English | Spanish | Dutch
Log in

ACCIONA invests in Machine Learning for tunnel construction

    Danilo Merges
    By Danilo Merges Replies (1)

    The company partners with SAALG Geomechanics to predict real ground movement during the execution of construction projects

    ACCIONA has become lead investor of SAALG Geomechanics, a software and engineering startup that predicts real ground movement during the entire construction cycle with a large volume of data.

    ACCIONA, as strategic partner, will allow SAALG Geomechanics to apply its Daarwin analysis software to the field of tunneling, in which ACCIONA has extensive experience, as it has a dozen tunnel-boring machines (TBMs) currently operating in different projects of high complexity around the globe.

    The technology company has raised €3.65 million through an operation partially funded by the European Commission's EIC Accelerator program, in a mixed model of capital investment and subsidies, with ACCIONA as lead investor and Creand Crèdit Andorrà as financial supporter. SAALG Geomechanics aims to subsequently raise new capital to reach €5 million.

    For ACCIONA, this bet on SAALG Geomechanics is a success story for its open innovation program called I'MNOVATION. Through this initiative, the company gives startups the opportunity to collaborate on real projects by applying their innovative solutions for the progress of society and environmental protection. SAALG was one of the companies that decided to apply for the program and, after a successful pilot project in direct collaboration with the business teams, ACCIONA has decided to invest in it. This investment confirms the company's commitment to innovation and the entrepreneurial ecosystem.

    AUTONOMOUS TBMs

    Tunnel-boring machines (TBMs) have emerged as the safest tunneling method in a context of technological advances in geotechnical engineering, improving working conditions inside tunnels and the use of ventilation systems, among other developments.

    Currently, more than 30% of tunnel construction projects worldwide experience geotechnical difficulties that lead to cost overruns or delays, with an average additional cost that can reach more than 55% of the original budget. The new functionalities of the Daarwin software, based on machine learning algorithms, make it possible to predict a TBM's forward speed, detect geotechnical anomalies in advance, assist TBM pilots in optimizing tunneling phases, and gather information for use in future projects. The new functionalities of this solution, which represents a significant increase in safety, efficiency and sustainability, are the first step towards the autonomous TBM.

    ACCIONA has broken several world records with TBMs and has helped to place this machine at the center of tunnel engineering. In its tunneling projects, the company uses some of the largest machines on the planet, up to 15 meters in diameter and up to 100 meters in length, which it adapts to the terrain in which they operate.

    Since its creation in 2016, SAALG Geomechanics has been involved in more than 50 civil engineering, large building and mining projects worldwide: tunnels, large excavations and roads in more than 15 countries. Since 2020, its Daarwin software is being used, for example, as a strategic innovation tool for the UK’s High-Speed Two (HS2) project, the largest European high-speed rail infrastructure project.

    https://www.acciona.com/updates/news/acciona-invests-machine-learning-tunnel-construction/?_adin=02021864894

    image

    image