Probabilistic 3D alignment optimization of underground transport infrastructure integrating GIS-based subsurface characterization

Ana Laura Costa, Rita L. Sousa, Herbert H. Einstein

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

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.

Original languageEnglish
Pages (from-to)233-241
Number of pages9
JournalTunnelling and Underground Space Technology
Volume72
DOIs
StatePublished - Feb 2018

Keywords

  • 3D Geological models
  • Optimization
  • Unexpected Events

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