Software and Systems Engineering Standards: Verification and Validation of Sy...
Nist project final report
1. Quantifying microstructural features
and finding structure-property
linkages in aging process of Al6061
ME8883 Materials Informatics
Ali Khosravani
2. Introduction
Alloys in this group have
high strength-to-weight ratio
Good weldability
good formability
good corrosion resistance
Soft Strength increase Peak Strength Overaged
Solid
Solution
Coherent
Precipitates (β”)
Partially
Coherent(β’)
Incoherent
Precipitates(β)
Application
Aircraft fittings
camera lens mounts
electrical fittings and connectors
brake pistons, hydraulic pistons
valves and valve parts
bike frames.
Strengthen by Precipitation of
Mg2Si, higher levels of Mg2Si
leeds to higher strength
3. Microstructure
Microstructural features of impact
exist at different length scales
• Coherent GP zones and semi-coherent
precipitate particles (TEM or SEM)
Volume fraction
Size (nm)
Aspect ratio
Spacing (nm)
• Al-Fe-Si-type constituent particles (OM)
Volume fraction
Size (microns)
Aspect ratio
Spacing (microns)
• Grain structure, including degree of
recrystallization and texture (EBSD)
Size (microns)
Aspect ratio
Texture
4. Mechanical Properties and microstructure
Precipitate hardening strengthen material
Mechanical Properties
is a result of :
Precipitate Volume fraction
Precipitate Size (nm)
Precipitate Aspect ratio
Precipitate Spacing (nm)
Particle Volume fraction
Particle Size (microns)
Particle Aspect ratio
Particle Spacing (microns)
Grain structure
Grain Size
Grain Aspect ratio
Texture
Grain Boundary
6. Mechanical testing
Uniaxial Tensile Test
Five tests were run for each condition.
ASTM E8-13a (Round specimens with a diameter
and gage length of 0.25” of 1” respectively.
The machine was run at a constant cross head
speed to achieve a strain rate of 0.005 in/in /s
Al 6061 Specimen
Type
Average Yield
Strength (ksi)
Average Ultimate
Tensile Strength (ksi)
400F HT 43.136 46.400
525F HT 26.022 33.188
650F HT 13.493 24.439
775F HT 8.633 20.321
AR RD 44.114 47.660
7. Microstructural Datasets
EBSD
75 scans and combined into
scan size of7x7 mm2
4 μm resolution
SEM
10 BSE images at random
regions
View field: 100x100 μm2
Optical Microscope (OM)
10 images at random regions
View field: 800x600 μm2
8. EBSD dataset
• Grain size distribution
Grain size distribution is
calculated based on number
of pixels in each grain.
• Grain aspect ratio distribution
The aspect ratio is defined as
the length of the minor axis
divided by the length of the
major axis and thus ranges
from 0 to 1
Grain aspect ratio =
푏
푎
9. OM dataset
Images were corrected and segmented
Volume fraction, Size, Aspect ratio, and Spacing of particle
were measured
400F
Original Image Corrected Image Segmented Image
775F
10. Chord Length
Calculating chord lengths row by row on x direction
and column by column in y directions on binary images
0 50 100 150 200 250 300 350 400 450 500
3
2
1
0
x 10
-4
Number of Pixels
Frequency
AR
400 F
525 F
650 F
775 F
Performing this operation over 10 images
11. TEM images required to provide
information about precipitate in
higher resolution and information
about precipitate/matrix interface
SEM dataset
Images were segmented
Volume fraction, Size, and Spacing of particle were measured
12. 2-Point Statistics vs Measures Values
2-point statistics contains all information
about particle size, aspect ratio, volume
fraction and their spacing.
PCA can be performed on 2-point statistic
instead of the calculated parameters (Size,
spacing, aspect ratio)
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-40 -20 0 20 40 60
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
PCA on 2-Point Statistics
-0.6
PC 1
PC 2
AR
400 F
525 F
650 F
775 F
-40 -20 0 20 40 60
PC 1
PC 3
0.1
0.08
0.06
0.04
0.02
0
-0.02
-0.04
-0.06
-0.08
-0.3 -0.2 -0.1 0 0.1 0.2
PC 1
PC 2
AR
400 F
525 F
650 F
775 F
0.03
0.02
0.01
0
-0.01
-0.02
-0.03
-0.3 -0.2 -0.1 0 0.1 0.2
PC 1
PC 3
PCA on Chord length(Particle
Spacing), Size, Aspect Ratio
13. 0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-30 -20 -10 0 10 20 30 40 50
PC 1
PC 2
AR
400 F
525 F
650 F
775 F
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-30 -20 -10 0 10 20 30 40 50
PC 1
PC 3
PCA on 2-Point Statistics
14. Averaging on Measured Values
Image dimensions from each OM, EBSD,
and SEM datasets are different.
The images were taken at random
regions on sample
To combine all Data together,
OM and SEM datasets need to
be averaged out
EBSD
OM
SEM
16. 0.1
0.05
0
-0.05
-0.1
-20 -10 0 10 20 30 40
0.06
0.04
0.02
0
-0.02
-0.04
-0.06
-0.08
-0.1
PCA on Average values from optical images (2-Point Statistics)
and EBSD values (Grain size, Grain aspect ratio)
-0.15
PC 1
PC 2
AR
400 F
525 F
650 F
775 F
-20 -10 0 10 20 30 40
PC 3
PC 1
Principal Component Analysis
17. Structure-property (Yield Strength) linkages
45
40
35
30
25
20
15
10
5
-20 0 20 40
Yield Strength (ksi)
PC 1
AR
400 F
525 F
650 F
775 F
45
40
35
30
25
20
15
10
5
-0.2 -0.1 0 0.1 0.2
Yield Strength (ksi)
PC 2
45
40
35
30
25
20
15
10
5
-0.1 -0.05 0 0.05 0.1
Yield Strength (ksi)
PC 3
18. Structure- property (Ultimate Tensile
Strength) linkages
50
45
40
35
30
25
20
-20 0 20 40
Ultimate Tensile Strength(ksi)
PC 1
AR
400 F
525 F
650 F
775 F
50
45
40
35
30
25
20
-0.2 -0.1 0 0.1 0.2
Ultimate Tensile Strength(ksi)
PC 2
50
45
40
35
30
25
20
-0.1 -0.05 0 0.05 0.1
Ultimate Tensile Strength(ksi)
PC 3
19. Future work
High Throughput Experiments
EBSD
OM
SEM
Local properties
Measuring local properties
through nano- and miro-indentation
Local microstructure
Collecting EBSD and OM
images at the same area, and
SEM images at the known
locations within marks
Including EBSD statistics (orientation, grain
boundaries) and precipitates statistics in PCA
Finding Structure, Property, Processing Linkages
20. Acknowledgments
Dr. Surya Kalidindi
Dr. Tony Fast
Jordan Weaver
Jon Yabansu
Ahmet Cecen
Andrew Castillo
