Evaluating risks using simulated annealing and Building Information Modeling

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review

8 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)5925-5935
Journal / PublicationApplied Mathematical Modelling
Volume39
Issue number19
Early online date13 May 2015
Publication statusPublished - 1 Oct 2015
Externally publishedYes

Abstract

Tunnel construction involves significant uncertainties in ground conditions, often causing cost overruns and schedule delays. To mitigate these risks, general contractors (GCs) should predict varying ground conditions based on information regarding ground conditions acquired before construction (i.e., borehole and geophysical investigations). Subsequently, GCs should also evaluate excavation costs and durations of their schedule based on predicted ground conditions; however, this is challenging because in current practice, GCs lack a method to incorporate these required processes into their existing evaluation process in a structured manner. To overcome this limitation, we developed a methodology to predict multiple sets of ground conditions by using simulated annealing (SA), which is a geo-statistical method, and then evaluate excavation costs and durations of a tunneling schedule via Building Information Modeling (BIM). For integration of SA and BIM, we extended existing BIM to accept multiple sets of ground conditions. To validate the effectiveness of our methodology, we applied it to a tunnel in Korea. Based on the application, we highlight that our methodology enables GCs to formally evaluate risks in excavation costs and durations of tunnel construction with complete information about ground conditions acquired before construction.

Research Area(s)

  • Building information modeling, Risk analysis, Simulated annealing, Tunnel construction

Citation Format(s)

Evaluating risks using simulated annealing and Building Information Modeling. / Ryu, Dong-Woo; Kim, Jung In; Suh, Sunduck; Suh, Wonho.

In: Applied Mathematical Modelling, Vol. 39, No. 19, 01.10.2015, p. 5925-5935.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalNot applicablepeer-review