University of Cambridge > > Engineering Department Geotechnical Research Seminars > Application of the new observational method framework on deep excavation retaining wall design in London Clay

Application of the new observational method framework on deep excavation retaining wall design in London Clay

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If you have a question about this talk, please contact Magdalena Charytoniuk.

Demands for underground infrastructure have been growing worldwide in response to global urbanization and the consequent growth of city developments. To achieve the balance between the safe excavation and the economy embedded retaining wall design for deep excavation in the over-consolidated soil like London Clay, the new observational method framework with four design approaches is proposed and applied to achieve the goal.

Based on the original observational method, the new observational method framework is established. With the proposed new observational method framework, discussions about the way to derive and calibrate the design parameters, undertaken the numerical back-analysis, and review & correct the field monitoring data for the back-analysis, the application of new observational method framework in deep excavation design in London Clay is enhanced. The reassessment of one of the Crossrail excavation case using the Ab initio Optimistic Approach A shows that the savings in construction material cost can be maximized and the potential savings in construction time is possible if things take place as expected the most probable condition.

The research findings include the lessons learned from the instrumentation and monitoring data review, the most probable soil design parameters for the London Clay subdivisions in relation to the type of FEM and soil constitutive models, and the demonstration of the maximized savings by the Ab-initio Optimistic Approach A design. The research findings may apply to other types of soils and other ground engineering design.

This talk is part of the Engineering Department Geotechnical Research Seminars series.

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