Optimisation of the penetration parameter of tunnelling machines based on geological conditions

  • 09 INDUSTRY, INNOVATION AND INFRAESTRUCTURE
  • 10 REDUCED INEQUALITIES

Optimisation of the penetration parameter of tunnelling machines based on geological conditions

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November 30

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February 21

END OF INSCRIPTIONS

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April 8

SELECTION DAY

The finalist startups will pitch to a committee that will decide the winner. This startup will develop a pilot in a real environment for 6 months with us.

January 26

DEMO DAY

Each team will present the results obtained to the decision committee that will evaluate the continuity and scaling of the program.

SOLUTIONS
Transport
DURATION
6 MONTHS
LOCATION
BUDGET
50 000 €
More information
Bases Legales
BUDGET
50 000 €

ACCIONA is a world reference in the construction of tunnels, with more than 825 kilometres constructed in Metro, road or railway tunnels, where it has acquired prestige in the construction of underground mega-infrastructures and tunnelling machinery.

 

The company’s know-how means that it is able to participate in the biggest projects worldwide, such as the tunnels along the Follo Line in Norway or the Quito Metro in Ecuador.

In the process of digging full tunnel sections with a tunnelling machine, the machine and knowledge of the soil are equally important, with the latter being the element that always provides the greatest uncertainty in a construction project, A geological study is essential when defining operating conditions. This leads to the optimisation of the digging performance of the tunnelling machine while ensuring conditions of safety and protection for the machine.

 

A real-time analysis of the data, the consistency of the data, and the experience of the team working on the project are a challenge and, therefore, an opportunity within this highly specialised area. We would highlight the singular nature of this project due to its technical complexity and the scale of the project.

ACCIONA seeks start-ups that can adapt their solution to improving the tunnelling machine’s performance, and only making use of the existing sources of data that such a machine generates. We are looking for a tool that will assist decision-making, optimising the digging process through the retro-analysis of geological parameters. We provide the historical data generated by a tunnelling machine for the development of such a tool, with the possibility of testing the tool in a real environment during the construction phase.