Conference proceeding
Probabilistic Risk Assessment of Bird-Turbine Collisions Using Flight Path Models
Proc. of the European Safety and Reliability Conference (ESREL2026), pp.2303-2310
The European Safety and Reliability Conference (ESREL 2026) (University of Minho in Braga, Portugal, 14/06/2026–19/06/2026)
2026
Abstract
A hybrid probabilistic framework was developed to assess bird collision risk using stochastic flight path models based on Brownian motion and Brownian bridge processes. Species-specific flight parameters for itinerant and nesting birds were derived from field surveys and radar data collected in a remote outback region of Australia. Simulations were conducted to estimate the probability of birds entering the rotor-swept area of turbines and the expected number of collisions, accounting for turbine characteristics and flight variability. The results indicate that higher expected collision numbers were generally observed for itinerant birds than for nesting birds under similar avoidance rates. For nesting birds, collision estimates obtained from the Brownian bridge model were comparable to those from the Brownian motion model but corresponded to longer flight durations.
Details
- Title
- Probabilistic Risk Assessment of Bird-Turbine Collisions Using Flight Path Models
- Authors/Creators
- Soudabeh Shemehsavar - Murdoch University, School of Mathematics, Statistics, Chemistry and PhysicsGraeme Hocking - Murdoch University, School of Mathematics, Statistics, Chemistry and PhysicsRoss Maller - Australian National UniversityPatricia FlemingWafaa Mansoor - Murdoch University, School of Mathematics, Statistics, Chemistry and Physics
- Publication Details
- Proc. of the European Safety and Reliability Conference (ESREL2026), pp.2303-2310
- Conference
- The European Safety and Reliability Conference (ESREL 2026) (University of Minho in Braga, Portugal, 14/06/2026–19/06/2026)
- Publisher
- Research Publishing
- Identifiers
- 991005904678107891
- Copyright
- © 2026 ESREL 2026 Organizers.
- Murdoch Affiliation
- School of Mathematics, Statistics, Chemistry and Physics; Centre for Terrestrial Ecosystem Science and Sustainability; School of Environmental and Conservation Sciences
- Language
- English
- Resource Type
- Conference proceeding
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