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dissertation global and local fracture properties of metal matrix ...

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Section 7<br />

Table 7.1. Data on the critical particle size for the PM-MMC Al6061-20%Al2O3 before <strong>and</strong><br />

after different number <strong>of</strong> ECAP passes.<br />

Number <strong>of</strong> ECAP passes 0 4 7<br />

dc [µm] 33.4 4.1 0.9<br />

The rod <strong>of</strong> investigated material is cut into samples with a length <strong>of</strong> 100 mm. These samples<br />

are heated to 370°C <strong>and</strong> pressed repeatedly through the ECAP die. The parameters <strong>of</strong> the<br />

ECAP die are ϕ = 90° <strong>and</strong> ψ = 20°. The material is subjected to 4 <strong>and</strong> 7 ECAP passes. The<br />

choice <strong>of</strong> these numbers <strong>of</strong> the ECAP passes can by explained by results <strong>of</strong> calculations given<br />

in Table 8.1. Here, the critical values <strong>of</strong> the particle size determined by Eq. 7.8 are presented<br />

for the as-fabricated MMC, <strong>and</strong> the MMC after 4 <strong>and</strong> 7 ECAP passes. It is seen that the<br />

increase <strong>of</strong> number <strong>of</strong> ECAP passes significantly decreases the dc-value. dc = 33.4 µm for the<br />

as-fabricated MMCs, thus, the strongly clustered particle distribution is expected for this<br />

material. After 4 ECAP passes, the dc-value decreases up to 4.1 µm. Taking into account that<br />

the particle size in investigated material is in the range <strong>of</strong> 1…5 µm, particle clusters should<br />

start to scatter. After 7 ECAP passes, the dc = 0.9 µm. Since this value is less than the lowest<br />

bound <strong>of</strong> the particle size, a homogeneous particle distribution after 7 ECAP passes can be<br />

expected.<br />

7.3. A quadrat method to estimate the homogeneity <strong>of</strong> the particle distribution in the<br />

<strong>metal</strong> <strong>matrix</strong> composites<br />

Different methods to estimate the homogeneity <strong>of</strong> the particle distribution in the MMCs have<br />

been proposed: the mean free path, the nearest neighbour distance, the radial distribution<br />

function, <strong>and</strong> the quadrat method [82]. As was found in [82], for the MMCs with strongly<br />

clustered particle distribution, the quadrat method is more effective to detect pronounced<br />

changes in the MMC microstructure in comparison to other methods. With the quadrat<br />

method, the image to be studied is divided into a grid <strong>of</strong> square cells <strong>and</strong> the number <strong>of</strong><br />

particles in each cell is counted [83]. In general, an ordered particle distribution would be<br />

expected to generate a large number <strong>of</strong> quadrats containing approximately the same number<br />

<strong>of</strong> particles, whereas a clustered distribution would be expected to produce a combination <strong>of</strong><br />

empty quadrats, quadrats with a small number <strong>of</strong> particles, <strong>and</strong> quadrats with many particles.<br />

83

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