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Tunnelling-induced ground surface settlement prediction still adopts empirical and analytical approaches; thus a step further in using a practical numerical analysis is now a challenging task. Because the deformation during tunnelling is a three-dimensional problem, several features were incorporated in two-dimensional analyses to capture aspects that are important in governing behaviour in the missing third dimension. This paper aims to present simplified methods for ground settlement computation of tunnelling works using the PLAXIS finite-element programme. Three simplified methods – contraction ratio, stress reduction and modified grout pressure – were considered in this study. Practical application requires correlations among these three methods. Such correlations among the three methods are proposed in this study and can be used in geotechnical practice. The results were based on a series of finite-element analyses of the Blue Line Bangkok Mass Rapid Transit tunnels. The geotechnical parameters were selected based on soil investigation reports carried out for construction purposes. The soil constitutive model adopted herein was the hardening soil model on soft and stiff clays. All the finite-element simulations were compared with the measured field deformations. Therefore, the analysis results can be considered as a Class-C prediction (back-analysis).

This paper proposes a probabilistic vehicle reidentification algorithm for estimating travel time using the image data provided by traffic surveillance cameras. Each vehicle is characterized by its color, type, and length, which are extracted from the video record using image processing techniques. A data fusion rule is introduced to combine these three features to generate a probabilistic measure for a reidentification (matching) decision. The vehicle-matching problem is then reformulated as a combinatorial problem and solved by a minimum-weight bipartite matching method. To reduce the computational time, the algorithm uses the potential availability of historic travel time data to define a potential time window for vehicle reidentification. This probabilistic approach does not require vehicle sequential information and hence allows vehicle reidentification across multiple lanes. The algorithm is tested on a 5-km section of the expressway system in Bangkok, Thailand. The travel time estimation result is also compared with the directly observed data.

Time domain reflectometry (TDR) is a nondestructive electromagnetic technique used to measure the volumetric water content of soil. A key component of the method is the calibration equation relating the apparent dielectric constant (Ka) to the volumetric water content (ϑ). In this study, tests were conducted to evaluate dimensional requirements for a TDR calibration cell. The results show that a PVC cylinder having the same dimensions as a standard compaction mold (diameter = 102 mm, height = 116 mm) is a suitable calibration cell for two-rod TDR probes having diameter = 4 mm, center-to-center spacing = 30 mm, and length = 80 mm. The cell can also be used for three-rod probes having the same dimensions as the two-rod probe, and a center-to-center rod spacing of 20 mm. Calibrations made with this small cell are essentially identical to calibrations made in a much larger cell where boundaries are unlikely to be important.

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