Underneath modern cities there exists a vast network of infrastructures where tunnels play a crucial role, facilitating transit of trains, metros, highways and utility services. Yet, the construction of these underground structures is no simple feat. Traditional methods of excavation are complex and prone to complications such as ground instability and surface disruptions. In response to these challenges, Tunnel Boring Machines (TBMs) emerged as a groundbreaking solution. TBMs revolutionized tunnel construction by offering a safer and more efficient alternative to traditional excavation methods. The 1990s saw a surge in the popularity of TBMs, especially in urban areas. This was primarily driven by the need for infrastructure expansion in densely populated cities, where traditional excavation methods would be impractical or disruptive.
While TBMs present a more efficient alternative to traditional methods, their performance is deeply influenced by ground conditions. Despite thorough ground investigation campaigns, uncertainties in soil behaviour can persist, posing challenges to tunneling operations. Variations in ground conditions can lead to discrepancies in TBM performance, potentially causing delays or jeopardizing project integrity. For instance, encountering unexpected soft soil may require slowing down TBM operations to prevent collapse, while encountering harder-than-anticipated rock may require additional maintenance.
In light of these uncertainties, it is vital that operators have access to advanced tools for real-time decision-making.
Gemini: Redefining Tunnel Construction with AI-Powered Technology
Gemini, developed by SAALG Geomechanics in collaboration with ACCIONA, is a cutting-edge software solution that leverages machine learning algorithms to transform TBM operations. By continuously analyzing TBM parameters and ground conditions in real-time, Gemini provides engineers and operators with predictive insights, anomaly detection, and optimization assistance.
As a first step towards autonomous TBMs, Gemini not only enhances efficiency but also revolutionizes decision-making in tunneling operations. By empowering TBM pilots with real-time predictive analytics and anomaly detection, Gemini enables them to confidently navigate through complex ground conditions, ensuring exceptional outcomes in tunneling projects.
Unlocking Efficiency: The Spanish Tunneling Success with Gemini
A small-diameter hydraulic tunnel in Spain was used as a case study to validate the transformative impact of Gemini on tunnel operations. A notable increase in TBM advance rate was estimated because of implementing Gemini in TBM operation, driven by predictive analysis optimization strategies. This efficiency translated into a significant reduction in excavation time, streamlining project schedules. Additionally, cost savings and CO2 emissions reduction underscore the profitability and environmental benefits of Gemini.
Embracing the Future: Paving the Way for Sustainable Tunneling Worldwide
Gemini leverages machine learning algorithms to provide real-time insights into TBM performance and ground conditions, empowering operators with predictive analytics, anomaly detection, and optimization assistance. By seamlessly integrating these capabilities, Gemini enhances efficiency, mitigates risks, and ensures smoother project execution. The success story of Gemini in Spain, marked by a notable increase in TBM advance rate, substantial reduction in excavation time, and significant cost savings, underscores its transformative potential. As Gemini prepares to make its mark in tunneling projects across Brazil, Australia, and Poland, it heralds a new era of innovation and efficiency in infrastructure development worldwide. With Gemini at the helm, the future of tunneling is not only safer and faster but also more sustainable and cost-effective.
