ABSTRACT
In the context of global climate change and the pressing need for sustainable development, the tunnelling industry is exploring innovative solutions to minimize its carbon footprint. This paper presents the concept of the Digital Carbon Twin (DCT), an advanced digital replica of physical tunnelling projects that integrates real-time data and predictive analytics to optimize environmental performance throughout the lifecycle of a tunnel. By utilizing Building Information Modeling (BIM), Internet of Things (IoT) sensors, and machine learning algorithms, the DCT facilitates the monitoring and management of carbon emissions from the design phase through construction and into operation.
The core functionality of the DCT involves continuous data acquisition and analysis, enabling stakeholders to make informed decisions that reduce energy consumption, material waste, and greenhouse gas emissions. This digital framework not only ensures compliance with environmental regulations but also enhances operational efficiency and cost-effectiveness.
A case study of a metropolitan tunnelling project demonstrates the practical application of the DCT. The study highlights significant reductions in carbon emissions achieved by optimizing construction schedules, selecting sustainable materials, and implementing energy-efficient technologies. Additionally, the DCT provides a platform for simulating various scenarios, allowing engineers to evaluate the environmental impact of different design and operational strategies.
The adoption of the Digital Carbon Twin in tunnelling projects represents a transformative approach to achieving sustainability goals. By integrating advanced digital technologies with environmental stewardship, the tunnelling industry can significantly contribute to global efforts in mitigating climate change. This paper underscores the potential of DCT to serve as a blueprint for future infrastructure projects, promoting a more sustainable and resilient built environment.
