• Journal of Advanced Marine Engineering and Technology
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• v.36 no.3
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• pp.368-377
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• 2012

Most tunnel simulations have been focused on the thermal field and the critical velocity for suppression of hot back-layering flow in case of fire and on the characteristics of a tunnel fire in terms of the flame propagation and the toxic gas generation. In this paper, a comparative study of the flow characteristics of polluted air with no heat source in a tunnel model opened and closed at both end sides is implemented into a recognized CFD simulation code. The model is used to investigate the flow characteristics depending on the three different Reynolds numbers of 640, 1270 and 2120, which have been chosen by the flow velocities of 0.3, 0.6 and 1.0 m/s through the inlet. The results of this study have shown that the CFD predictive and experimental approaches are available in qualitatively studying the correlation of flow behaviors for a better tunnel design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.223-230
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• 2008

This paper deals with the measurements of wireless image signal in subway tunnels at 2.45GHz. Measurements have been conducted in 3 subway stations with different types; a straight tunnel and two curved tunnels. As a analysis result for the measured data, we found that the signal level inside straight tunnel by the strong multipath waves fluctuate deeply compared to the curved tunnel. The path loss exponent for the Shin-hung station with the straight tunnel is 2.5, those for the Pan-am and Dae-dong station with curved tunnels are 1.6 and 1.9, respectively. The fade depth and width at 50% point became relatively serious at Shin-hung station, the level crossing rate inside the Pan-am station is larger than the other stations. Therefore, it can be concluded that the fading phenomena affect to the signal performance generate seriously at straight tunnel compared to the curved tunnel.

• Clinical Pain
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• v.18 no.2
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• pp.70-75
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• 2019

Objective: The purpose of this study is to evaluate the usefulness of infrared thermography in patients with carpal tunnel syndrome by comparing with electrodiagnostic and ultrasonographic findings. Method: From January 2014 to October 2017, electrodiagnosis, ultrasound, and digital infrared thermal image (DITI) of unilateral carpal tunnel syndrome diagnosed in a single hospital were retrospectively analyzed. The subjects with bilateral symptoms of carpal tunnel syndrome, peripheral vascular disease, diabetes, thyroid disease, fibromyalgia, rheumatic disease, systemic infection, inflammation, malignant tumor, and other musculoskeletal disorders such as finger osteoarthritis, peripheral neuropathy, cervical radiculopathy, and the previous history of surgery were excluded. Results: Of 53 patients diagnosed with carpal tunnel syndrome, 11 were male and 42 were female. The visual analogue scale was 4.9 ± 1.9, and the duration of symptom was 11.8 ± 12.5 months. There was no statistically significant difference in the body surface temperature between the unaffected and affected sides. The severity of symptoms, electrodiagnostic findings, and cross-sectional area of the median nerve significantly correlates to each other. The temperature difference between the second fingers of the affected and unaffected sides showed a weak correlation with the amplitude of sensory nerve action potential and onset latency of compound muscle action potential, when there was no significant correlation with the other parameters. Conclusion: The difference in temperature on the surface of the body, which can be confirmed by DITI, is little diagnostic value when DITI is performed in unilateral carpal tunnel syndrome patients, especially when compared with ultrasonography.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.83-90
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• 2015

Almost of current Automatic Incident Detection(AID) algorithms involve the vulnerability that detects the traffic accident in open road or in tunnel as the traffic jam not as the traffic accident. This paper proposes the improved accident detection algorithm to enhance the detection probability based on accident detection algorithms applied in open roads. The improved accident detection algorithm provides the preliminary judgment of potential accident by detecting the stopped object by Gaussian Mixture Model. Afterwards, it measures the detection area is divided into blocks so that the occupancy rate can be determined for each block. All experimental results of applying the new algorithm on a real incident was detected image without error.

• Geophysics and Geophysical Exploration
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• v.6 no.3
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• pp.138-142
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• 2003

Crosswell seismic data were acquired in three sections crossing a tunnel of 3 different types; one was empty, another was ailed by sand, and the other was filled by rock debris. Both the P- and S-wave first arrivals were picked and the traveltime tomography was conducted to generate the P- and S- wave velocity tomograms on the all three sections. Among six tomograms, only one tomogram shows a low velocity zone that can be interpreted as a tunnel image. The tomogram is the P wave velocity image of a section that crosses an empty tunnel. The result of numerical analysis for the spatial resolution of the traveltime tomography was consistent to this finding.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1796-1802
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• 2011

In this paper, the radio propagation path loss prediction simulator in tunnel was developed. It used a image theory method for analysing precise radio propagation path. And it can predict radio propagation path loss in straight and curved tunnels. The simulator can plot realtime radio propagation paths using various parameters which was input by user. And it can simulate from changing transmitter and receiver positions. The predicted path loss of simulator was compared with the measurements in Chunhyun tunnel and confirmed the validity.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.549-558
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• 2021

In order to keep infrastructures such as tunnels and underground facilities safe, cracks of concrete lining in tunnel should be detected by regular inspections. Since regular inspections are accomplished through manual efforts using maintenance lift vehicles, it brings about traffic jam, exposes works to dangerous circumstances, and deteriorates consistency of crack inspection data. This study aims to provide methodology to automatically extract cracks from tunnel concrete lining images generated by the existing tunnel image acquisition system. Specifically, we train a deep learning based semantic segmentation model with open dataset, and evaluate its performance with the dataset from the existing tunnel image acquisition system. In particular, we compare the model performance in case of using all of a public dataset, subset of the public dataset which are related to tunnel surfaces, and the tunnel-related subset with negative examples. As a result, the model trained using the tunnel-related subset with negative examples reached the best performance. In the future, we expect that this research can be used for planning efficient model training strategy for crack detection.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.2
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• pp.119-131
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• 2021

In general, the stress is concentrated on the pillar of very near parallel tunnel (VNPT), and the pillar has been reinforced by using steel-wires to maintain the stability of the tunnel. However, since the strength of the pillar decreases in the soil layer, the reinforcing pillar with the steel-wires is insufficient for tunnel stability. In this study, the laboratory tunnel experiment was conducted to examine the reinforcement effect for a new method, of which the pillar of VNPT is strengthened by using steel-pipes. As a result, against overburden stress, the bearing capacity of the steel-pipe reinforcement was 22% greater than that of the steel-wire reinforcement. In using the Particle Image Velocimetry method, the analysis shows that the steel-pipe reinforcement forms a more favorable condition of which uniformly the overburden load acts on the VNPT and the pillar than the steel-wire reinforcement. Based on the results, the steel-pipe reinforcement is expected to bring a more positive effect on tunnel stability than the steel-wire reinforcement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.7A
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• pp.676-682
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• 2002

In this paper, an effective stereo image compression and reconstruction technique using a new adaptively compensated-disparity prediction scheme is proposed. That is, by adaptively predicting the mutual correlation between the stereo image using the proposed method, the bandwidth of the stereo input image can be compressed to the level of the conventional 2D image and the predicted image also can be effectively reconstructed using this transmitted reference image and disparity data in the receiver. Especially, in the proposed method, once the feature values are extracted from the input stereo image, then the matching window size for the predicted image reconstruction is adaptively selected in accordance with the magnitude of this feature values. From this adaptive disparity estimation method, reduction of the mismatching probability of the disparity vectors is expected and as a result, the image quality in the reconstructed image can be improved. In addition, from some experiments using the CCETT's stereo images of 'Fichier', 'Manege' and 'Tunnel', it is shown that the proposed method improves the PSNR of the reconstructed image to about 9.08 dB on average by comparing with that of the conventional methods. And also, it is found that there is almost no difference between the original image and the predicted image reconstructed through the proposed method by comparison to that of the conventional methods.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.471-476
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• 2003

The presence of voids under pavements or behind tunnel linings results in their deterioration. To detect these voids effectively by non-destructive tests, a method using radar was proposed. In this research, not only the detection of shape of voids, but also the location of reinforcing bars by radar image analysis is investigated. The experiments and image processing were conducted to detect voids and to locate reinforcing bars in or under concrete pavements (or tunnel linings) with reinforcing bars. From the results, the fundamental algorithm for tracing the reinforcing bars and voids, improving the horizontal resolution of the object image and detecting shape of objects, was verified.