While “Storm Eunice” was officially named on Monday 14th February, the Red ‘take action’ warning status was not pronounced until the early hours of the day itself when the storm hit, 5 days later. However, that Monday, MetSwift’s forecasting team and their corrective Artificial Intelligence solution was able to confidently predict both the timing and intensity of this weather event and identify the potential dangers it presented, providing Align JV an effective and accurate early warning, 5 days ahead of the storm.
“MetSwift provides the Align JV with invaluable weather predictions. On Monday 14th February MetSwift anticipated three spells of severe weather were likely that week. The first on Wednesday 16th, the second on Friday 18th and the third on Sunday 20th and Monday 21st. MetSwift were able to give advanced warning to Align that the Friday storm had the potential to be a once-per-decade event with 65-80 mph wind gusts during the day at our main site in Maple Cross. The early notification from MetSwift that Friday’s storm was likely to receive a RED (stay at home) weather warning from the Met Office, allowed us to plan ahead for bad weather”
- David Hall, Align Lifting Manager.
HS2 Ltd’s main works contractor Align JV is delivering the Central 1 (C1) package of HS2 Phase One which consists of 21.6 km of high-speed rail infrastructure. This package includes a 3.37 km viaduct, 16.04 km twin-bored tunnel and five vent shafts handling both intervention and tunnel ventilation facilities. Work began in early 2021 on the foundations for the Colne Valley Viaduct, the UK’s longest railway bridge, with an expert team of ground engineers sinking the first of almost 300 piles that will form the foundations to support the viaduct piers. The viaduct structure consists of 56 piers and 1000 deck segments and will sit 10 m above the surface of the water with some spans up to 80 m long crossing lakes, River Colne and Grand Union Canal. Installing the piles, piers and segments is done by cranes and a launching girder and requires a high degree of accuracy and precision.
These types of lifting operations are highly dependent on weather with strict limits on wind speed and visibility. To optimise their lifting operations, Align has contracted MetSwift to provide an innovative artificial intelligence weather forecasting platform to help improve decision making and planning, as well as a forecasting delivery service, custom built alongside Align.
The MetSwift platform helps clients and contractors in the construction industry by
· Improving the planning related to lifting operations
· Improving the efficiency relating to the use of unloading slots
· Supporting the re-sequencing of works to suit crane availability
· Improving the accuracy of down time predictions
Metswift and Align have developed a new weather forecasting tool which uses AI to refine regional weather forecasts to site specific / height specific accurate predictions. It uses site-based weather station data to inform the AI. In time, this will use wind speeds from a tower crane anemometer to better inform the system for variations with height and the impact of local topography. This innovation provides instant access to site specific weather insights with both user limits applied and time window selection function, enabling different users to drill down to the type and intensity of weather which they are either at risk from or can utilise - this proactive solution aims to reduce site downtime cost and maximise operational efficiency, whilst promoting safer working practices.
"I would like to thank the team at Align for embracing and supporting our innovative forecasting solutions. Working with these construction experts has really helped us develop our technology. We aim to continue providing earlier, accurate and specific updates and warnings to support their operational safety in future. As the climate changes and the spectrum of severe events with it, such advanced, project-specific guidance will become paramount in U.K. construction."
- James Banasik MSc, CEO of MetSwift
