CS代考 CM-247LC nickel super-alloy)

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Applications of SRAS in NDE

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Obtaining Orientation

Calculated SAW velocity model: Nickel

Material elastic constants
SAW phase velocity
Crystallographic orientation
Literature
using SRAS
Orientation
information output
All linked

Obtaining Orientation

Obtain experimental data for many wave propagation directions

Obtaining Orientation
For each pixel compare the experimental data to the model of possible shapes and store the figure of merit.
(how well they match)

Obtaining Orientation

The location of highest figure of merit shows the crystallographic orientation for that pixel.

Repeat for all pixels in the image

This is a brute force search and is quite slow.

We use some tricks to speed this up in reality.

Orientation Images

Orientation properties determine material performance

Digital signal processing

Silicon solar cells

Orientation in 111 direction better for converting light into electricity hence the blue colour of the main cell

SRAS obtains similar values for orientation compared to gold standard technique electron back scatter diffraction (EBSD)

Digital signal processing

Also works for different crystal symmetries, in this case hexagonal.
EBSD has higher spatial resolution

Defect detection

Good Probe level
Good acoustic signal
No acoustic signal

Defect detection

Good Probe level
No acoustic signal
Good Probe level
‘modified’ acoustic signal

Defect detection for 3D printing
Powder-laser based methods useful for creating intricate geometry
Performance materials used, such as Titanium and Nickel-based alloys
Laser used to melt layers together to create parts
Weight saving and performance improvements possible

Figure: Lattice samples made with 3D printing

Defect detection
Previous layers are melted and affected during the following layers build
This can create defects away from the surface
If we only inspect the surface, then we need to scan every layer
Want to minimise inspection time

Inspected layers
Defect map

Defect detection

Real-time monitoring of laser powder bed fusion process using high-speed X-ray imaging and diffraction, Zhao et al. Scientific & Reports, 7, (2017)

Defect detection

Design choices

Scan speed
Laser powder
Layer height
Hatch spacing

Processing choices

Contamination

Creep resistance

Refocus this to why AM is useful!

Video SLM and WAAM side by side

Defect detection

Initial studies highlighted shifts in velocity
Detecting mode converted ‘Lamb’ waves
Normal range for titanium

Exemplary detail

Defect detection

Polished samples: subsurface porosity quantified (validated by XCT)

SRAS optical
SRAS optical (magn.)
SRAS acoustic
SRAS acoustic (magn.)
XCT subsurface image
SEM surface image

Polished 1cm3 cube

Defect detection

Expected hatching pattern
Polished powder bed part with manufacturing defect (CM-247LC nickel super-alloy)

SRAS acoustic
Observed hatching pattern

SRAS optical

Digital signal processing
Grain boundary mapping

Allows statistics on the microstructure to be produced.
Mean size and standard deviation of grains
Distribution of grain sizes
Proportion of ‘fast’ and ‘slow’ grains etc.

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