So what kind of data is generally gathered from rocket test flights, and how is the analysis of this data done?
I presume the test vehicle is wired up with lots of instrumentation, whose data is being sent back as telemetry. And this is time-series data, consisting of many parameters. But using the latest Starship test flight as an example, on the order of how many parameters roughly might have been gathered? And what kinds of parameters might they have been?
So if we picture this as a vast table of time-series data, then what are we trying to do with it? From past stats courses I've taken, I'd be looking for target variables and to identify input variables as predictors for those targets. But what are the target variables I should be most interested in?
So I'll have families of variables, based around particular vehicle subsystems. And I'll perhaps be looking for "anomalous data" -- something that doesn't match the parameter values shown during testing. So I'd be comparing flight data against previous test data based on nominal test runs, and looking for major deviations in the flight data.
Is this detective work done all purely guided by the examination of events in the flight? Or are there brute force methods of analysis that can just be applied across the board, to pull out insights that might not otherwise be noticed?
Rocket test flights gather data through instrumentation and telemetry, providing a time-series dataset with multiple parameters. The analysis involves detecting anomalies, comparing data to previous tests, refining models, and improving design iterations. Both manual examination and systematic analysis methods, including statistical techniques and machine learning, are employed to uncover insights and optimize performance.