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Originally posted in page 50 by: pale5218
Originally posted by: Zaphod58
A reply to: LaBTop
The hijackers knew about the FAA radar gaps through several ways. Every time the radars in those areas had problems the FAA put out a NOTAM. Those can be looked up online,even back then.
Even if they knew, I can't see how this even was an element of their plan.
1) they didn't use this tactic on the other flights, if they tried, it didn't work for those planes to go invisible.
2) the flight started the deviation from course before turning off transponder. It started a turn to the south off the filed airway.
3) how would they know they were in that area, distance from a fix? Time clocked from departure point?
I have a hard time buying this gap in radar as part of the plan. I could be wrong about this but I don't see this as a calculated effort by the hijackers, too many variables to rely on this.
I think it was just a beneficial coincidence. Other than the flight turning back through this area, is there any other indications that it wasn't a coincidence?
I'm not sure if I missed something?
Salander : You may be willing to give Hanjour superhuman status, superpilot status and skills, but I am not. Numerous line pilots are on the record saying they could not fly that maneuver Hanjour did, and I'm very sympathetic to the statements of those airline pilots because I am a pilot myself, including flight instructor, and it is absurd to claim that somebody with Hanjour's reputation could do that. Downright silly.
Page 1 of 24, Introduction :
Current and future composite material technologies have the potential to greatly improve the performance of large transport aircraft. However, the coupling between aerodynamics and structures makes it challenging to design optimal flexible wings, and the transonic flight regime requires high fidelity computational models. We address these challenges by solving a series of medium- and high-fidelity aerostructural optimization problems that explore the design space for the wing of a large transport aircraft. We consider three different materials: aluminum, carbon-fiber reinforced composites and an hypothetical composite based on carbon nanotubes. The design variables consist of both aerodynamic shape (including span), and structural sizing, as well as ply angle fractions in the case of composites. Pareto fronts with respect to takeoff weight and fuel burn are generated. The
wing performance in each case is optimized subject to stress and buckling constraints. We found that composite wings consistently resulted in lower fuel burn and lower structural weight, and that the carbon nanotube composite did not yield the increase in performance one would expect from a material with such outstanding properties. This was in part due to the minimum structural thickness constraint. For all materials, the minimum fuel burn wings were found to be longer, heavier, thinner, more flexible, and more lightly loaded than their minimum TOGW counterparts.
--snip--
In the structural parametrization for the metallic, composite and CNT-based composite wings, we split the wing structure into approximately flat panels that are analyzed and designed based on the stress state in the global finite-element model under a series of loading conditions. These panels consist of the structural components formed between the ribs and spars of the wing. In order to obtain an accurate estimate of the overall wing-box weight it is necessary to have a design tool that can correctly size panels over a wide range of loading conditions. The panels range from relatively lightly loaded at the tip to heavily loaded at the wing root. Over this range, it is most important to capture the behavior of the heavily loaded parts of the structure, since these structural components will have the greatest impact on the structural wing weight. --snip--
Page 17 etc. : B. --snip-- The objective is to identify differences in the resulting designs that are primarily caused by the higher fidelity aerodynamic analysis and the additional flexibility introduced through the airfoil shape variables.
Table 4 shows the data for the TOGW and fuel burn optimizations, and Figure 13 compares the pressure contours, airfoil shapes, structural thicknesses, spanwise lift distributions, twist distributions, and t/c distributions for these two optimizations.
--snip--
Page 22/24 : The optimal wing trends were consistent among the different materials: the minimum fuel burn wings were found to be longer, heavier, thinner, more flexible, and more lightly loaded than their minimum TOGW counterparts. The optimal composite wings exhibited larger spans than the metallic wings, and the CNT wings had even larger spans, reaching a maximum of almost 97 m for the minimum fuel burn case.
* Realistic XML controlled Wingflex, reacting to turbulences.
Flight Dynamics:
* Realistic Flight Model.
* Developed based on real Level-D Simulators and tested by real life Pilots.
Calculating Grms
(Root-Mean-Square Acceleration)
It is very easy to describe the Grms (root-mean-square acceleration, sometimes written as GRMS or Grms or grms or grms) value as just the square root of the area under the ASD vs. frequency curve, which it is. But to physically interpret this value we need to look at Grms a different way. The easiest way to think of the Grms is to first look at the mean square acceleration.
Mean-square acceleration is the average of the square of the acceleration over time. That is, if you were to look at a time history of an accelerometer trace and were to square this time history and then determine the average value for this squared acceleration over the length of the time history, that would be the mean square acceleration. Using the mean square value keeps everything positive.
The Grms is the root-mean-square acceleration (or rms acceleration), which is just the square root of the mean square acceleration determined above.
If the accelerometer time history is a pure sinusoid with zero mean value, e.g., a steady-state vibration, the rms acceleration would be .707 times the peak value of the sinusoidal acceleration (if just a plain average were used, then the average would be zero). If the accelerometer time history is a stationary Gaussian random time history, the rms acceleration (also called the 1 sigma acceleration) would be related to the statistical properties of the acceleration time history (you may have to refresh your probability and statistics knowledge for this):
68.3% of the time, the acceleration time history would have peaks that would not exceed the +/- 1 sigma accelerations.
95.4% of the time, the acceleration time history would have peaks that would not exceed the +/- 2 sigma accelerations.
99.7% of the time, the acceleration time history would have peaks that would not exceed the +/- 3 sigma accelerations.
There is no theoretical maximum value for the Gaussian random variable; however, we typically design to 3 sigma since it would only be theoretically exceeded 0.3% of the time. In addition, from a practical point of view, we know that it would be physically impossible to achieve unreasonably high sigma values.
In an extremely strange and suspicious twist that we can only pray is a coincidence, about a week after we had obtained the CITGO witnesses testimony on film, Christopher Landis committed suicide.
The most amazing thing however, in that CITGO video, is the total absence of the view of that canopy camera, that hung under the NWestern corner of that northern canopy, with a full sight of the whole NoC flight path, up to impact.
The gas station manager later in 2006 told the CIT team, that that camera position was PLAYING onscreen on 9/11, but was absent from the FOIA freed CITGO surveillance cams video. She remembered that detail for 5 long years, so it must have upset her quite a bit.
AND, the FBI screwed exactly that camera off the ceiling, and it was never replaced again..... how about that for obstruction of justice.?