3 ms·

I, too, have no words to communicate my astonishment. A phrase comes to mind: "To screw up this bad you need an MBA." Which is not really intended as a dig on

I, too, have no words to communicate my astonishment. A phrase comes to mind: "To screw up this bad you need an MBA." Which is not really intended as a dig on MBA's... but rather to indicate that this debacle has the feeling of business decisions overruling sound engineering design. This seems poor system engineering on multiple levels: - the whole airframe / engine thrust composite flight characteristic requiring an agressive AoA limiting safety... on a commercial airliner? what? - The default MCAS relying on a single sensor, which seems to be occasionally quite unreliable, without sensor truth'ing based on other measurements (i.e. dividing ground speed by rate of altitude change to estimate AoA, then also figuring for control surface position feedback. - The MCAS not having proper situational behavior: i.e. "I'm only 500 feet of the deck... maybe this not a great time to try to tip the nose down too hard... you know, in case that stupid sensor is wrong. Oh... and the pilot is also pulling back on the yoke trying to correct something I'm doing. yeah... my bad, MCAS will chill right now and assume the pilot is NOT trying to fly this thing like a stunt plane 500 feet off the deck".

chipsa 8y ago
Angle of Attack cannot be inferred from ground speed and vertical speed. It's quite possible to have a massively negative vertical speed (10000 feet per minute descent), and have an Angle of Attack greater than 45 degrees. Angle of Attack is strictly the angle of the airflow compared to the aircraft.
- cashsterling 8y ago
  We could argue about this (technically, you are not wrong) but the point is, the aircraft MCAS should be able to do this robustly with available sensor data.* Without going into a lengthy analysis... you can infer AoA from groundspeed, rate of climb/descent, pitch/yaw/roll, and position feedback of control surfaces. Recent information on these data points can be used to calculate present and near future flight dynamics. The fields of Kalman filtering, adaptive control, and optimal control as applied to aerospace engineering are decades old. There are many examples where adaptive flight controls can fly an aircraft that has inherently unstable flight dynamics... In fact most modern jet fighter require computer controlled flight controls to maintain stable flight. Applying these algorithms to an airliner for sensor truth'ing is a cake walk. * I think you actually can infer situational AoA from ground speed and altitude data: An example you could build a regression model of standard take-off scenarios and using recent groundspeed, altitude change, and the rate of change of (groundspeed/altitude). You could build this off of flight test data and simulation. In practice, there may be no point to doing this because a wealth of additional flight sensor information is available.

chipsa 8y ago

Angle of Attack cannot be inferred from ground speed and vertical speed. It's quite possible to have a massively negative vertical speed (10000 feet per minute descent), and have an Angle of Attack greater than 45 degrees. Angle of Attack is strictly the angle of the airflow compared to the aircraft.

cashsterling 8y ago
We could argue about this (technically, you are not wrong) but the point is, the aircraft MCAS should be able to do this robustly with available sensor data.* Without going into a lengthy analysis... you can infer AoA from groundspeed, rate of climb/descent, pitch/yaw/roll, and position feedback of control surfaces. Recent information on these data points can be used to calculate present and near future flight dynamics. The fields of Kalman filtering, adaptive control, and optimal control as applied to aerospace engineering are decades old. There are many examples where adaptive flight controls can fly an aircraft that has inherently unstable flight dynamics... In fact most modern jet fighter require computer controlled flight controls to maintain stable flight. Applying these algorithms to an airliner for sensor truth'ing is a cake walk. * I think you actually can infer situational AoA from ground speed and altitude data: An example you could build a regression model of standard take-off scenarios and using recent groundspeed, altitude change, and the rate of change of (groundspeed/altitude). You could build this off of flight test data and simulation. In practice, there may be no point to doing this because a wealth of additional flight sensor information is available.