PSI - Issue 54

Wojciech Skarka et al. / Procedia Structural Integrity 54 (2024) 506–513 Author name / Structural Integrity Procedia 00 (2019) 000 – 000

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• Force imitating the weight of electrical components and cage - 4,64N.

Fig.9. Stress distribution on the drone model

The model under the influence of Earth's gravity, with the simulated mass of electrical components, exhibits significant stress characteristics. These stress values are crucial in understanding how the model responds to external forces and loads. Let's further expand on these stress parameters: • Maximum Stress Tensor: The maximum stress tensor experienced by the model is approximately 0.60433 MPa. This value represents the highest level of stress within the material or structure. It occurs at specific points or regions within the model, where the applied forces or loads are most intense. Understanding the maximum stress is essential for assessing the structural integrity and potential failure points of the model. In this case, it serves as a key reference point for evaluating the model's strength under gravitational forces and electrical component mass. • Minimum Stress Tensor: Conversely, the minimum stress tensor in the model is exceptionally low, approximately 9.3591e-006 MPa. This minimal stress level suggests areas within the model where the applied forces have a minimal impact or where the material is under less strain. While this value is significantly lower than the maximum stress, it still plays a role in the overall behaviour of the model, particularly in determining how it reacts to varying loads and gravitational forces. • Average Stress Tensor: The average stress tensor across the model is approximately 2.2928e-002 MPa. This value provides insights into the overall stress distribution within the structure. It represents an essential parameter for assessing the model's performance and longevity under the combined influence of gravitational forces and the simulated mass of electrical components. The average stress offers a general indication of how the material behaves under typical conditions and helps identify areas that might require reinforcement or optimization. The previous design of our drone model has undergone a thorough metamorphosis, transforming into a new, much more advanced version (Fig. 10). The engineers in our team decided to make a major modification to achieve even better performance. The most important change was to reduce the weight of the drone. The new model is much lighter, which has a huge impact on its ability to fly into the air. As a result, we now have fewer problems with ascending and maintaining stability during flight. In addition, the increased surface area of the model was used in a more efficient way. As a result, the new drone has greater torsion in the air, which makes it more agile and easier to operate. The new aileron allows for even better control over the drone, which significantly increases its manoeuvrability and ability to use it in various tasks. In addition, we have achieved a huge improvement in drone control by adding a new design of torsion control darts. Our new model is also much more compact than the previous one. This is important as it allows for easier transport and storage of the drone, which greatly increases its usability in the field.