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Concrete Sensors Used in London Airport Project

Thursday, January 23, 2020

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Contractors with United Kingdom company BAM Nuttall are utilizing what is being billed as the first commercial machine-learning program for concrete.

Funded with an Innovate U.K. grant awarded in 2018, BAM collaborated with construction technology firm Converge on the technology: sensors that give an accurate prediction of when concrete will reach its required strength.

The Project

BAM Nuttall was contracted for a new concrete deck extension at the London City Airport. (The contract is estimated at 95 million euros ($105.4 million).

BAM Nuttall

Contractors with United Kingdom company BAM Nuttall are utilizing what is being billed as the first commercial machine-learning program for concrete.

The 75,000-square-meter (807,293-square-foot) project is the first stage of construction and is part of the 480 million-pound ($630.9 million) City Airport Development Program, which aims to update the airport’s facilities, expand offered flights and grow accommodations for passengers.

The goal is to grow the airport’s passengers from the current 4.5 million to 6.5 million. Work on the deck started in spring 2018 and is expected to be complete early this year.

The Sensors

The deck extension is made of precast planks, beams and insitu sitting on piles, which are typically 30 meters long (10 meters through the dock’s water and 20 meters into the ground) on a roughly 10-meter-by-10-meter grid, according to New Civil Engineer.

The beams are generally 9.8 meters long and 900 millimeters by 930 millimeters (35.4 inches) wide. They span across the piles and can weigh up to 43 tons each. On top of those, acting as secondary beams, are the precast planks which are 300 millimeters deep by 1.5 meters wide and 9.5 meters long.

Finally, the insitu concrete covers the whole deck, tying the precast elements together.

The work is being done in increments; once a section is finished, it forms the base for the next one. This is where the technology comes in.

“Our users were waiting for concrete to hit a critical strength before scheduling the next activity, but this often meant that the site teams needed to strike formwork or tension the slab were deployed in other areas when the time came to act,” said Converge Product Lead, Sam Ellenby. “Thus, critical actions were frequently delayed.”

The technology is referred to as an “advanced artificial intelligence strength prediction engine.”

“Within hours of concrete being poured, Converge can predict the time a critical strength will be reached, several days in advance, by applying the latest in machine learning techniques,” BAM said in a statement.

“The predictions engine combines local weather data, a database of historical concrete curing data and the Converge concrete monitoring platform’s real-time measurements from the pour. This gives Converge the unique ability to predict the time the concrete will reach strength with an accuracy of +/- 5%, several days in advance.”

Each sensor has a QR code that is scanned into the software system. The tip of the sensor is also a thermometer, which takes readings after a pour. The sensor transmits its temperature and is processed, alerting an engineer on the ground when the sensor has indicated the concrete has reached strength.


Tagged categories: Airports; concrete; EMEA (Europe, Middle East and Africa); EU; Ongoing projects; Tools & Equipment

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