The project "Case Study: CFD Investigation on Harvesting Piston Wind Energy in Tunnels", delivered for Q-sustain Ltd in 2024, addressed a practical energy challenge through computational fluid dynamics (CFD). Rather than producing simulation images in isolation, the study was organised around the client's design questions: what controlled performance, where the principal risks or losses occurred, and how the design or operating strategy could be improved.

When a train passes through a tunnel, the air in the tunnel is squeezed by the train and follows it. A negative pressure region forms behind the train, drawing fresh air into the tunnel and pushing the existing air out. This phenomenon is known as ‘piston effect’. In this project, Manchester Simulation was commissioned to conduct a CFD-based feasibility study to assess the effectiveness of harvesting energy from the piston effect using a wind turbine in a typical tunnel. CFD simulations were conducted for a single 5-car Class 802 train, passing through a tunnel. The CFD results captured the flow physics and estimated the piston effect for different scenarios. Air velocity in 3 different locations within the tunnel were obtained and by utilising experimental data, the maximum potential power output in Watts was estimated for each location. Due to the success of this project, the UK Research Council funded the continuation of this project for our team to develop a novel vertical-axis wind turbine (VAWT) to utilise this piston wind and to be deployed in the UK.

The methodology centred on a transient CFD model of a Class 802 train moving through a representative tunnel and generating the piston effect. The representation retained the train, tunnel blockage, annular clearance and the measurement locations where pressure waves and induced airflow could be harvested. Boundary and operating conditions covered the selected train passage and turbine locations, with experimental performance data used to convert airflow into potential electrical output, with material, fluid and equipment properties assigned from the available design information. Resolution was concentrated in regions where steep velocity, thermal, concentration or phase gradients were expected, while the overall model remained efficient enough to compare several credible configurations. This balance allowed system-level performance to be linked to the local mechanisms responsible for it.

The assessment compared candidate turbine positions and a future vertical-axis wind-turbine concept. Performance was judged using time-varying air velocity, pressure response, duration and repeatability of the piston wind, and estimated power at the candidate locations. Results were reviewed through quantitative summaries and engineering visualisations, such as contours, vectors, streamlines, sections and time histories, selected to suit the physics. Important assumptions and operating uncertainties were considered so that the recommendations relied on repeatable comparative trends rather than a single nominal case.

For Q-sustain Ltd, the principal value was a positive feasibility case and the technical foundation for continued turbine and toolkit development. The final evidence linked each recommendation to the relevant model or process output, making it suitable for internal design reviews, supplier or contractor discussions and, where applicable, planning, safety or regulatory dialogue. The work also created a reusable baseline that can be updated as geometry, operating data or test results become available, reducing the cost and risk of later design iterations.