The complex geological structure of Taiwan often makes it difficult to control the deformation behavior of tunnel excavations. To simplify analyses, most traditional empirical formulations and modern numerical analyses do not consider the existence of rock bolts. For this reason, this study aimed to investigate the vertical displacements caused in tunnel crowns under various geological conditions using a three-dimensional finite element analysis with tunnels of different cross sections as an example. The analysis was performed using two rock material models: the Mohr–Coulomb and Hoek–Brown models. The results indicated that there was an insignificant difference between the two models in terms of the magnitudes of displacement and the distribution profiles obtained. When a tunnel was being excavated, the weaker the site was geologically and the larger the cross section, the larger the vertical crown displacement. In addition, the presence of rock bolts had a significant influence on the displacement in areas where the geology was weak and the cross section was large. The numerical analysis results of the Mohr–Coulomb and Hoek–Brown models were compared with the values calculated using the formulas suggested by Unlu and Gercek. At the excavation face, the displacement ratio derived from the prediction formula of Unlu and Gercek was smaller than the numerical analysis result, and the difference between the two became larger when the rock mass quality was worse.

Several information technology approaches have been applied to life cycle analyses to improve decision-making performance and prolong infrastructure life spans. Belief function theory (BFT), also known as the Dempster-Shafer theory of evidence, is a method of representing uncertain, incomplete, and imprecise evidence of a system’s knowledge base. BFT has rarely been applied to pavement management until now. For pavement management decision-making, pavement engineers must formulate relationships between various objectives, incorporate subjective judgment, and pool evidence from various sources. These issues are not adequately addressed in the existing analytical tools used in pavement management. This paper conducts a study of pavement maintenance and rehabilitation (M&R) activities using BFT. Questionnaires are carried out to establish an evidential tree, which is used to quantify the level of uncertainty associated with M&R activities. With respect to the given evidence in the case study, the belief interval of (0.222, 0.778) with uncertainty for the M&R activities can be obtained by using Dempster’s rule of combination. BFT provides a more rigorous but straightforward approach to assisting pavement engineers with M&R decision-making.