Prediction and interpretation of the performance of a deep excavation in Berlin sand

This paper describes the application of a generalized effective stress soil model, MIT‐S1, within a commercial finite element program, for simulating the performance of the support system for the 20m deep excavation of the M1 pit adjacent to the main station “Hauptbahnhof” in Berlin. The M1 pit was...

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Bibliographic Details
Main Authors: Nikolinakou, Maria A., Whittle, Andrew, Schran, Ute
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Format: Article
Language:en_US
Published: American Society of Civil Engineers 2011
Online Access:http://hdl.handle.net/1721.1/67027
https://orcid.org/0000-0001-5358-4140
https://orcid.org/0000-0003-3194-3477
Description
Summary:This paper describes the application of a generalized effective stress soil model, MIT‐S1, within a commercial finite element program, for simulating the performance of the support system for the 20m deep excavation of the M1 pit adjacent to the main station “Hauptbahnhof” in Berlin. The M1 pit was excavated underwater and supported by a perimeter diaphragm wall with a single row of prestressed anchors. Parameters for the soil model were based on an extensive program of laboratory tests on the local Berlin Sands. This calibration process highlights the practical difficulties in both measurements of critical state soil properties and in model parameter selection. The predictions of excavation performance are strongly affected by vertical profiles of two key state parameters, the initial earth pressure ratio, K0, and the in‐situ void ratio, e0. These are estimated from field dynamic penetration test data and geological history. The results show good agreement between computed and measured wall deflections and tie‐back forces for three instrumented sections. Much larger wall deflections were measured at a fourth section and may be due to spatial variability in sand properties that has not been considered in the current analyses. The results of this study highlight the importance of basic state parameter information for successful application of advanced soil models.