Harpur Hill, Buxton Derbyshire, SK17 9JN T: +44 (0)1298 218000 F: +44 (0)1298 218590 W: www.hsl.gov.uk Loughborough University Loughborough Leicestershire LE11 3TU UK P: +44 (0)1509 223416 F: +44 (0)1509 223981 http://www.lboro.ac.uk/transport 12.09.2014 A Review and Statistical Modelling of Accidental Aircraft Crashes within Great Britain MSU/2014/07 HSL Report Content Loughborough University Report Content Report Approved Report Approved Andrew Curran David Pitfield for Issue By: for Issue By: Date of Issue: 12/09/2014 Date of Issue: 12/09/2014 Lead Author: Emma Tan Lead Author: David Gleave Contributing Contributing Nick Warren David Pitfield Author(s): Author(s): Technical Technical David Pitfield / Nick Warren Reviewer(s): Reviewer(s): David Gleave David Pitfield / Editorial Reviewer: Charles Oakley Editorial Reviewer: David Gleave HSL Project Loughborough PH06315 N/A Number: Project Number: HSL authored 7 ,8 ,9 Appendix (a) Loughborough 3 ,4 ,5 ,6 ,10 ,12 sections and Appendix (b) authored sections Appendix (c ) HSL/Loughborough HSL/Loughborough 1, 2, 11 1, 2, 11 Joint authorship Joint authorship 1, 2 ,7 ,8 ,9 ,11 , Loughborough HSL Quality 3 ,4 ,5 ,6 ,10 ,12 Appendix (a) and quality approved approved sections Appendix (c ) Appendix (b) sections DISTRIBUTION Matthew Lloyd-Davies Technical Customer Tim Allmark Project Officer Gary Dobbin HSL Project Manager Andrew Curran Science and Delivery Director Charles Oakley Mathematical Sciences Unit Head David Pitfield Loughborough University David Gleave Loughborough University © Crown copyright (2014) EXECUTIVE SUMMARY Background One of the hazards associated with nuclear facilities in the United Kingdom is accidental impact of aircraft onto the sites. Although it is the responsibility of the licensee to assess this hazard and to demonstrate that the resulting risk is adequately managed, the Office for Nuclear Regulation (ONR) provides oversight and challenge to these assessments and on occasion has the need to make its own independent assessment of the risks. The methods used to assess aircraft crash frequency to nuclear facilities in the UK (the “Byrne model”) were originally developed by the UK Atomic Energy Authority during the 1980s. Although it has subsequently been revised by AEA Technology (formed from the commercial arm of the UKAEA) under contract to HSE (HSE Research Report 150/1997, 1997) and ESR Technology (formerly the Engineering, Safety and Risk business of AEA Technology) (ESR Technology, 2008), the method remains substantively unchanged and based upon sparse historical data on accidents that occurred within Great Britain (GB). Aims The general aims of this report were to review the methods currently used for assessing accidental aircraft crash frequency to UK nuclear installations and consider whether improvements to the methods are possible and advisable. Specifically the aims were: to determine the models that are available to estimate the likelihood of accidental aircraft crash at a particular location, what their key characteristics are and what scope there is for potential further development; to compare the Byrne model (Byrne, 1997) with other models, and determine whether it can be enhanced with larger contemporary datasets; to develop statistical models for the frequency of accidental aerodrome and off-aerodrome crashes in GB; to examine the available data on crash locations and develop a new statistical model for the probability of a crash at a particular location relative to an aerodrome; to consider methods for incorporating variation in risks between aerodromes into the assessment methods due to variation in factors such as operational and meteorological conditions; and to compare and propose improvements to the existing aircraft crash methods. Main Findings Comparison of models In summary, the Byrne model did not account for the hazardous scenario of the licensed nuclear site acting as an obstacle to an otherwise safe flight; did address the shadow shielding of part of a site by structures on another part of a licensed nuclear site; i did address the skidding of an aircraft into a licensed nuclear site; did address the projectile bounce of an aircraft making its initial impact outside a licensed nuclear site; did address projectiles falling from aircraft; did not address issues relating to hazardous materials carried on-board the aircraft and hazardous materials used in the structural composition of the aircraft; did not appear to consider gyrocopters, gliders, airships, gas-lifting balloons and hot-air balloons; did address unmanned aerial vehicles and concluded that they posed an insignificant risk; is considered to be a generalised area model suitable for calculating average crash frequencies over a nation, but not a good model for predicting the crash frequency onto a specific location; did not consider curved flight paths; and did not consider quantification of uncertainty. Most other methods of assessing accidental aircraft crash risks do not quantify the overall uncertainty in estimated crash probabilities. As such, their use is considered unsuitable for assessing aircraft crash risk to UK nuclear sites until statistical uncertainty can be quantified. All of the models suffered from either an inability to consider all types of aircraft, or they may not take local flightpaths into account if the site was within the vicinity of an aerodrome. Whilst the Wong (Wong, 2007), and ACRP 3 (TRB, 2008) models provide some useful information for assessing inter-aerodrome variation in crash frequencies, some of the risk factors may not be relevant for GB, such as the US Federal Aviation Administration (FAA) hub airport size. The risk factors relating to meteorological conditions, which are based on data rather than an assumed causal mechanism, are considered to be reliable for application to GB. The model with the greatest ease of application was the DOE standard model (DOE, 2006), allowing non- aviation specialists to take account of site-specific factors more easily than applying the Byrne model and the Philips model if light fixed-wing aircraft had to be accounted for. The model included a tabulated set of data that was relatively easy to apply to a site but it would also be possible to expand the concept to a Geographic Information System (GIS) to highlight the aviation risk exposure over the whole of GB. A GIS would have the benefit of being relatively easy to use for reference purposes and it would be a major advance in public understanding of aviation risk exposure across GB. Statistical analysis of aircraft crash rates and location distributions Statistical analysis of aircraft crash data for GB for the period 1985 to 2006 found no evidence of a change in the background annual rate of crashes (expressed per km2) for any of the aircraft categories considered. However, it should be noted that due to the low number of accidents in the small and large transport aircraft categories (≤20,000 kg and >20,000 kg Maximum Certified Take-off Mass (MCTOM) respectively), the statistical power to detect any trend over time is low. Statistical analysis of civil aerodrome-related crashes for GB for the period 1979 to 2006 found no evidence for a change in the rate of crashes (expressed per movement) for small and large transport aircraft. However, a statistically significant increase in the accident rate for light aircraft (<2,700 kg MCTOM) of 4.4% and in the accident rate for helicopters of 4.7% per year was found. Based upon accidents between 1985 and 2006 the estimated background crash rate was greatest for England. For light aircraft, the annual crash rate for England is 2.93 x 10-5km-2 (95% C.I. [2.34, 3.63 x 10-5km-2]); for ii helicopters is 1.39 x 10-5km-2 (95% C.I. [1.00, 1.90 x 10-5km-2]); for small transport aircraft is 0.31 x 10-5km-2 (95% C.I. [0.14, 0.60 x 10-5km-2]); and for large transport aircraft is 0.04 x 10-5km-2 year-1 (95% C.I. [0.00, 0.19 x 10-5km-2]). Based upon accidents between 1979 and 2006 the estimated aerodrome-related crash rates were similar across England, Scotland and Wales, hence the GB rates may be used. The crash rate per million movements for light aircraft is 1.61 (95% C.I. [1.36, 1.90]); for helicopters is 2.12 (95% C.I. [1.43, 3.03]); for small transport aircraft is 3.14 (95% C.I. [2.18, 4.39]); and for large transport aircraft is 0.14 (95% C.I. [0.05, 0.32]). Adjusting the rate for light aircraft by the estimated trend of +4.4% per year gives a crash rate for 2014 of 3.89 per million movements (95% C.I. [2.51, 6.03]). Similarly, adjusting the rate for helicopters by the estimated trend of +4.7% per year gives a crash rate for 2014 of 5.16 per million movements (95% C.I. [2.19, 14.35]). Analysis of accident data compiled by the US National Transportation Safety Board (NTSB) for the period 1993 to 2012 determined an improvement in reliability of approximately 6.4% per year for flights operating under regulation 14 CFR 121 and 1.6% annum for general aviation. Both these aviation categories relate only to US operated flights and not foreign operated ones. Previous research by Loughborough University has identified that for accidents in the proximity of an aerodrome, the accident rate for flights of foreign origin/destination may be considerably higher than for domestic US flights. Thus even if these improvements in reliability are representative of UK operated flights (excluding light aircraft) they may not be representative of changes in the overall accident rates in the United Kingdom. An analysis of crash location data for crashes that occurred in the US, supplied by Loughborough University, was undertaken with a number of distributions investigated.