Abstract:
Scalability relationships are applied on systems to handle growing amount of data and generate governing laws of complex phenomena. Most complex and diverse fields including the nature itself follow simple scaling laws. Using these laws, raw data is converted into significant facts, relationships, patterns and trends to help in taking analytical decisions. It also helps in allocating resources optimally and to maximize the efficiency of systems.
Unmanned Air Vehicles (UAVs) are becoming the primary element of choice for versatile missions because of their number of advantages over manned aircrafts. Militaries around the world are raising separate divisions / units to handle UAV operations. Similarly, in civil, UAVs are being deployed for applications ranging from traffic control to food and books delivery. A huge amount of data about these UAVs is commercially available. Just like other areas of life where the scalability laws have played an important role in enhancing the scientific body of knowledge and suggested a way forward, UAVs should also take benefit from them.
This research work is a successful attempt in developing scalability laws on UAVs. Specifically, geometric parameters are used to identify the performance characteristics. The geometric parameters include wingspan, overall length, payload and maximum take-off weight. The performance characteristics, predicted from these geometric parameters include endurance, ceiling and maximum speed of the UAVs. These relationships are derived from linear regression technique and tested statistically. Results show that scaling is indeed a pervasive property in UAVs. Similarly, preliminary studies on scalability trends in birds are also modeled and studied.
