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Top1. Introduction
Measuring pressure, temperature and relative humidity fast enough in order to provide real-time information of the momentum state of the atmosphere plays an important role in navigation and instrumentation applications for soaring gliders and in UAV (Unmanned aerial vehicles) (Akhtar, Whidborne, & Cooke, 2012). This is achieved via suitable electronics for providing online information to the pilot inside the UAV cockpit (Reddy, Celani, Sejnowski, & Vergassola, 2016). However, as we are aware, appropriate light-weight multy-sensory systems for paragliders, for example, have not been designed yet, and the pilot relies on intuitive decisions most of the time of the soaring flight.
Sensors with low power consumption, digital interfaces, miniature and light-weight packing, based on piezo-resistive technology such as Bosch Sensortec BME280, for example, are available at a low-cost price today and can be implemented in the multi-sensory system (MSS) for assessment of the momentum state of the atmosphere. At the same time, mathematical processing of the data is necessary in order to accomplish the micro-scaled dynamics evaluation in order for the multi-sensory system to implement intelligence solutions to provide better cognitive support to the pilot rather than just displaying raw data. One promising approach is based on ornithology studies (Laurenza, 2007), since the soaring of a glider and a bird share many commonalities like – being lightweight, motor-less, relying on current atmospheric dynamics at low altitude of flight.
Numerous accounts of birds soaring without flapping their wings, ranging from observations by Leonardo da Vinci to Octave Chanute can be found in the literature (Laurenza, 2007). Birds circling in thermals are typical examples for the advantageous use of the atmospheric energy to preserve one’s position in the air (Ákos, Nagy, Leven, & Vicsek., 2010). For instance, nowadays different types of gliders are soaring thermals and reaching hundreds of kilometers and dozens of hours in the air in a single unpowered flight (Pagenan, 1992).
It is well known that there are different forms of energy in the atmosphere boundary layer (Ákos, Nagy, Leven, & Vicsek., 2010). Some of them are stronger, but less predictable than others. Dynamical forms of energy can be found in:
- 1.
Ridges (orographic lift, where the slopes of hills and mountains deflect wind);
- 2.
Atmospheric thermals (uneven heating of the ground, which produces buoyant instabilities);
- 3.
Waves (long period oscillations of the atmosphere, which occur in the lee of large mountain ranges). These waves were used in the altitude flight record by Airbus Perlan Project, for example, (https://www.airbus.com/newsroom/press-releases/en/2018/09/airbus-perlan-mission-ii-glider-soars-to-76-000-feet-to-break-ow.html). In recent years also theoretical and experimental investigations of energy extraction from atmospheric turbulence are performed with main application large aircrafts (Patel & Kroo, 2008). With UAV, however, the forms of energy, influencing the flight, differ in scale and dynamics, which needs further investigation and modeling.
The atmospheric thermals are the most commonly used forms of energy for soaring flights. Although they occur frequently and over various types of terrains, in both hilly and flat areas. Their nature is not understood well, which has led to a number of casualties with light planes without being able to define the exact reason for this to occur (Pagenan, 1992).
Our hypothesis is that providing further investigation of the atmospheric boundary layer dynamics can contribute substantially to the safety of the flights. Thus, the present paper is focused on the evaluation of the atmosphere boundary layer dynamics on a micro-scale, since exactly in this boundary layer most of the soaring flights are performed.