Comparison of Simulation Results with existing Certified Data

Integration of Simulation Results into the Four Corner Sheet Concept

The Four Corner Sheet was introduced in Chapter 7 in order to show possible relationships between the three existing certified data sets and the expected simulation results. The relation-ships between each of the four fields shall now be presented, completed with the actual results and shown exemplarily at MSL in Tab. 8.12 and 8.13. Where the Climb Weight Limit be-comes effective, the data field is left empty.

Table 8.12 Four Corner Sheet of BFL at SL with Simulation Results Stores+Wet (Time Step 0,1 s) Clean + Dry

(AVCON STC ST00608WI and AFMS 9702-2)

Stores + Dry

(AVCON STC ST00608WI and AFMS 9702-2) Weight (lbs)

(AVCON STC ST00608WI and AFMS 9702-2 + Wet Data Addendum applied/adjusted)

Stores + Wet (Simulation)

0 5 10 15 20 25 30 0 5 10 15 20 25 30 OAT (°C)

Table 8.13 Four Corner Sheet of V1 at SL with Simulation Results (Time Step 0,1 s) Clean + Dry

(AVCON STC ST00608WI and AFMS 9702-2)

Stores + Dry

(AVCON STC ST00608WI and AFMS 9702-2) Weight (lbs)

(AVCON STC ST00608WI and AFMS 9702-2 + Wet Data Addendum applied/adjusted)

Stores + Wet (Simulation)

0 5 10 15 20 25 30 0 5 10 15 20 25 30 OAT (°C)

The takeoff weight of 18500 lbs was selected as a baseline for the test cases, because the same test case is used in the results validation performed in Chapter 9.

The trend of higher BFL for lower air density conditions is clearly shown in Fig. 8.3, where the results for MSL from the Four Corner Sheet are plotted.

Fig. 8.3 Balanced Field Lengths for 18500 lbs TOW and MSL from Four Corner Sheet Data

As can be seen clearly from Figure 8.3, the slope of the graph of the simulation results for Stores+Wet is equal to the slope of the graphs of the other data from the AFMS. A rising OAT incurs a rising BFL.

Fig. 8.4 Decision Speeds V1 for 18500 lbs TOW and MSL from Four Corner Sheet Data

For the decision speed, Fig. 8.4 shows two remarkable characteristics. The kink of the graph at a temperature of 20°C OAT is present in all data. This is very likely due to the thrust reduc-tion at the flat rate temperature of 22°C (compare Fig. 6.3) with a resulting increase in takeoff distance at constant braking distance.

This leads to an increasing decision speed, as the acceleration performance reduces consider-ably, at relatively constant deceleration performance.

The second effect clearly visible in Fig. 8.4 is the fact that the decision speed calculated by the simulation initially decreases at a constant rate with increasing OAT, while the other graphs remain constant at the level before the flat rating becomes active. This effect is another consequence of the flat rating behavior of the engine, and must be validated. This is done in Sect. 9.2.1.

Percental Relationships between Data in the Four Corner Sheet

The percental deviation between the values of the Four Corner Sheet shows the relationship of the four data corners to each other. The following percental data is given as calculated as the difference between neighboring fields of the Four Corner Sheets. Four neighboring relation-ships are present in a Four Corner Sheet, therefore four tables are presented in this paragraph.

Fig. 8.5 summarizes the data presented in tables 8.14 to 8.17. This allows an important con-clusion on the calculation method used to obtain the simulation results.

Table 8.14 Deviation of BFL from Clean+Dry towards Clean+Wet values

20% 20% 20% 20% 20% 20% 20% 19600 Weight (lbs)

In Table 8.14, the upper left hand corner of the Four Corner Sheet was compared to the lower left hand corner, it presents the deviation from the Clean+Dry data to the Clean+Wet data. In-terestingly, the values for BFL of the wet runway are exactly 20% higher than the BFL values for the dry runway. An exception is the correction for 13000 lbs, for which the effect of the minimum control speed limit leading to higher BFL has already been discussed.

The simple relationship between the data for the Clean+Dry and the Clean+Wet values results from the simple scaling method of the AFMS 9702-2 through the Wet Data Addendum to yield wet runway data from dry runway data. Individual differences between different takeoff weights and pressure altitudes are disregarded. The correction method must be evaluated ac-cordingly in terms of precision.

Table 8.15 Deviation of BFL from Clean+Dry towards Stores+Dry values

25% 25% 25% 25% - - - 19600 Weight (lbs)

15% 15% 15% 25% 25% 25% - 18500

15% 15% 15% 15% 15% 15% 15% 16000

15% 15% 15% 15% 15% 15% 15% 13000

0 5 10 15 20 25 30 OAT(°C)

In Table 8.15, the upper left hand corner of the Four Corner Sheet was compared to the upper right hand corner. It presents the deviation from the Clean+Dry data to the Stores+Dry data.

The BFL values for the aircraft with stores are either 15% or 25% higher than the values for the clean aircraft. From the GJE EXTJFD-003report it is known that a simplified calculation method has been the baseline for the calculation of the AFMS 9702-2 data for the Stores+Dry configuration. Hence, it is not surprising that there are also simplified relationships between the performance data for these two aircraft configurations.

As the simulation however does not base on a simplified method but utilizes a completely dif-ferent numerical integration method, it can be expected that the percental deviations between different configurations are not constant. This is clearly confirmed by the data in Tab. 8.16 and 8.17.

Table 8.16 Deviation of BFL from Stores+Dry towards Stores+Wet values

24% 22% 20% 19% - - - 19600 Weight (lbs)

Table 8.16 suggests that the simulation results for BFL in the Stores+Wet configuration are on average 23% higher than for the Stores+Dry configuration. This appears reasonable and may be even conservative, given that the BFL for the clean conditions rises by 20% from the Clean+Dry to the Clean+Wet configuration.

It should be noted that the cross check performed in Tab. 8.16 also satisfies the requirement of CS-25.113 b) for wet runways, as outlined in Section 3.2. It has been shown that the takeoff distances on a dry runway are lower than on a wet runway with the same aircraft configura-tion. Hence, the wet data becomes limiting for the Stores+Wet configuraconfigura-tion.

Table 8.17 Deviation of BFL from Clean+Wet towards Stores+Wet values

29% 27% 25% 24% #### #### #### 19600 Weight (lbs)

Shifting from the bottom left to the bottom right hand corner of the Four Corner Sheet, it pre-sents the deviation from the Clean+Wet data to the Stores+Wet data. The BFL rises by an av-erage of 14%. This is comparable to the rise of 22% in BFL (excluding 13000 lbs TOW) when shifting from a Clean+Dry to a Stores+Dry configuration (top left to top right corner).

The 13000 lbs TOW data again is exhibiting a noticeable difference to the other data. This is a consequence of the artificial increase in V1 to VMCG. The BFL adjustment factor for the Clean+Wet aircraft was estimated to 1,35 (compared to 1,2 for other TOW). At a rejected takeoff from 109 KIAS, the aircraft with stores however is assisted in its braking performance due to the additional drag force – which yields to the decreased BFL in comparison to the clean aircraft. It is therefore not surprising that the deviation analysis yields even reduced dis-tances in the Stores+Wet configuration, where the effect on the BFL of an artificial increase in V1 has been considered accurately.

Figure 8.5 summarizes the deviation analysis performed and presents the average deviations calculated between all four neighboring data sets.

Fig. 8.5 Synthesis of Percental Deviations within the Four Corner Sheet

What can be seen clearly from the synthesis of percental deviations is that the simulation de-termines approximately the same deviations between its neighboring configurations in the Four Corner Sheet as the existing certification data. This must be seen as a strong support of the plausibility of the simulation results, as it integrates very well into the existing Four Cor-ner Sheet data.

The analysis also showed that the remainder of the Four Corner Sheet is likely to represent only simplified relations, all data having been calculated in simplified methodology. This must be considered judging possible deviations between the simulation results and the AFMS.

+ ~23%

+ ~22%

+ 20%

+ 15-25%

8.2.2 Comparison of Takeoff Distance from Simulation with