• The Journal of the Acoustical Society of Korea
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• v.37 no.4
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• pp.223-231
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• 2018

Recently, due to various environmental problems, blast tracks in tunnel are replaced with concrete tracks, but they have more adverse effects on noise than blast tracks so that additional noise measures are needed. Among these measures, sound-absorbing blocks start to be used due to its easy and quick installation. However, the performance of sound absorption blocks need to be verified under real environmental and operational conditions. In this paper, interior noise levels in KTX train cruising in Dalseong tunnel are measured before and after the installation of sound-absorbing blocks and the measured data are analyzed and compared. Additionally, noise reduction are estimated by modeling the high speed train, the tunnel and absorption blocks. Measurement devices and methods are used according to ISO 3381 and the equivalent sound pressure levels during the cruising time inside the tunnel are computed. In addition to overall SPLs(Sound Pressure Levels), 1/3-octave-band levels are also analyzed to account for the frequency characteristics of sound absorption and equipment noise in a cabin. In addition, to consider the effects of train cruising speeds and environmental conditions on the measurements, the measured data are corrected by using those measured during the train-passing through the tunnels located before and behind the Dalseong tunnel. Analysis of measured results showed that the maximum noise reduction of 6.8 dB (A) can be achieved for the local region where the sound-absorbing blocks are installed. Finally, through the comparison of predicted 1/3-octave band SPLs for the KTX interior noise with the measurements, the understanding of noise reduction mechanism due to sound-absorbing blocks is enhanced.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.915-936
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• 2017

In this study, current status of Korean hazard mitigation guideline for tunnel operation is summarized. It shows that requirement for CCTV installation has been gradually stricted and needs for tunnel incident detection system in conjunction with the CCTV in tunnels have been highly increased. Despite of this, it is noticed that mathematical algorithm based incident detection system, which are commonly applied in current tunnel operation, show very low detectable rates by less than 50%. The putative major reasons seem to be (1) very weak intensity of illumination (2) dust in tunnel (3) low installation height of CCTV to about 3.5 m, etc. Therefore, an attempt in this study is made to develop an deep-learning based tunnel incident detection system, which is relatively insensitive to very poor visibility conditions. Its theoretical background is given and validating investigation are undertaken focused on the moving vehicles and person out of vehicle in tunnel, which are the official major objects to be detected. Two scenarios are set up: (1) training and prediction in the same tunnel (2) training in a tunnel and prediction in the other tunnel. From the both cases, targeted object detection in prediction mode are achieved to detectable rate to higher than 80% in case of similar time period between training and prediction but it shows a bit low detectable rate to 40% when the prediction times are far from the training time without further training taking place. However, it is believed that the AI based system would be enhanced in its predictability automatically as further training are followed with accumulated CCTV BigData without any revision or calibration of the incident detection system.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.15-22
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• 2002

Transportation project appraisal should be precise in order to increase the social welfare and efficiency, and it has been evaluated by only a single criterion analysis such as benefit/cost analysis. However, this method cannot assess some qualitative items, and cannot get a proper solution for the clash of interests among various groups. Therefore, the multi-criteria analysis, which can control these problems, is needed, and then Saaty has developed one of these methods, AHP(Analytic Hierarchy Process) method. In AHP, the project is evaluated through weighted score of the criteria and the alternatives, which is surveyed by a questionnaire of specialists. It is based on some strict suppositions such as reciprocal comparison, homogeneity, expectation, independence relationship between multi-criteria, but supposing that each criterion has independence relation with others is too difficult in two reasons. First, in real situation, there cannot be perfect independence relationship between standards. Second, individuals, even though they are specialists of that area, do not feel the degree of independence relation as same as others. This paper develops a modified AHP method for solving this dependence relationship between multi-criteria. First of all. in this method, the degree of dependence relationship between multi-criteria that the specialist feels is surveyed and included to the weighted score of multi-criteria This study supposes three methods to implement this idea. The first model products the degree of dependence relationship in the first step for calculating the weighted score, and the others adjust the result of weighted score from the basic AHP method to the dependence relationship. One of the second methods distributes the cross weighted score to each standard by constant ratio, and the other splits them using Fuzzy measure such as Bel and Pl. Finally, in order to validate these methods, this paper applies them to evaluate the alternatives which can control public resentments against Korean rail path in a city area.