Advancement in the Sky: A MATLAB-fueled Innovation in Rocket Development by BME Suborbitals

BME Suborbitals, a rocket development competition team from BME, leverages MATLAB to tackle aerospace challenges. From simulating radax joints to optimizing propulsion systems, discover how MATLAB enhances efficiency and accuracy in rocket development. Explore their innovative projects and contributions to space education.

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Recent times have seen a ramping up of space exploration and other space-related activities. Space technology has become an integral part of our daily lives; everyday activities are now inconceivable without GPS technology, satellite telecommunications, or experiments conducted in outer space.

In 2021, a group of enthusiastic and ambitious students from the Budapest University of Technology and Economics founded the BME Suborbitals, a rocket development team whose primary goal is to represent their university and country, as well as to challenge themselves in international aerospace competitions, while also promoting space education and research.

BME Suborbitals exists not only as a competitive team but also as a platform that provides opportunities for high school and university students to participate in various aerospace developments and projects. Simultaneously, members actively engage in research and development in various engineering challenges in rocketry.

Members of the group work independently to develop and construct their rockets solely for the purposes of research and education. They are involved in tasks ranging from design, simulation, and assembly to testing. Throughout these phases, the team takes advantage of the capabilities offered by MATLAB, showcasing their commitment to innovation and hands-on learning.

The BME Suborbitals team at the EuRoC'22 continental competition where they achieved 5th place in their category.
Image 1. The BME Suborbitals team at the EuRoC’22 continental competition where they achieved 5th place in their category.


The members of BME Suborbitals face numerous challenges during their development processes. Among the most significant hurdles this past season were the design of various components, a simulation of an engine they had developed, and the evaluation of measurement data. MATLAB proved to be a valuable tool in dealing with each of these problems.

One particularly important component is the so-called radax (“radial-axial”) joint, which enables interconnection between individual rocket modules. At the connection point, forces are transferred by screws, making their placement, positioning, and quantity crucial for a rocket’s successful flight. The correct arrangement and number of screws play a vital role in ensuring the structural integrity and stability of a rocket during its flight. Such a connection needs to be strong enough to withstand the forces and loads associated with the launch, yet it must not be too heavy, as excess weight would detract from the rocket’s payload capacity.

The goal of the rocket engine development project was to create a solid-fuel rocket engine that meets the team’s needs, is easy and inexpensive to manufacture, and is reliable in operation. Extensive calculations, literature review, and detailed planning were all key to achieving these objectives. In addition to development, the team placed a strong emphasis on research. This meant not only creating the rocket motor but also developing new manufacturing technologies, advancing current methods, and experimenting with new propellant compositions.

As in most engineering workflows, it is crucial to validate and assess the results. Valuable insights can be drawn from flight data, helping to detect potential errors and identify new development trajectories. For this purpose, the data needs to be interpreted and presented in a comprehensible format that is easily understood by everyone involved.


The most time-consuming part of designing a radax joint is determining the appropriate size. While there are several sources available to guide the design of such a connection, despite careful planning, in practice, there are cases where the connection fails to withstand the load. To prevent this problem and facilitate the design process, the team has created a MATLAB script that makes it easy to determine the position and quantity of screws to be used for a radax joint based on the forces acting on the connection and the screws’ mechanical properties. Later, simulations were carried out based on the finite-element method – the outcome having confirmed the reliability of the simplified model.

A radax connector simulation includes determining its equivalent mechanical stresses.
Image 2: A radax connector simulation includes determining its equivalent mechanical stresses.

The development of a propulsion system involves sizing the thrust to ensure that the rocket reaches the desired altitude. Before such a simulation, a program written in MATLAB generated nearly a million thrust-time curves with specific boundary values. Using these curves and their corresponding mass flow rate-time curves, we conducted an equal number of flight simulations (one for each thrust curve). These simulations solved differential equations using both the Euler and fourth-order Runge-Kutta methods. Meanwhile, a MATLAB code accompanying the flight simulation evaluated the results of the simulated flight. Following flight simulations, it was necessary to model the combustion and internal conditions of the engine. The combustion simulation calculated the evolving combustion surface area on a continuous basis, from which, with the help of input parameters, the resulting pressure could be determined. Subsequently, using internal pressure, the resulting thrust and thrust-time curve could be determined. The two simulations complemented each other and were used in parallel.

Chart of Height, Velocity, and Thrust for 1500 m target height and 4 kg dry mass
Image 3: Height, Velocity, and Thrust for 1500 m target height and 4 kg dry mass

The MATLAB App Designer was used in the data evaluation process. Information from different onboard sensors, saved by the onboard computer, can be seamlessly imported into MATLAB. Utilizing the capabilities of the App Designer, these data sets can be visualized in an interactive way. This approach facilitates efficient and rapid data processing, and the resulting plots are not only suitable for expert evaluations but also for teaching purposes.

A magnetic field change occurred during the flight according to the 3-axis magnetometer. A sinusoid change can be observed as the rocket is spinning during the flight.
Image 4: A magnetic field change occurred during the flight according to the 3-axis magnetometer. A sinusoid change can be observed as the rocket is spinning during the flight.


The efficiency and usefulness of programs created with MATLAB have been proven many times over. More reliable and accurate systems have been developed using the programs created. Measurement data usually confirm the accuracy of simulations. Those parts and assemblies that have been designed can be produced faster and are more robust than those that came before them via MATLAB use. Overall, development and manufacturing processes have been shortened by weeks thanks to simulations and efficient data evaluation.



Rocket development and the space industry present numerous opportunities and challenges for today’s engineers, researchers, and developers. To address those, the members of BME Suborbitals have enlisted MATLAB’s capabilities to address two crucial issues:

  • Facilitation of engineering work through specialized and targeted component simulations; and
  • Swift data evaluation and feedback by promptly assessing measurement results, even on-site, when necessary.


MATLAB is a versatile and powerful engineering simulation tool that users can completely customize to suit their own needs. Using various numerical methods and algorithms, several MATLAB programs have been produced to simulate and estimate the load or operating parameters of individual rocket components. Moreover, more efficient data evaluation was achieved with the help of App Designer.


MATLAB programs enhanced efficiency, accuracy, and robustness in system development, shortening overall timelines through simulations and streamlined data evaluation.

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