Dr Graeme Anderson and Andrew Chadwick from Frazer-Nash Consultancy outline how modelling tools can help increase our understanding of the potential outcomes of collisions between drones and critical national infrastructure.
Market analysts suggest that by 2021 there could be 67.9 million annual shipments of unmanned aerial vehicles – frequently referred to by commercial and leisure users as ‘drones’ – to consumers across the globe[i]. Drones’ popularity, like the vehicles themselves, is soaring, with leisure, racing and photography drones available for prices that range from tens to thousands of pounds. An increasing variety of applications, from aerial mapping to emergency response investigations and security monitoring, is making drones a useful tool. But this growth does not come without risk.
The aerospace sector is particularly concerned. In just two years, reported ‘near misses’ involving drones and aircraft have increased, with 69 reported incidents in 2016 – more than double the 29 in 2015, and more than eleven times the six reported in 2014.[ii] But while potential collisions with aircraft have been a key focus, the upsurge in drone use increases risk across a much wider range of industries. Areas which could see an increase in risk include the transport, power and energy sectors, with the potential for extensive and costly disruption if a drone crashes into signalling equipment, power lines or distribution networks.
Indeed, these kinds of incidents are already occurring. In 2016 alone, the global media featured reports of a drone colliding with power lines in Sichuan in China, causing an electricity blackout that took six hours to fix[iii]; another drone crashed into the site of a nuclear power facility near Cape Town in South Africa[iv]; while on the UK’s North York Moors Railway a drone hit one of the carriages being pulled by heritage steam locomotive the Flying Scotsman[v]. Sometimes, however, simply the potential threat of a collision can affect operations: Dubai International Airport was closed three times in four months in 2016 due to unauthorised drone activity, with flights diverted and an estimated cost to the airport of $1 million per minute[vi].
The majority of reported drone incidents are believed to be due to inadvertent error by amateur operators, and in the aerospace sector the Civil Aviation Authority has identified this as the highest risk. This risk is likely to increase in line with the projected growth in drone use: the Royal Aeronautical Society suggests that “as the number of drones increases, so does the risk of accidents”[vii]. Even drone operators who have undertaken training, and who use their craft for commercial purposes could make a mistake, lose control, or experience a technical fault that causes the drone to lose power mid-flight. Perhaps more worryingly, there is also the potential for those intent on causing harm to use drones as a tool for malicious acts. A drone’s ability to fly over perimeter defences could see it used to assault a high-profile individual, or even to threaten crowds at a packed sporting event.
Similarly, drone impact could result in widespread disruption and damage to the UK’s critical national infrastructure (CNI), including the power generation industry, defence sector, and transmission, distribution, communication and transport networks. In addition to the potential for accidental impact – a drone colliding with the fuel pipeline or electricity pylon it is surveying, for example – CNI could also be at risk from malicious physical attack using drones. A motivated individual or group could potentially launch an attack on a nuclear cooling tower, rail or road bridges or tunnels, possibly even using a drone with a chemical or explosive payload. Any organisation, CNI or otherwise, which has assets including buildings, systems and personnel, that could be damaged by drone impact needs to consider the effect this may have on their operations.
A first step in this is to quantify the potential risk that drone impact could pose to the organisation’s assets. Modelling can help with this – it can increase key stakeholders’ understanding of the risk, by analysing the potential effects of a variety of drone types striking a range of assets, from buildings to humans. The potential effects of most drone impacts are currently unknown: few studies have been performed to understand the possible consequences of a drone collision, so the extent of the risk is often unclear. Using proven modelling techniques previously employed to analyse the effect that bird strikes might have on aircraft, Frazer-Nash has developed computer modelling and analysis tools that provide an indication of the likely outcomes of drone collision. These tools offer industry the opportunity to significantly improve their understanding of the effect an impact could have on their assets and systems.
Analysis and modelling offer many additional benefits to an organisation, and can underpin physical testing. Modelling is a flexible, inexpensive, and rapid approach to examining and comparing a range of scenarios, enabling analysis to be undertaken to define the risk of impact, including any danger to life. Once the model is validated, it can be used to look at any number of different impact conditions: angles, masses, velocities, locations. With aircraft, for example, modelling can predict what might happen if a drone battery came into contact with an aeroplane engine: the damage that might be caused and the possible fire risk. Modelling can also provide clarity on failure modes, identifying which failure mode of an asset hit by a drone would be of most concern, and can even provide clarity on failure modes for the drone itself.
The understanding that modelling and analysis provide helps deliver business resilience. For example, modelling a drone colliding with a substation could help define an electricity company’s operational guidance, or assist in the development of actions to minimise the collision’s outcome – perhaps through changes to an asset’s design that help protect its key function. The risk profile uncovered by modelling and analysis can inform the level of investment needed to mitigate the effects of drone strike on an organisation’s assets.
While the exact nature of these mitigating activities would depend upon individual circumstances, and multiple measures may be required, these could include solutions which detect drones’ radio frequency signals, wireless or ultrasound transmissions, alerting security or operational personnel. Organisations may even decide to use anti-drone ‘bazookas’, which fire nets to capture the drone.
Changes in drone legislation may be enacted in the future to reduce potential risks to infrastructure and assets. The UK Government has recently (21 December 2016) set up a consultation on the safe use of drones. This looks at addressing the safety, security and privacy challenges and concerns that they present and the evidence base provided by responses to the consultation will inform the development of impact assessments for proposed legislation.
However, while newspaper reports ensure drone collisions remain in the public eye, without understanding the level of risk it is possible that the potential for harm may be overstated – it is often the drone that is more likely to be damaged than the asset with which it collides. Through modelling, organisations can identify the potential outcomes of drone impact on their assets, understand the risk, quantify it and feed it into their risk assessment – allowing them to manage the potential effects it can have on their operational activity.
[ii] UK Airprox Board, Current Drone Airprox Count and Information
Frazer-Nash Consultancy is a leading systems and engineering technology consultancy