Information Technology Reference
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AI
i
pj
()
.
=
({[
j
2
Δ
j
...
j
− Δ −
j
1]
max
max
∪+ Δ−
[
j
j
1...
j
+
2
Δ
j
]},
max
max
(11)
{[
A
()
i
...
A
()
i
]
pj
.
−Δ
2
j
pj
.
−Δ−
j
1
max
max
()
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i
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j
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pj
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max
where I ( X , Y , Z ) is a function that interpolates the function values Y defined over the
domain X onto the set Z . Here, we use cubic splines. In other words, the values of
A p.j ( i ) in the neighbourhood of j max are “restored” using the values of A p.j ( i ) from the
surrounding of j = j max -
j . Figure 9(a) shows the “smoothened” surrogate
model response corresponding to that of Fig. 8. Figure 9 shows the surrogate and the
high-fidelity model responses, both C p and C f , at x ( i ) and at some other design x .
Δ
j , ..., j max +
Δ
1
0.5
0
-0.5
-1
0
0.2
0.4
0.6
0.8
1
x/L
Fig. 8. Surrogate model C p.s ( i ) (7)-(9) at x ( i ) (- - -), and at some other design x (▬). By defini-
tion, C p.s ( i ) ( x ( i ) ) = C p.f ( x ( i ) ). Note that C p.s ( i ) ( x ) has large spikes around the points where C p.s ( i ) ( x ( i ) )
is close to zero.
Fig. 9. (a) Smoothened surrogate model (7)-(10) C p.s ( i ) ( x ( i ) ) = C p.f ( x ( i ) ) (—), C p.s ( i ) ( x ) (- - -),
C p.c ( x ) (⋅ ⋅ ⋅), and C p.s ( x ) (▬); (b) Smoothened responses C f.s ( i ) ( x ( i ) ) = C f.f ( x ( i ) ) (—), C f.s ( i ) ( x )
(- - -), C f.c ( x ) (⋅ ⋅ ⋅), and C f.s ( x ) (▬)
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