the hardening 
behaviour in the simulations, but not on yield stress. Nevertheless, when combined with the effect 
of  initial  dislocation  density  (higher  in  the  materials  with  lower  grain  size),  the  results  of  the 
simulation show a good correspondence with experimental results.  

Figure 61. Fitting of model parameters using experimental data from tensile tests at two different 
directions for four different LoSi bainitic steels. Data points from two different experiments for each 
material and direction are shown with dots, while the result of the model is displayed using 
continuous lines. 

Figure 62. Influence of microstructural parameters on tensile behaviour. Top-left: martensite 
fraction; top-right: bainite lath size; bottom-left: bainite dislocation density; bottom-right: fraction 
or size of carbides in bainite. 

Page 51 of 112 

 
 
 
 
3.2.4.  Models integration (transformation models will be coupled to 

micro-mechanical and crystallography based models) 

The final goal of this task is the integration of a cellular automata model for phase transformation 
(CASIPT) [48] with advanced crystal plasticity models in order to be able to study the combination 
of all the thermal and mechanical processes that take place during the production of steel. This is an 
extremely ambitious goal, and in particular making possible to completely simulate the formation of 
the  bainitc  steels  under  study  would  require  numerous  modifications  to  the  model  (not  only  the 
formation of bainitc phases, but also the formation of martensite is problematic, and crystallographic 
considerations cannot be neglected).  As part of this effort, which is being performed in collaboration 
between  different  projects,  the  work  in  Baseform  has  been  focused  on  the  integration  of 
crystallographic aspects of phase transformations in the CASIPT model, which previously ignored the 
effects of crystal orientation. 

Crystallographic  considerations  are  of  extreme  importance  in  phase  transformation  processes,  as 
well  as  in  crystal  plasticity  modelling.  Fully  integrating  both  modelling  approaches  will  certainly 
require that crystallographic aspects are taken into account in the CASIPT model. 

With regard to the role of crystallography in Fe-γ to Fe-α transformations, it has already been shown 
in  previous  works  [49]  that  the  occurrence  of  a  double  Kurdjumov-Sachs  (DKS)  orientation 
relationship [50] for a ferrite grain nucleating at a grain boundary of the parent austenite structure, 
strongly  favours  the  nucleation  rate,  as  the  double  coherent  interface  of  the  newly  formed  phase 
boundary drastically reduces the phase boundary energy. This condition implies a variant selection 
rule, as only one out of the 24 possible variants will comply with the requirement of approaching a 
DKS orientation relation. Therefore, the DKS relationship not only influences the nucleation rate at 
different boundaries, but also determines the orientation of the product grains and, consequently, 
the transformation texture. 

In order to study the effect of crystallographic orientation in the phase transformation process, an 
orientation  is  assigned  to  each  grain.  This  orientation  is  used  to  determine  nucleation  probability 
based on the orientation relationships between neighboring grains, assuming that nucleation has a 
larger probability for the boundaries for which the grains are closer to a DKS orientation relationship, 
following a normal probability distribution. The KS variant for which the misorientation with respect 
to any KS variant of the neighbor grain is minimal is chosen as the orientation of the new grain. 

The  CASIPT  model  enhanced  with  crystallographic  orientations  has  been  applied  to  the  study  of 
ferritic transformations for several typical austenite initial textures. In all the simulations, an initial 
fully  austenitic  2D  microstructure,  generated  by  the  Voronoi  cell  method,  with  the  chosen  input 
texture, is cooled down from an initial temperature of 800ºC at a cooling rate of 1K/s during 300s, 
in order to induce the γ-to-α transformation. An example of the microstructural changes during the 
simulation is shown in Figure 63. 

Figure 63. An initial Fe-γ microstructure (in orange) is cooled down from 800ºC to 600 ºC during 
300s, leading to the formation of Fe-α (in blue). 

The first texture studied is a random texture, in which all possible crystal orientations have a uniform 
probability.  The  study  of  the  random  texture  allows  to  verify  that  the  assignment  of  initial 
crystallographic  orientations  indeed  is  truly  random,  and  is  not  affected  by  any  simulation 
parameters,  such  as  the  number  of  grains.  Figure  64  and  Figure  65  compare  the  theoretical 
distributions of misorientations between neighbour grains and of misorientations with respect to an 
ideal DKS orientation relationship and the distributions obtained in the model for different number of 
grains. Figure 64 shows that the misorientations distribution in the model matches almost perfectly 
the theoretical Mackenzie distribution for the higher number of grains, 14062, while some small but 
acceptable deviations are observed for 5062. When only 562 grains are used, the distribution starts 

Page 52 of 112 

 
 
 
diverging from the theoretical one, although it still follows a very similar trend. Similar results are 
observed for the distance to a DKS orientation relationship in Figure 65 although, in this case, even 
for the smallest number of grains, the differences with respect to the theoretical distribution are very 
low. In addition to the distributions of misorientations, the ODF of the texture assigned to the model 
is  shown  in  Figure  66,  for  the  model  with  5062  grains.  As  it  can  be  observed  in  the  figure,  the 
intensities of the ODF are always in the vicinity of one, which is the value corresponding to an ideal 
random texture. 

Once it has been stablished that the initial orientations are correctly assigned, it is possible to use 
the model to make predictions regarding the Fe-α product texture obtained after cooling. Figure 66 
shows the obtained texture together with the initial one. It is clearly seen that the obtained product 
texture, according to expectations, is also a random texture. 

Figure 64. Distribution of misorientations between pairs of grains in three simulated 
microstructures with different number of grains (left) and theoretical Mackenzie distribution (right). 

Figure 65. Distribution of misorientations with respect to a DKS orientation relationship between 
pairs of grains in the three simulated microstructures (left) and theoretical (right). 

The  random  texture,  although  interesting  from  a  theoretical  point  of  view,  does  not  show  the 
influence of variant selection on the transformation texture. In order to check if the model is correctly 
predicting the orientation of the product grains, the case of a strong cube texture for Fe-γ has been 
studied. This texture is typically obtained after recrystallization, and therefore commonly found in 
steel products. It is well known that, applying a single KS orientation relationship to the original cube 
texture,  a  product  texture  with  rotated  cube,  Goss  and  rotated  Goss  components  of  the  same 
intensity  is  obtained.  However,  experiments  have  shown  that,  as  a  consequence  of  the  variant 
selection rule, the intensities of these components should be different. Figure 67 shows that, using 
the CASIPT model, different intensities are indeed obtained for each of these components. 

Work  on  the  CASIPT  model,  including  crystallographic  aspects  and  its  integration  with  crystal 
plasticity models, will continue in other projects such as the 3D-Micro project by M2i and the DENS 
(Digitally-Enhanced New Steels) project being carried out by Tata Steel Europe. The results obtained 
in the Baseform project are already being used in these projects and it is expected that the modified 
model presented here will serve as a strong basis for future work. 

Page 53 of 112 

 
 
 
 
 
 
Figure 66. ODF of parent austenite phase (left) and ferritic product texture (right) for the 
simulation with a microstructure of 5062 grains. 

Figure 67. Initial austenitic texture with a strong cube component and ferrite product texture with a 
(weak) rotated cube component and weaker Goss and rotated Goss components. 

Page 54 of 112 

 
 
 
 
 
 
3.3. Conclusions 

Processing parameters-mechanical properties-microstructure relationships (Cold rolled materials) 

a)  The main processing parameters that control the microstructure and, thus, the mechanical 
behaviour  for  the  applied  annealing  treatments  are  the  overaging  TOA  and  tOA.  Annealing 
temperature and final cooling rate to RT affect the mechanical properties to a lesser extent. 
b)  The YS and the TS are chiefly affected by both the bainite lath size/dislocation density and 
fraction of secondary phases. The overaging temperature influences the lath size, whereas 
the overaging time greatly affects the 2ry phase fraction.  

c)  Martensitic  phases  enhance  YS  and  TS  but  neatly  impairs  HEC.  Martensitic  phases  appear 
due to short tOA and/or an insufficient stabilization of the austenite during overaging upon 
further cooling to room temperature. 

d)  The  residual/retained  austenite  involves  a  noticeable  improvement  in  the  ductility  and 
bending.  Its  effect  on  the  HEC  parameter  appears  to  be  negative  due  to  its  mechanically 
unstable character (TRIP effect). Its influence on YS/TS cannot be separated experimentally 
from the effects of other parameters. 

Mean-field approach 

a)  The  formulation  based  on  Weng´s  micro-mechanical  model,  which  applies  to  two-phase 
materials,  has  been  extended  to  multicomponent  AHSS  steels  with  the  help of  a  stepwise 
homogenization  method.  This  stepwise  method  takes  into  account  the  microstructural 
distribution and relative strength of the micro-constituents. 

b)  Some modifications of the single-phase models for the yield stresses of bainite, martensite 
and austenite with regard to those proposed in previous RFCS projects [31] and Bouquerel 
et al. [35] have been needed. Instead, the work hardening models, already available, are 
valid for these AHSS bainitic matrix steels. 

c)  A  TRIP  model  has  been  implemented  according  to  the  formulation  proposed  in  [31].  This 
model  integrates  the  Olson-Cohen  strain  induced  martensite  formation  and  the  austenite 
grain refinement produced by the nucleation of the martensite plates. 

d)  The  mean-field  model  and  the  application  of  the  stepwise  methodology  provide  a  good 

description of the mechanical behavior of the AHSS microstructures developed in this project.   

Crystal plasticity models 

a)  A crystallographic texture optimization method has been presented, capable of finding the 
texture for which formability properties of the material are optimized. Moreover, the method 
provides useful information for steel producers about how to reach the optimum in the most 
efficient manner. 

b)  Applying the optimization method to the textures of the materials studied in the Baseform 
project showed that ideal conditions are met when the texture approaches a strong gamma 
fiber  texture.  However,  the  path  towards  this  optimum  has  some  differeces  for  different 
materials. 

c)  The VPSC model has been extended with a physical hardening law that takes into account 
numerous material parameters such as chemical composition, dislocation density, and the 
presence of carbides. 

d)  Using a fitting algorithm and experimental data, the model parameters have been fitted for 
the  steels  studied  in  this  project.  A  good  match  between  experiments  and  simulations  is 
observed.  The  model  has  also  been  used  to  study  the  effect  of  different  microstructural 
parameters on the mechanical behavior of the material. 

Models integration 

a)  The  concept  of  crystallographic  orientations  has  been  introduced  in  the  CASIPT  phase 
transformation model, making possible to consider its effect on ferrite nucleation and predict 
transformation textures in Fe-γ to Fe-α transformation processes. This is an essential task in 
order to fully integrate the CASIPT model with crystal plasticity. 

b)  The modified model can successfully assign initial orientations to reproduce a specified input 

texture, as well as of calculating the texture obtained after transformation. 

Page 55 of 112 

 
 
 
 
Page 56 of 112 

 
 
4. Damage 

Understanding  the  micro-mechanisms  of  damage  initiation  during  plastic  deformation  is  a  key  to 
further  mechanical  properties  enhancement.  In  this  project,  damage  initiation  micro-mechanisms 
were studied in bainitic multiphase steels with a more focus on the LoSi grade. For this purpose, two 
samples with the following annealing parameters: TAN=920 TOA=450 tOA~120 and TAN=820  TOA=450 
tOA~120  were  chosen.  Eventually  microstructures  consist  of  bainitic  matrix  and  martensite  as  a 
second  phase  constituent,  however,  carbide  precipitates  were  also  observed.  This  study  was 
conducted  by  experiments  and  using  Visco-Plastic  Self-Consistent  (VPSC)  modelling.  Section  4.1 
focuses  on  the  results  obtained  from  experimental  work,  which  is  divided  to  two  disciplines  of 
crystallographic orientation and topological aspects leading to damage initiation. The details of the 
experimental  works  and  results  are  present  in  [51],  [52].  In  section  4.2,  crystal  plasticity  based 
model of VPSC is integrated with the experimental work of section 4.1, in order to predict the damage 
initiation spots in the crystallographic orientation (Euler) space.  

4.1. Experimental 

4.1.1.  Crystallographically resolved damage initiation 

In order to study the role of crystallographic orientation on damage initiation, an electron backscatter 
diffraction (EBSD) based analysis is used to capture the orientations around the voids in TAN=920 
TOA=450 tOA~120 (LoSi). Afterwards, textures were compared in order to understand the correlation 
between  damage  and  crystallographic  orientation.  For  this  purpose,  33  voids  were  analyzed.  The 
selection  procedure  is  schematically  represented  in  Figure  68.  Later,  the  ODF  was  derived  from 
approximately 131,000 void neighbouring pixels, represented in the ϕ2 = 45° section of Euler space 
and  denominated  the  VODF  (Void  ODF),  cf.  Figure  69b.  Because  on  the  level  of  individual  voids, 
sample symmetry has to be ignored and thus the Euler space limits are set to 0 < ϕ1 < 360° and 0< 
ϕ2, Φ < 90. Similarly, also the texture was considered of the regions with no voids, which produces 
the  No-Void  ODF  (NVODF),  cf.  Figure  69c.  It  is  expected  that  regions  with  no  voids  have  more 
dispersed orientations compared to regions selected around the voids. Therefore, after merging all 
of  these  orientations  away  from  the  voids,  the  No-Void  ODF  (NVODF)  plot  reveals  smoother 
distribution.  

Figure 68. Schematic illustration of orientation selection on an overlapped image quality and 
inverse pole figure map; (a) complete area of analysis (Neck-IPF), (b) area selected around the 
void with faces approximately equal to 3 times of a void diameter (Void-IPF) and (c) remaining 
area (No void-IPF). 

Figure  69  shows  the  textures  in  the  ϕ2=45°  section  of  the  material  at  two  different  strain  levels, 
uniform and post uniform, respectively. By visually comparing the VODF and NVODF with respect to 
the Neck-ODF it is observed that the NVODF closer resembles the texture observed in the necked 
region (Neck-ODF). Conversely, by visually comparing VODF and NVODF with the uniform texture, it 
appears that the VODF better resembles the uniform ODF. This can be explained by the fact that the 
local stress relaxation process at a certain moment is occurring by the void initiation rather than by 
plastic deformation accommodated by dislocation glide. Upon further macroscopic deformation, two 
micro-mechanisms can dissipate the local stress concentration produced by the presence of a void, 
i.e. void growth and/or local further plasticity surrounding the initiated void. The results from the 
comparison between UODF, VODF and Neck-ODF demonstrate that after voids were formed, the local 
stress dissipation process around voids is rather governed by void growth than local plasticity as the 
Void-ODF clearly resembles the uniform ODF. Nevertheless, a void is nothing but a free surface within 
the  microstructure,  which  may  relax  the  local  constraint  of  the  surrounding  grains  and  thus  can 
potentially ease the local plastic deformation. However, the competing role of the locally hardening 
and free surface lead to the final contribution of plasticity and/or void growth on the stress relaxation. 

Page 57 of 112 

 
 
 
 
Figure 69. φ2=45° section of ODFs of the material at two different deformation levels; (a) Uniform 
deformation UODF (calculated from 796000 data points), (b) post uniform VODF (131000 data 
points), (c) post uniform NVODF (460000 data points) and (d) Necking or post uniform ODF consist 
of the merged ODFs in b and c. 

4.1.2.  Effect of topology on damage initiation 

This section presents the analysis of the role of martensite bands as meso-scale heterogeneities on 
micro-mechanisms of damage initiation. In order to achieve this goal, first, two samples introduced 
in the section 5 were characterized by Scanning Electron Microscope (SEM) equipped with Electron 
Back-scatter  Diffraction  (EBSD)  detector.  Martensitic  bands  and  their  micro-segregations  were 
characterized by SEM imaging and Electron Probe Microanalysis (EPMA). Micro-hardness tests were 
conducted  to  assess  the  topological  effect  of  bands,  as  meso-scale  heterogeneities,  on  their 
mechanical contrast with respect to the matrix. After uniaxial tensile tests, a quantitative analysis of 
the damage sites was conducted by image processing of SEM micrographs. 

Comprehensive SEM imaging through the thickness along the ND direction showed the presence of 
martensite  bands  parallel  to  the  RD  direction  in  the  bainitic  matrix  of  both  CAL  820°C/-
100°C/s/450°C/120s and CAL 920°C/-100°C/s/450°C/120s samples. Figure 70 (a and c) shows two 
SEM  micrographs  of  CAL  820°C/-100°C/s/450°C/120s  and  CAL  920°C/-100°C/s/450°C/120s  
samples, respectively. Bands are shown by arrows. The EPMA analysis (see Figure 70e) perpendicular 
to the bands, as depicted in Figure 70a, illustrates the micro-segregation of Mn in these bands. It is 
observed that in CAL 920°C/-100°C/s/450°C/120s  sample, the number of visible bands through the 
thickness is higher compared to the CAL 820°C/-100°C/s/450°C/120s  sample. Thermodynamically, 
the coarser prior austenite grain size leads to a lower nucleation rate and/or slower kinetics of bainite 
transformation,  particularly  in  the  banded  regions.  The  CAL  920°C/-100°C/s/450°C/120s    sample 
reveals a coarser topology with larger distance between MA blocks while the bands in the CAL 820°C/-
100°C/s/450°C/120s  sample are more fragmented due to a more complete bainite transformation 
in these regions. EBSD analysis also confirms the topological differences of the bands between both 
samples, in which CAL 920°C/-100°C/s/450°C/120s  sample exhibits coarser networks of martensite 
bands along RD. Figure 70b and d show their corresponding image quality overlaid with phase maps, 
whereby  dark  bands  with  low  IQ  value  are  more  apparent  in  CAL  920°C/-100°C/s/450°C/120s  
sample. The schematic illustration of the band topologies of the CAL 920°C/-100°C/s/450°C/120s  
and  CAL  820°C/-100°C/s/450°C/120s    samples  is  shown  in  Figure  70  (f  and  g).  The  fraction  of 
retained austenite in both samples is less than 0.5%, due to the low silicon content in this bainitic 
steel.  

Page 58 of 112 

 
 
Figure  70.  Microstructure  characterization  of  both  samples.  CAL  920°C/-100°C/s/450°C/120s  
sample:  (a)  SEM  micrograph  where  the  dashed  rectangle  indicates  the  location  of  the  EBSD 
analysis.  The  solid  arrow  is  the  position  of  the  EPMA  line  analysis,  (b)  overlaid  IQ  and  phase 
maps (solid white arrows show dark bands with low IQ value). CAL 820°C/-100°C/s/450°C/120s  
sample: (c) SEM micrograph, (d) overlaid IQ and phase maps. (e) EPMA chemical analysis with 
four arrows corresponding to the bands in TAN= CAL 920°C/-100°C/s/450°C/120s  sample show 
in  (a)  and  (f  and  g)  schematic  illustration  of  the  bands  topology  of  CAL  920°C/-
100°C/s/450°C/120s  and CAL 820°C/-100°C/s/450°C/120s  samples, respectively. 

Micro-hardness measurements along ND and RD are represented in Figure 71a and b respectively. 
Figure 71a includes the schematic illustration of micro indentation through the thickness (along ND) 
in  both  samples.  The  dark  regions  represent  the  MA  bands  along  RD  and  the  background  white 
medium  represents  the  bainitic  matrix  including  auto-tempered  martensite  (ATM).  Comparing  the 
Vickers  micro-hardness  profile  of  CAL  920°C/-100°C/s/450°C/120s 
  and  CAL  820°C/-
100°C/s/450°C/120s  samples in Figure 71a, it is observed that CAL 920°C/-100°C/s/450°C/120s  
sample  shows  more  spread  in  micro-hardness  values  compared  to  TAN=820    TOA=450  tOA~120 
sample. This is observed by subtracting the first and third quartile of the box plots, interquartile rang 
(IQR), which in the case of CAL 920°C/-100°C/s/450°C/120s  sample is 61 HV and it is approximately 
2.3 times higher than IQR of CAL 820°C/-100°C/s/450°C/120s sample. The red line within the box 
plot is the median value. This value is lower in CAL 920°C/-100°C/s/450°C/120s  sample compared 
to CAL 820°C/-100°C/s/450°C/120s  sample due to its coarser microstructure. The whiskers of the 
micro-hardness  profile  represent  the  maximum  and  minimum  values  of  the  measurement  points, 
while the outliers are the data points of which the values exceed 1.5 * IQR from the first and third 
quartiles  of  the  box  plot.  In  Figure  71b,  the  micro-hardness  results  along  RD  are  shown  on  two 
locations within the microstructure corresponding to a matrix and a martensitic band. The box plots 
corresponding  to  the  matrix  of  both  samples  demonstrate  identical  median  values  of  438 HV. 
However,  the  spread  of  the  data  is  higher  in  CAL  920°C/-100°C/s/450°C/120s    sample,  while 
relatively  lower  hardness  values  are  observed  compared  to  CAL  820°C/-100°C/s/450°C/120s  
sample.  Considering  the  bands  in  both  samples,  it  is  clearly  observed  that  CAL  920°C/-
100°C/s/450°C/120s    sample  exhibits  higher  Vickers  hardness  values  and  simultaneously  higher 
spread. The median difference of the bands hardness between two samples is 58 HV. The mechanical 
contrast  of  these  two  regions,  bands  and  matrix,  is  compared  by  their  median  difference  in  both 

Page 59 of 112 

 
 
 
samples,  whereby  it  is  27  and  85 HV  in  CAL  820°C/-100°C/s/450°C/120s    and  CAL  920°C/-
100°C/s/450°C/120s  samples, respectively. CAL 820°C/-100°C/s/450°C/120s  sample showed less 
contrast between bands and the matrix caused by the fragmentation and finer topology of the bands 
(see Figure 70d and g). The interaction of the finer MA phase interrupted by the adjacent soft matrix 
with  the  indenter  leads  to  a  relatively  lower  hardness  values  of  bands  in  CAL  820°C/-
100°C/s/450°C/120s  sample, compared to CAL 920°C/-100°C/s/450°C/120s  sample. The bands in 
CAL 920°C/-100°C/s/450°C/120s  sample revealed higher scatter in the hardness value compared 
to the bands in CAL 820°C/-100°C/s/450°C/120s  sample. This is due to the fact that the indentation 
along the band occasionally are located either in the soft matrix between two separated coarse MA 
blocks or in a coarse MA block (see Figure 70b and f). 

Figure 71. Box plot of micro-hardness measurements of low and high temperature samples: (a) 
Vertical micro-hardness profile of the CAL 820°C/-100°C/s/450°C/120s  and CAL 920°C/-
100°C/s/450°C/120s  samples austenized at 820 and 920°C performed with 10 gf load 
(Indentation is conducted every 50 µm), and (b) Horizontal micro-hardness measurements on the 
martensitic bands and the matrix of both samples loaded with 5 gf.  

Table  16  summarises  the  tensile  properties  of  both  CAL  920°C/-100°C/s/450°C/120s    and  CAL 
820°C/-100°C/s/450°C/120s  samples. It is observed that necking starts at earlier stage in TAN=920 
TOA=450 tOA~120 sample. In addition, it is seen that CAL 920°C/-100°C/s/450°C/120s  sample has 
lower fracture strain compared to CAL 820°C/-100°C/s/450°C/120s  sample. 

Table 16. Tensile properties of the high and low temperature samples along the RD. 

Samples 

Yield 
stress 
[MPa] 

Tensile 
strength 
[MPa] 

Uniform 
elongation 
(%) 

Total 
elongation 
(%) 

Fracture 
strain 
(%) 

CAL 920°C/-100°C/s/450°C/120s 

743 ± 9 

874 ± 9 

5.0 ± 0.14 

5.35 ± 0.07 

112 ± 5 

CAL 820°C/-100°C/s/450°C/120s 

817 ± 2 

933 ± 14 

6.1 ± 0.14 

12.20 ± 0.56 

118 ± 9 

CAL 820°C/-100°C/s/450°C/120s  sample showed relatively considerable post necking deformation 
compared  to  CAL  920°C/-100°C/s/450°C/120s    sample.  This  can  be  explained  by  the  particular 
microstructure  of  TAN=820  TOA=450  tOA~120  sample,  i.e.  the  interrupted  and  more  dispersed 
networks  of  MA  bands  within  the  soft  matrix  accommodates  more  homogeneously  the  plastic 
deformation  compared  to  TAN=920  TOA=450  tOA~120  sample.  However,  the  microstructure  of  CAL 
920°C/-100°C/s/450°C/120s  sample shows coarser bands and the distance between adjacent MA 
blocks  along  the  band  is  also  larger.    This  resulted  in  the  earlier  deformation  localization  and 
macroscopic 
in  TAN=920  TOA=450  tOA~120  sample  compared  to  CAL  820°C/-
100°C/s/450°C/120s  sample. This is in line with the study of Tasan et al. and de Guess et al. [53], 
[54] in which a homogeneous distribution of fine martensite phase within a soft ferrite matrix resulted 
in a higher strain hardening capacity and a better dispersed strain accommodation by surrounding 
ferrite grains.  

fracture 

Figure  72  and  Figure  73  show  the  SEM  micrographs  of  CAL  920°C/-100°C/s/450°C/120s    CAL 
820°C/-100°C/s/450°C/120s  samples.  It  is  observed  that  voids  are  initiated  at  the  interface  of 
bainite and martensite. The dashed circles in Figure 73a are voids formed at the interface of carbides 
and matrix. The fraction of these carbide related voids was really low while their size compared to 
martensite  related  voids  is  remarkably  smaller.  Therefore,  it  is  expected  that  their  role  on  global 
fracture behaviour of the material is negligible [55]. 

Page 60 of 112 

 
 
 
 
 
Voids density (VD) and area fraction (VAF) of both LT and CAL 920°C/-100°C/s/450°C/120s  samples 
as  a  function  of  true  plastic  strain  are  shown  in  Figure  74  a  and  b,  respectively.  VD  reveals  the 
nucleation rate of void incidence, while VAF may include three events: nucleation, growth and /or 
void  coalescence.  CAL  820°C/-100°C/s/450°C/120s    sample  exhibits  the  higher  VD  and  VAF 
compared to CAL 920°C/-100°C/s/450°C/120s  sample. It is observed that around 0.6 and 0.75 of 
plastic strain VD and VAF start to increase in low and high temperature samples, respectively.  

Figure 72. Micrographs of the CAL 920°C/-100°C/s/450°C/120s  fractured sample (RD// LD) etched 
by Klemm. 

Figure 73. Micrographs of CAL 820°C/-100°C/s/450°C/120s  fractured sample (RD// LD) etched by 
Klemm. 

Figure 74. Void quantification: (a) void density vs. local true plastic strain and (b) void area 
fraction vs. local true plastic strain. 

Considering  the  band’s  meso-scale  configurations  in  both  samples  with  their  corresponding 
topological differences along with their damage activities in Figure 74, it is observed that CAL 820°C/-
100°C/s/450°C/120s    sample  showed  higher  damage incidents  (VD  and/or  VAF)  compared  to the 
high temperature sample at the same strain levels. The shorter distance between MA blocks in the 
fragmented  bands  of  CAL  820°C/-100°C/s/450°C/120s    sample  results  in  a  higher  local  strain 
gradient within the soft matrix between two adjacent MA islands. Therefore, as reported by Yan et 
al.  [56],  the  critical  local  strain  in  which  a  void  initiate  is  lower  and  this  leads  to  more  damage 
incidents. This is also reflected in an earlier increase in void quantities (VD and VAF), at the strain 

Page 61 of 112 

 
 
 
 
 
 
level  of  0.6  in  CAL  820°C/-100°C/s/450°C/120s    sample  compared  to  0.75  in  TAN=920  TOA=450 
tOA~120 sample. Higher damage incidents lead to more local stress relaxation and depending on the 
microstructural features of grains surrounding a void such as size, orientation and the meso-scale 
arrangements of the hard phase, the initiated void can be arrested by the local strain hardening. 

Eventually, the higher quantity of the voids within the microstructure cannot essentially lead to earlier 
macroscopic failure but rather the meso-scale arrangement of the hard phase causes either earlier 
localization  of  the  deformation  followed  by  the  macroscopic  failure  or  delaying  the  deformation 
instability. 
Bands  are  meso-scale  microstructural  heterogeneities  with  a  specific  topology  and  with  a  certain 
mechanical contrast with respect to the surrounding matrix. The specific topology, which consists of 
parallel banded patterns that are fragmented at certain distances, favour shear banding in bainitic 
microstructure. The strain localization, particularly when occurring early on, leads to failure at lower 
strain levels.  

4.2.  Modeling of damage 

In order to study damage initiation in the LoSi materials, the same VPSC model described in section 
3.2.3  is  employed.  As  discussed  in  previous  sections,  void  initiation  is  mostly  observed  at  the 
interface of bainite and martensite grains, as the result of the mechanical heterogeneities between 
them. Using the VPSC model, it is possible to estimate what will be the average mechanical state for 
the grains of each phase with a given crystallographic orientation. Therefore, in order to find what 
pairs of grains will tend more to be damage initiation sites, the VPSC model can be used to identify 
the grains for which mechanical incompatibilities will be larger. 

The model used in section 3.2.3 has been modified to provide additional output that can be used to 
find these heterogeneities. On one hand, the model gives, for every simulation step, the maximum 
difference  between  two  grains  for  each  of  the  components  of  the  stress  and  strain  tensors.  The 
objective is to identify which is the component of stress or strain for which larger heterogeneities are 
observed for the loading conditions of the tensile test. On the other hand, the model writes, at the 
selected  time  increments,  texture  files  that  include  the  values  of  each  of  the  stress  and  strain 
components for each of the grains (of any phase) considered in the simulation. Since the value of 
each  component  will  depend  on  crystallographic  orientation,  it  is  possible  to  represent  this 
information  analogously  to  an  ODF,  using  the  same  analysis  tools  usually  employed  to  study 
crystallographic textures. If the predictions of the model are correct, it should show that the largest 
heterogeneities are observed for pairs of grains with orientations that correspond with high intensities 
in the VODF of Figure 69. 

Figure 75 shows the maximum heterogeneities for stress and strain observed for the LoSi materials 
studied in section 3.2.3. It is observed that the largest strain heterogeneity is found, in both cases, 
for  the  23  component,  which  corresponds  with  the  TD-ND  plane.  For  stress,  the  largest 
incompatibilities are observed for the 33 component, in the normal direction. 

The  figure  shows  that  maximum  stress  heterogeneities  are  always  in  the  normal  direction  of  the 
plate (direction 33), while for strain the maximum difference is in the shear component 23. Therefore, 
it is expected that damage initiation occurs first between the pairs of grains for which the difference 
in the value of the 23 component of the strain tensor is higher. In order to verify this hypothesis, the 
distribution  function  of  the  23  strain  component  is  shown  (for  CAL  920°C/-100°C/s/450°C/120s  
material), with the intensity levels of the VODF superimposed, in Figure 76. 

The figure shows that indeed the orientations for which the 23 component of strain reaches minimum 
and maximum values correspond with the orientations for which the intensity of the VODF is higher. 
Although  the  largest  difference  is  observed  between  martensite  grains  with  different  orientations, 
since martensite is mostly distributed in isolated MA islands in the bainitic matrix, the candidates for 
void initiation will be the interfaces between bainite and martensite grains for which the difference is 
larger. These orientations have been indicated by red arrows in Figure 76. 

As a conclusion, it has been shown that, although a homogenization method such as VPSC provides 
only average values for each orientation and damage initiation is, by definition, a local phenomenon, 
the model can be used to predict which grains will be more likely to participate in the process of void 
initiation,  and  therefore  damage.  Moreover,  having  a  crystal  plasticity  model  available,  makes 
possible to study how specific microstructural parameters will influence the process. 

Page 62 of 112 

 
 
Figure 75. Maximum difference in stress (left) and strain (right) components between two grains as 
a function of macroscopic strain in the longitudinal direction for the samples with heat treatment 
CAL 820°C/-100°C/s/450°C/120s  and CAL 820°C/-100°C/s/450°C/120s. 

Figure 76. Distribution of the strain component 23 by orientation (

 section) compared with 

the VODF determined experimentally. 

𝜑𝜑2 = 45

∘

Page 63 of 112 

 
 
 
 
 
 
 
4.3. Conclusions 

Damage  micro-mechanisms  of  the  LoSi  bainitic  steel  were  studied  by  advanced  characterization 
techniques  integrated  with  a  crystal  plasticity  modeling.  Both  Topological  and  crystallographic 
aspects of damage micro-mechanisms were addressed in this work. It was shown that higher damage 
quantities (VD and VAF) and earlier damage initiation do not essentially lead to earlier fracture. With 
the help of crystal plasticity model and orientations captured around voids by the EBSD analysis, it 
was  shown  that  orientations  associated  to  VODF  coincide,  where  the  strain  tensor  E23  has  its 
maximum or minimum values. Therefore, strain incompatibilities can lead to damage initiation. This 
incompatibility  can  arise  by  the  phase  contrast  and  its  topology,  nevertheless,  the  effect  of 
crystallographic orientations on strain partitioning is also inevitable. 

Page 64 of 112 

 
 
 
5. Final conclusions and guidelines 

The project goal is to optimize the microstructures with a bainitic matrix in order to improve the cold 
formability and edge-cracking behavior of advanced high-strength steels with bainitic matrices. This will 
enable such AHSS to become very efficient in automotive  applications: (1) weight reduction without 
loss of formability, (2) enhanced energy absorption due to high yield strength combined with higher 
elongation and (3) favorable crash folding behavior due to improved bending properties [57]. The main 
aspects  are  the  understanding  of  process-microstructure  and  microstructure-properties  relations  in 
steels with a bainitic matrix, to integrate physical models allowing to simulate thermo-mechanical and 
material performance and to understand the damage process in such steels. Based on the preliminary 
study on lab samples and further integration of industrial processes restrictions like continuous annealing 
and  galvanizing  lines  a  guideline  for  producing  these  kinds  of  steels  with  good  combinations  of 
mechanical behaviours and forming capacity could be drawn. 

Below  the  main  conclusions  obtained  in  the  project  are  listed.  Moreover,  guidelines  are  given  for 
producing bainitic AHSS with high elongation and high forming capacity (bending, hole expansion) which 
can be used to design new products. 

5.1.1.  Conclusions 

The  steel  microstructure,  which  is  determined  by  the    chemical  composition  and  the  processing 
conditions,  has  the  most  dominant  influence  on  steel  properties.  To  produce  an  AHSS  (Advanced 
High  Strength  Steel)  with  optimum  combination  of  strength,  elongation  and  other  forming 
parameters,  especially  hole  expansion,  it  is  essential  to  know  the  correlation  between  processing 
conditions  and  mechanical  properties.  In  this  work  this  relationship  was  established  via 
microstructure.  Not  only  mechanical  properties  are  important  for  steel  customers,  but  also  the 
damage behavior. Special effort was done to esses the damage behoviour od studied alloys.   

The two melts HiSi and LoSi have been processed on laboratory scale to make both hot rolled and 
cold rolled annealed materials through different annealing cycles. Moreover, a complementary third 
alloy CrSi has also been used to produce hot rolled materials. Consistent with literature it has been  
demonstrated in this project that the replacement of Cr (0.6%) by Si (~1.5%) leads to enhanced 
nucleation  of  bainite,  and  retardation  of  carbide  formation.  As  a  consequence,  more  residual 
austenite is stabilized. This leads to lower YS, higher elongation and better bending properties (with 
comparable TS) for these steels. The effect of stabilizing the residual austenite and the retardation 
of carbide formation were even more pronounced for CrSi steel in hot rolled condition. The effect of 
the  residual  austenite  on  bending  properties  and  elongations  could  not  directly  be  distinguished, 
because  the  higher  tensile  strength  of  these  steels  also  affects  the  bendability.  CrSi  steel  shows  
relatively  slow  bainite  formation,and  therefore  this  alloy  was  only  been  used  to  create  hot  rolled 
material. 

Table 17 summarises the main relationships between process and microstructure as well as process 
and mechanical properties which have been deduced from the results of the hot rolled materials. The 
main influencing parameters for the three steels are the coiling temperature (CT) and finishing rolling 
temperature (FRT). The following microstructural parameters were analysed: ferrite (F), Pearlite (P), 
Bainite  (B),  Carbides  (F3C),  martensite  (M),  residual  austenite  (RA),  carbon  in  RA  (C  in  RA))  and 
bainite  lath  size.  The  mechanical  properties  tested  were:  yield  stress  (YS),  tensile  strength  (TS), 
uniform elongation (Ag), total elongation (A25), hole expansion coefficient (HEC) and bending angle 
(α)). The arrows indicate the direction and magnitude of the relationships that have been evaluated 
during this project (“-“:no measured correlation).  

It has been found that: 

• 

• 

• 

the combined addition of Cr and Si in CrSi steel is more effective to maintain austenite after 
long  bainitic  holding  during  coiling  due  to  the  strong  retardation  effect  in  bainite 
transformation kinetics, and a more efficient resistance to pearlite and carbides formation;  
the decrease in FRT leads to a refinement of bainite lath size. It leads to also an increase in 
MA fraction for hot rolled CrSi steel; 
the  increase  coiling  temperature  results  in:  (1)  an  increase  in  lath  size;  (1)  much  higher 
tendency to form pearlite.  

Analogous to Table 17, Table 18 summarises the results of the cold rolled materials. In the analysis 
the change in microstructure and mechanical properties was compared to the variation in annealing 
parameters: the annealing temperature (TA), the overaging temperature (TOA), time (tOA) and the 
cooling rate (CR). It has been found that: 

• 
• 
• 

• 

TA has limited impact (here TA was lower than FRT in hot rolling);  
TOA shows no linear correlation to M but to HEC and 2ry phases (M+RA);  
longer tOA delivers more completed transformation to bainite, which indicates that overage 
time, or equivalently, overage section length, is one of the biggest limitations in producing 
bainitic steels on industrial scale;  
very low cooling rates promote the formation of ferrite. 

Page 65 of 112 

 
Table 17. The dependence of the microstructure and mechanical properties of hot rolled materials on 
production parameters (The number of arrows indicates how strong the effect is). 

Microstructure 

Mechanical properties 

Mat.  Par. 

F 

P  Fe3C  B  M+RA  M  RA  C in RA  B lath     YS 

TS 

Ag  A25 

   Var.  %  %  %  %  %  %  %  wt.% 

µm 

  MPa  MPa  %  % 

LoSi 
HR  

HiSi 
HR  

CrSi 
HR  

↑ FRT 

↑ CT 

↑ FRT 

↑ CT 

↑ FRT 

↑ CT 

↓ 

↓ 

↓ 

↓ 

↓ 

↓ 

↑ 

↑ 

↑ 

↓ 

↑ 

↑ 

↑ 

↑ 

↑  

↑ 

↑ 

↑ 

↑ 

↑ 

↑ 

↑ 

↑↑ 

↑ 

↑↑ 

↑ 

↑↑ 

HEC 
% 

- 

- 

- 

Furthermore, the analysis showed that YS and TS decrease strongly with increasing bainite lath size, 
and HEC decreases with increasing amount of 2ry phases, mainly martensite content. As expected, it 
was  also  found  that  the  tensile  elongation  of  HiSi  materials  increases  with  contents  of  residual 
austenite. A deeper analysis of the influence of secondary phases by modelling shows that the yield 
stress  (YS)  and  the  uniform  elongation  (Ag)  decrease  with  increasing  M-content,  whereas  YS 
decreases  and  Ag  increases  with  increasing  RA-content.  Except  for  the  overaging  time,  a  clear 
difference  between  CGL  and  CAL  could  not  be  discerned  in  the  analysis  of  microstructures  and 
mechanical properties. 

Table 18. Microstructure and mechanical properties in dependence of production parameters in cold 
rolled material. 

Microstructure 

Nano  
hardness 

Mechanical properties 

Mat.  Par.     F  P  Fe3C  B  M+RA  M  RA  C in RA  B lath       

   YS  TS  Ag  A25 

HEC 

Comment 

   Var.     %  %  %  %  %  %  %  wt.% 

µm 

B 

M 

   MPa  MPa  %  % 

↑ 
TA 
↑ 
TOA 

LoSi  
↑ 
CR  
tOA 

↑ 
CR 
↑ 
TA 
↑ 
TOA 
↑ 
tOA 
↑ 
CR 

HiSi  
CR  

         ↑  ?  

   ↓ 

- 

   - 

- 

- 

- 

    ↑ 

1)  ↑↑  ↑   ↑ 

↓2) 

↑↑ 

  ↓ 

? 

  ↓↓  ↓↓  ↑↑  ↑↑ 

↓↓  ↑↑ 
3) 

↓  

↑↑ 

  ↓ 

↑     ↓ 

↓ 

↑ 

   ↓  ↓ 

↓ 

 ? 

   ↓ 

- 

   - 

- 

- 

- 

    ↑ 

1)  ↑↑  ↑   ↑ 

↓2) 

↑↑ 

  ↑   ? 

  ↓↓  ↓↓  ↑↑  ↑↑ 

↓↓  ↑↑ 
3) 

↑↑  

↑↑ 

  ↓ 

↑     ↓ 

↓ 

↑ 

   ↓  ↓ 

↓ 

   ↑ 

% 

- 

↓↓ 

↑↑ 

- 

↓↓ 

↑↑ 

limited impact  

no linear correlation to MS  
but to HEC and 2ry phases 

the higher tOA the more  
completed transformation 
to bainite; highest limitation  
to produce bainitic steels 

 limited impact  

no linear correlation  
to MS but to HEC and 2ry phases 
the higher tOA the more completed 
transformation to bainite; highest  
limitation to produce bainitic steels 

1) highest at 450°C (long tOA) 

2) maximum at 450°C for LoSi 

3) very short times 

Another main aspect that has an influence on the properties of bainitic steels is the morphology. The 
morphology in HiSi and LoSi steels changes from upper bainite (low TOA) to granular bainite (high 
TOA). Because of superimposing effects arising from the above-analysed microstructural features, no 
clear correlation of these effects could be drawn here. 

Besides  optimization  of  the  mechanical  properties  through  microstructure  control,  it  is  of  key 
importance to develop steels with adequate resistance to damage initiation. Damage initiation can 
be a severe problem since it may lead to premature failure of the component during forming or crash. 
Therefore, analysis of damage mechanisms is important. It has been found that the occurrence of 
less contrast in mechanical properties between bainite and martensite delays damage initiation to 
the latest stages of the plastic deformation prior to final failure. Also, microstructural banding has a 
big influence on the failure mechanism. The topology of martensite bands significantly affects void 
nucleation  and  macroscopic  plastic  deformation.  The  dispersion  and  fragmentation  of  martensite 

Page 66 of 112 

  
  
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
  
  
  
  
  
  
 
 
  
  
     
  
 
   
 
 
 
 
 
  
  
  
  
  
  
     
  
  
  
  
  
  
  
  
        
  
  
  
     
  
 
   
 
 
 
 
 
  
  
  
  
     
  
  
  
  
  
  
  
  
 
bands  with  a  short  distance  between  MA  blocks,  separated  by  the  relatively  softer  bainitic  matrix 
resulted in an improvement of the total elongation. Eventually, it was observed that the macroscopic 
response  of  the  material  is  controlled  by  the  length-scale  of  heterogeneities  within  the 
microstructure, rather than by local damage activities. Lowering the austenitization temperature can 
result  in  a  fragmentation  of  the  banding  phenomena  through  the  accelerated  kinetics  of  bainitic 
transformation.  

It  is  observed  that  both  uniform  elongation  and  strength  under  high  strain  rate  deformations  are 
improved.  Therefore,  this  shows  that  energy  absorption  under  high  strain  rate  deformations  is 
enhanced,  which  can  be  an  advantage  during  car  crash  events.  The  individual  role  of  retained 
austenite  and  martensite  phases  on  ductility  and  strengthening  was  observed.  The  strain  rate 
sensitivity  factor  of  each  material  consisting  of  various  second  phase  constituents  was  calculated 
experimentally  and  also  predicated  by  Johnson-Cook  model.    It  is  observed  that  the  higher  the 
fraction of second phase constituents, the lower is strain rate sensitivity become. However, individual 
role of RA and M phases on the strain rate sensitivity could not be addressed due to simultaneous 
change  of  both  phases.  In  addition,  microstructure  refinement  leads  to  strain  rate  sensitivity 
reduction. 

Figure 77 shows that some of the cold rolled annealed materials made during this project meet the 
tensile  properties  requested  in  VDA  239-100  [58]  for  the  following  grades:  CR570Y780T-CP, 
CR780Y980T-CP and CR900Y1180T-CP. Besides tensile properties, the requirements of certain steel 
grades  often  also  involve  targets  for  the  chemical  composition  and  application  properties  (HEC,  
bending, weldability etc); these requirements are sometimes not declared in norms but dependent 
on the customer. With respect to this, it is mentioned that both LoSi and HiSi have a relatively high 
carbon content and therefore the chemical requirement of CR570Y780T-CP is not met; for the other 
two specifications the carbon content of LoSi and HiSi (0.22 wt%) is just within the limitations (< 
0.23 wt%) of the norms. Since the main focus of this project was the study of cold rolled steels, no 
further  examination  was  performed  for  the  hot  rolled  materials.  Remark  to  Figure  77b:  the  used 
samples have a gauge length of 25mm, and the total elongation A50 was evaluated according to the 

Oliver-Formular in DIN EN 2566-1 [59]: 

𝐴𝐴50 = 𝐴𝐴25 × �

0,4

√2
2 �

Figure 77. Yield stress to TS (L to RD a) and A50 (evaluated according to DIN EN 2566-1 §9.3 [51] 
to TS (L to RD b) together with the requirements from VDA 239-100 [58]. 

5.1.2.  Guidelines 

As demonstrated in this project, there are many parameters to optimize the microstructure and, as 
a  result,  the  mechanical  parameters  with  production  parameters.  Of  most  interest  to  the  steel 
industry  is  that  adjustment  of  the  processing  parameters  within  industrial  restrictions.  For  the 
analysed  steels  the  main  applications  are  cold  stamping,  deep  drawing,  stretch  forming  and  roll 
forming, but also crash applications. Most of the different demands need different properties to be 
optimized.  “There  exist  components  whose  failure  in  production  during  press  forming  is  mainly 
determined  by  geometric  instability,  i.e.  necking.  For  such  parts,  grades  exhibiting  high  strain 
hardening  are  necessary  for  the  successful  press  forming,  since  high  work  hardening  results  in 
reduced  localized  strain.  Parts  formed  via  processes  involving  high  local  strains  should  consist  of 
materials  with  a  high  resistance  to  damage  initiation.  To  satisfy  these  two  opposing  demands, 
different steels are necessary” [60]. Good crash properties often request high yield stress and good 
elongation (high crash energy) and good bending properties (good folding behaviours) [57]. 

There  are  many  industrial  limitations,  especially  for  cold  rolled  steels.  Bainitic  steels  need  to  be 
completely  austenitizised  before  cooling  and,  during  cooling,  ferrite  formation  has  to  be  avoided. 
Moreover,  relatively  long  overaging  in  the  bainitic  regime  is  necessary  for  proper  austenite 
stabilization and maximum bainite transformation. However, too long overaging leads to enhanced 
growing  of  carbides  or  even  decomposition  of  austenite  to  pearlite.  The  most  important  steels  to 

Page 67 of 112 

  
 
 
 
automotive industry are the group of galvanized steels. Most of the galvanizing lines are restricted 
in overaging times and annealing temperatures.  

In this project, it was shown that annealing has to be performed at a temperature higher than Ac3eff, 
which is a temperature higher than Ae3 but not higher than Ac3, which depends on the austenization 
time. For HiSi steel, 850°C/1min was found to be sufficient to get a fully austenitic structure. A low 
annealing temperature TA is also favorable to avoid banding of martensite (if present). 

As already mentioned, which parameter has to be optimized depends on the application. If elongation 
in  uniaxial  mode  is  the  main  forming  operation  for  e.g.  cold  rolled  steels  then  dual-phase  steels 
should be favored since they show the highest elongations. On the other hand, complex phase steels, 
where bainitic steels belong to, are the first choice in operations whereby high local damage (e.g. 
bending, hole expansion) takes place.  From literature [61], it is known that the martensite content 
plays a crucial role for the bending performance of steel. In this project it was also found that HEC 
strongly decreases when the martensite content increases. Moreover, poor RA stability has negative 
influence on HEC. Consistent with previous findings the results obtained in this project demonstrate 
that a relatively low overaging temperature leads to a more homogeneous and fine microstructure 
and, therefore improved hole expansion, higher YS, and higher TS, but as a tradeoff a lower A25. 
High overaging temperatures result in a higher fraction of 2ry phases and coarser grain size which 
deteriorates in some cases the hole expansion but improve the tensile elongation (higher fraction of 
austenite).  It  should  be  noted  that  evaluating  microstructure  property  relationships  is  not  always 
straightforward since a change in microstructural features often has an influence on more than one 
mechanical property. For example, more martensite  increases  TS and decreases HEC. The decrease 
in HEC can often be primarily attributed to the higher martensite content, but also the increase in TS 
can partly contribute  to the lower HEC [62]. It was shown that very short overaging times (~14s) 
lead  to  very  high  YS  and  TS  and  low  A25  and  HEC.  Therefore,  long  overaging  times  are  of  key 
importance to  obtain desired properties. 

If  high  HEC  has  to  be  achieved,  LoSi  steels  should  be  chosen  for  steel  applications.  Here  no/less 
residual austenite can transform to martensite during hole expension test. Also, higher YS, but lower 
elongations observed in LoSi steels with equal strength level. 

If high bending angles are aimed (roll-forming), HiSi steels are the first choice, because RA supports 
higher elongation and with higher A25*HEC lead to higher bending angles. 

Combined  addition  of  Cr  and  Si  is  more  effective  to  maintain  austenite  after  long  bainitic  holding 
during  coiling  due  to  its  strong  retardation  effect  on  bainite  transformation  kinetics,  and  a  more 
efficient resistance to pearlite and carbides formation. This is the best achieved in hot rolled material. 
As  mentioned  before,  most  galvanizing  plants  have  too  short  overaging  times  to  play  on  this 
advantage.  

At this point, nothing could be concluded from different morphologies of the bainite. For the analysed 
steels, the effect of the other parameters screens the influence of the morphology on the mechanical 
and damage response of these steels. More experimental work involving different compositions and 
different bainitic regimes (lower or higher M) must be addressed to gain knowledge on this aspect.  

Page 68 of 112 

 
 
 
 
 
6. Exploitation and impact of the research results 

6.1.1.  Actual applications 

One group of AHSS, where bainitic steels belong to, are the complex phase steels (CP). These steels 
are  characterized  by  high  energy  absorption,  high  residual  deformation  capacity  and  good  hole 
expansion [62]. Therefore, they are particularly suitable for crash-relevant parts such as pillars, side-
impact intrusion beams and bumper bars [56]. Because of their high hole expansion, they are also 
promising candidates for more complex geometries. Also, in applications where stretch-flangeability 
(expanded  holes,  expanded  edges)  are  an  important  factor  in  the  press  shops,  these  steels  show 
advantageous properties. The bending properties of the analysed material are quite good, whereas 
hole expansion for all analysed steel grades is acceptable but not remarkable. 

Other automotive cold rolled AHSS, such as 980MPa and 1180MPa high formability steel grades, have 
microstructures which are mainly composed of bainite laths as matrix phase and secondary phases 
like fresh martensite and retained austenite. In these steels, a good combination of total elongation 
and hole expansion ratio should be guaranteed to succeed in the forming of automotive parts. The 
chemistry  of  these  two  grades  are  not  far  away  from  the  chemical  compositions  of  HiSi  and  CrSi 
steels,  which  gives  the  opportunity  to  help  optimizing  the  final  continuous  annealing  process  and 
microstructure of these industrial grades. 

The HiSi alloy can potentially be suitable to produce a DH1000 grade (VDA norm CR700Y980T-DH), 
either on a Continuous Annealing (CA) line or a Hot-Dip Galvanizing (HDG) line. This DH (Ductility 
High)  grade  is  often  categorized  as  a  3rd  generation  steel.  It  has  a  better  formability  than  a 
conventional  DP1000  grade  and  therefore  enables  down-gauging:  it  has  approximately  the  same 
formability as a DP800 grade and thus can replace DP800 for making a certain car part albeit with a 
smaller thickness. Such a DH1000 grade can also be a problem solver for a customer when with a 
DP1000 too much part failure is experienced in the press shop due limited formability of DP1000. 

6.1.2.  Technical and economic potential for the use of the results 

Bainite has since long been known to form a very beneficial, very fine matrix structure, which can 
further  be  optimized  by  controlling  martensite  inclusions  for  enhanced  strength  and/or  retained 
austenite for enhanced formability. However, production of bainitic steels on conventional annealing 
lines, which have limited capabilities with respect to the austenitizing temperature and the overaging 
time, can result in too low hole expansion, too low yield stress and/or too low elongations. Bainitic 
steels should be austenitized at tempertures higher than Ac3, the subsequent cooling rate should be 
high enough to avoid ferrite formation and furthermore, the overage section should be relatively long 
for  the  bainite  transformation  to  complete.  These  demands  are  mostly  conflictive  to  industrial 
restrictions  of  the  lines.  For  example,  a  continuous  galvanizing  line  has  restricted  annealing 
temperatures <880°C, and restricted overaging temperatures and times.  

Some of the demands are conflictive. A low overaging temperature leads to very fine microstructure, 
mostly  high  hole  expansion,  but  low  elongation.  The  understanding  of  the  plant  and  the  exact 
engineering to the process is mandatory to understand the microstructural transformation and the 
kinetics in this promising steel grade. Moreover, differentiation to other steel grades has to be taken 
into account. High tensile strength with good elongation is achieved by dual phase steels, or high 
tensile strength with middle hole expansion and good elongation is achieved by trip steels. These 
steels have very high hole expansion protrude bending properties for this class of strength.  

The  knowledge  that  we  acquired  on  the  effect  of  alloying  elements,  for  example,  the  combined 
addition of Cr and Si to retard bainite transformation kinetics, refine bainite laths, and to maintain 
more efficiently retained austenite at much longer holding time or much slower cooling rate (coiling), 
allows us to design/improve our alloying additions of new/existing grades in order to adapt process 
conditions (short remaining time in bainitc transformation range for continuous annealing line, very 
long time for hot rolled  products during coiling, varied time during the cooling of long products with 
a section of different thickness or diameter) to achieve strength, ductility and formability targes. In 
addition,  the  obtained  large  database  with  detailed  microstructure  characterisations,  process 
parameters  and  mechanical  properties  is  precious  for  the  modelling  of  the  relationship  between 
process,  microstructure  and  mechanical  properties,  which  in  return  can  be  employed  to  adjust 
industrial  process  and  provide  guideline  to  resolve  quality  problem  of  industrial  products  without 
costly experimental tests. 

This  report  contains  guidelines  for  producing  continuous  annealed  steel  products  with  enhanced 
formability whereby the most critical parameters in both a CA and HDG line have been identified. 
The  results  achieved  in  the  project  contribute  to  the  understanding  required  to  produce  formable 
advanced high strength steels via two types of process lines. As mentioned above, such steels will 
enable  weight  reductions  and  thereby  can  have  economic  impact,  for  example  in  the  automotive 
sector where light weighting can reduce fuel consumption and CO2 emission. 

Page 69 of 112 

 
6.1.3.  Publications / conference presentations resulting from the project 

Publications in journals and proceedings 

1.  M.C.  Taboada,  I.  Gutiérrez,  D.  Jorge-Badiola,  S.M.C.  van  Bohemen,  F.  Hisker  and  G.  Paul 
“Influence of the processing variables on the microstructure evolution of a bainitic carbide-free steel” 
Mat. Sci. Forum 879 (2017) 867-872. 

2.  J.  Galán-López,  L.A.I.  Kestens  and  P.  Verleysen;  Optimization  of  crystallographic  texture  for 
improved sheet formability using crystal plasticity modeling, Comptes rendus de Mécanique (French 
Academy  of  Sciences),  International  conference  on  COmputational  methods  in  Manufacturing 
Processes, ICOMP'16, Liege, Belgium (2016) 

3. Shakerifard, B. Lopez, J. Hisker, F. kestens, L. A. I. Crystallographically resolved damage initiation 
in advanced high strength steel. Iop Conf Ser-Mat Sci. Vol 375. 012022. 2018. 

4. B. Shakerifard, J. Galán-López, D. Jorge-Badiola, F. Hisker and L.A.I. Kestens; Effect of banding 
on micro-mechanisms of damage initiation in bainitic steels; Material Science and Engineering (A). 
Published, September-2018. 

5.  S.M.C.  van  Bohemen,  “Exploring  the  correlation  between  the  austenite  yield  strength  and  the 
bainite lath thickness”, Materials Science and Engineering: A 2018 vol: 731 pp: 119-123. 

6. S.M.C. van Bohemen, “Bainite growth retardation due to mechanical stabilisation of austenite”, 
Materialia 7 (2019) 100384. 

7.  J.  Galán-López  and  L.A.I.  Kestens,  Optimization  of  crystallographic  texture  for  sheet  forming 
applications  using  Taylor  based  models;  Metallurgical  and  Materials  Transactions  A  (2018). 
https://doi.org/10.1007/s11661-018-4869-8. 

8.  B.  Shakerifard,  J.  G.  Lopez,  M.  C.  Taboada  Legaza,  P.  Verleysen,  L.A.I.  Kestens,  Strain  rate 
dependent  dynamic  mechanical  response  of  bainitic  multiphase  steels,  Materials  Science  and 
Engineering: A 2018 vol: 745 pp: 279-290. 

9.  M.C.  Taboada,  M.R.  Elizalde,  D.  Jorge-Badiola,  Austempering  in  low-C  steels:  microstructure 
development and nanohardness characterization Journal of Materials Science 2019 vol: 54 pp: 5044-
5060 

10. B. Shakerifard, From micromechanisms of damage initiation to constructive mechanical behavior 
of bainitic multiphase steels, Dissertation, Technical University Delft, 2019. 

Oral and poster presentations at conferences 

1.  Mari  Carmen  Taboada,  Amaia  Iza-Mendia,  Isabel  Gutierrez,  Denis  Jorge-Badiola,  Substructure 
evolution and damage initiation during tensile tests in a Carbide-free bainitic steel, MSIA 2018, 2018 
June 26-29, Warsaw, Poland 

2.  M.  C.  Taboada,  S.M.C.  Van  Bohemen,  F.  Hisker,  D.  Jorge-Badiola,  Relationships  between 
microstructure  and  mechanical  properties  in  carbide  free  bainitic  steels,  XV  Congreso  Nacional  de 
Materiales / I Iberian Meeting, 2018 July 4-6, Salamanca, Spain. 

3.  Stefan  van  Bohemen,  Effect  of  the  austenite  yield  strength  on  the  bainite  lath  thickness, 
International symposium “Nano and Micro Scale Damage in Metals”, 2018 February 7-9, Utrecht, the 
Netherlands. 

4. F. Hisker, D. Jorge-Badiola, M.C. Taboada, S. van Bohemen, Influence of martensite content on 
Hole Expansion in bainitic steels, International symposium “Nano and Micro Scale Damage in Metals”, 
2018 February 7-9, Utrecht, the Netherlands. 

5. M.C. Taboada, D. Jorge-Badiola, F. Hisker, I. Gutiérrez, Some aspects of the damage in a carbide 
free bainitic steel deformed in tensile mode, International symposium “Nano and Micro Scale Damage 
in Metals”, 2018 February 7-9, Utrecht, the Netherlands. 

6. Jesús Galán-López, Behnam Shakerifard and Leo A.I. Kestens, Prediction of damage initiation in 
bainitic steels using crystal plasticity homogenization models, International symposium “Nano and 
Micro Scale Damage in Metals”, 2018 February 7-9, Utrecht, the Netherlands. 

7. Sebastian Schreiber, Bainitic steels with small second phase fractions, International symposium 
“Nano and Micro Scale Damage in Metals”, 2018 February 7-9, Utrecht, the Netherlands. 

8.  B.  Shakerifard,  J.G.  Lopez  and  L.A.I.  Kestens,  Banding  and  its  topological  effect  on  micro-
mechanisms  of  damage  initiation  in  low  silicon  bainitic  steels  under  static  loading  condition, 

Page 70 of 112 

 
 
 
International symposium “Nano and Micro Scale Damage in Metals”, 2018 February 7-9, Utrecht, the 
Netherlands. 

9. K. Zhu, S. van Bohemen, D. Jorge-Badiola, Optimizing combination of elongation and edge ductility 
through microstructure control in hot rolled bainitic steel, International symposium “Nano and Micro 
Scale Damage in Metals”, 2018 February 7-9, Utrecht, the Netherlands. 

10. J. Galán-López and L.A.I. Kestens; Optimization of texture for improved formability using Taylor 
models and the gradient descent method; 2016 March 31-April 1. 37. Meeting of DGM-Fachausschuss 
„Texturen“  and  DGM-Arbeitskreis  “EBSD”  Joint  French-German  Meeting,  SF2M  –  DGM  Dresden, 
Germany 

11.  J.  Galán-López,  L.A.I.  Kestens  and  P.  Verleysen;  Optimization  of  crystallographic  texture  for 
improved  sheet  formability  using  crystal  plasticity  modeling;  2016  May  18-20;  ICOMP-16;  Liege, 
Belgium. 

12. J. Galán-López and L.A.I. Kestens; Formability gradient distribution function: Application to the 
optimization of BCC textures for improved deep-drawing behavior; 2017 January 3-9;International 
Conference on Plasticity, Damage and Fracture. Puerto Vallarta, Mexico. 

13. J. Galán-López and L.A.I. Kestens;  Formability  gradient distribution function; 2017 March  31; 
Texture and Anisotropy Symposium; Delft, the Netherlands. 

14. J. Galán-López, B. Shakerifard and L.A.I. Kestens; Modeling of damage initiation in bainitic steels 
with VPSC; 2017 September 20-22; IWCMM-27; Leuven, Belgium. 

15. J. Galán-López, B. Shakerifard and L.A.I. Kestens;  Crystallographic orientation dependence of 
damage initiation in multiphase steels using VPSC; 2018 January 3-9; International Conference on 
Plasticity, Damage and Fracture. San Juan, Puerto Rico. 

16. J. Galán-López, B. Shakerifard and L.A.I. Kestens; Modelling of tensile behavior of bainitic steels 
at  different  strain  rates  using  VPSC  and  a  physical  hardening  model;  October  2018  (accepted); 
IWCMM-28; Glasgow, Scotland. 

6.1.4.  Symposium “Nano and Micro Scale Damage in Metals” 

The international symposium “Nano and Micro Scale Damage in Metals” was organised from 7 till 9 
February at the Jaarbeurs in Utrecht, the Netherlands to disseminate the knowledge developed within 
the BaseForm project. It were three days of intensive knowledge exchange, learning and networking 
with a total of more than 70 participants from 6 different countries. 

The initiative for this symposium originates from two running research collaborations coordinated by 
M2i:  the  RFCS  project  ‘Baseform’  (RFSR-CT-2014-00017)  and  the  FOM  Industrial  Partnership 
Program ‘Physics of Failure’, in which universities and industry join forces to better understand the 
origins of damage and failure in  steels. Topics included both experimental and modelling work on 
formability, hot tearing, fatigue, anisotropic damage and multi scale modelling. This Symposium was 
organized by TU Delft, M2i, FOM and Tata Steel and with the financial support of FOM (Dutch funding 
agency) and European Commission (RFCS fund).  

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Page 72 of 112 

 
 
Name 

Page 

List of figures 

Figure 1. Schematic of the laboratory set-up for hot rolling at Tata Steel in 
Ijmuiden.  

Figure 2. Schematic of a HR slab and samples for various tests. 

Figure 3. Dilatometer samples: a) flat, b) cylindrical. 

Figure 4. Fraction of bainite as a function of time during bainitic transformation for 
HiSi (a) and LoSi (b) in the temperature range 370 – 570 ºC. 

Figure  5.  Scheme  of  annealing  performed  annealing  cycles,  CAL  (continuous 
annealing line) and CGL (continuous galvanizing line). 

Figure 6. Bending test (in dependence on VDA 238-100[13]), Hole-Expansion test 
(ISO 16630) and Tensile test in dependence of DIN EN ISO 6892 , p. 6892, (here 
with Lt=83mm, Lc=37,5mm, L0=25mm, b0=6,25mm). t is the material thickness. 

Figure 7. Bainite transformation kinetics at (a) 380 °C, (b) 430 °C, (c) 480 °C, (d) 
530 °C for HiSi (red curves) and LoSi (black curves) and CrSi (blue curves) steels 
after austenitization at 1000 °C for 5 min. 

Figure 8. Dilatometry curves showing bainite transformation kinetics for HiSi and 
LoSi steels after an austenitization at 1000°C or 1150°C for 5min followed by a 
bainitic holding at different temperatures. a) HiSi and b) LoSi alloys. 

Figure 9. Retained austenite fraction obtained with XRD for different steels 
irrespective of the applied experimental conditions. 

Figure 10. Microstructures of (a) HiSi and (b) CrSi at FRT = 935°C and CT= 450°C. 

Figure 11. FEG-SEM images of CrSi steel hot rolled at (a) FRT=940°C and (b) 
FRT=865°C followed by a coiling at 390°C. 

Figure 12. FEG-SEM images of CrSi steel hot rolled at a FRT of 940-980°C, ROT 
exit temperature at (a) 380°C and (b) 490°C followed by a coiling at 450°C. 

Figure 13. Microstructures obtained at FRT= 940°C and (a) ROT exit =410°C, 
CT=390°C, (b) ROT exit =490°C, CT=450°C for CrSi steel. P – Pearlite, M – 
martensite. 

Figure 14. Several examples of the transformed volume fraction vs. time during 
bainitic reactions for different overaging temperatures, TOA. a) LoSi and b) HiSi. 

Figure 15. Dilatometry method for effective Ac3 (a) and ferrite fraction vers. time at 
TA=830°C. 

Figure 16. Optical micrographs of several HiSi dilatometry samples, a) HiSi 920°C/-
100°C/s/540°C/120s - pearlite formation, b) HiSi 920°C/-100°C/s/450°C/14s - 
high fraction of 2ry phases and c) HiSi 920°C/-100°C/s/390°C/120s - homogeneity. 
Nital etching. 

Figure 17. Microstructures corresponding to a) HiSi and b) LoSi after the same 
thermal cycle (920ºC/-100°C/s /450ºC/120s). 

Figure 18. Evolution of the a) volume fraction of 2ry phases, b) RA and c) lath size 
(2º) for HiSi and LoSi steels as a function of the overaging temperature. 

Figure 19. FEG-SEM images for TA=920°C. Overaging temperatures TOA = a) 
390ºC, b) 450ºC, c) 480ºC (HiSi steel) and d) 390ºC, e) 450ºC and f)480 ºC (LoSi 
steel). 

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Page 73 of 112 

 
Figure 20. Microstructures after tOA=14s at TOA=450°C for a) HiSi (TA=860°C) 
and c) LoSi (TA=820°C) and after 120s at 450°C for b) HiSi (TA=860°C) and d) 
LoSi (TA=820°C). Klemm III etching. 

Figure 21. Evolution with overaging time of the volume fraction of a) 2ry phases, 
b) MA phase, c) RA and d) bainite lath size for various TOA. 

Figure 22. Evolution of the volume fraction of 2ry phases with TA (tOA≅120s). 

Figure 23. Micrographs corresponding to: CR=-20°C/s (a,d) -30°C/s (b, e) and -
100°C/s (c, f) cooling rates from TA down to 450°C. From a) to c) HiSi steel and 
from d) to f) LoSi steel. 

Figure 24. Evolution of volume fraction of 2ry phase a), RA b) and bainite lath size 
c) for various cooling rates between TA and TOA. 

Figure 25. Change in the volume fraction of 2ry phases in a) HiSi, d)  LoSi, volume 
fraction of RA in b) HiSi, e) LoSi and lath size (2º and 15º) of c) HiSi f) LoSi for 
varying overaging time (tOA) and temperature (TOA) of CGL simulations. 

Figure 26. Micrographs etched with LePera corresponding to LoSi steel after 
different CGL simulations. (CAL TA,°C/ CR,K/s/TOA, °C/tOA, s). 

Figure 27. Evolution of experimental (1-f_γ  DIL) and simulated (1-f_γ,…) phase 
volume fractions and carbon mole fractions obtained from the transformation 
simulation for HiSi and LoSi variant at overaging temperature of 480°C (a, b), 
450°C (c, d), 420°C (e, f) and 390°C (g, h). 

Figure 28. Parameters β and δ and the effect of alloy composition and 
temperature. 

Figure 29. Single constituent flow curve models (dashed) compared to 
experimentally measured results (solid). 

Figure 30. Mixed microstructures flow curves computed with the ISO-E model 
(dotted) compared to experimentally measured results (solid). 

Figure 31. Total elongation against ultimate tensile strength for L (left) and T 
(right) direction. 

Figure 32. Total elongation against yield strength for L (left) and T (right) direction. 

Figure 33. Yield strength against ultimate tensile strength. 

Figure 34. HEC performance against tensile strength (left) and total elongation 
(right). 

Figure 35. Bending angle (Q) (left) and bending angle (L) (right) against tensile 
strength. 

Figure 36. Overview of tension tests (a) and HEC (b) results measured on HiSi and 
LoSi according to Tensile strength (TS). 

Figure 37. Overview of a) HEC to A25 (total elongation) and b) HEC (hole 
expansion coefficient) and A25 to YS/TS (yield strength ratio) measured on HiSi 
and LoSi. 

Figure 38. Bending angle a to a) TS and b) A25*HEC. 

Figure 39. Mechanical properties to overaging temperature TOA (CAL TA=920°C; 
CR=-100 °C/s; tOA=120s). 

Figure 40. Mechanical properties a) YS,TS and b) A25,HEC to overaging 
temperature TOA (CAL TA=850°C; CR=-50 °C/s; tOA~120s) 

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Page 74 of 112 

Figure 41. Mechanical properties a) YS, TS and b) A25, HEC to overaging 
temperature tOA (CAL TA=920°C; CR=-100°C/s; TOA=450°C). 

Figure 42. Mechanical properties a) YS,TS and b) A25,HEC to cooling rate CR (CAL 
TA=850°C; TOA=450°C; tOA~120s). 

Figure 43. Mechanical properties a) YS,TS and b) A25,HEC to cooling line speed v 
with different lines (TA=850°C; TOA=450°C; tOA~long). 

Figure 44. Relationship between (a) YS and lath size defined with 2-5° 
misorientation and (b)  hole expansion ratio (HER) and secondary phases fraction 
(martensite + austenite + MA) fraction for hot rolled products. 

Figure 45. Observation of carbides distribution and localisation in the 
microstructure using FEG-SEM: (a) LoSi steel coiled at 390°C, (b) LoSi steel coiled 
at 420°C and (c) CrSi steel with a ROT exit temperature at 390°C then a coiling at 
450°C 

Figure 46. YS and TS (0° to RD) as a function of bainite lath size (2°) 

Figure 47. YS and A25 (0° to RD) vers. phase contents. 

Figure 48. HEC vers. bainite lath size (a) and fraction of secondary phases (b) for 
all performed cycles (Cr ≤50K/s) 

Figure 49. HEC vers. M/Carbide/RA-content and C-content of residual austenite 
vers. TOA 

Figure 50. Volume fraction of M vers. TOA (tOA>60s) and tOA (TOA=450°C). 

Figure 51. Evolution of the amount of secondary phases with the overaging 
temperature tOA a) HiSi, b) LoSi for all the applied overaging temperatures. 

Figure 52. a) Retained austenite fraction as a function of the overaging 
temperature TOA and time tOA. HiSi steel TA=950ºC (Dilatometry samples). b) 
Evolution of the retained austenite as a function of the overaging temperature and 
austenitizing temperature (tOA=120s). 

Figure 53. Evolution of the nanohardness of the various micro-constituents with 
the overaging time and temperature a) Bainite, b) Low-C martensite, c) High-C 
martensite in MA, d) RA. 

Figure 54. a) Evolution of the nano-, micro- hardness with the carbon content, b) 
Evolution of the effective carbon content with the amount of low-C martensite. 

Figure 55. Schematic representation of the multiphase model strategy for a 
microstructure constituted by a bainitic+ thermal low-C martensite matrix and a 
dispersion of MA (austenite+high carbon martensite).  

Figure 56. Stress-strain curves of austenite and austenite plus TRIP and of the 
evolution of the strain induced martensite volume fraction. 

Figure 57. Comparison between model predictions (dashed lines) and experimental 
curves (symbols) for a) several CAL Vatron-LoSi samples and b) CAL Vatron-HiSi 
920°C/-100°C/s/450°C/14s sample. 

Figure 58. Average and standard deviation of the q-values with respect to the 
variation of the initial ODF using the Taylor and pancake models. 

Figure 59. Initial textures (at left) and optimized textures using the Taylor and 
pancake models after, respectively, 5, 50, 200 and 500 optimization steps. 

Figure 60. Gradients of the average and standard deviation of the q-values and 
increment of texture for the first and the fifth optimization steps for LoSi and HiSi 
materials. 

38 

38 

39 

39 

40 

40 

41 

41 

41 

42 

42 

43 

44 

44 

45 

46 

47 

48 

49 

49 

Page 75 of 112 

Figure 61. Fitting of model parameters using experimental data from tensile tests 
at two different directions for four different LoSi bainitic steels. Data points from 
two different experiments for each material and direction are shown with dots, 
while the result of the model is displayed using continuous lines. 

Figure 62. Influence of microstructural parameters on tensile behaviour. Top-left: 
martensite fraction; top-right: bainite lath size; bottom-left: bainite dislocation 
density; bottom-right: fraction or size of carbides in bainite. 

Figure 63. An initial Fe-γ microstructure (in orange) is cooled down from 800ºC to 
600 ºC during 300s, leading to the formation of Fe-α (in blue). 

Figure 64. Distribution of misorientations between pairs of grains in three 
simulated microstructures with different number of grains (left) and theoretical 
Mackenzie distribution (right). 

Figure 65. Distribution of misorientations with respect to a DKS orientation 
relationship between pairs of grains in the three simulated microstructures (left) 
and theoretical (right). 

Figure 66. ODF of parent austenite phase (left) and ferritic product texture (right) 
for the simulation with a microstructure of 5062 grains. 

Figure 67. Initial austenitic texture with a strong cube component and ferrite 
product texture with a (weak) rotated cube component and weaker Goss and 
rotated Goss components. 

Figure 68. Schematic illustration of orientation selection on an overlapped image 
quality and inverse pole figure map; (a) complete area of analysis (Neck-IPF), (b) 
area selected around the void with faces approximately equal to 3 times of a void 
diameter (Void-IPF) and (c) remaining area (No void-IPF). 

Figure 69. φ2=45° section of ODFs of the material at two different deformation 
levels; (a) Uniform deformation UODF (calculated from 796000 data points), (b) 
post uniform VODF (131000 data points), (c) post uniform NVODF (460000 data 
points) and (d) Necking or post uniform ODF consist of the merged ODFs in b and 
c. 

Figure 70. Microstructure characterization of both samples. CAL 920°C/-
100°C/s/450°C/120s  sample: (a) SEM micrograph where the dashed rectangle 
indicates the location of the EBSD analysis. The solid arrow is the position of the 
EPMA line analysis, (b) overlaid IQ and phase maps (solid white arrows show dark 
bands with low IQ value). CAL 820°C/-100°C/s/450°C/120s  sample: (c) SEM 
micrograph, (d) overlaid IQ and phase maps. (e) EPMA chemical analysis with four 
arrows corresponding to the bands in TAN= CAL 920°C/-100°C/s/450°C/120s  
sample show in (a) and (f and g) schematic illustration of the bands topology of 
CAL 920°C/-100°C/s/450°C/120s  and CAL 820°C/-100°C/s/450°C/120s  samples, 
respectively. 

Figure 71. Box plot of micro-hardness measurements of low and high temperature 
samples: (a) Vertical micro-hardness profile of the CAL 820°C/-
100°C/s/450°C/120s  and CAL 920°C/-100°C/s/450°C/120s  samples austenized 
at 820 and 920°C performed with 10 gf load (Indentation is conducted every 50 
µm), and (b) Horizontal micro-hardness measurements on the martensitic bands 
and the matrix of both samples loaded with 5 gf. 

Figure 72. Micrographs of the CAL 920°C/-100°C/s/450°C/120s  fractured sample 
(RD// LD) etched by Klemm. 

Figure 73. Micrographs of CAL 820°C/-100°C/s/450°C/120s  fractured sample 
(RD// LD) etched by Klemm. 

Figure 74. Void quantification: (a) void density vs. local true plastic strain and (b) 
void area fraction vs. local true plastic strain. 

Figure 75. Maximum difference in stress (left) and strain (right) components 
between two grains as a function of macroscopic strain in the longitudinal direction 

51 

51 

52 

53 

53 

54 

54 

57 

58 

59 

60 

61 

61 

61 

63 

Page 76 of 112 

for the samples with heat treatment CAL 820°C/-100°C/s/450°C/120s  and CAL 
820°C/-100°C/s/450°C/120s. 

Figure 76. Distribution of the strain component 23 by orientation (
compared with the VODF determined experimentally. 

𝜑𝜑2 = 45

 section) 

63 

∘

Figure 77. Yield stress to TS (L to RD a) and A50 (evaluated according to DIN EN 
2566-1 §9.3 [51] to TS (L to RD b) together with the requirements from VDA 239-
100 . 

Figure 78. HiSi - inclusion distribution (22.98mm in width and 0.741mm in sheet 
thickness). 

Figure 79. LoSi- inclusion distribution (24.89mm in width and 0.593mm in sheet 
thickness). 

Figure 80. Chemical analysis of the inclusions by PSEM. 

Figure 81. CCT diagrams of LoSi (a) and HiSi (b) determined from dilatometry 
signals measured for various cooling rates after austenitisation at TA=920°C. 

Figure 82. TTT diagrams of isothermal transformation to bainite at different 
temperatures for LoSi (a) and HiSi (b). 

Figure 83. Examples of microstructures on flat dilatometer samples 

Figure 84. Bending angle vers A25 (left) and HEC (right). 

Figure 85. A25 (0° to RD) vers bainite lath size. 

Figure 86. TS (0° to RD) vers phase content. 

Figure 87. Left LoSi and right HiSi (a,d) The measured dilatation as a function of 
temperature, (b,e) the evaluated fraction against temperature, and (c,f) bainite 
kinetics at the temperature TOA. 

Figure 88. Left: calculated start curve (3 vol.%) for LoSi (solid line) compared to 
the experimental data (open circles). The open triangles represent the 
experimental kinetics at 30 % transformation Right: the calculated kinetics of 
bainite formation compared to experimental data for TOA temperatures in the 
range 390−450 °C. 

Figure 89. a) calculated start curve (3 vol.%) for HiSi (solid line) compared to the 
experimental data (open circles). The open triangles represent the experimental 
kinetics at 30 % transformation b) the calculated kinetics of bainite formation 
compared to experimental data for temperatures in the range 390−450 °C. 

Figure 90. Dynamic and static flow curves of HiSi samples; (a) CAL 920°C/-
100°C/s/450°C/120s (b) CAL 920°C/-100°C/s/450°C/14s  and (c) CAL 860°C/-
100°C/s/450°C/120s. Legends indicate the corresponding strain rate level of each 
curve. 

Figure 91. Dynamic and static flow curves of LoSi samples; (a) CAL 920°C/-
100°C/s/450°C/120s, (b) CAL 920°C/-100°C/s/390°C/120s and (c) CAL 820°C/-
100°C/s/450°C/120s. Legends indicate the corresponding strain rate level of each 
curve. 

67 

87 

87 

88 

89 

89 

94 

96 

96 

97 

104 

106 

107 

111 

112 

Page 77 of 112 

 
 
Page 78 of 112 

 
 
 
List of tables 

Name  

Page 

Table 1. Chemical composition of the material as determined by Tata Steel and TKSE. 

Table 2. Chemical composition of high Cr high Si alloy as determined by Tata Steel. 

Table 3. Hot rolling parameters. 

Table 4. Measured and calculated values of Ac1, Ac3 and Ms for LoSi and HiSi (°C). 

Table 5. Quantification of microstructures [vol.%] and hardness values of HiSi and LoSi 
samples for various cooling rates. MA: Martensite-Austenite; B: Bainite; P: Pearlite; F: 
Ferrite; RA: residual austenite; M+B+P+F=100%; RA is determined by X-Ray diffraction. 

Table 6. Overview of the microconstituent and the techniques and methods applied for 
the characterization of their volume fractions 

Table 7. Selected thermal cycles to be applied in Vatron annealing simulator for model 
microstructures (CAL: Continuous Annealing Line). 

Table  8.  Additional  thermal  cycles  closer  to  the  industrial  lines  conditions  (CGL: 
Continuous Galvanizing Line and CAL: Continuous Annealing Line). 

Table 9. Prior austenite grain size (in µm). 

Table 10. Parameters for β(T). 

Table 11. Parameters for δ(T). 

Table 12. Considered microstructures of the LoSi variant. 

Table  13.  Selected  new  temperature-time  overaging  conditions  for  the  modelling 
requirements. 

Table 14. Physical parameters used in the VPSC model. 

Table  15.  Fitted  model  parameters: 
equation, is fixed to 0.5, 
the dislocations, the constants 
𝛽𝛽
shape of the carbides (only present in the bainite phase). 

 is the annihilation distance, 

𝐶𝐶1
 and 

𝑦𝑦

𝐶𝐶2

2
𝜎𝜎𝑚𝑚𝑚𝑚𝑏𝑏

  is  related  with  yield  stress, 

𝛼𝛼
 to stage IV hardening and 

,  from  the  Taylor 
 is related to the structure of 
 depends on the 

𝐶𝐶𝑝𝑝

Table 16. Tensile properties of the high and low temperature samples along the RD. 

Table 17. The dependence of the microstructure and mechanical properties of hot rolled 
materials  on  production  parameters  (The  number  of  arrows  indicates  how  strong  the 
effect is). 

Table  18.  Microstructure  and  mechanical  properties  in  dependence  of  production 
parameters in cold rolled material. 

Table 19. Non-metallic inclusions according to DIN EN 50602 on HiSi. 

7 

7 

9 

10 

10 

13 

21 

21 

25 

29 

29 

30 

43 

50 

50 

60 

66 

66 

87 

Page 79 of 112 

 
Table 20. Non-metallic inclusions according to DIN EN 50602 on LoSi. 

Table  21.  Process  parameters  of  the  different  hot  rolled  steel  samples,  as  well  as  the 
retained austenite fraction and C content in retained austenite measured using XRD. 

Table  22.  Intercepted  bainitic  lath  size  obtained  using  EBSD  and  the  fractions  of 
secondary phases quantified using FEG-SEM images. F-ferrite, P-pearlite, MA-martensite 
austenite islands, M- martensite 

Table 23. Tensile (T) and bending properties of hot rolled substrates. 

Table 24. Phase fractions of bainite, martensite and retained austenite determined from 
dilatometry  data  for  LoSi  steel  isothermally  transformed  in  the  range  390-480ºC  (the 
typical uncertainty for each phase is +/- 0.02). 

Table 25. Phase fractions of bainite, martensite and retained austenite determined from 
dilatometry  data  for  HiSi  steel  isothermally  transformed  in  the  range  390-480ºC  (the 
typical uncertainty for each phase is +/- 0.02). 

87 

91 

91 

92 

103 

105 

Table  26.  Parameters  used  in  the  simulations  to  optimize  the  agreement  with 
experimental data. 

107 

Page 80 of 112 

 
 
 
 
A  
Ac1  
Ac3  
Ac3eff 
Ae1  
Ae3  
Ag 
AHSS    
AMMR   
ATM 
A25 
B 
BS  

bcc 
BSE 
F 
fcc 
CA 
CAL 
CCT  
CGL 
CP  
CRSS 
CrSi 
CR  
CR 
CT  
CEIT    
Dγ 
DH 
DKS  
EBSD    
EPMA   
IPF 
IQ 
IQR  
FEG-SEM 
FRT  
HDG 
HEC 
HET 
HiSi 
HR  
HT  
L 
LT  
LOM 
LoSi 
M 
MA 
MS  

M2i 
ND 
NVODF  
OA 
ODF 
OG 
OS 
P 
PSC  
RA 
RD 
ROT  
SEM  
SHTB    
SS 

List of acronyms and abbreviations 

austenite; 
austenite start formation temperature during heating; 
austenite finish formation temperature during heating; 
austenite finish effective formation temperature during heating 
austenite start formation temperature according to equilibrium conditions; 
austenite finish formation temperature according to equilibrium conditions; 
uniform elongation; 
advanced high strength steel; 
ArcelorMittal Maizières Research SA; 
auto-tempered martensite; 
total elongation; 
bainite; 
bainite  start  temperature:  temperature  below  which  austenite  can  transform  to 
bainite;  
body centred cubic; 
back scattered electrons; 
ferrite; 
face centred cubic; 
continuous annealing; 
continuous annealing line; 
continuous cooling transformation; 
continuous galvanizing line; 
crystal plasticity; 
critical resolved shear stress; 
alloy with high Cr and Si content; 
cold rolled; 
cooling rate; 
coiling temperature; 
Centro de Estudios e Investigaciones Técnicas de Gipuzkoa; 
austenite grain size; 
ductility high; 
double Kurdjumov-Sachs orientation; 
electron back-scatter diffraction; 
electron probe micro analysis; 
inverse pole figure; 
image quality; 
interquartile rang, 
Field Emission Gun scanning electron microscope; 
finish rolling temperature; 
Hot-Dip Galvanizing; 
hole expansion coefficient; 
hole expension test; 
alloy with high Si content; 
hot rolled; 
high temperature sample;  
longitudinal direction; 
low temperature sample;  
light optical microscopy; 
alloy with low Si content; 
martensite; 
martensite austenite (islands); 
 temperature at which transformation of austenite to martensite starts during rapid 
cooling; 
Material innovation institute; 
normal direction; 
No-Void orientation distribution function; 
oxides in solution; 
orientation distribution function; 
globular oxides; 
oxides in line; 
pearlite; 
plain strain compression; 
retained (residual) austenite; 
rolling direction; 
Run-Out-Table; 
scanning electron microscopy; 
Split Hopkinson tensile test bar samples; 
sulphides in line; 

Page 81 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
T 
T 
TA 
TOA 
t 
tOA 
Tata Steel 
TD 
TKSE    
TKM 
TRIP Steel 
TS 
TTT  
TU Delft 
UHSS    
UTS 
VAF 
VD  
VODF    
VPSC 
WDS    
XRD  
YR 
YS 
αm 

transverse direction; 
temperature; 
annealing temperature; 
overaging temperature; 
time, s; 
overaging time; 
Tata Steel Nederland Technology BV; 
transverse direction; 
ThyssenKrupp Steel Europe AG; 
Theoretical martensite start temperature related to Koistinen Marburger equation; 
TRansformation Induced Plasticity steel; 
tensile strength; 
time, temperature, transformation; 
Technische Universiteit Delft; 
ultra high strength steel; 
ultimate tensile strength; 
voids area fraction; 
voids density; 
void orientation distribution function; 
visco-plastic self-consistent model; 
Wavelength Dispersive Spectroscopy; 
x-ray diffraction; 
yield ratio; 
yield strength; 
rate parameter of martensite formation in Koistinen Marburger equation. 

Page 82 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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[57] P. Larour, H. Pauli, T. Kurz and T. Hebesberger, “Inluence of post uniform tensile and bending 
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for Standardization, 1999. 

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[62] S. Keeler, M. Kimchi and P. Mooney, “Advanced High-Strength Steels Application Guidelines , 

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Haidemenopoulos,  T.  Hebesberger  and  K.  Satzinger,  “Design  of  bainite  in  steels  from 
inhomogeneous  microstructures  using  physical  approach 
homogeneous  and 
(BainiteDesign),”  Luxembourg:  Off.  for  Official  Publ.  of  the  Europ.  Communities,  Vols. 
RFSR-CT-2007–00022, 2013.  

[64] G.  Paul,  R.  Großterlinden,  T.  Pretorius  and  T.  Heller,  “in  4th  International  Conference  on 
Modelling  and  Simulation  of  Metallurgical  Processes  in  Steelmaking  SteelSim  2011,” 
VDEh. Düsseldorf, vol. 2011 (Ed.: VDEh), 2011.  

[65] C.  Gallez,  V.  Suarez,  M.  Maier  and  W.  M.  van  Haaft,  “Online  prediction  of  the  mechanical 
properties of hot rolled strips. Final report. Luxembourg: Office for Official Publications of 
the European Communities (ECSC Re,” 2006. 

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[66] D. Quidort and Y. Brechet, ISIJ Int., vol. 42, p. 1010, 2002.

[67] L. C. D. Fielding, Mater. Sci. Techn. 29, vol. 4, pp. 383-399, 2013.

[68] T. Ko and S. A. Cottrell, J. Iron Steel Inst., London 172, p. 307, 1952.

[69] E. Swallow and H. K. D. H. Bhadeshia, “Mater. Sci. Technol.,” vol. 12, p. 121, 1996.

[70] H. Bhadeshia and D. Edmonds, Metall. Trans. A, vol. 10, p. 895, 1979.

[71] S. van Bohemen, M. Hermans and G. den Ouden, Materials Science and Technology, vol. 18, 

pp. 1524-1528, 2002. 

[72] G. Rees and H. Bhadeshia, “Materials Science and Technology,” vol. 8, p. 985, 1992.

[73] N. Chester and H. Bhadeshia, J. Phys. IV, vol. 7, p. 41, 1997.

[74] H. Matsuda and H. Bhadeshia, Proc. Royal Society London A, vol. 460, p. 1707, 2004.

[75] M. Santofimia, F. Caballero, C. Capdevila, C. Garcia and C. de Andres, “Mater. Trans.,” vol. 47, 

p. 1492, 2006.

[76] D. Gaude-Fugarolas and P. Jacques, ISIJ International, vol. 46, p. 712, 2006.

[77] S.  van  Bohemen  and  J.  Sietsma,  “Modeling  of  isothermal  bainite  formation  based  on  the

nucleation kinetics,” Inter. J. of Mater. Res., vol. 7, p. 739–747, 2008. 

[78] S. van Bohemen, “Modeling Start Curves of Bainite Formation,” Metall. Mater. Trans. A , vol. 

41, p. 285–294, 2010. 

[79] S. van Bohemen and D. Hanlon, “A physically based approach to model the incomplete bainitic 

transformation in high-Si steels,” Inter J. Mater. Res., pp. 987-991, 2012. 

[80] S. van Bohemen, Phil. Mag., vol. 93, no. 4, pp. 388-408, 2012.

[81] H. Bhadeshia, Mater Sci. Eng. A , vol. 378, no. 1, pp. 34-39, 2004.

[82] S. Chatterjee, H. Wang, J. Yang and H. Bhadeshia, Mater. Sci. Technol., vol. 22, p. 641–644, 

2006. 

[83] S. van Bohemen and D. Hanlon, “A physically based approach to model the incomplete bainitic 
transformation in high-Si steels,” Inter J. Mater. Res., pp. pp. 987-991, 2012. 

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transformation in high-Si steels,” Inter J. Mater. Res., pp. 987-991, 2012. 

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[87] B.  Shakerifard,  J.  G.  Lopez,  M.  Taboada  Legaza,  P.  Verleysen  and  L.  Kestens,  “Strain  rate 
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and Engineering, vol. 745, no. A, pp. 279-290, 2018.  

Page 86 of 112 

Appendix 1. Non-metallic inclusions. 

Table 19. Non-metallic inclusions according to DIN EN 50602 on HiSi. 

Size code 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

0,05 

0,10 

0,20 

0,50 

1,00 

2,00 

5,00 

10,00 

20,00 

50,00 

Factor 

area, 
mm2 

K0  

S+O 

K0  

S 

K0  

O 

1000 
mm2 

1000,00 

36,66 

30,97 

5,69 

sort 

measured 
area 

219,60 

8,05 

SS 

106,00 

15,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

6,80 

OA 

OS 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

2,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

1,25 

OG 

17,00 

3,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

Table 20. Non-metallic inclusions according to DIN EN 50602 on LoSi. 

Size code 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

0,05 

0,10 

0,20 

0,50 

1,00 

2,00 

5,00 

10,00 

20,00 

50,00 

Factor 

area, 
mm2 

K0  

S+O 

K0  

S 

K0  

O 

1000 
mm2 

1000,00 

7,20 

5,82 

1,38 

sort 

measure
d area 

180,52 

1,30 

1,05 

SS 

OA 

19,00 

1,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,25 

OS 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

OG 

1,00 

2,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

0,00 

Figure 78. HiSi - inclusion distribution (22.98mm in width and 0.741mm in sheet thickness). 

22.98mm*0.741mm

Figure 79. LoSi- inclusion distribution (24.89mm in width and 0.593mm in sheet thickness). 

24.89mm*0.593mm

Page 87 of 112 

Si-O

Sulfide

Figure 80. Chemical analysis of the inclusions by PSEM. 

Page 88 of 112 

Appendix 2. CCT and TTT diagrams. 

a)

b)

Figure 81. CCT diagrams of LoSi (a) and HiSi (b) determined from dilatometry signals measured for 
various cooling rates after austenitisation at TA=920°C. 

Figure 82. TTT diagrams of isothermal transformation to bainite at different temperatures for LoSi 
(a) and HiSi (b). 

Page 89 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
Page 90 of 112 

Appendix 3. Microstructure and mechanical properties of hot rolled materials.  

Table 21. Process parameters of the different hot rolled steel samples, as well as the retained 
austenite fraction and C content in retained austenite measured using XRD. 

Alloy 

Sample 
code 

390-15 

390-16 

LoSi 

420-13 

420-14 

450-3 

390-9 

390-12 

HiSi 

420-10 

420-11 

450-2 

390-8 

390-7 

CrSi 

420-5 

450-4 

450-1 

ID 

LoSi-15 

LoSi-16 

LoSi-13 

LoSi-14 

LoSi-3 

HiSi-9 

HiSi-12 

HiSi-10 

HiSi-11 

HiSi-2 

CrSi-8 

CrSi-7 

CrSi-5 

CrSi-4 

CrSi-1 

FRT, 
ºC 

ROT  
entry, 
ºC 

Cooling 
rate, 
ºC/s 

ROT 
exit, 
ºC 

CT 
furnace, 
ºC 

XRD (Ruhl & Cohen) 

% γ 

%C in γ 

925 

870 

930 

870 

940 

935 

860 

930 

855 

930 

940 

865 

935 

940 

970 

800 

760 

820 

800 

830 

810 

760 

820 

770 

810 

820 

760 

820 

830 

870 

95 

90 

100 

80 

75 

100 

80 

90 

75 

75 

100 

90 

80 

80 

110 

420 

415 

400 

470 

530 

380 

430 

450 

440 

500 

410 

400 

490 

490 

380 

390 

390 

420 

420 

450 

390 

390 

420 

420 

450 

390 

390 

420 

450 

450 

0 

0 

0 

0 

0 

1 

<1 

<1 

<1 

2 

9 

4 

10 

10 

4 

1,01 

0,80 

0,81 

0,59 

0,95 

0,43 

Table 22. Intercepted bainitic lath size obtained using EBSD and the fractions of secondary phases 
quantified using FEG-SEM images. F-ferrite, P-pearlite, MA-martensite austenite islands, M- 
martensite. 

Alloy 

Sample 
code 

ID 

Lath size (μm) 

Secondary phases 

2° 

5° 

10°  15°  20° 

Austenite    

F, %  P, %  MA, %  M, % 

10 ° 

390-15 

LoSi-15  0,62  0,86  0,95  0,98  1,01 

390-16 

LoSi-16  0,64  0,88  0,97  1,00  1,03 

LoSi 

420-13 

LoSi-13  1,00  1,24  1,35  1,45  1,50 

420-14 

LoSi-14  0,68  0,92  1,03  1,08  1,13 

450-3 

LoSi-3 

1,18  1,99  2,31  2,58  2,73 

390-9 

HiSi-9 

0,74  1,02  1,08  1,14  1,19 

0,16 

390-12  HiSi-12  0,49  0,74  0,84  0,88  0,91 

HiSi 

420-10  HiSi-10  1,07  1,38  1,54  1,65  1,77 

420-11  HiSi-11  0,57  0,80  0,88  0,92  0,96 

450-2 

HiSi-2 

1,28  1,62  1,80  2,01  2,10 

390-8 

CrSi-8 

0,78  1,00  1,07  1,13  1,16 

390-7 

CrSi-7 

0,80  0,92  0,98  1,05  1,08 

CrSi 

420-5 

CrSi-5 

0,97  1,19  1,25  1,30  1,33 

450-4 

CrSi-4 

0,93  1,24  1,31  1,37  1,38 

450-1 

CrSi-1 

0,61  0,85  0,94  0,98  1,01 

0,21 

0,24 

0,83 

0,24 

0,23 

0,10 

0 

0 

0 

0 

7 

5 

1 

3 

13 

15 

23 

22 

5 

0 

0 

0 

0 

0 

5,5 

4,5 

0 

0,5 

1 

4 

11 

13 

12 

1 

<2 

5-7 

10-15 

2 

<5 

10-15 

<1 

2 

Page 91 of 112 

 
  
 
  
  
 
 
 
 
 
 
 
 
 
 
 
  
  
 
  
  
  
  
  
  
 
 
 
 
 
 
 
 
 
 
 
  
  
 
  
  
  
  
  
  
 
 
 
 
 
 
 
 
 
 
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Remarks to bending results listed in Table 23  

The  width  of  the  HR  samples  was  30  mm  and  therefore  the  width  to  thickness  ratio  was  slightly 
smaller than 10 which is thus not exactly according  to the norm. Furthermore, for each condition 
only  one  sample  was  available  for  testing.  Measurements  were  performed  parallel  to  the  rolling 
direction RD (Q: bending line perpendicular to RD) for all 15 samples, and 9 samples were available 
for testing transverse to RD. The latter is usually the more critical direction and designated as L in 
the VDA norms. The bending angles determined for the 3.6 mm HR samples have been converted to 
the equivalent bending angles for 1 mm thickness. This allows making a comparison with the results 
on the cold rolled annealed materials.  

Table 23. Tensile (T) and bending properties of hot rolled substrates. 

Alloy 

Annealing 
aim 

avg 

avg 

YR (T), 

YS (T), 

MPa 

MPa 

avg 

TS 
(T), 

MPa 

940ºC-390ºC 

860ºC-390ºC 

0.92 

830 

899 

0.95 

1145 

1203 

LoSi 

940ºC-420ºC 

860ºC-420ºC 

940ºC-450ºC 

940ºC-390ºC 

860ºC-390ºC 

HiSi 

940ºC-420ºC 

860ºC-420ºC 

940ºC-450ºC 

940ºC-390ºC 

860ºC-390ºC 

CrSi 

940ºC-420ºC 

940ºC-450ºC 

970ºC-450ºC 

0.89 

0.91 

0.89 

0.95 

0.88 

0.81 

0.93 

0.78 

0.73 

0.76 

0.69 

0.71 

0.80 

714 

706 

677 

995 

764 

682 

908 

609 

787 

894 

784 

816 

873 

805 

779 

759 

1050 

871 

837 

972 

785 

1075 

1175 

1144 

1153 

1087 

avg 

Ag 
(T), 

% 

2.6 

2.6 

2.4 

2.4 

2.9 

1.4 

4.9 

7.1 

2.4 

8.1 

8.9 

5.0 

5.5 

6.8 

4.8 

avg 

error 

A25 
(T), 

% 

10.2 

9.0 

12.6 

5.0 

4.3 

5.0 

5.0 

11.0 

5.0 

12.3 

16.0 

6.6 

10.0 

11.6 

9.2 

A25 
(T), 

% 

1.0 

1.6 

4.0 

4.0 

4.0 

4.0 

4.0 

5.2 

4.0 

5.3 

0.3 

4.0 

4.0 

1.7 

1.2 

Bending 
angle 
(Q) @ 
1mm, 

Bending 
angle 
(L) @ 
1mm, 

º 

117 

119 

110 

133 

115 

112 

107 

147 

178 

109 

116 

111 

110 

111 

º 

111 

110 

92 

162 

126 

87 

67 

111 

100 

111 

Page 92 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Appendix 4. Additional light optical micrographs (etched by Nital and Lepera) and Secondary 
Electron micrographs of several HiSi and LoSi cold-rolled, flat dilatometry samples after different 
annealing treatments (TOA/tOA).  

Light Optical 
Microscopy LOM (Nital 
etching) 

Light Optical Microscopy 
LOM (Lepera etching) 

Secondary Electron 
Micoscopy (FEG-SEM) 

TOA/tOA 

F 

MA 

F 

F 

F 

MA 

F 

F 

F 

MA 

M 

MA 

MA 

MA 

HiSi 

920°C/-
100°C/s/450°C/12
0s 

HV 1=377 

HiSi 

920°C/-
100°C/s/390°C/12
0s 

HV 1=377 

HiSi 

920°C/-
100°C/s/450°C/14
s 

HV 1=356 

LoSi 

920°C/-
100°C/s/450°C/12
0s 

HV 1=313 

LoSi 

920°C/-
100°C/s/390°C/12
0s 

HV 1=433 

Page 93 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
F 

MA 

Figure 83. Examples of microstructures on flat dilatometer samples 

LoSi 

920°C/-
100°C/s/450°C/14
s 

HV 1=315 

Page 94 of 112 

 
 
 
 
 
Appendix 5. Mechanical data for cold rolled products.  

There  are  many  limitations,  which  have  to  be  considered  when  it  comes  to  translating  lab  scale 
observations to industrial processes, such as continuous annealing (CAL) and galvanizing lines (CGL). 
The  annealing  temperatures  are  limited  due  to  the  refractory  lining,  energy  costs  and  economic 
reasons to ~max. 860°C, cooling rates are limited to ~-50°C/s (gas-jet cooling) and overaging and 
annealing times are limited because of line length. Steel has to be coiled at nearly room temperature 
(RT). Also cooling from TOA (overaging temperature) to RT is limited to a specific rate. 
Therefore, to get a more reliable validation data, additional industrial oriented annealing cycles were 
performed like e.g. TA=850°C, CR=-50°C/s (to avoid ferrite formation) or -20°C/s (to form ferrite), 
different overaging temperatures and line speeds. For some annealing cycles, 2 samples were used 
in order to determine HEC and tensile properties. Latter was not performed on all samples due to 
the lack of material. All annealing cycles were performed in a Vatron Annealing Simulator. Annealing 
parameters were derived from preliminary investigations performed on lab scale samples and are 
summaried together with mechanical and microstructural data in this appendix and Appendix 6.  

Steel 

cycle 

YS 

TS 

TE 

YS 

TS 

TE 

MPa 

MPa  % 

MPa 

MPa  %  % 

a 

° 

Tension 
Test 

   HET  bending 

Transverse 

Longitudinal 

   HER 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

HiSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

CAL 850°C/-100°C/s/450°C/120s 

CAL 850°C/-50°C/s/450°C/120s 

CAL 850°C/-50°C/s/420°C/120s 

CAL 850°C/-50°C/s/450°C/100s 

CAL 850°C/-50°C/s/450°C/150s 

CGL 850°C/-100°C/s/450°C/80s 

CGL 850°C/-50°C/s/450°C/80s 

CGL 850°C/-50°C/s/420°C/80s 

CGL 850°C/-50°C/s/450°C/80s 

CGL 850°C/-50°C/s/450°C/66,7s 

CGL 850°C/-50°C/s/450°C/100s 

CGL 920°C/-50°C/s/450°C/80s 

CGL 850°C/-20°C/s/450°C/80s 

CGL 850°C/-50°C/s/390°C/80s 

CAL 850°C/-20°C/s/450°C/120s 

CAL 920°C/-100°C/s/450°C/120s 

CAL 920°C/-100°C/s/450°C/120s 

CAL 860°C/-100°C/s/450°C/120s 

CAL 920°C/-100°C/s/390°C/120s 

CAL 920°C/-100°C/s/420°C/120s 

CAL 920°C/-100°C/s/480°C/120s 

CAL 860°C/-100°C/s/390°C/120s 

CAL 860°C/-100°C/s/480°C/120s 

CAL 860°C/-100°C/s/450°C/120s 

CAL 920°C/-30°C/s/450°C/120s 

CAL 850°C/-100°C/s/450°C/120s 

CAL 850°C/-50°C/s/450°C/120s 

CAL 850°C/-50°C/s/420°C/120s 

CAL 850°C/-50°C/s/450°C/100s 

CAL 850°C/-50°C/s/450°C/150s 

CGL 850°C/-100°C/s/450°C/80s 

566 

595 

605 

601 

587 

648 

613 

643 

555 

574 

599 

539 

583 

781 

584 

771 

836 

802 

989 

862 

673 

923 

613 

818 

561 

726 

700 

785 

637 

658 

644 

945  14.9 

939  19.8 

943  15.9 

937  19.9 

932  15.7 

970  20.2 

958  19.7 

957  17.8 

957  14.4 

952  16.5 

972  18.2 

971  14.6 

959  19.5 

985  16.0 

928  20.3 

961  17.7 

1169  13.3 

966  16.6 

765 

598 

640 

611 

588 

659 

629 

675 

605 

608 

586 

637 

568 

759 

603 

783 

818 

769 

1085  5.5 

952  19.9  23 

951  19.7  28 

151 

146 

951  19.3 

946  19.4 

967  19.9 

972  19.3  28 

981  18.6  27 

945  20.8  27 

147 

147 

147 

960  20.2 

964  19.0 

980  17.5 

972  20.0  23 

1000  16.6  31 

946  17.4  17 

967  18.1  26 

1160  14.8  15 

951  21.0  31 

1206  8.7 

1008 

1221  11.7  29 

1075  14.3 

918  20.5 

1117  8.8 

970  11.2 

1145  14.9 

972  16.9 

941  11.6 

932  11.2 

934 

5.9 

938 

8.7 

917  10.4 

938 

8.7 

877 

668 

969 

795 

711 

750 

704 

826 

682 

695 

735 

1077  15.3  29 

943  22.2  25 

1223  12.2  28 

24 

1123  15.4  20 

966  18.5  21 

931  11.5 

920  13.2  25 

961 

6.1 

38 

926  11.4 

909  12.2 

923  12.3 

131 

147 

134 

150 

117 

144 

117 

129 

125 

109 

124 

118 

141 

106 

135 

Page 95 of 112 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

LoSi 

CGL 850°C/-50°C/s/450°C/80s 

CGL 850°C/-50°C/s/420°C/80s 

CGL 850°C/-50°C/s/450°C/80s 

CGL 850°C/-50°C/s/450°C/66,7s 

CGL 850°C/-50°C/s/450°C/100s 

CGL 920°C/-50°C/s/450°C/80s 

CGL 850°C/-20°C/s/450°C/80s 

CGL 850°C/-50°C/s/390°C/80s 

CAL 850°C/-20°C/s/450°C/120s 

CAL 920°C/-100°C/s/450°C/120s 

CAL 920°C/-100°C/s/390°C/120s 

CAL 820°C/-100°C/s/450°C/120s 

CAL 920°C/-100°C/s/480°C/120s 

CAL 920°C/-100°C/s/390°C/120s 

CAL 920°C/-100°C/s/450°C/120s 

CAL 820°C/-100°C/s/390°C/120s 

CAL 820°C/-100°C/s/450°C/120s 

CAL 920°C/-30°C/s/450°C/120s 

627 

696 

649 

671 

684 

569 

697 

874 

676 

797 

940 

806 

678 

982 

863 

948 

9.4 

921  10.9 

963 

9.0 

935  13.1 

921  12.9 

966 

6.3 

909  13.9 

918 

1.3 

907  11.6 

939  10.2 

1101  7.6 

941 

8.9 

940  10.4 

1186  7.0 

1102  8.9 

732 

813 

727 

697 

704 

685 

660 

864 

696 

744 

960 

818 

675 

997 

834 

922  12.6  27 

985 

9.2 

32 

921  12.7  26 

128 

132 

138 

915  13.6 

910 

8.9 

928 

8.7 

925  12.5  22 

955 

5.4 

36 

944 

6.3 

25 

874 

5.4 

43 

116 

123 

129 

142 

1069  8.4 

35 

91 

933  12.2  34 

142 

958  12.3  19 

1177  8.1 

20 

1058  10.6  18 

89 

79 

85 

91 

101 

113 

1037 

1108  2.9 

1072 

1148  9.3 

27 

797 

673 

1047  10.8 

909 

5.3 

830 

733 

1031  12.0  19 

878  11.1  28 

Figure 84. Bending angle vers A25 (left) and HEC (right). 

Figure 85. A25 (0° to RD) vers bainite lath size. 

Page 96 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 86. TS (0° to RD) vers phase content. 

phase content (%) 

Page 97 of 112 

 
 
 
Page 98 of 112 

Appendix 6. Microstructural data: HiSi steel. 

Identification 

Processing parameters 

TA (ºC) 

tA (s) 

TOA (ºC)  v (m/s)  CR (ºCs-1) 

tOA(s) 

CR(galv.)  tgalv(s) 

CR 
(to 
RT) 

MICROSTRUCTURE 

)

%

(

e
t
i
r
r
e
F

)

%

(

r
o
r
r
E

)

%

(
R
A

C
%

y
r
a
d
n
o
c
e
S

)

%

(

s
e
s
a
h
p

r
o
r
r
E

C
-
w
o
L

e
t
i
s
n
e
t
r
a
M

)

%

(

CAL 850°C/-
100°C/s/450°C/120s 
CAL 850°C/-
50°C/s/450°C/120s 
CAL 850°C/-
50°C/s/420°C/120s 
CGL 850°C/-
100°C/s/450°C/80s 
CGL 850°C/-
50°C/s/450°C/80s 
CGL 850°C/-
50°C/s/420°C/80s 
CGL 850°C/-
50°C/s/450°C/80s 
CGL 850°C/-
50°C/s/450°C/66,7s 
CGL 920°C/-
50°C/s/450°C/80s 
CGL 850°C/-
20°C/s/450°C/80s 
CGL 850°C/-
50°C/s/390°C/80s 
CAL 850°C/-
20°C/s/450°C/120s 
CAL 860°C/-
100°C/s/390°C/120s 
CAL 860°C/-
100°C/s/450°C/120s 
CAL 860°C/-
100°C/s/450°C/120s 
CAL 860°C/-
100°C/s/480°C/120s 
CAL 920°C/-
30°C/s/450°C/120s 
CAL 920°C/-
100°C/s/450°C/120s 
CAL 920°C/-
100°C/s/450°C/120s 
CAL 920°C/-
100°C/s/390°C/120s 
CAL 920°C/-
100°C/s/420°C/120s 
CAL 920°C/-
100°C/s/480°C/120s 

850 

120 

450 

100 

100 

120,7 

100 

116,7 

2 

2 

13,1 

1,33 

19,9 

2,0 

12,3 

1,20 

18,1 

1,2 

450 

100 

100 

850 

120 

450 

850 

120 

420 

50 

50 

850 

850 

850 

850 

80 

80 

80 

80 

450 

420 

450 

850 

66,7 

450 

920 

850 

850 

80 

80 

80 

450 

450 

390 

850 

120 

450 

50 

50 

50 

50 

50 

20 

50 

20 

100 

116,1 

1,8 

13,4 

1,33 

17,8 

1,1 

56 

52 

43,9 

80 

41,6 

50,6 

40 

35,8 

100 

100 

100 

120 

100 

100 

100 

100 

104,7 

4 

4 

4 

4 

4 

4 

4 

4 

2 

2,4 

2,1 

2,4 

2,1 

2,4 

2,1 

2,4 

2,4 

2 

2,5 

2,4 

2,1 

11,0 

1,30 

20,8 

1,0 

12,5 

1,29 

20,8 

1,6 

13,7 

1,28 

19,0 

1,4 

10,3 

1,25 

21,0 

1,9 

14,6 

1,29 

21,4 

3,0 

13,0 

1,15 

21,2 

2,0 

2,4 

2,1 

39 

4 

11,6 

1,24 

26,7 

2,0 

2,4 

2,1 

<5 

11,0 

1,20 

18,0 

2,7 

59 

7 

4,0 

0,44 

23,9 

1,3 

1,50 

14,2 

0,9 

5,4 

4,7 

2,2 

0,0 

0,3 

2,9 

2,9 

4,1 

6,6 

2,7 

0,3 

0,9 

0,0 

860 

120 

390 

100 

100 

120 

860 

120 

450 

100 

100 

14 

860 

120 

450 

100 

100 

860 

120 

480 

100 

100 

920 

120 

450 

30 

100 

920 

120 

450 

100 

100 

920 

120 

450 

100 

100 

920 

120 

390 

100 

100 

920 

120 

420 

100 

100 

920 

120 

480 

100 

100 

120 

120 

120 

14 

120 

120 

120 

120 

20 

20 

20 

20 

20 

20 

20 

20 

20 

20 

A
M

)

%

(

e
s
a
h
p

14,5 

13,4 

15,7 

20,8 

20,5 

16,2 

18,1 

17,3 

14,6 

n
o
b
r
a
c

h
g
H

i

)

%

(

e
t
i
s
n
e
t
r
a
m

1,4 

1,1 

2,2 

9,8 

8,0 

2,5 

7,8 

2,8 

1,6 

c
i
t
i
s
n
e
t
r
a
M

)

%

(

s
e
s
a
h
p

6,8 

5,8 

4,4 

9,8 

8,3 

5,3 

F
/
e
t
i
n
a
B

i

c
i
t
i
r
r
e

s
e
s
a
h
p

Bainite 
grain size 2º 

Bainite 
grain size 
15º 

1,19 

1,51 

1,26 

1,62 

1,28 

1,60 

1,36 

1,78 

1,33 

1,65 

1,22 

1,43 

10,7 

1,35 

1,71 

6,8 

8,2 

1,32 

1,68 

1,40 

1,74 

24,0 

12,3 

15,0 

1,42 

1,64 

17,7 

6,8 

7,0 

1,20 

1,49 

23,0 

19,1 

19,9 

1,42 

1,65 

14,2 

7,0 

7,0 

0,94 

1,05 

r
o
r
r
E

4,7 

1,0 

2,6 

0,0 

1,4 

3,1 

1,4 

4,3 

5,2 

1,8 

0,2 

0,4 

0,0 

7,2 

7,3 

5,0 

9,6 

5,8 

1,23 

32,1 

0,5 

12,0 

0,52 

20,2 

12,8 

24,8 

1,01 

1,12 

14,5 

1,24 

18,9 

1,5 

1,10 

21,6 

2,2 

1,23 

21,4 

1,4 

0,0 

0,0 

0,0 

0 

0 

0 

18,9 

4,4 

4,4 

1,28 

1,54 

21,6 

16,6 

16,6 

1,40 

1,74 

21,4 

11,8 

11,8 

1,30 

1,85 

1,22 

39,0 

1,4 

19,0 

1,42 

20,0 

14,2 

33,2 

0,79 

1,09 

12,2 

1,28 

20,4 

0,9 

4,6 

9,1 

9,5 

1,27 

16,4 

1,9 

1,33 

18,3 

1,1 

1,23 

22,0 

1,7 

0,0 

0,0 

0,0 

0,0 

0,0 

0,0 

0,0 

0,0 

20,4 

8,3 

8,3 

1,35 

1,56 

16,4 

11,8 

11,8 

0,80 

0,91 

18,3 

9,2 

9,2 

1,21 

1,25 

22,0 

12,5 

12,5 

1,53 

1,96 

Page 99 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Microstructural data: LoSi steel. 

Identification 

Processing parameters 

TA 
(ºC) 

tA (s) 

TOA 
(ºC) 

v 
(m/s
) 

CR  
(ºCs-1) 

tOA(s) 

CR(galv.) 

tgalv(s) 

CR 
(to 
RT) 

MICROSTRUCTURE 

)

%

(

e
t
i
r
r
e
F

)

%

(

r
o
r
r
E

)

%

(
R
A

C
%

y
r
a
d
n
o
c
e
S

)

%

(

s
e
s
a
h
p

r
o
r
r
E

C
-
w
o
L

e
t
i
s
n
e
t
r
a
M

)

%

(

r
o
r
r
E

A
M

)

%

(

e
s
a
h
p

n
o
b
r
a
c

h
g
H

i

e
t
i
s
n
e
t
r
a
m

850 

120 

450 

100 

50 

116,7 

2 

2,7  1,0  3,1  1,7 

0,0 

0,0 

3,1  0,4 

850 

120 

420 

100 

50 

116,1 

1,8 

0,0 

- 

0,8  0,5 

0,0 

0,0 

0,8  0,8 

CAL 850°C/-100°C/s/450°C/120s 

CAL  850°C/-100°C/s/420°C/120s 

CGL 850°C/-100°C/s/450°C/80s 

CGL 850°C/-100°C/s/450°C/80s 

CGL 850°C/-100°C/s/420°C/80s 

CGL 850°C/-120°C/s/450°C/80s 

CGL 850°C/-100°C/s/450°C/66,7s 

CGL 920°C/-100°C/s/450°C/80s 

CGL 850°C/0°C/s/450°C/80s 

CGL 850°C/0°C/s/390°C/80s 

CAL 850°C/0°C/s/450°C/120s 

CAL 820°C/0°C/s/390°C/120s 

CAL 820°C/0°C/s/450°C/120s 

CAL 820°C/0°C/s/450°C/120s 

CAL 920°C/0°C/s/450°C/120s 

CAL 920°C/0°C/s/450°C/120s 

CAL 920°C/0°C/s/450°C/120s 

CAL 920°C/0°C/s/390°C/120s 

CAL 920°C/0°C/s/390°C/120s 

CAL 920°C/0°C/s/480°C/120s 

850 

80 

450 

100 

100 

850 

80 

450 

100 

50 

56 

52 

850 

80 

420 

100 

50 

43,9 

850 

80 

450 

100 

50 

80 

850  66,7 

450 

120 

50 

41,6 

920 

80 

450 

100 

50 

50,6 

850 

80 

450 

850 

80 

390 

20 

50 

40 

35,8 

850 

120 

450 

20 

104,7 

820 

120 

390 

100 

120 

820 

120 

450 

100 

14 

820 

120 

450 

100 

120 

920 

120 

450 

30 

120 

920 

120 

450 

100 

14 

920 

120 

450 

100 

120 

920 

120 

390 

100 

24 

920 

120 

390 

100 

120 

920 

120 

480 

100 

120 

4 

4 

4 

4 

4 

4 

4 

4 

2 

20 

20 

20 

20 

20 

20 

20 

20 

20 

2,4 

2,1 

5,5  1,0  6,9  1,0 

0,8 

1,8 

6,1  0,7 

2,4 

2,1 

3,8  1,1  5,7  1,6 

0,4 

1,3 

5,3  1,5 

2,4 

2,1 

3,1  1,0  5,1  3,8 

0,0 

0,0 

5,1  2,0 

2,4 

2,4 

1,5  1,0  3,4  1,4 

0,0 

0,0 

3,4  1,9 

2 

2,5 

4,8  1,1  8,1  2,8 

1,5 

1,2 

6,6  1,8 

2,4 

2,1 

1,9 

- 

8,1  2,9 

0,4 

0,8 

7,7  5,8 

2,4 

2,1 

40 

8  7,3  0,5  7,9  2,8 

1,3 

1,4 

6,6  0,0 

2,4 

2,1 

4,0  0,8  3,9  0,9 

0,0 

0,0 

3,9  0,0 

42 

4  5,8 

1,3 

- 

- 

9,0  1,4 

0,8 

1,0 

8,2  2,4 

1,3  0,3 

1,3  0,0 

5,5  0,9 

14,
8 

0,5 

10,7 

1,0 

4,1  0,0 

9,3 

3,2  0,7  2,4  0,5 

2,4  0,0 

0,0 

3,0  0,7 

5,0  0,7 

1,9 

0,0 

0,0 

- 

- 

- 

17,
1 
26,
0 

0,4 

15,1 

2,9 

2,0  0,0 

14,1 

0,7 

21,1 

2,8 

4,9  0,0 

21,0 

3,4  1,1 

3,4  1,5 

1,5 

26,
1 

0,4 

23,8 

6,1 

2,3  2,3 

26,1 

0,5  0,2 

0,5  0,5 

0,5 

4,5  0,6 

13,
9 

0,6 

10,9 

2,5 

3,0  0,0 

9,4 

c
i
t
i
s
n
e
t
r
a
M

)

%

(

s
e
s
a
h
p

0,4 

0,8 

1,5 

1,9 

2,0 

1,9 

3,3 

6,2 

0,6 

0,0 

3,1 

0,0 

/
e
t
i
n
a
B

i

c
i
t
i
r
r
e
F

s
e
s
a
h
p

Bainite 
grain size 2º 

Bainite 
grain size 15º 

1,04 

1,04 

1,13 

0,96 

1,04 

1,08 

1,10 

1,22 

1,16 

1,07 

1,25 

0,68 

0,89 

1,12 

1,39 

0,90 

1,30 

0,85 

1,02 

1,24 

1,38 

1,38 

1,48 

1,34 

1,35 

1,36 

1,31 

1,66 

1,40 

1,39 

1,42 

0,85 

1,11 

1,55 

1,84 

1,05 

1,60 

0,98 

1,17 

1,78 

Page 100 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Appendix 7. Selection of the bainite model 

Various bainite transformation kinetics models available in the literature have been reviewed. Based 
on this comprehensive assessment the Azuma model [19] has been selected as the most preferred 
model because: 

− 

− 

− 

it is the only model that explicitly describes the formation of cementite, either in austenite 
(upper bainite) or in bainitic ferrite (lower bainite); 
the  model  has  been  extensively  assessed  and  validated  in  the  previous  RFCS  project 
BainiteDesign [63]. Further testing has led to improvements made by G. Paul et al., and the 
rigorous validation has enhanced the accuracy of predictions [64];  
the model calculations can be implemented in a microstructure-properties model to predict 
mechanical properties which is important for the current project. As an example, it has been 
implemented in the online TK-StripCam model which is used to predict the properties of hot 
rolled products [65]. 

Remarks on other available models 

The diffusional model developed by Quidort et al. [66] assumes that carbon  diffusion in austenite 
controls  the  growth  of  bainitic  ferrite.  This  growth  mechanism  is  in  disagreement  with  various 
characteristics of bainite which have been observed experimentally [67] such as the surface reliefs 
[68],  [69],  the  incomplete  reaction  phenomenon  [70],  and  the  in-situ  monitoring  of  acoustic 
emissions accompanying the transformation [71]. These observations strongly indicate that bainite 
grows in a displacive manner whereby the neigbouring austenite is plastically deformed which causes 
the  growth  of  subunits  to  cease.  Besides  the  fact  that  Quidort’s  model  assumes  an  incorrect 
transformation mechanism, even from a pragmatic  point of view Quidort’s model is not attractive 
since their model calculations require knowledge of a large number of parameters, which so far can 
only be obtained by fitting against experimental data. For example, the model has an incubation time 
as  input  parameter,  which  can  only  be  obtained  by  fitting  of  S-shaped  fraction  curves.  Moreover, 
such an incubation time has no physical meaning. 

Many kinetic models based on displacive growth of bainite have been developed. All the displacive 
models described in Refs [72], [73], [74], [75], [76] have following drawbacks: 

− 

− 

they do not account for cementite formation, and are thus not suitable to describe bainite 
formation in low Si steels. 
they  predict  that  at  a  temperature  just  below  the  bainite-start  temperature  (Bs)  the 
transformation  kinetics  are  maximum  and  decrease  with  decreasing  temperature.  This 
contradicts experimental data in various TTT diagram which show that bainite start-curves 
are  C-shaped,  and  that  the  maximum  transformation  kinetics  occur  at  the  so-called  nose 
temperature which is significantly lower than Bs.  

The kinetic models based on displacive growth of bainite proposed by van Bohemen [77] [78] gives 
a  correct  prediction  of  the  C-shape  of  bainite  start-curves.  In  Appendix  8  model  simulations  are 
compared to experimental data of LoSi and HiSi. It is concluded that the model can be improved on 
various aspects such as: 

−  Cementite formation is not explicitly described. Instead, the calculation of the carbon content 
in  the  remaining  austenite  relies  on  the  mass  balance  and  an  assumed  “effective”  carbon 
content of the bainitic ferrite which is an input parameter in the model. This “effective” carbon 
content  in  fact  represents  the  carbon  which  is  not  dissolved  in  austenite  and  thus  is  (i) 
dissolved  in  (supersaturated)  bainitic  ferrite  and/or  (ii)  precipitated  as  cementite  or  other 
carbides and/or (iii) trapped at dislocations or grain boundaries. Although this approach with 
an “effective” carbon content of bainite enables modelling of bainite kinetics in both low- and 
high-Si steels [79], [80], the explicit simulation of carbide formation analogous to Azuma’s 
model is preferred because the fraction and distribution of carbides is important as input for 
mechanical models. 

−  The  analytical  model  [78]  relies  on  a  mean  field  approach  and  this  might  give  inaccurate 
predictions when  a heterogeneous carbon distribution develops in the remaining austenite 
during the course of transformation.  

−  Mechanical stabilization of austenite is not incorporated in the model. The shape deformation 
accompanying the displacive formation of bainitic subunits, which has a shear and dilatational 
component, strengthens the remaining austenite and therefore the resistance against further 
transformation  increases  [81].  Analogous  to  this  transformation  induced  strengthening  of 
austenite, it is well known that plastic deformation of austenite can also significantly influence 
the bainitic transformation. On the one hand dislocations in austenite may act as potential 
nucleation sites [36] and/or influence the nucleation rate at grain boundaries [80], and on 
the  other  hand,  the  dislocation  strengthening  increases  the  resistance  against  shape 
deformation and thereby retards the transformation [82]. 

Page 101 of 112 

 
 
 
Page 102 of 112 

 
 
Appendix 8. Compareson of modelling to experimental data of LoSi and HiSi 

In this appendix it is first demonstrated how the experimental bainite kinetics of LoSi and HiSi are 
evaluated from dilatometry data, and subsequently the comparison with simulations using the model 
from Ref. [77] is discussed. 

Experimental fraction curves determined by dilatometry  

Dilatometry measurements were performed using cylindrical samples (5 mm diameter) of LoSi and 
HiSi. The annealing involved 5 minutes soaking at 920ºC, followed by fast cooling to an isothermal 
holding temperature of 390, 420, 450 and 480ºC. When a plateau was reached in the dilatometry 
signal,  indicative  that  bainite  formation  has  ceased,  the  samples  were  cooled  in  He  gas  to  room 
temperature, in a natural manner, i.e. without active gas blowing to the sample. 

The phase fractions and transformation kinetics have been evaluated from dilatometry data with the 
Lever rule applied to the data using the non-linear equations for the thermal contraction of bcc and 
fcc lattices derived in Ref. [7]. Figure 87a shows that the non-linear thermal expansion of bcc phase 
(green line) is found to agree well with the dilatation data measured during cooling of the LoSi sample 
from  420  to  20  ºC  after  the  bainitic  hold  (overage  temperature,  TOA).  Furthermore,  the  blue  line 
(non-linear thermal expansion of fcc phase) in Figure 87a shows an adequate fit of dilatation data 
measured  during  cooling  from  austenitizing  to  the  hold  temperature.  The  fraction-temperature 
dependence plotted in Figure 87b is evaluated by applying the Lever rule, and from the analysis of 
the dilatation data during the overage the bainite kinetics in Figure 87c are derived. It is seen that a 
fully bainitic microstructure is formed in the LoSi sample. The fractions evaluated for the other TOA 
are listed in Table 24. 

For  HiSi  transformed  at  450ºC  the  bainitic  transformation  is  incomplete  (Figure  87d),  and  the 
dilatation data measured for the B + RA microstructure during cooling from 450 to 200 ºC can be 
fitted using a thermal expansion calculated, using a rule of mixtures, for a microstructure consisting 
of  88%  bcc  and  12%  fcc  phase  (red  dashed  line).  The  fraction  austenite  of  12  vol.%  in  the 
microstructure after the incomplete bainite formation at 450ºC is not very stable and therefore the 
dilatometry  data  deviate  from  the  red  dashed  line  below  200  ºC  which  indicates  the  formation  of 
martensite. From this analysis it follows that at room temperature 2% M is formed. Figure 87e shows 
the  fraction  evolution  as  a  function  of  temperature.  The  bainite  transformation  kinetics  evaluated 
from the measured dilatation ∆L during the bainitic hold are plotted in Figure 87f. Table 25 shows 
the phase fractions formed in HiSi at the other TOA. 

Table 24. Phase fractions of bainite, martensite and retained austenite determined from 
dilatometry data for LoSi steel isothermally transformed in the range 390-480ºC (the typical 
uncertainty for each phase is +/- 0.02). 

Temperature, 

Time, 

B 

M 

RA 

[ºC] 

390 

420 

450 

480 

[s] 

190 

130 

130 

120 

1.0 

1.0 

0.99 

0.93 

0.01 

0.07 

Page 103 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
LoSi-420ºC 

HiSi-450ºC 

a)

160

120

]

m
µ
[
L
∆

80

40

d)

160

120

]

m
µ
[
L
∆

80

40

cooling LoSi-920ºC-420ºC-130s

bcc expansion

fcc expansion

cooling HiSi-920ºC-450ºC-130s
bcc expansion
fcc expansion
0.88 bcc + 0.12 fcc

0

0

100 200 300 400 500 600
T [ºC]

0

0

100 200 300 400 500 600
T [ºC]

b)

1,0

0,8

0,6

f

0,4

0,2

0,0

1,0

0,8

0,6

0,4

0,2

0,0

c)

f

fraction  LoSi-920ºC-
420ºC-130s

0

100 200 300 400 500 600
T [ºC]

fraction  LoSi-920ºC-420ºC-130s

e)

1,0

0,8

0,6

f

0,4

0,2

0,0

1,0

0,8

0,6

0,4

0,2

0,0

f)

f

fraction  HiSi-920ºC-
450ºC-130s

0

100 200 300 400 500 600
T [ºC]

fraction  HiSi-920ºC-450ºC-130s

0

40

80

t [s]

120

0

40

80

t [s]

120

Figure 87. Left LoSi and right HiSi (a,d) The measured dilatation as a function of temperature, 
(b,e) the evaluated fraction against temperature, and (c,f) bainite kinetics at the temperature TOA.  

Page 104 of 112 

 
 
 
 
 
 
 
 
 
 
Table 25. Phase fractions of bainite, martensite and retained austenite determined from 
dilatometry data for HiSi steel isothermally transformed in the range 390-480ºC (the typical 
uncertainty for each phase is +/- 0.02). 

Temperature, 
ºC 
390 
420 
450 
480 

Time, 
s 
190 
130 
130 
70 

B 

0.90 
0.89 
0.88 
0.85 

M 

0.01 
0.01 
0.02 
0.03 

RA 

0.09 
0.10 
0.10 
0.12 

Calculations with Van Bohemen’s model  

Model 

The displacive model proposed in Ref. [77] was extensively validated in Ref. [78] using the bainite-
start curves of various Si-lean alloys, and in later work [83] it was demonstrated that the displacive 
model  can  capture  the  incomplete  transformation  in  a  Si-rich  steel  when  a  simple  procedure 
accounting for carbon enrichment in the remaining austenite is applied to calculate the change in the 
zero  transformation  temperature  Bs,  which  is  a  key  parameter  in  the  model  controlling  the 
transformation kinetics.  

In the model developed in Ref. [77] the number density of potential nucleation sites Ni is assumed 
to be proportional to the driving pressure and thus Ni increases linearly with undercooling (Bs – T). 
In the derivation of this model no specific assumptions are made regarding carbon enrichment and 
therefore the model can be applied to calculate the kinetics of bainite formation in high-Si steels by 
numerical integration of the differential equation for the change of the bainite fraction f as a function 
of time t [77]:  

Eq. 18 

𝑑𝑑𝑓𝑓
= (1 − 𝑓𝑓)(1 + 𝜆𝜆𝑓𝑓)𝜅𝜅
in which λf accounts for the autocatalytic contribution to the overall kinetics. The rate parameter κ 
𝑑𝑑𝑤𝑤
in Eq. (16) is given by [78] 

Eq. 19 

𝑍𝑍𝛿𝛿
𝑑𝑑

𝐾𝐾1Γ
𝑅𝑅

𝑄𝑄b
𝑅𝑅𝑇𝑇

�

𝛾𝛾 𝛼𝛼m(𝐵𝐵s − 𝑇𝑇)exp �−

� exp �−

𝜅𝜅 = 𝜈𝜈
which is dependent on both temperature and composition. In the case of high-Si steels, when the 
carbon concentration of the austenite increases, κ will mainly decrease due to a smaller undercooling 
(Bs  –  T)  and  also  because  the  effective  activation  energy  Qb  will  increase  [59].  Furthermore,  the 
above equations show that the kinetics are inversely proportional to the austenite grain diameter dγ 
because the austenite grain boundaries provide the nucleation sites initially present. For both LoSi 
and HiSi the parameter αm in Eq. 19 is calculated as 0.02 K-1 using the empirical equation proposed 
in Ref. [6]. The attempt frequency ν is assumed to be 1×1013 s-1. The constants δ and Z, respectively 
the effective thickness of the austenite grain boundary and a geometrical factor, are chosen as δ = 
1 nm and Z = 6. The parameter K1 is a material constant, and Γ = d(∆Gm) /dT  is the derivative of 
the  maximum  driving  force ∆Gm  with  respect  to  T.  The  autocatalytic  parameter λ  is  the  main 
temperature dependent fit parameter and can be determined on the basis of isothermal fraction-time 
curves. It has been found that λ increases with increasing austenite grain size dγ and some studies 
suggest that λ might also be dependent on the chemical composition. 

Model calculations for LoSi compared to experimental data 

The open circles in Figure 88a represent the experimental start curve (3 vol.%) of LoSi; the error 
bars indicate the ± 1 vol.% inaccuracy. Furthermore, the open triangles represent the experimentally 
determined  30  %  transformation  curve.  The  start  curve  can  be  simulated  with  the  procedure 
described  in  Ref.  [78].  The  best  agreement  with  the  3  vol.%  transformation  data  (solid  line)  is 
obtained using Bs = 556 °C [6], dγ = 4 µm, λ = 22 (the mean value of the autocatalytic parameter 
in the temperature range 390-450 ºC determined from fraction−time data as explained later), and 
Qb = 53.5 kJ mol-1; the material-independent relationship K1Γ = (169.8 kJ mol-1 – Qb)/(705 K) found 
in Ref. [78] leads to K1Γ = 165 J mol-1 K-1. The difference with the value predicted using the empirical 
relationship for Qb [78], which is 41.5 kJ mol-1, is within the estimated uncertainty range discussed 
in Ref. [78]. 

Page 105 of 112 

 
 
 
 
 
 
 
 
calc. start-curve f = 0.03
exp.  f =  0.03
exp.  f =  0.30

620

580

540

500

]

C

460

º
[
T

420

380

340

300

1,0

0,8

0,6

f

0,4

0,2

0,0

LoSi-920ºC-390ºC-
190s

LoSi-920ºC-450ºC-
130s

0

1

10

t  [s]

100

0

20

40

60

80
t  [s]

100 120 140

Figure 88. Left: calculated start curve (3 vol.%) for LoSi (solid line) compared to the experimental 
data (open circles). The open triangles represent the experimental kinetics at 30 % transformation 
Right: the calculated kinetics of bainite formation compared to experimental data for TOA 
temperatures in the range 390−450 °C. 

Figure 88b shows the comparison between the experimental kinetics (symbols) and the simulations 
(lines). The autocatalytic parameter λ, which determines the S-shape of the fraction−time curve, has 
been varied between λ = 20 and 24 to optimize the fits (see Table 26). For each temperature the 
agreement  is  adequate  up  to  a  fraction  of  approximately  0.75.  However,  for  the  final  stage  of 
transformation large discrepancies are seen, especially for low TOA. The sluggish experimental bainite 
kinetics  at  the  final  stage  of  transformation  is  currently  being  studied  [84]  whereby  mechanical 
stabilization of the remaining austenite due to bainite is assumed to play a key role. When a bainitic 
lath is formed then the surrounding austenite is work hardened due to the plastic accommodation of 
the shape change associated with the transformation. This is assumed to lead to both dislocation-
induced nucleation (autocatalysis) and mechanical stabilization.  

Model calculations for HiSi compared to experimental data 

The experimental start curve (3 vol.%) of HiSi are represented by the open circles in Figure 89a, and 
the open triangles represent the experimentally determined 30 % transformation curve. Analogous 
to LoSi (see above) the start curve can be simulated with the procedure described in Ref. [78]. The 
best agreement with the 3 vol.% transformation data (solid line) is obtained using Bs = 579 °C [6], 
dγ = 4 µm, the mean value of the autocatalytic parameter λ in the temperature range 390-450 ºC is 
approximately  22  (exact  values  evaluated  from  the  fraction−time  data  are  given  later),  and  Qb  = 
60.3 kJ mol-1; the material-independent relationship K1Γ = (169.8 kJ mol-1 – Qb)/(705 K) found in 
Ref. [78] leads to K1Γ = 155 J mol-1 K-1. The differences with the values predicted using the empirical 
relationships,  Bs  =  569  °C  and  Qb  =  55.3  kJ  mol-1,  are  within  the  estimated  uncertainty  ranges 
discussed in respectively Ref. [6] and Ref. [78]. 

Since  carbon  enrichment  is  very  small  at  the  beginning  of  the  bainite  transformation  in  a  high-Si 
steel, a satisfactory agreement is found for the beginning of transformation using the model from 
Ref.  [78].  However,  this  model  (developed  for  lean-Si  steels)  would  overestimate  the  kinetics  of 
transformation  at  a  later  stage  of  transformation,  which  is  due  to  the  fact  that  with  the  original 
simulation procedure no increase in the carbon content of the austenite in predicted when the fraction 
of bainite increases. Application to kinetics in high-Si steels is possible by straightforward numerical 
integration of Eq. 18 and calculating the change in κ (see Eq. 19) in each time step due to carbon 
enrichment.  The  higher  carbon  concentration  in  the  austenite xγR  leads  to  a  higher  Qb  [78]  and  a 
lower Bs according to the carbon dependence given by the empirical equations proposed in Ref. [6]. 
The undercooling (Bs – T) in particular has a large effect on the transformation kinetics. This modified 
modeling  approach  dictates  that  the  transformation  will  cease  when  Bs  equals  the  isothermal 
transformation temperature. Validation of this extended model has been reported in Ref. [85] using 
experimental fraction−time curves of Fe-0.3C-2.4Mn-1.8Si. 

The carbon concentration in the remaining austenite, which is the key parameter determining the 
kinetics of bainite formation in high-Si steels, is controlled by both the carbon content of the bainitic 
ferrite  and  the  degree  of  carbide  precipitation  [86].  For  HiSi  it  is  assumed  that  the  carbon 
supersaturation is small since bainite is formed at relatively high temperatures. In addition, it seems 
justified to assume that some carbide precipitation can occur in the remaining austenite despite the 
presence  of  Si.  In  the  model  it  is  assumed  that  the  carbon  content  of  the  bainitic  ferrite  xαb  is 
effectively  higher  than  the  para-equilibrium  value  due  to  a  combination  of  supersaturation  and 
carbide precipitation. 

Page 106 of 112 

 
 
 
 
 
calc. start-curve f = 0.03
exp.  f =  0.03
exp.  f =  0.30

620

580

540

]

C

500

º
[
T

460

420

380

340

300

1,0

0,8

0,6

f

0,4

0,2

0,0

HiSi-920ºC-390ºC-
190s

HiSi-920ºC-450ºC-
130s

0

1

10

t  [s]

100

0

20

40

60

80
t  [s]

100 120 140

a) 

b) 

Figure 89. a) calculated start curve (3 vol.%) for HiSi (solid line) compared to the experimental 
data (open circles). The open triangles represent the experimental kinetics at 30 % transformation 
b) the calculated kinetics of bainite formation compared to experimental data for temperatures in 
the range 390−450 °C. 

In the present work the carbon content of the bainitic ferrite x λb is adjusted to account for various 
degrees  of  carbon  supersaturation  and  carbide  precipitation,  both  of  which  depend  on  the 
temperature  of  bainite  formation.  Table  26  shows  that  values  of  xλb  between  0.05  and  0.13  are 
chosen to optimize the agreement with the experimental fraction curves shown in Figure 89a. The 
values of the autocatalytic parameter λ, which determines the S-shape of the fraction−time curve, 
are  in  the  range  21-23  (see  Table  26)  as  evaluated  from  the  best  fits.  It  can  be  seen  that  the 
simulations (solid lines) are in reasonable agreement with the experimental data. Similar as for LoSi, 
the deviations become large at the final stage of transformation. 

Table 26. Parameters used in the simulations to optimize the agreement with experimental data. 

LoSi 

HiSi 

TOA 
(°C) 
390 
420 
450 

xαb 
(wt.%) 
0.22 
0.22 
0.22  

λ 

20 
22 
24 

xαb 
(wt.%) 
0.05 
0.09 
0.13  

λ 

22 
21 
23 

Page 107 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Page 108 of 112 

 
 
Appendix 9. Azuma model 

In  the  Azuma  model  –  like  in  most  bainite  models  that  assume  displacive  transformation  –  the 
starting assumption is that the nucleation rate 

 can be expressed by 

𝛼𝛼𝐵𝐵

𝛼𝛼𝐵𝐵
�𝐼𝐼𝑜𝑜,𝑝𝑝𝑝𝑝

  the  volume  fraction  of  bainitic  ferrite, 

𝛼𝛼𝐵𝐵
𝐼𝐼𝑜𝑜
with 
  the  factor 
accounting for autocatalysis. Azuma et al. proposed that the initial nucleation rate can be described 
by, a formulation he called “classical nucleation theory”, as [63] 

  the  initial  nucleation  rate,  and 

= �1 + 𝛽𝛽𝑓𝑓𝑜𝑜
𝛼𝛼𝐵𝐵
𝑓𝑓𝑜𝑜

𝛼𝛼𝐵𝐵
𝐼𝐼𝑜𝑜,𝑒𝑒𝑝𝑝

𝛽𝛽

𝛼𝛼𝐵𝐵
𝐼𝐼𝑜𝑜

Eq. 20 

𝛾𝛾
𝑄𝑄𝐶𝐶
𝑅𝑅𝑇𝑇� 𝑒𝑒𝑒𝑒𝑒𝑒 �−

∗

∆𝐺𝐺𝛾𝛾→𝛼𝛼𝐵𝐵,𝑜𝑜

= 𝑁𝑁𝑜𝑜

𝛼𝛼𝐵𝐵
𝑘𝑘𝑇𝑇
𝐼𝐼𝑜𝑜,𝑝𝑝𝑝𝑝
 describes the initial density of (potential) nucleation sites which can 
The pre-exponential factor 
ℎ 𝑒𝑒𝑒𝑒𝑒𝑒 �−
depend strongly on the properties of austenite (i.e. the grain size). The factor kT/h represents the 
attempt  frequency.  The  nucleation  rate  depends  on  two  probability  functions  of  which  the  last 
exponential factors depends on the activation energy 

 for nucleation. 

𝑁𝑁𝑜𝑜

𝑅𝑅𝑇𝑇

�

Eq. 21 

Different from approaches followed in both diffusional and displacive models, Azuma et al. calculate 
the activation energy for para-equilibrium nucleation of ferrite in austenite according to [19] 

∗
∆𝐺𝐺𝛾𝛾→𝛼𝛼𝐵𝐵,𝑜𝑜

3
16𝜋𝜋𝜎𝜎𝛼𝛼𝛾𝛾
2
3(∆𝐺𝐺𝑣𝑣)

=

− 𝐺𝐺𝑁𝑁

∗
∆𝐺𝐺𝛾𝛾→𝛼𝛼𝐵𝐵,𝑜𝑜
which shows a dependence on two terms: the first term equals the activation energy common for 
classical nucleation of diffusional phase products and the second term represents a term utilized in 
displacive models - the so-called "universal nucleation function" 
 which was defined by Bhadeshia 
[86] 

Eq. 22 

𝐺𝐺𝑁𝑁

Eq. 23 

In displacive bainite models the temperature below which bainite can form requires that both the 
𝐺𝐺𝑁𝑁 = 3.637(𝑇𝑇 − 273.18) − 2540 (𝐽𝐽/𝑚𝑚𝑜𝑜𝑚𝑚)
nucleation condition (
 ) are satisfied 
[86]. 
 represents the free energy change for a transformation without a change in composition, 
and for bainite this energy should balance the stored strain energy of bainite which is approximated 
∆𝐺𝐺v
as 400 J/mol. 

 ) as well as the growth condition (

400 J/mol

∆𝐺𝐺𝑚𝑚 

∆𝐺𝐺v

𝐺𝐺𝑁𝑁

𝛾𝛾→𝛼𝛼′

𝛾𝛾→𝛼𝛼′

> 

> 

The prediction of the bainite kinetics in Azuma’s model is coupled with the calculation of the cementite 
formation in either the austenite and/or the bainitic ferrite. All three concurrent processes determine 
the  carbon  concentration  in  the  austenite  as  a  function  of  temperature  and  time,  which  is  an 
important parameter governing the bainite kinetics. Details about the calculation of nucleation and 
growth of cementite are given in Ref. [63]. 

The nucleation of cementite in bainitic ferrite competes with the carbon depletion of ferrite by the 
diffusion of carbon into the austenite phase. The diffusion of carbon is represented by the equation 

Eq. 24 

𝛼𝛼𝜖𝜖

𝛼𝛼𝜖𝜖

𝛼𝛼𝜖𝜖𝛾𝛾

𝛼𝛼𝜖𝜖

𝑊𝑊𝛼𝛼𝐵𝐵
𝛼𝛼
4(𝐷𝐷𝐶𝐶
𝑡𝑡)

0.5

�

𝛼𝛼𝜖𝜖𝛾𝛾

𝑋𝑋𝐶𝐶

− 𝑋𝑋�𝐶𝐶

=   𝑋𝑋�𝐶𝐶

�𝑒𝑒𝑝𝑝𝑓𝑓𝑒𝑒 �

+ �𝑋𝑋𝐶𝐶
 is the carbon concentration of ferrite in para-equilibirum with austenite, 

𝑋𝑋𝐶𝐶
where 
 is the carbon 
 is the average carbon 
concentration of bainitic ferrite normal to the 
concentration in bainitic ferrite which at the time of first bainitic nucleation is equal to the austenite 
carbon concentration since the nucleation happens diffusionless. The bulk diffusion of carbon in ferrite 
 is the bainite plate thickness and depends on the temperature, strength of 
austenite and driving force for transformation. The trained neural network of Singh and Bhadeshia 
𝛼𝛼
𝐷𝐷𝐶𝐶
is applied for its computation [63]. 

-interface at time 

 is given in [63]. 

 and 

𝛼𝛼𝐵𝐵/𝛾𝛾

𝑊𝑊𝛼𝛼𝜖𝜖

𝑋𝑋�𝐶𝐶

𝑋𝑋𝐶𝐶

𝛼𝛼𝜖𝜖

𝛼𝛼𝜖𝜖

𝑤𝑤

Page 109 of 112 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Page 110 of 112 

 
 
 
Appendix 10. Comparison of static and dynamic flow curves 

This appendix demonstrates the high strain rate flow respones of the developed high silicon and low 
silicon  bainitic  steels.  The  detail  decription  of  post  processing  of  the  recorded  signals  in  order  to 
translate them into stress and strain curves, and the quantitative correlation between microstructural 
variables  and  the  strain  rate  sensitivity  of  these  steels  was  discussed  in  [87].  Shakerifard  et  al. 
demonstrated  that  any  microstructural  variables  that  increase  the  strength  of  steels  result  in  the 
reduction of strain rate sensitivity. For instance, martensite phase as a second phase constituent and 
fine microstructure decrease the stain rate sensitivity.   

Dynamic Flow curves 

Figure  90  shows  the  flow  curves  of  HiSi  steels.  Generally,  in  all  samples  a  positive  strain  rate 
sensitivity is observed which means at higher strain rates compared to static tests (strain rate=0.8 
[s-1]), a strengthening phenomenon is seen. Besides, a delayed necking behaviour is observed, where 
the necking region of the flow curves are started at higher strain levels compared to the static ones. 
This indicates, a better uniform elongation or ductility behaviour is seen under the dynamic loading 
condition. 

Figure 90. Dynamic and static flow curves of HiSi samples; (a) CAL 920°C/-100°C/s/450°C/120s (b) 
CAL  920°C/-100°C/s/450°C/14s    and  (c)  CAL  860°C/-100°C/s/450°C/120s.  Legends  indicate  the 
corresponding strain rate level of each curve. 

Figure 91 shows the flow curves of LoSi steels. Similarly, as mentioned for HiSi grades, in all samples 
of LoSi grade a strengthening and enhanced elongation properties are seen. This indicates a positive 
strain rate sensitivity in the LoSi similar to HiSi grade.  

The  simultanious  increase  in  strength  and  ductility  of  both  grades  reveal  an  improved  energy 
absorption under high strain rate deformations which is of advantage during crash events and cold 
forming processes.  

Page 111 of 112 

 
 
 
  
 
Figure 91. Dynamic and static flow curves of LoSi samples; (a) CAL 920°C/-100°C/s/450°C/120s, 
(b)  CAL  920°C/-100°C/s/390°C/120s  and  (c)  CAL  820°C/-100°C/s/450°C/120s.  Legends  indicate 
the corresponding strain rate level of each curve. 

Page 112 of 112 

 
 
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focusses  on  control  and 
BaseForm  project 
optimization  of  the  very  promising  combination 
of  steel  phases:  bainite,  martensite  and  retained 
austenite. Two alloy compositions, with low and high 
Si  content,  were  studied  with  the  aim  to  produce 
cold-rolled  annealed  microstructures  consisting  of 
a  bainitic  matrix  with  a  small  fraction  of  second-
phase  constituents.  It  was  observed  that  both 
heat  treatment  conditions  and  alloy  composition 
have  strong  effect  on  mechanical  properties.  The 
main  influencing  parameters  for  the  two  treated 
steels  are  the  annealing  temperature,  the  cooling 
rate  and  mainly  the  averaging  temperature  and 
averaging time. Yield stresses and tensile strength 
decrease strongly with increasing bainite lath size, 
total elongation increases with contents of residual 
austenite  and  the  hole  expansion  coefficient 
decreases  with  increasing  amount  of  2rv  phases, 
mainly  martensite.  A  deeper  analysis  of  the 
influence of secondary phases by modelling shows 
that yield stress and the uniform elongation increase 
with  increasing  martensite  content,  whereas  yield 
stress  decreases  and  uniform  elongation  increases 
with  increasing  retained  austenite  content.  The 
effect  of  different  bainite  morphologies  was  not 
that pronounced. For the analysed steels, the effect 
of  the  other  parameters  screens  the  influence  of 
the  morphology  on  the  mechanical  and  damage 
response.  Attempt  was  made  to  link  thermo-
dynamic  based  transformation  models  with  micro-
mechanical  and  crystallography  based  models. 
Special attention was given to the material damage. 
All  the  collected  data  were  used  to  develop  the 
Guidelines  for  European  steel  industry  to  produce 
high  strength  bainitic  Advanced  High-Strength 
Steels  with  high  elongation  and  hole-expansion 
behavior under industrial constrictions.