Deployable morphing aircraft are gaining popularity in the academic and industrial world. Their deployability offer the possibility to be stored and takes less space. This is advantageous in volume limited applications like space explorations, where every cubic centimeter is impo
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Deployable morphing aircraft are gaining popularity in the academic and industrial world. Their deployability offer the possibility to be stored and takes less space. This is advantageous in volume limited applications like space explorations, where every cubic centimeter is important. Another field where this aircraft is increasingly used is the military field. Deploying it in the battlefield directly from a carrier aircraft opens endless possibility to the operation of such aircraft. However, mid-air deployment is subjected to several internal and external factors that could lead to the failure of the deployment.
In this study, a method to assess the safety of deployment of a deployable morphing UAV is constructed. To do this, an aircraft test case is taken and a corresponding model of the aircraft is made using the Multibody dynamics approach. This model is then verified and validated by two different methods. First, a comparison of the stability derivatives of the created model and an off-the-shelf aerodynamic solver is performed. Secondly, the response of the created model is compared with actual flight test data, where the test case aircraft performs a maneuver. For both validation methods used in this study, the created model is able to resemble the output from the off-the-shelf aerodynamic solver and the flight test data. The validated model is then used as to test the method developed in this study.
The method developed starts with the definition of a safe deployment of a deployable morphing aircraft, where three different safety concerns are considered. The definition of a safe deployment also helps in deriving different categories of deployment which includes safe and various unsafe deployment depending on what causes the deployment to be unsafe. This method is tested on two different deployment scenarios.
By using the method developed in this study, safety deployment spaces are constructed from the range of input parameters determined for the two different scenarios. It is revealed from this safety deployment space what combination of input parameters is favorable for a safe deployment, and what causes the different unsafe deployments. Unsafe deployments are also categorized to understand which of the safety concern causes the deployment to be unsafe.