ALBERT

Description: This paper presents an improved design methodology for shield tunnels. Here, a new framework for three-dimensional analysis of shield tunnel “performance” (defined herein as the structural safety and serviceability of each tunnel ring) is developed, which considers the effect of the longitudinal variation of input parameters on the tunnel performance. Within this framework, random fields are used to simulate the longitudinal variation of input parameters, and the three-dimensional problem of shield tunnel performance is solved through a two-stage solution involving a one-dimensional model (for tunnel longitudinal behavior) and a two-dimensional model (for performance of segment rings). Furthermore, the robust design concept is integrated into the design of shield tunnels to guard against the longitudinal variation of tunnel performance caused by the longitudinal variation of input parameters. In the context of robust design, a new measure is developed for determining the robustness of the tunnel performance against the longitudinal variation of noise factors. A multi-objective optimization is then performed to optimize the design with respect to the design robustness and the cost efficiency, while satisfying the safety and serviceability requirements. Through an illustrative example, the effectiveness and significance of the improved shield tunnel design methodology is demonstrated.

Description: This paper presents a gradient-based robustness measure for robust geotechnical design (RGD) that considers safety, design robustness, and cost efficiency simultaneously. In the context of robust design, a design is deemed robust if the system response of concern is insensitive, to a certain degree, to the variation of noise factors (i.e., uncertain geotechnical parameters, loading parameters, construction variation, and model biases or errors). The key to a robust design is a quantifiable robustness measure with which the robust design optimization can be effectively and efficiently implemented. Based on the developed gradient-based robustness measure, a robust design optimization framework is proposed. In this framework, the design (safety) constraint is analyzed using advanced first-order second-moment (AFOSM) method, considering the variation in the noise factors. The design robustness, in terms of sensitivity index (SI), is evaluated using the normalized gradient of the system response to the noise factors, which can be efficiently computed from the by-product of AFOSM analysis. Within the proposed framework, robust design optimization is performed with two objectives, design robustness and cost efficiency, while the design (safety) constraint is satisfied by meeting a target reliability index. Generally, cost efficiency and design robustness are conflicting objectives and the robust design optimization yields a Pareto front, which reveals a tradeoff between the two objectives. Through an illustrative example of a shallow foundation design, the effectiveness and significance of this new robust design approach is demonstrated.