Probabilistic 3D alignment optimization of underground transport infrastructure integrating GIS-based subsurface characterization. (February 2018)

• Record Type: Journal Article
• Authors: Costa, Ana Laura; Sousa, Rita L.; Einstein, Herbert H.
• Is Part Of: Tunnelling and underground space technology. Volume 72(2018)
• Page Start: 233
• Page End: 241
• Publication Date: 2018-02
• Subjects: Optimization -- Unexpected Events -- 3D Geological models; Tunneling -- Periodicals; Underground construction -- Periodicals; Tunnels -- Periodicals; Underground areas -- Periodicals; 624.193
• DOI: 10.1016/j.tust.2017.11.027
• Languages: English
• ISSNs: 0886-7798

Abstract

Highlights: Development of an integrated probabilistic alignment optimization tool for underground tunnel planning and construction. Consideration of uncertainties associated with geology and construction processes in the optimization process. Demonstration through an application to the optimization of a subway line at Masdar City, Abu Dhabi. Abstract: Underground Transport construction is affected by various sources of uncertainty. These uncertainties must be identified, quantified and inherent risks assessed and managed. A crucial step in underground risk management is the planning and design phase. This paper presents an innovative probabilistic alignment optimization tool for underground tunnel construction, which considers uncertainties associated with geology and construction processes. It consists of an integrated approach of two existing tools; an interactive support system, the Decision Aids for Tunneling (DAT), and an optimization tool for linear infrastructure (Opt), which uses GIS-derived maps as input. The capabilities of the approach are demonstrated through an application to the optimization of a subway line at Masdar City, Abu Dhabi in the United Arab Emirates.