In this paper, we developed a predictive model of maintenance and repair cost based on the element-level condition state by using information collected through the inspection/diagnosis of individual bridges for use in maintenance strategy analysis. The reliability of the prediction model can be improved through of big data analysis using various factors and additional data.

This study evaluated the applicability of visible-light-driven N- and S-doped titanium dioxide(TiO2) for the control of low-level dimethyl sulfide(DMS) and dimethyl disulfide(DMDS). In addition, a photocatalytic unit(PU)-adsorption hybrid was evaluated in order to examine the removal of DMS and DMDS which exited the PU and a gaseous photocatalytic byproduct(SO2) which was generated during the photocatalytic processes. Fourier-Tranform-Infrared(FTIR) spectrum exhibited different surface characteristics among the three-types of catalysts. For the N- and S-doped TiO2 powders, a shift of the absorbance spectrum towards the visible-light region was observed. The absorption edge for both the N- and S-doped TiO2 was shifted to λ 720 nm. The N-doped TiO2 was superior to the S-doped TiO2 in regards to DMS degradation. Under low input concentration(IC) conditions(0.039 and 0.027 ppm for DMS and DMDS, respectively), the N-doped TiO2 revealed a high DMS removal efficiency(above 95%), but a gradual decreasing removal efficiency under high IC conditions(7.8 and 5.4 ppm for DMS and DMDS, respectively). Although the hybrid system exhibited a superior characteristic to PU alone regarding the removal efficiencies of both DMS and DMDS, this capability decreased during the course of a photocatalytic process under the high IC conditions. The present study identified the generation of sulfate ion on the catalyst surface and sulfur dioxide(maximum concentrations of 0.0019 and 0.0074 ppm for the photocatalytic processes of DMS and DMDS, respectively) in effluent gas of PU. However, this generation of SO2 would be an insignificant addition to indoor air quality levels.