Environmental Engineering Reference
In-Depth Information
where 2.26 is the t -score associated with a confidence level of 95% and nine degrees
of freedom. Once L app and U L app were both known for each of the ten-measurement
sets, referring to U L as the expanded uncertainty of the probe electrical length in
air, the measurement uncertainty was evaluated using the uncertainty propagation
theory [34], according to the following equation:
L U L 2
2
∂ε
∂ε
i
i
=
U ε i =
U L app ( i )
+
L app ( i )
2
2
2 L app ( i )
L 2
2
2
L app ( i )
=
U L app ( i )
+
U L
(5.7)
L 3
In the above equation, U ε i is the propagated uncertainty associated to the i -th mea-
surement of the
ε app value. Finally, data with corresponding uncertainty bars were
fitted in a
app curve.
To determine the
θ ε
relationship, the experimental data were fitted, thus
obtaining the optimal calibration curve. As also reported in many related papers,
third order polynomial curves prove to be a good fitting of experimental data:
ε
θ
app
app
app
θ =
+
+
+
B 0
B 1
ε
B 2
ε
B 3
ε
(5.8)
app
where B 0 , B 1 , B 2 and B 3 are the regression coefficients. This way, (5.8) represents
the calibration curve: in correspondence of each measured dielectric constant value
ε app , the curve provides the corresponding
θ
.
from a metrological point of view,
the associated uncertainty was evaluated through the non-linear regression theory
[34]. Hence, the variance analysis for the single values expected from the previous
equation was conducted according to
To characterize the extrapolated value of
θ
2 1
(5.9)
∂θ
2
∂θ
cov
1
n + i
∂θ
ij
var
[ θ ]= σ
+
var
[
B i ]+
2
[
B i ,
B j ]
B i
B i
B j
2 is the variance between ex-
perimental and fitted data; n is the number of experimental points; i
where var
[ θ ]
is the variance of the moisture level;
σ
,
j = 0,1,2,3; and
cov
is the covariance between B i and B j parameters.
For a confidence level of 95%, the equations associated to the lower and upper
confidence limits for the regression curve are given by the following equations:
alpha
[
B i ,
B j ]
= B 0
app
t n 4 , 1 2 var
app
L low
+
B 1
ε
+
B 2
ε
+
B 3
ε
[ θ ]
(5.10)
app
 
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