Graph Percolation as Decision Threshold for Risk Management in Cross-Country Thermal Soaring
For operators of soaring aircraft, this work provides a theoretical framework for risk management during long-range unpowered flight.
This paper applies graph percolation theory to model the risk of failing to find updrafts in cross-country thermal soaring, and validates the model using flight logs from human pilots. The analysis shows that pilots rarely operate outside percolation conditions, maintain a desired minimum node degree, and accept lower climb rates to preserve percolation.
Long range flight by fixed-wing aircraft without propulsion systems can be accomplished by "soaring" -- exploiting randomly located updrafts to gain altitude which is expended in gliding flight. As the location of updrafts is uncertain and cannot be determined except through in situ observation, aircraft exploiting this energy source are at risk of failing to find a subsequent updraft. Determining when an updraft must be exploited to continue flight is essential to managing risk and optimizing speed. Graph percolation offers a theoretical explanation for this risk, and a framework for evaluating it using information available to the operator of a soaring aircraft in flight. The utility of graph percolation as a risk measure is examined by analyzing flight logs from human soaring pilots. This analysis indicates that in sport soaring pilots rarely operate in a condition which does not satisfy graph percolation, identifies an apparent desired minimum node degree, and shows that pilots accept reduced climb rates in order to maintain percolation.