Stability and performance are crucial characteristics for aerospace vehicles. The ability to investigate the aerodynamics and performance of rockets gives an insight into their stability before flight and the potential for design and performance enhancements. For the past 13 years, the rocketry Division within the students’ space Association of Warsaw University of technology has been developing sounding rockets of different designs and mission profiles. Two rockets have been chosen for the CFD (Computational Fluid Dynamics) campaigns, FOK and Twardowsky. This paper describes the mathematical model of aerodynamic loads used by the Division for sounding rocket simulation, followed by CFD campaigns for the two rockets. The results of the CFD analysis are then used to calculate the rockets’ aerodynamic derivatives according to a previously defined mathematical model.

The accuracy of aerodynamically controlled guided projectile simulations is largely determined by the aerodynamic model employed in flight simulations which impacts vehicle interaction with the surrounding air. In this work, the performance of projectile path following with two distinct aerodynamic models is examined for their possible influence on trajectory following accuracy. The study incorporates the path following guidance algorithm, which enables the object to navigate along a predefined path. The simulation mathematical model is developed in the MATLAB/Simulink environment. In addition, by integrating the path-following algorithm with the two aerodynamic models, the dynamic behaviour of the aerodynamically controlled projectile can be compared. This allows for a more comprehensive analysis of the trajectory and the effects of each model on the desired flight path. Further research can explore the differences between the two models in greater detail and quantify their impact on unmanned projectile trajectory predictions, in addition to further exploring the specific characteristics and limitations of each model. This will involve analysing their assumptions, computational methods, and inputs to identify potential sources of error or uncertainty in the simulations. Moreover, these results have important implications for the design of aerodynamically controlled projectiles as well as a deeper understanding of aerodynamic mathematical modelling in flight simulation.

Thrust vector control (TVC) might be used to control aircraft at large altitudes and in post-stall conditions when aerodynamic control surfaces are ineffective. This study demonstrated that the implementation of the TVC on high-speed aircraft is a reasonable solution and might be an alternative when compared to the complicated reaction control system or large aerodynamic control surfaces. The numerical flight dynamics model of the X-15 experimental aircraft was developed and implemented in MATLAB/Simulink and then used to investigate the proposed solution. The obtained results indicate that the aircraft, equipped with full 3D thrust vectoring and two independent horizontal stabilizers to control the roll angle, was able to achieve flight along the path that was defined by a set of waypoints. This paper also highlights the potential benefits and challenges of using TVC as a control method for aircraft. The results of this study contribute to the growing body of research on aircraft control and simulation. Future work can explore the use of TVC for other aircraft with unique configurations and low maneuverability features.

Modern aviation technology development heavily relies on computer simulations. SIL (Software-In-The-Loop) simulations are essential for evaluating autopilots and control algorithms for multi-rotors, including drones and other UAVs (Unmanned Aerial Vehicle). In such simulations, it is possible to compare the flight parameters achieved by flying platforms using various commercial autopilots widely used in the UAV sector. This research aims to provide objective and comprehensive insights into the effectiveness of different autopilot systems This article examines the simulated flight test results of a drone performing the same mission using different autopilot systems. The X-Plane software was used as an environment to simulate the dynamics of the drone and its surroundings. Matlab/Simulink r2023a provided the interface between autopilot software and X-Plane models. Those methods allowed us to obtain an appropriate comparison of the autopilot systems and indicate the main differences between them. This research focused on analyzing UAV flight characteristics such as stability, trajectory tracking, response time to control changes, and the overall effectiveness of autopilots. Various flight scenarios including take-off, landing, flight at a constant altitude, dynamic manoeuvrers and, flight along a planned trajectory were also examined. In order to obtain the most accurate and realistic results, the tests were carried out in various weather conditions. The aim of this research is to provide objective data and analysis to compare the performance of commercial autopilots. This method offers several advantages, including cost-effective testing, the ability to test in diverse environmental conditions, and the evaluation of autopilot algorithms without the need for real hardware. The findings of this study may have a considerable impact on how autopilot designers and developers choose the best platforms and technologies for their projects. Future research on this topic will compare the obtained data with flight test data.

Propulsion system operation is known to affect the aerodynamic characteristics of rockets. Specifically, the net axial force acting on a rocket in flight cannot be precisely obtained by combining the static thrust with drag values computed for a rocket with an inactive motor. One of the main reasons for this is the influence of motor operation on pressure at the base of the rocket. The aim of this paper is to investigate the effect of motor operation on the aerodynamic parameters of the Grot sounding rocket developed by the Students’ Space Association, Warsaw University of Technology. The study consists of two series of axisymmetrical computational fluid dynamic simulations of flow around the rocket – one with the motor being non-operational and the other with active thrust. In the post-processing phase, the axial force acting on various components of the rocket is computed, with an emphasis on the base and nozzle exit sections. Quantitative and qualitative differences between the cases with and without active thrust are highlighted and discussed. The obtained results are compared to a semi-empirical model found in the literature. Finally, a semi-empirical base drag model is proposed for use in Grot flight simulation.

Safe and accurate recovery of fixed-wing Unmanned Aerial Vehicles (UAVs) is a critical aspect of autonomous operations, especially for systems designed for hand or catapult launch, which may lack landing gear. Under these conditions, parachute systems are often used for a safe landing, although using these systems for precise recovery in populated areas, high terrain, and water presents significant challenges. In addition, weather conditions have a major impact on the descent path post-parachute deployment, further complicating landing within the designated safe zones. Improper location and timing of parachute deployment may risk large errors or unsafe touchdown, increasing the need for precise parachute deployment location and timing. This study presents the development of an autonomous parafoil deployment and recovery path planning algorithm for fixed-wing UAVs. The proposed solution calculates the optimal parachute deployment point and generates a recovery trajectory that guides the UAV toward this point while ensuring appropriate deployment orientation with respect to the desired landing location. The algorithm integrates UAV flight states, the descent characteristics of the combined UAV-parachute system, and prevailing weather conditions to determine the deployment point and recovery trajectory. A simulation model of the algorithm, along with the UAV dynamic model, was developed in MATLAB/Simulink to investigate its performance. The results indicate that the proposed algorithm can improve UAV recovery strategies, minimising landing errors, and increasing operational safety within the considered simulation conditions. Future validation of the algorithm under real-world conditions may provide further insight into its reliability and lead to refinements in subsequent iterations.