• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.3
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• pp.561-573
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• 2018

In order to design the ventilation in the road tunnel, it is necessary to know the ratio of average annual daily traffic by vehicle type. In general, the road tunnels are onedirectional tunnel, so the traffic of each vehicle type does not change along the tunnel. On the other hand, in the case of network road tunnels, since the connections in the tunnels are complex, the traffic of vehicle-type varies depending on the network composition of tunnels. In the studying the easy method for calculating the ratio of vehicle type for the network road tunnel are proposed with using incidence matrix.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.9
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• pp.838-844
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• 2004

In a long road tunnel, a tunnel ventilation system may be used in order to reduce the pollution below the required level. To develop control algorithms for a tunnel ventilation system, a dynamic simulation program may be used to predict the pollution level in a tunnel. Research was carried out to develop better pollution models for a tunnel ventilation control system. A neural network structure was adopted and compared by using actual poilution data. Simulation results showed that the dynamic model developed by a neural network may be effective for the development of tunnel ventilation control algorithms.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.157-162
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• 2004

Recently, Life Cycle Cost (LCC) for civil infrastructures, such as pavements, bridges, and dams, has been emphasized. However there are few cost models for road tunnel especially for maintenance phase. The road network is composed of highways, bridges, and road tunnels. Thus it is as important as for road tunnels to keep safe for traffic. The maintenance strategies for road tunnels can be achieved based on the minimization of LCC in maintenance phase. For this purpose, in this paper, cost model and cost classification for road tunnel in maintenance phase are suggested.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.2
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• pp.107-116
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• 2012

The experiment was performed to analyze the intersectional ventilation efficiency by intersection structure and Jet Fan in network-form road tunnel. For this, the size of real road tunnel was reduced by 1/45. To apply traffic inertia force when driving, blower fan was used to form an airflow in model tunnel and the intersectional efficiency was also investigated by measuring the speed at local point of the tunnel. To improve the reduction of ventilation caused by the structure character, Jet Fan was installed to optimize ventilation efficiency in tunnel.

• Tunnel and Underground Space
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• v.27 no.3
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• pp.132-145
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• 2017

Shock loss was not applied for the tunnel ventilation of road tunnel in the past. However, pressure losses due to the shock loss can be significant in network double-deck road tunnel in which combining and separating road structures exist. For the optimum ventilation design of network double-deck road tunnel, this study conducted 3D CFD numerical analysis for the shock loss at the combining and separating flows. The CFD model was made with the real-scale model that was the standard section of double-deck road tunnel. The shock loss coefficient of various combining and separating angles and road width was obtained and compared to the existing design values. As a result of the comparison, the shock loss coefficient of the $30^{\circ}$ separating flow model was higher and that of the two-lane combining flow model was lower. Since the combining and separating angles and road width can be important for the design of shock loss estimation, it is considered that this study can provide the accurate design factors for the calculation of ventilation system capacity. In addition, this study conducted 3D CFD analysis in order to calculate the shock loss coefficient of both combining and separating flows at flared intersection, and the result was compared with the design values of ASHRAE. The model that was not widened at the intersection showed three times higher at the most, and the other model that was widened at the intersection resulted two times higher shock loss coefficients.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.252-254
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• 2003

In this study, it was purposed to develop the new method for the prediction of pollutant concentration in road tunnels. The new method was the use of artificial neural network with the back-propagation algorithm which can model the non-linear system of tunnel environment. This network system was separated into two parts as the visibility and the CO concentration. For this study, data was collected from two highway road tunnels on Yeongdong Expressway. The tunnels have two lanes with one-way direction and adopt the longitudinal ventilation system. The actually measured data from the tunnels was used to develop the neural network system for the prediction of pollutant concentration. The output results from the newly developed neural network system were analysed and compared with the calculated values by PIARC method. Results showed that the prediction accuracy by the neural network system was approximately five times better than the one by PIARC method. ill addition, the system predicted much more accurately at the situation where the drivers have to be stayed for a while in tunnels caused by the low velocity of vehicles.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.147-155
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• 2005

For a long road tunnel, a tunnel ventilation system may be used in order to reduce the pollution level below the required level. To control the tunnel pollution level, a closed loop control algorithm may be used. The cascade control algorithm, which composed of a jet fan control algorithm and an air velocity setpoint algorithm, was developed to regulate the CO level in a tunnel. The verification of control algorithms was carried out by dynamic models developed from real tunnel data sets. The simulation results showed that control algorithms developed for this study were effective to control the tunnel ventilation system.

• Tunnel and Underground Space
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• v.28 no.1
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• pp.111-124
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• 2018

The purpose of this study is to analyze ventilation design factor for network-type double-deck road tunnel that have been developed actively around the world. A numerical analysis was carried out through computational fluid dynamics (CFD) to derive shock loss coefficient that occurs due to the change in cross sectional area at both merging section and diverging section. The model used for the numerical analysis is real-scale model and the reliability of the result is secured by comparing with the coefficient of the previous studies. As a result of this study, shock loss coefficient was calculated depending on the change in cross-sectional area ratio and was higher than the result of previous studies in case of both merging section and diverging section. It is considered that the characteristics of the geometrical structure of network-type double-deck road tunnel have a great impact on shock loss coefficient. Therefore, the result of this study is expected to be helpful for more accurate ventilation design of network-type double-deck road tunnel.

• Structural Monitoring and Maintenance
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• v.5 no.3
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• pp.363-377
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• 2018

The proper functioning of critical points on transport infrastructure is decisive for the entire network. Tunnels and bridges certainly belong to the critical points of the surface transport network, both road and rail. Risk management should be a holistic and dynamic process throughout the entire life cycle. However, the level of risk is usually determined only during the design stage mainly due to the fact that it is a time-consuming and costly process. This paper presents a simplified quantitative risk analysis method that can be used any time during the decades of a tunnel's lifetime and can estimate the changing risks on a continuous basis and thus uncover hidden safety threats. The presented method is a decision support system for tunnel managers designed to preserve or even increase tunnel safety. The CAPITA method is a deterministic scenario-oriented risk analysis approach for assessment of mortality risks in road tunnels in case of the most dangerous situation - a fire. It is implemented through an advanced risk analysis CAPITA SW. Both, the method as well as the resulting software were developed by the authors' team. Unlike existing analyzes requiring specialized microsimulation tools for traffic flow, smoke propagation and evacuation modeling, the CAPITA contains comprehensive database with the results of thousands of simulations performed in advance for various combinations of variables. This approach significantly simplifies the overall complexity and thus enhances the usability of the resulting risk analysis. Additionally, it provides the decision makers with holistic view by providing not only on the expected risk but also on the risk's sensitivity to different variables. This allows the tunnel manager or another decision maker to estimate the primary change of risk whenever traffic conditions in the tunnel change and to see the dependencies to particular input variables.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.103-110
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• 2012

PURPOSES : In Korea, over 70 percent of the land consists of mountainous and rolling area. Thus, tunnels continue its upward trend as road network are extended. In these circumstances, the importance of tunnel has been increased nowadays and then its safety investigation and research should be performed. This study is focus on confirming and improving the safety of tunnel. On tunnel hood, sunglare effect can irritate driver's behavior instantly and this can result in incident. METHODS : The study of this phenomenon is rarely conducted in domestic and foreign papers, so there is no proper measure for this. This study analyzes the driving environment of the effect of sunglare effect on tunnel hood. RESULTS : Traffic accidents stem from complex set of factors. This study build the Traffic Accident Prediction Models to find out the effect of sunglare effect on tunnel's hood. The independent variables are traffic volume, geometric design of road, length of tunnel and road side environment. Using these variables, this model estimates accident frequency on tunnel hood by Poisson regression model and Negative binomial regression model. Although Poisson regression model have more proper goodness of fit than Negative binomial regression model, Poisson regression model has overdipersion problem. So the Negative binomial regression model is used in this analysis. CONCLUSIONS : Consequently, the model shows that sunglare effect can play a role in driving safety on tunnel hood. As a result, the information of sunglare effect should be noticed ahead of tunnel hood so this can prevent drivers from being in hazard situation.