Automating the Handling Qualities Predictions of the Flying-V

Abstract

As the Flying-V goes through subsequent design iterations, each new model requires dedicated handling qualities research. A part of that work, namely obtaining the handling qualities predictions, is highly repetitive and can be automated. To address that issue, a Python library for automated handling qualities prediction evaluations of the Flying-V was developed. The library's functionalities cover model implementation, trim and linearization, model reductions, identification of the modal parameters, and finally, the evaluation of the requirements. The library takes a semi 'black-box' approach toward the model structure, relying on defining it through a set of functions instead of parameters. With that, it can accommodate various sources and formulations of the model. The library was successfully validated on two different aircraft models. Part of the validation was replicating some of the previous Flying-V handling qualities research data. It is expected that the use of the library will bring time savings to future handling qualities research of the Flying-V, as well as reduce the risk of mistakes in the process.