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In recent decades, reinforced-concrete bridges have experienced premature deterioration and other problems during service due to severe environmental effects such as fire and corrosion. Previous studies have shown that the use of ultra-high-performance concrete (UHPC) can improve the durability of bridge structures. In this study, four-point bending tests were conducted on twelve UHPC-NC laminated beams with different UHPC-layer heights and at different temperatures in order to evaluate their flexural performance under fire conditions. The test variables were the UHPC heights (20 mm, 50 mm, 80 mm) and temperatures (20 °C, 200 °C, 400 °C, 600 °C), and the effects on the flexural load capacity of UHPC-NC laminated beams under the influence of these factors were investigated. The test results show that the increase in temperature causes the concrete color to change from grayish blue to white and leads to a significant decrease in the flexural load capacity of the stacked beams. The height of the UHPC layer has an important effect on the stiffness of the stacked beams and delays the formation of local cracks, thus improving the durability of the stacked beams.

Low visibility and hot smoke environment under fire conditions can largely hamper the related fire rescue processes. Ultrasound obstacle avoidance technology is then useful for guidance. However, the biggest challenge of adopting ultrasound technology comes from accurate distance measurements under the disturbances of high temperature and soot particle concentration. It is critical to measure the propagation speed under the complicated fire conditions. Therefore, in this study, a baffle calibration method was proposed to improve the accuracy of distance measurement of an obstacle. The method is based on two ultrasound measurement systems, while one is used to calibrate the propagation speed of ultrasound based on the fixed distanced baffle and the other is for the dynamic measurement of obstacle distance based on the calibrated speed. The viability of this method on the guided vehicle was confirmed based on the experiments. From its comparison to those existing methods, such as constant speed and temperature compensation methods, it was known from that the proposed baffle calibration method provides the best prediction. It was obtained that the maximum errors based on the baffle calibration method are 2.75% and 2.62% under the two representative fire scenarios, respectively, which are much lower than those of constant speed (7.81% and 8.4%) and temperature compensation methods (10.4% and 5.12%).