Numerical Prediction and Corresponding Circular Economy Approaches for Resource Optimisation and Recovery of Underground Structures

Han-Mei Chen , Rongxin Zhou , Cristian Ulianov

Urban Rail Transit ›› 2020, Vol. 6 ›› Issue (1) : 71 -83.

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Urban Rail Transit ›› 2020, Vol. 6 ›› Issue (1) : 71 -83. DOI: 10.1007/s40864-019-00124-0
Original Research Papers

Numerical Prediction and Corresponding Circular Economy Approaches for Resource Optimisation and Recovery of Underground Structures

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Abstract

The transition from a linear economy to a circular economy is a significant component of economic, environmental and social sustainability. Underground metro infrastructures such as tunnels can play a vital role in a circular economy, resulting in greater sustainability and less contribution to climate change. This paper presents numerical models of small-scale brick-lined railway tunnels to identify the critical locations, and then proposes corresponding circular approaches and solutions for the design, maintenance, life extension and end-of-service-life (EoSL) stages of underground infrastructures. The proposed numerical model is firstly verified with respect to the relevant experimental model based on tests under various loading conditions. The results demonstrate that detailed failure processes can be realistically captured by the numerical model, while the macroscopic behaviour compares well with experimental observations. Numerical modelling and subsequent prediction stand out as a practical approach and a powerful performance-based tool for analysing the reuse/recycling potential of metro tunnels and then carrying out easy repair and design for adaptability, disassembly and recoverability of underground infrastructures for a circular economy.

Keywords

Resource optimisation / Waste recovery / Underground metro infrastructures / Numerical modelling / Circular economy

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Han-Mei Chen, Rongxin Zhou, Cristian Ulianov. Numerical Prediction and Corresponding Circular Economy Approaches for Resource Optimisation and Recovery of Underground Structures. Urban Rail Transit, 2020, 6(1): 71-83 DOI:10.1007/s40864-019-00124-0

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