Uncertainty and Sensitivity Analysis of Significant Parameters for Superlarge Diameter Shield Excavation

Elton J Chen,Yang-Yang Chen,Han-Bin Luo,Lin-Chun Wei

doi:10.1155/2021/8819393

Abstract

Excavation of a superlarge diameter tunnel by tunnel boring machine (TBM) is different from that of a shield tunnel with normal dimension, in which the control system of the superlarge TBM is very complicated and difficult to operate. Hence, it is very important to focus on the control and management of significant parameters to ensure excavation stability under uncertainty. In this paper, we (i) utilize a BIM-based big data platform (BIM-BDP) to manage the essential construction data of tunnel project in digital format; (ii) adopt the global sensitivity analysis (SA) to recognize significant parameters for shield excavation based on polynomial chaos expansion (PCE)–extended Fourier amplitude sensitivity test (eFAST) model; and (iii) employ the uncertainty analysis (UA) to discover the correlation between significant parameters from the data of the BIM-BDP. This research contributes to (i) the body of knowledge of proposing a more appropriate research methodology that can cope with aleatory and epistemic uncertainty and support uncertainty and sensitivity analysis (UA/SA) processes based on data from BIM-BDP and (ii) the state of practice by providing a data-driven surrogate model to simulate system behaviors of shield excavation with high reliability and to reduce dependency on domain experts. Here, we pay close attention to the most influential parameters that require priority parameter control, which can help administrators optimize the management of shield parameters during tunnel excavation.

Highlights

Tunnel boring machine (TBM) is the main tool for urban tunnel excavation due to its high excavation efficiency, high safety, environmental friendliness, and high cost-effectiveness [1]
For the output deviation angle (s2), the maximum thrust force (x1), synchronous grouting pressure (x2), advancing speed (x4), cutter rotation speed (x6), cutter torque (x8), soil excavation volume (x9), and actual volume excavation (x10) are influential parameters according to the main sensitivity index (MSI), while cutter rotation speed (x6), cutter torque (x8), soil excavation volume (x9), and actual volume excavation (x10) are influential parameters according to the total sensitivity index (TSI). e most important parameter is actual volume excavation (x10) reaching an MSI of up to 0.353 and a TSI of up to 0.388. e important parameter, soil excavation volume (x9), reaches an MSI value of up to 0.299 and a TSI value of up to 0.380. e MSIs and TSIs of other input parameters are much lower than the above two parameters
The Latin hypercube sampling (LHS) method is used to generate inputs based on the distribution, and the output is generated using the polynomial chaos expansion (PCE)-extended Fourier amplitude sensitivity test (eFAST) model

Summary

Introduction

Tunnel boring machine (TBM) is the main tool for urban tunnel excavation due to its high excavation efficiency, high safety, environmental friendliness, and high cost-effectiveness [1]. E uncertainty and sensitivity analysis (UA/SA), which helps researchers better understand the relative importance of each parameter [10, 11], of shield machine construction parameters is an important research direction for parameters control. In the SA methods, the global sensitivity analysis (GSA) can perceive and distinguish the influence magnitude of parameters associated with the excavation stability to help reduce the cognitive uncertainty caused by the limitation of human cognition and uncertain factors, for Advances in Civil Engineering example, incomplete information. E extended Fourier amplitude sensitivity test (eFAST) method is a global and quantitative GSA algorithm that can be applied to complex nonlinear and nonmonotonic models [12,13,14]. GSA provides guidance for identifying parameters whose information should be collected to enhance the system reliability. e extended Fourier amplitude sensitivity test (eFAST) method is a global and quantitative GSA algorithm that can be applied to complex nonlinear and nonmonotonic models [12,13,14]. e key idea of eFAST is that from one simulation run to another, all factors fluctuate around their nominal values [15]. e importance of the factor is determined by analyzing the Fourier decomposition of the model response

Results

Discussion

Conclusion