Estimating Foreign-Object- Debris Density From Photogrammetry Data

Within the first few seconds after launch of STS-124, debris traveling vertically near the vehicle was captured on two 16-mm film cameras surrounding the launch pad. One particular piece of debris caught the attention of engineers investigating the release of the flame trench fire bricks. The question to be answered was if the debris was a fire brick, and if it represented the first bricks that were ejected from the flame trench wall, or was the object one of the pieces of debris normally ejected from the vehicle during launch. If it was typical launch debris, such as SRB throat plug foam, why was it traveling vertically and parallel to the vehicle during launch, instead of following its normal trajectory, flying horizontally toward the north perimeter fence?

By utilizing the Runge-Kutta integration method for velocity and the Verlet integration method for position, a method that suppresses trajectory computational instabilities due to noisy position data was obtained. This combination of integration methods provides a means to extract the best estimate of drag force and drag coefficient under the non-ideal conditions of limited position data. This integration strategy leads immediately to the best possible estimate of object density, within the constraints of unknown particle shape. These types of calculations do not exist in readily available off-theshelf simulation software, especially where photogrammetry data is needed as an input.

A robust numerical method of iteratively solving for the drag force and coefficient of drag of an unknown object has been developed and implemented in Mathematica in a form readily convertible to other codes. This algorithm is based on an innovative combination of the Verlet and Runge- Kutta integration methods. The input data is object position data as a function of time, which might, for example, be based on a previous photogrammetry analysis. This new method is not limited to object location based on photogrammetry.

This work was done by Jason Long and Philip Metzger of Kennedy Space Center, and John Lane of ASRC Aerospace Corporation. KSC-13251

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