Optimal adaptive decision rules in geotechnical construction considering uncertainty

Abstract

To design a geotechnical engineering structure optimally, an iterative decision-making process is required due to the prevailing uncertainty of the ground conditions. At present, these decisions are taken based on simple deterministic rules and models. This paper proposes a risk-based decision-theoretic framework to the optimal planning for geotechnical construction. This framework combines geotechnical probabilistic models, cost analysis using Monte Carlo simulation and the observational method. The framework is illustrated on the design of the surcharge for an embankment on soft soil, whereby the optimal preloading sequence of added surcharge is adapted to the observed settlement. The approach balances the cost of surcharge material against financial penalties related to project delays and insufficient overconsolidation, which causes damage due to residual settlement. The result is a preloading strategy that optimally accounts for information obtained from settlement measurements under uncertain ground conditions. The findings highlight the potential of using risk-based decision planning in geotechnical engineering, in particular when combined with the observational method. For the investigated case study, a reduction in the expected cost in the order of 25% is observed.