3.1. First-Order Sensitivities of the Maximum Rod Surface Temperature
The maximum temperature of the rod’s surface,
, can be represented in the following form:
where
is implicitly defined by the relation in Equation (9). The first-order total differential,
, of
depends, in principle, on all of the first-order sensitivities of
with respect to the imprecisely known model and boundary parameters through the following relation:
The total differential
is obtained by applying the definition of the G-differential to Equation (15), which yields:
The indirect-effect term,
, in Equation (17) depends only on the variation in the respective state function, namely
, and is defined as follows:
Thus, the indirect-effect term depends on the parameter variations indirectly, through the variation
in the rod temperature. In contradistinction, the direct-effect term
in Equation (17) depends directly on parameter variations and is defined as follows:
Thus, the direct-effect term
can already be computed at this stage by using Equation (6) to obtain:
The variation
is the solution of the “
first-level forward sensitivity system” (1st-LFSS) which is obtained by G-differentiating the original system defined by Equation (1) through Equation (5). Applying the definition of the G-differential to Equation (1) through Equation (5) yields the following relations:
Carrying out in Equation (21) through Equation (25) the differentiations with respect to
and setting
in the resulting expressions yields the following set of equations, which constitute the 1st-LFSS:
The first term on the right-side of Equation (26) can be simplified by using Equation (1) to obtain the following equation:
The terms containing derivatives of
in Equation (28) can also be simplified using Equations (1) and (3) to obtain the following equation:
Since the equations underlying the 1st-LFSS, cf. Equations (27) and (29) through Equation (32), depend on the parameter variations, it is computationally expensive to repeatedly solve the 1st-LFSS for all possible parameter variations. The need for repeatedly solving the 1st-LFSS can be circumvented by expressing the indirect-effect term defined in Equation (18) in terms of the solution of a “
first-level adjoint sensitivity system” (1st-LASS), which will be constructed next by applying the general principles of the 1st-CASAM-CP presented in [
6].
The Hilbert space appropriate for the heat transport benchmark under consideration comprises the space of all square-integrable two-component vector functions of the form
, endowed with an inner product
of the form
Using the definition provided in Equation (33), construct the inner product of a square integrable vector function
, where
and
denote the adjoint sensitivity functions that correspond to the forward functions
and
, with Equations (29) and (31), respectively, to obtain the following relation:
The left-side of Equation (34) is now integrated by parts (twice over the variable
and once over the variable
) to obtain
Using the boundary condition given in Equation (27) and imposing the boundary condition
eliminates the last term on the right-side of Equation (35). Imposing the boundary condition
eliminates the unknown function
on the right-side of Equation (35). Using the boundary condition given in Equation (30) to replace the term
on the right side of Equation (35) and replacing the left-side of Equation (35) by the right-side of Equation (34) yields the following expression equivalent to Equation (35):
The unknown quantity
, which appears in the last term on the right-side of Equation (38) is eliminated by using the boundary condition given in Equation (32); this operation transforms Equation (38) into the following form:
The unknown quantity
, which appears in third and fourth terms on the right-side of Equation (39), is eliminated by imposing the following interface condition on the (adjoint) function
:
Inserting Equation (40) into the right-side of Equation (39) reduces it to the following form:
The two terms that contain the unknown function
in Equation (41) are grouped together, transforming Equation (41) into the following form
The second term on the right-side of Equation (42) will represent the indirect-effect term
defined in Equation (18) by requiring that the following equations be satisfied:
Inserting the relations provided in Equations (43) and (44) into Equation (18) and re-arranging the resulting equation yields the following expression for the indirect-effect term
:
Inserting the definitions provided for
and
in Equations (29) and (31), respectively, into Equation (45) yields the following expression:
Inserting the results obtained in Equations (20) and (46) into Equation (17) and identifying the expressions that multiply the various parameter variations by comparing Equation (46) to Equation (16) yields the following results for the partial sensitivities of
with respect to the uncertain parameters, interface, and boundaries:
The sensitivities obtained in Equation (47) through Equation (54) can be computed efficiently, using just quadrature formulas, after the adjoint sensitivity functions and are obtained by solving the “first-level adjoint sensitivity system” (1st-LASS), which comprises Equations (43) and (44) together with the interface condition provided in Equation (40) and the boundary conditions given in Equations (36) and (37). The 1st-LASS is solved in a manner that is “reverse/backwards” by comparison to the way in which the solution proceeds for solving the 1st-LFSS and/or for the original heat transport model. Thus, while the 1st-LFSS and the original heat transport model are solved by starting with the fluid flow equation (which is solved from the inlet to the outlet of the fluid flow) and subsequently solving the heat conduction equation in the rod, the solution of the 1st-LASS proceeds in the reverse manner, by first solving the heat conduction in the rod, followed by solving the fluid flow equation from the outlet to the inlet. Notably, the 1st-LASS, is independent of parameter variations and needs to be solved just once to obtain the adjoint functions and .
Solving the 1st-LASS yields the following expressions for the adjoint functions
and
:
Using Equations (55) and (56) in Equation (47) through Equation (54) and carrying out the respective integrations yields the following expressions for the 1st-order sensitivities of the maximum rod temperature,
:
3.2. First-Order Sensitivities of the Critical Point (Maximum) of the Rod Surface Temperature
As has been shown in Equation (9), the maximum value, , of the rod surface temperature is attained at the critical point . As Equation (10) indicates, the components of the critical point are subject to uncertainties since they depend on imprecisely known parameters. The sensitivities of the radial component are evident: the only non-zero sensitivity is .
On the other hand, the component
of the critical point
of
depends, in principle, on all of the uncertain parameters, which means that the total differential
will have the following expression:
Since the closed-form expression provided in Equation (10) would not be available in general, the expression of
will be obtained by applying the general methodology presented in [
6]. This application commences by writing the relations provided in Equation (9), which implicitly define the location,
, in the following form:
Taking the G-differential of Equation (66) yields the following relation:
The relation in Equation (67) can be re-written in the following form:
where the quantities
and
are computed using Equation (6) for this benchmark model (or are computed numerically when the closed form of
is unavailable) to obtain
The term
in Equation (68) can be expressed in terms of adjoint functions by applying the procedure outlined in [
6] to obtain the following result:
where the adjoint functions are the solutions of the following 1st-LASS:
Introducing the results obtained in Equation (69) through Equation (76) into Equation (68) and equating the coefficients corresponding to the same parameter variations yields the following expressions for the sensitivities of the location
to the imprecisely known model, interface, and boundary parameters:
The expressions obtained in Equation (77) through Equation (84) can be evaluated after solving (numerically or analytically) the 1st-LASS represented by Equation (72) through Equation (76) to determine the adjoint functions
and
. Since
and
do not depend on any parameter variations, the 1st-LASS needs to be solved only once to obtain the respective adjoint functions, which are subsequently used in Equation (77) through Equation (84) to compute, using simple quadrature formulas, all of the sensitivities of
to the imprecisely known model, interface, and boundary parameters. Solving the 1st-LASS analytically yields the following expressions for the adjoint functions
and
:
Using the expressions for
and
provided in Equations (85) and (86) in Equation (77) through Equation (84) and performing the respective integrations yields the following closed-form expressions for the sensitivities of
to the imprecisely known model, interface, and boundary parameters:
For this benchmark model, the closed-form expression for is available (which would not be the case for large-scale models) in Equation (10). Consequently, Equation (10) can be used to verify that the expressions obtained using the general 1st-CASAM-CP (which has specifically yielded the 1st-LASS comprising Equation (72) through Equation (76)) has produced exact expressions, in Equation (87) through Equation (94), for the sensitivities of the location of the maximum rod surface temperature to all of the system’s imprecisely known parameters.