Drainage Services in Seoul, South Korea

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Drainage inlets at the Namsan #3 traffic tunnel in Seoul, South Korea were found to be clogged with calcium carbonate scale deposits. Officials were concerned the clogged drains would further stress the already deteriorating traffic tunnel and wanted to see if there were any practical and economical solutions in removing or preventing scale deposits. A tunnel drainage simulator was constructed to determine the feasibility of using magnets to inhibit scale precipitation and deposition. Test results from the simulation show 6.0 and 4.4 g of deposited calcium carbonate in pipes inclined at 2° and 5° respectively, while magnetically treated water resulted in 10.8 and 4.3 g of deposited calcium carbonate in pipes inclined at 2° and 5° respectively. Calcium carbonate scale samples from the tunnel drainage test underwent x-ray diffraction analysis and showed the magnetically treated water to precipitate more aragonite. The solubility product and crystalline structures of calcite and aragonite are able to help explain tunnel drainage test results and suggest water flow velocity to be a potentially important factor in calcium scale inhibition if magnets are used.

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The development of a smart expressway ensuring all-weather safe access represents the future trajectory of transportation infrastructure. A key task in this advancement is the precise prediction of water film depth (WFD) on road surfaces. Conventional WFD prediction models often assume constant grade and cross slope, an oversimplification that may affect predictive accuracy. In this study, typical highway alignments were meticulously modeled in three dimensions (3D) using Building Details Modeling (BIM) technology, and WFD simulations were conducted using a coupled discrete phase model and Eulerian wall film model (DE-WFD model). Simulation results revealed that the DE-WFD model consistently predicts higher WFD compared to the RRL and PAVDRN models. In contrast, its predictions are approximately 0.12 mm (40%) lower than those of the Gallaway model when rainfall intensity is below 7.8 mm/h. At higher rainfall intensities, DE-WFD predictions closely align with the Gallaway model. Field tests conducted with a feeler gauge of 0.01 mm resolution confirmed the accuracy of these predictions, showing a maximum deviation of just 7% between predicted and measured values. Additionally, the study assessed the sensitivity of the DE-WFD model to variations in grade and cross slope along the road length. Results indicated that on road surfaces employing dispersed drainage, WFD is approximately 6% higher at sag vertical curves and lower at crest vertical curves compared to constant slope segments. Moreover, WFD increases by over 35% at superelevation transitions. To quantify the impact of rainfall on road safety, a critical WFD parameter was developed. This parameter defines the maximum WFD under specific rainfall conditions that reduces the pavement-tire tangential friction coefficient to a level corresponding to the standard stopping sight distance. Using the DE-WFD model, simulations of hourly rainfall intensity and duration identified conditions under which WFD reaches this critical value for various roadway geometries. These findings offer valuable references for the precision management of highway operational safety. This suggests that traffic safety authorities should implement warning and intervention measures when critical rainfall conditions are exceeded to ensure driving safety.

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