**6.7. Summary of results**

146 Nuclear Power – Practical Aspects

Different ranges of conditional explosion-probability PE are depicted in Figure 14. The denotation of the different ranges of the explosion event probability PE, which is normalised on 1m2, is as follows: red area (> 1E-07/m2), orange area (≤ 1E-07/m2), yellow area (≤ 5E-08/m2), green area (≤ 1E-08/m2). The methods, number of trials, the simulation time and the

results like mean value, variance and figure of merit (fom) are listed in Table 6.

**Figure 14.** Gas-tanker accident - ranges of conditional explosion event probability PE/1m2

**method trials time [s] mean variance fom** 

MCS-lee 1E05 7.91 1.24E-03 1.24E-03 1.02E07

biased 1E05 28.02 1.30E-03 1.67E-05 2.14E08

MCS-ffe 1E05 8.52 1.31E-03 1.20E-04 9.80E07

biased 1E05 28.67 1.27E-03 1.35E-05 2.58E08

**Table 6.** Gas-tanker accident - conditional probability of an explosion event within the plant area with

Close to the river-sections 2 and 3 the conditional explosion event probability increases, this is due to the higher accident frequency in these sections combined with the specific wind-

As the different Monte Carlo methods (Table 6) are compared it can be found out that most solutions fit a mean about approx. 1.3E-04 which verifies the results as well as the adopted different Monte Carlo algorithms. If the variance and the figure of merit are regarded the Monte Carlo simulations in combination with the ffe and biasing techniques is the most

*6.6.2. Results* 

MCS-lee

MCS-ffe

direction frequencies.

efficient approach.

radius rP

The results of the MCS are evaluated on the condition that the accident already occurred. In order to assess the frequency of occurrence of an external explosion event the frequency of accidents with combustible gas has to be considered. It should be noticed that the results for the frequency of occurrence of an external explosion event will be several magnitudes lower than the results for the conditional explosion event probability given in this paper. Furthermore the events, boundary conditions, parameters and results given in Figures 5 to 14 and Tables 2 to 6 are only example values and do not represent conditions and results of any specific application.

Figures 10, 12, and 14 indicate that the conditional explosion-frequency decreases as the distance to the place of accident increases. This is due to the exponentially distributed ignition probability which depends on the time or the distance to the accident.

The results in Tables 4, 5 and 6 indicate that the conditional probability of occurrence of external explosion pressure waves in consideration of realistic conditions (accident frequency depending on environmental conditions, wind direction & wind speed) can be successfully assessed by means of the MCS.

With the aid of biasing techniques the MCS becomes more efficient, the variance is reduced and the figure of merit (fom) rises. In most cases it can be found out that the solutions fit approx. the same mean which verifies the results as well as the adopted different Monte Carlo algorithms. If the variance and the figure of merit are regarded the MCS in combination with the ffe and biasing techniques is the most efficient approach.
