• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.29-39
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• 2017

In this research, thermal design data such as heat transfer coefficient on the wall surface required for ventilation system design which is to prevent the temperature rise in the underground utility tunnel that three sides are adjoined with the ground was investigated in numerical analalysis. The numerical model has been devised including the tunnel lining of the underground utility tunnel in order to take account for the heat transfer in the tunnel walls. The air temperature in the tunnel, wall temperature, and the heating value through the wall based on heating value(117~468 kW/km) of the power cable installed in the tunnel and the wind speed in the tunnel(0.5~4.0 m/s) were calculated by CFD simulation. In addition, the wall heat transfer coefficient was computed from the results analysis, and the limit distance used to keep the air temperature in the tunnel stable was examined through the research. The convective heat transfer coefficient at the wall surface shows unstable pattern at the inlet area. However, it converges to a constant value beyond approximately 100 meter. The tunnel wall heat transfer coefficient is $3.1{\sim}9.16W/m^2^{\circ}C$ depending on the wind speed, and following is the dimensionless number:$Nu=1.081Re^{0.4927}({\mu}/{\mu}_w)^{0.14}$. This study has suggested the prediction model of temperature in the tunnel based on the thermal resistance analysis technique, and it is appraised that deviation can be used in the range of 3% estimation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.594-600
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• 2022

When a large liquefied natural gas (LNG) carrier is anchored at a coastal terminal, calculations on mooring forces of mooring cables induced by environmental loads such as strong winds and currents are needed to secure mooring safety. The advantages and disadvantages of several existing mooring force calculation methods are compared and analyzed with their application conditions. Resultingly, mooring equipment guidelines of the Oil Companies International Marine Forum (OCIMF) are chosen as the computational method for this study. In this paper, the mooring forces of a large LNG carrier with spectrum was calculated using the OCIMF mooring equipment guidelines. The calculation shows similar maximum forces resulted from the calculation using experiment data of a wind tunnel test. To verify the results, OPTIMOOR, a dedicated mooring force calculation software, is used to calculate the same mooring conditions. The results of both calculations show that the computational method recommended by OCIMF is safe and reliable. OPTIMOOR calculates more detailed tensile force of each mooring cable. Thus, the calculation on mooring forces of mooring cables of a large LNG carrier using OCIMF mooring equipment guidelines is verified as an applicable and safe method.

• Smart Structures and Systems
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• v.32 no.4
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• pp.267-279
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• 2023

Data modelling and interpretation for structural health monitoring (SHM) field data are critical for evaluating structural performance and quantifying the vulnerability of infrastructure systems. In order to improve the data modelling accuracy, and extend the application range from data regression analysis to out-of-sample forecasting analysis, an improved most likely heteroscedastic Gaussian process (iMLHGP) methodology is proposed in this study by the incorporation of the outof-sample forecasting algorithm. The proposed iMLHGP method overcomes this limitation of constant variance of Gaussian process (GP), and can be used for estimating non-stationary typhoon-induced response statistics with high volatility. The first attempt at performing data regression and forecasting analysis on structural responses using the proposed iMLHGP method has been presented by applying it to real-world filed SHM data from an instrumented cable-stay bridge during typhoon events. Uncertainty quantification and correlation analysis were also carried out to investigate the influence of typhoons on bridge strain data. Results show that the iMLHGP method has high accuracy in both regression and out-of-sample forecasting. The iMLHGP framework takes both data heteroscedasticity and accurate analytical processing of noise variance (replace with a point estimation on the most likely value) into account to avoid the intensive computational effort. According to uncertainty quantification and correlation analysis results, the uncertainties of strain measurements are affected by both traffic and wind speed. The overall change of bridge strain is affected by temperature, and the local fluctuation is greatly affected by wind speed in typhoon conditions.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.5
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• pp.23-33
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• 2008

Extra dosed bridge among the Cabled-stayed bridges have been increasingly built in korea in recently. But such bridges were often damaged by fire due to car collison. In this study Extra dosed bridges among the cabled-supported bridges are selected to analysis model frequently to be designed and/or constructed in recent and furture in this study. COSMOS FloWorks 2007 software are used for Heat Transfer Analysis and Thermal Stress Analysis. The safety of wire, HDPE pipe and stainless steel pipe are investigated. In the case of the constant of the temperature of the heat source, the significant three variables for the analysis are selected for study : (1) the distance between the fire-proof bulk head and the heat source, (2) wind velocity, (3) the height of the end of Stainless steel pipe.

• Smart Structures and Systems
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• v.31 no.1
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• pp.57-68
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• 2023

Bridge hangers, such as those in suspension and cable-stayed bridges, suffer from cumulative fatigue damage caused by dynamic loads (e.g., cyclic traffic and wind loads) in their service condition. Thus, the identification of damage to hangers is important in preserving the service life of the bridge structure. This study develops a new method for condition assessment of bridge hangers. The tension force of the bridge and the damages in the element level can be identified using the Bayesian optimization method. To improve the number of observed data, the additional mass method is combined the Bayesian optimization method. Numerical studies are presented to verify the accuracy and efficiency of the proposed method. The influence of different acquisition functions, which include expected improvement (EI), probability-of-improvement (PI), lower confidence bound (LCB), and expected improvement per second (EIPC), on the identification of damage to the bridge hanger is studied. Results show that the errors identified by the EI acquisition function are smaller than those identified by the other acquisition functions. The identification of the damage to the bridge hanger with various types of boundary conditions and different levels of measurement noise are also studied. Results show that both the severity of the damage and the tension force can be identified via the proposed method, thereby verifying the robustness of the proposed method. Compared to the genetic algorithm (GA), particle swarm optimization (PSO), and nonlinear least-square method (NLS), the Bayesian optimization (BO) performs best in identifying the structural damage and tension force.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.315-321
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• 2023

Long-span bridges are flexible structures with low natural frequencies and damping ratios, making them susceptible to vibrational serviceability problems. However, the current design guideline of South Korea assumes a uniform threshold of wind speed or vibrational amplitude to assess the occurrence of harmful vibrations, potentially overlooking the complex vibrational patterns observed in long-span bridges. In this study, we propose a pointwise vortex-induced vibration (VIV) detection method using a deep-learning-based signalsegmentation model. Departing from conventional supervised methods of data acquisition and manual labeling, we synthesize training data by generating sinusoidal waves with an envelope to accurately represent VIV. A Fourier synchrosqueezed transform is leveraged to extract time-frequency features, which serve as input data for training a bidirectional long short-term memory model. The effectiveness of the model trained on synthetic VIV data is demonstrated through a comparison with its counterpart trained on manually labeled real datasets from an actual cable-supported bridge.