3. Deterministic computational methodology

Several steps are involved in the simulation of FP behavior inside the reactor building starting from the generation of FP in fuel along with the fuel burn-up. Leakage of FP into the coolant and then from the coolant to containment along with the leakage of coolant. The computational steps are listed in Figure 3. A two-stage methodology has

Figure 3. Flow chart of incontinent FP source term estimation.

been adopted: (1) evaluation of activity in the core just before the accident and (2) kinetic quantification of airborne activity under confined conditions. The core activity has been evaluated at for one complete fuel cycle to get maximum core activity. The behavior of airborne FP activity has been quantified for loss of the coolant accident (LOCA) under NUREG-1465 [8] and regulatory guide 1.183 [32] assumptions. The developed model uses subroutine functions containing coupled ODEs and Runge–Kutta (RK) method. The ODEs (Eqs. (1)–(12)) are implemented in MATLAB. The system of ODEs (Eqs. (1), (3), (7), (8)) is coupled and solved numerically using the Runge–Kutta (RK) method in this program.

The RK numerical provides efficient time-domain solution, yielding static as well as dynamic values of FPAs corresponding to about 84 different dominant FPs. The computational cycle starts with the initialization of the variables with t = 0. In the time loop, the values of FPAs inside the containment building are calculated using RK scheme for each next time step. The program allows performing these calculations for spray system operation.
