Excercise-1 SN Data
22
Fatigue data R=0 (sebagai contoh) No f (Hz) R N Failure 1 A-23 5.672 0 200 186,188 yes right 2 A-03 5 & 3,6 0 200 179,751 yes left 3 A-04 3.6 0 200 177,544 yes right 4 A-02 5 & 3 0 200 166,501 yes right 5 A-17 0,2 & 5 0 100 1,139,055 yes left 6 A-01 5 0 100 1,199,370 yes left 7 A-07 5 0 100 1,069,049 yes right 8 A-41 5 0 77 2,273,995 yes left Tugas -1 * Buat S-N curve (mean & design curve) untuk data hasil uji fatigue di bawa * Buat laporan tugas dengan ketentuan sbb: - Diketik di kertas A-4 - Buat analisa hasil S-N curve untuk masing-2 data (R=0 & R=-1) terutam - Jika data digabung berikan analisa perbandingan dengan data individua R=-1 No f (Hz) R N Failure 1 A-05 4 -1 200 153,750 yes left 2 A-06 4 -1 200 185,567 yes right 3 A-11 4 -1 200 185,108 yes right 4 A-13 4 -1 200 168,610 yes right 5 A-08 4 -1 200 356,347 yes right 6 A-09 5 -1 100 1,297,310 yes left 7 A-10 5 -1 100 1,284,457 yes right 8 A-12 5 -1 100 1,248,776 yes right Data Gabungan R=0 & R=-1 No f (Hz) R N Failure 1 A-23 5.672 0 200 186,188 yes right 2 A-03 5 & 3,6 0 200 179,751 yes left 3 A-04 3.6 0 200 177,544 yes right 4 A-02 5 & 3 0 200 166,501 yes right 5 A-17 0,2 & 5 0 100 1,139,055 yes left 6 A-01 5 0 100 1,199,370 yes left 7 A-07 5 0 100 1,069,049 yes right 8 A-41 5 0 77 2,273,995 yes left Specimen No. DSnom Failure location Specimen No. DSnom Failure location Specimen No. DSnom Failure location
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S-N Curve
Transcript of Excercise-1 SN Data
Fatigue data
R=0 (sebagai contoh)
No f (Hz) R N Failure
1 A-23 5.672 0 200 186,188 yes right 2 A-03 5 & 3,6 0 200 179,751 yes left 3 A-04 3.6 0 200 177,544 yes right 4 A-02 5 & 3 0 200 166,501 yes right 5 A-17 0,2 & 5 0 100 1,139,055 yes left 6 A-01 5 0 100 1,199,370 yes left 7 A-07 5 0 100 1,069,049 yes right 8 A-41 5 0 77 2,273,995 yes left
Tugas -1 * Buat S-N curve (mean & design curve) untuk data hasil uji fatigue di bawah ini* Buat laporan tugas dengan ketentuan sbb:
- Diketik di kertas A-4- Buat analisa hasil S-N curve untuk masing-2 data (R=0 & R=-1) terutama sebaran datanya- Jika data digabung berikan analisa perbandingan dengan data individual sebelum digabung
R=-1
No f (Hz) R N Failure
1 A-05 4 -1 200 153,750 yes left2 A-06 4 -1 200 185,567 yes right3 A-11 4 -1 200 185,108 yes right4 A-13 4 -1 200 168,610 yes right5 A-08 4 -1 200 356,347 yes right6 A-09 5 -1 100 1,297,310 yes left7 A-10 5 -1 100 1,284,457 yes right8 A-12 5 -1 100 1,248,776 yes right
Data Gabungan R=0 & R=-1
No f (Hz) R N Failure
1 A-23 5.672 0 200 186,188 yes right 2 A-03 5 & 3,6 0 200 179,751 yes left 3 A-04 3.6 0 200 177,544 yes right 4 A-02 5 & 3 0 200 166,501 yes right 5 A-17 0,2 & 5 0 100 1,139,055 yes left 6 A-01 5 0 100 1,199,370 yes left 7 A-07 5 0 100 1,069,049 yes right 8 A-41 5 0 77 2,273,995 yes left
Specimen No. DSnom
Failure location
Specimen No. DSnom
Failure location
Specimen No. DSnom
Failure location
100,000 1,000,000 10,000,000 10
100
1000R GABUNGAN (R=0 & R=-1)
R=0R=-1
log N (cycle)
log
ΔS (M
Pa)
9 A-05 4 -1 200 153,750 yes left10 A-06 4 -1 200 185,567 yes right11 A-11 4 -1 200 185,108 yes right12 A-13 4 -1 200 168,610 yes right13 A-08 4 -1 200 356,347 yes right14 A-09 5 -1 100 1,297,310 yes left15 A-10 5 -1 100 1,284,457 yes right16 A-12 5 -1 100 1,248,776 yes right
100,000 1,000,000 10,000,000 10
100
1000R GABUNGAN (R=0 & R=-1)
R=0R=-1
log N (cycle)
log
ΔS (M
Pa)
100,000 1,000,000 10,000,000 10
100
1000R=0
R=0
log N (cycle)
log
ΔS (M
Pa)
100,000 1,000,000 10,000,000 10
100
1000R=-1
R=1
log N (cycle)
log
ΔS (M
Pa)
100,000 1,000,000 10,000,000 10
100
1000R GABUNGAN (R=0 & R=-1)
R=0R=-1
log N (cycle)
log
ΔS (M
Pa)
100,000 1,000,000 10,000,000 10
100
1000R GABUNGAN (R=0 & R=-1)
R=0R=-1
log N (cycle)
log
ΔS (M
Pa)
Fatigue test data
R=0
N y=log(N) m b=log (K1)
200 0 200 186,188 2.3010 5.2700 2.6753 11.4049200 0 200 179,751 2.3010 5.2547 2.6753 11.4049200 0 200 177,544 2.3010 5.2493 2.6753 11.4049200 0 200 166,501 2.3010 5.2214 2.6753 11.4049100 0 100 1,139,055 2.0000 6.0565 2.6753 11.4049100 0 100 1,199,370 2.0000 6.0790 2.6753 11.4049100 0 100 1,069,049 2.0000 6.0290 2.6753 11.404977 0 77 2,273,995 1.8865 6.3568 2.6753 11.4049
Linear reggresion formula
snom max snom minDsnom
x=log(Dsnom)
SD=√((∑_(i=1)^n▒e^2 )/(n-2))y=b-mxslope: m=(n(∑▒〖 xy)-(∑▒〖 x)(∑▒y)〗〗 )/(n(∑▒〖 x^2) 〗 (∑▒x)^2 )intercept: b=(∑▒〖 y-m(∑▒x) 〗 )/n
Regression line
error error^2 r log (K1) m
5.2489 0.0210 0.0004 -0.9992 0.9985 11.4049 2.6753 500 2.698975.2489 0.0057 0.0000 11.4049 2.6753 400 2.602065.2489 0.0004 0.0000 11.4049 2.6753 300 2.4771215.2489 -0.0275 0.0008 11.4049 2.6753 200 2.301036.0543 0.0023 0.0000 11.4049 2.6753 100 26.0543 0.0247 0.0006 11.4049 2.6753 50 1.698976.0543 -0.0253 0.00066.3580 -0.0012 0.0000
0.0025SD= 0.0204
y=log (N mean) r2 Dseq
log (Dsnom)
Serror^2=
1.00E+05 1.00E+06 1.00E+0710
100
1000
Column Emean line
Cycle to failure (N)
Stre
ss ra
nge
(S)
log (N mean) N (mean) SD log (K2) N-2SD
4.1843 15,287.57 0.0204 11.3642 4.143624 13,919.52 4.4436 27,771.65 0.0204 11.3642 4.402888 25,286.44 4.7779 59,958.43 0.0204 11.3642 4.737136 54,592.92 5.2489 177,397.37 0.0204 11.3642 5.208233 161,522.59 6.0543 1,133,163.80 0.0204 11.3642 6.013579 1,031,760.20 6.8596 7,238,327.01 0.0204 11.3642 6.818924 6,590,589.76
log (N mean-2SD)
1.00E+05 1.00E+06 1.00E+0710
100
1000
Column Emean line
Cycle to failure (N)
Stre
ss ra
nge
(S)
R = 0
No Specimen No. R
1 A-23 0 200 0 2002 A-03 0 200 0 2003 A-04 0 200 0 2004 A-02 0 200 0 2005 A-17 0 100 0 1006 A-01 0 100 0 1007 A-07 0 100 0 1008 A-41 0 77 0 77
snom max snom min Dsnom
N y = log(N) m b = log (K1) y = log (N mean)
186,188 2.3010 5.2700 2.6753 11.4049 5.2489 179,751 2.3010 5.2547 2.6753 11.4049 5.2489 177,544 2.3010 5.2493 2.6753 11.4049 5.2489 166,501 2.3010 5.2214 2.6753 11.4049 5.2489 1,139,055 2.0000 6.0565 2.6753 11.4049 6.0543 1,199,370 2.0000 6.0790 2.6753 11.4049 6.0543 1,069,049 2.0000 6.0290 2.6753 11.4049 6.0543 2,273,995 1.8865 6.3568 2.6753 11.4049 6.3580
x = log(Dsnom)
Reggresion Line
error r log (K1) m
0.0210 0.0004 -0.9992 0.9985 11.4049 2.6753 500 2.698970004340.0057 0.0000 11.4049 2.6753 400 2.602059991330.0004 0.0000 11.4049 2.6753 300 2.47712125472-0.0275 0.0008 11.4049 2.6753 200 2.301029995660.0023 0.0000 11.4049 2.6753 100 20.0247 0.0006 11.4049 2.6753 50 1.69897000434-0.0253 0.0006-0.0012 0.0000
0.0025SD = 0.0204
error2 r2 Dseq log (Dsnom)
Serror2 =
log (N mean) N (mean) SD log (K2) log (N mean-2SD) N-2SD
4.1843 15,287.57 0.0204 11.3642 4.14362440816569 13,919.52 4.4436 27,771.65 0.0204 11.3642 4.40288775348761 25,286.44 4.7779 59,958.43 0.0204 11.3642 4.73713633944815 54,592.92 5.2489 177,397.37 0.0204 11.3642 5.20823326212557 161,522.59 6.0543 1,133,163.80 0.0204 11.3642 6.01357877076353 1,031,760.20 6.8596 7,238,327.01 0.0204 11.3642 6.81892427940149 6,590,589.76
R = -1
No Specimen No. R
1 A-23 -1 200 -200 4002 A-03 -1 200 -200 4003 A-04 -1 200 -200 4004 A-02 -1 200 -200 4005 A-17 -1 100 -100 2006 A-01 -1 100 -100 2007 A-07 -1 100 -100 2008 A-41 -1 77 -77 154
snom max snom min Dsnom
N y = log(N) m b = log (K1) y = log (N mean)
186,188 2.6021 5.2700 2.6753 12.2102 5.2489 179,751 2.6021 5.2547 2.6753 12.2102 5.2489 177,544 2.6021 5.2493 2.6753 12.2102 5.2489 166,501 2.6021 5.2214 2.6753 12.2102 5.2489 1,139,055 2.3010 6.0565 2.6753 12.2102 6.0543 1,199,370 2.3010 6.0790 2.6753 12.2102 6.0543 1,069,049 2.3010 6.0290 2.6753 12.2102 6.0543 2,273,995 2.1875 6.3568 2.6753 12.2102 6.3580
x = log(Dsnom)
Reggresion Line
error r log (K1) m
0.0210 0.0004 -0.9992 0.9985 12.2102 2.6753 500 2.6989700040.0057 0.0000 12.2102 2.6753 400 2.6020599910.0004 0.0000 12.2102 2.6753 300 2.477121255-0.0275 0.0008 12.2102 2.6753 200 2.3010299960.0023 0.0000 12.2102 2.6753 100 20.0247 0.0006 12.2102 2.6753 50 1.698970004-0.0253 0.0006-0.0012 0.0000
0.0025SD = 0.0204
error2 r2 Dseq log (Dsnom)
Serror2 =
log (N mean) N (mean) SD log (K2) log (N mean-2SD) N-2SD
4.9897 97,652.61 0.0204 12.1695 4.94896991680365 88,913.95 5.2489 177,397.37 0.0204 12.1695 5.20823326212557 161,522.59 5.5832 382,997.35 0.0204 12.1695 5.54248184808611 348,724.01 6.0543 1,133,163.80 0.0204 12.1695 6.01357877076353 1,031,760.20 6.8596 7,238,327.01 0.0204 12.1695 6.81892427940149 6,590,589.76 7.6650 46,236,367.64 0.0204 12.1695 7.62426978803945 42,098,806.91
