Every time a train rumbles through an underground tunnel, that vibration travels through the ground into nearby buildings, rattling walls and humming through floors. Over 7.5 million Europeans face potential disturbance from railway noise and vibrations, which can damage structural integrity, disrupt sensitive equipment, and harm quality of life. The META-NOVIB project aims to build a digital twin—a virtual replica of a real tunnel system—that uses machine learning to predict and control this ground-borne noise and vibration in real time. The system will also evaluate seismic metamaterials, engineered structures that can physically block or redirect vibrations before they reach buildings. If successful, this framework will give engineers a practical tool for making decisions during tunnel operation and maintenance, allowing them to keep noise and vibration within legal limits without costly retrofits. The impact extends beyond passenger comfort: reducing vibration protects historical buildings from structural fatigue and shields nearby residents from chronic noise exposure. This is applied engineering with a clear, measurable goal—making underground rail systems quieter and less disruptive to the cities they serve.
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Nowadays, comfort is a design requirement of all structural products that guarantees the quality and competitiveness. Noise constitutes a significant form of environmental pollution that impacts the lives of hundreds of millions of people globally, leading to various socio-economic consequences. Intense vibration has the potential to jeopardise both the structural integrity and the performance of equipment and hardware, and produce significant level of noise thereby affecting the comfort of individuals in several aspects. Subways represent a primary source of ground-borne noise and vibration in urban areas. Over 7.5 million Europeans face potential disturbance from railway noise and vibrations. In response to public concerns, governments have established laws and regulations to limit the permissible exposure of citizens and facilities to ground-borne noise and vibration. The goal of the META-NOVIB project is to develop a comprehensive framework to effectively predict and control the vibration and noise induced by underground railway tunnels using digital twin technology supported by machine learning tools. This system provides valuable insights for engineering decisions throughout the operation and maintenance of these tunnels. Additionally, it evaluates the performance of seismic metamaterials (SMM) in attenuating the level of noise and vibration to meet the allowable limit. META-NOVIB will provide an integrated platform for visualisation and real-time prediction and virtual control of the railway-induced noise and vibration during the operation and the maintenance phase. Thus, the output will have wide implications on the health of nearby residents due to vibrations and prevent any structural damage to historical buildings or structures, with high academic and industrial impact.
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