PSI - Issue 2_A
Grzegorz Lesiuk et al. / Procedia Structural Integrity 2 (2016) 3218–3225 Lesiuk et. al/ Structural Integrity Procedia 00 (2016) 000–000
3221
4
2 0 ˆ ( ) v F B B F B F Q 1
2
(4)
In this figure, ˆ ( ) v F L estimated linear function of a linear regime of the recorded hysteresis loop, ˆ ( ) v F Q estimated quadratic function of a non-linear regime of the recorded hysteresis loop. From linear regression the constants A 0 and A 1 will be easily obtained. The values B 0 , B 1 , B 2 are unknown and they should respect the following conditions from the common F k – knee value identification: ˆ ( ) ˆ ( ) v F v F L Q (5)
( ˆ ( )) Q
dF d v F
ˆ ( ) v F L
(6)
(for F=F
k )
According to the above conditions, we obtain:
k k B B F B F A A F B B F A A F 1 0 2 2 1 0 1 0 2 1 2 k k
(7)
k
The constants B 0 , B 1 , B 2 should be optimal from the mathematical point of view. In order to validity their optimal values, we can find the mentioned constants minimalizing the residual sum of squares (RSS) defined as:
Q for P P v F v for P P v F v 2 2 ( ˆ ( ) ) ( ˆ ( ) ) i i i
1
N i 1
k
(8)
.
2
(
)
v v max
min
L
i
i
i
k
The value of F k which corresponds to the minimal value will be treated as closure load F cl . V max and V min are the maximal and minimal values of COD during each cycle of loading. The described method is easy to automatization during the experiment with a guarantee of the optimal value F cl corresponding to the minimal . However, if the raw data are strongly influenced by the noise (or wrong tuning of the recorded signals) in that case, the algorithm may choose a wrong value of identified closure load point.
Table 1. Chemical composition of analyzed steel Chemical element C [%]
Mn [%]
Si [%]
P [%]
S [%]
PP – steel (1863)
0.08 0.06 0.09
0.025
0.15 0.17 0.02 N/A
0.245 0.198
0.015 0.025
RS – steel 1850-1900 BC– steel 1850-1900
0.1 0.2
0.03 <0.6
0.03
Typical puddle iron based on Czapliński et al. (2009) Typical mild 19 th century rimmed steel based on Czapliński et al. (2009)
<0.08
<0.4
variable
0.02-0.15
0.2-0.5
Variable
0.03-0.06
0.02-0.15
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