• Smart Structures and Systems
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• v.29 no.5
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• pp.653-660
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• 2022

Gravel scattering that is generated during operation of high-speed railway vehicle is cause to damage of vehicle such as windows, axle protector and so on. Especially, those are frequently occurred in winter season when snow ice is generated easily. Above all, damage of vehicle windows has not only caused maintenance cost but also increased psychological anxiety of passengers. Various methods such as heating system using copper wire, heating jacket and heating air are applied to remove snow ice generated on the under-body of vehicle. However, the methods require much run-time and man power which can be low effectiveness of work. Therefore, this paper shows that large-area heating system was developed based on heating coat in order to fundamentally prevent snow ice damage on high-speed railway vehicle in the winter season. This system gives users high convenience because that can remotely control the heating system using IoT-based wireless communication. For evaluating the applicability to railroad sites, a field test on an actual high-speed railroad operation was conducted by applying these techniques to the brake cylinder of a high-speed railroad vehicle. From the results, it evaluated how input voltage and electric power per unit area of the heating specimen influences exothermic performance to draw the permit power condition for icing. In the future, if the system developed in the study is applied at the railroad site, it may be used as a technique for preventing all types of damages occurring due to snow ice in winter.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.339-342
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• 2003

According to the results of structural safety analysis, allowable safe snow depth for type B(wood frame with single span) was 25.9cm, and those for type A(wood frame with multi span) and type C and D (steel frame with multi span) were 17.6cm, 25.8cm, and 20.0cm respectively. An experiential example study on meteorological disasters indicated that a strong wind damage was experienced once every 20 years, and a heavy snow damage once every 9.5 years. The most serious disaster was a heavy snow and it was found that a half break or complete collapse of structures were experienced by about 70% of farmhouses.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.319-322
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• 2007

This study aims to find the characteristics of damage and states of natural disasters at the Korean Peninsula from 1985 to 2004. Using the data of Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration. we have analyzed the cause, elements, and vulnerable regions for natural disasters. Major causes of natural disaster at Korean Peninsula are four, such as a heavy rain, heavy rain typhoon, typhoon, storm snow, and storm. The frequency of natural disaster is the highest from June to September. The period from December to March also shows high frequency. The total amount of damage is high during the summer season(Jul.-Sept). The period from January to March shows relatively high amount of damage due to storm and storm snow The areas of Gangwon-do, Gyeongsangnam-do and Gyeongsangbuk-do are classified the vulnerable region for the natural disasters. By establishing mitigation plans which fit the type and characteristics of disaster for each region, damage from disaster can be reduced with efficient prevention activities.

• Journal of Korean Society of Forest Science
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• v.73 no.1
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• pp.63-69
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• 1986

In general, the snow injury in forestry is an unusual disaster. The degree of snow injury varies greatly depending on stand density and the local topography. This study was conducted to investigate the snow injury in analyzing the demaged by snow-fall in Jinju, Gyeongsangnamdo. The results obtained were summarized as follow; Among 466 total damaged trees, 425 trees were broken and 41 trees were uprooted, the ratio of damage were 5.22%, 2.49%, 0.92% and 0.2% for Pinus densiflora, Pinus thunbergii, Pinus rigida, Alnus hirsuta respectively. The 95% of the damage trees were in the range of 3 to 11 m for height and in the range of 3 to 20 cm for D. B. H.. The directions of the damage trees had a large influence by direction of the wind, but they shown at high tendency to aspect of the slope relatively. The 82% of the damaged trees ranged from 11 to 24 age. The ratio of broken height ($H_B/H$) indicated that the damage was most frequent in the part of stem as 24%, 45%, 31% in the part of the root collar (0.1), stem (0.2-0.4), crown (0.5-1.0) respectively. In general, trees with stem-form coefficient ($H_B/D$) over 0.7-0.8 are apt to suffer by snow damage. The average of stem-form coefficient of trees in this area was 1.06. Therefore, the ratio of damage was high tendency as 3.14%. These results indicate that it is necessary to apply pertinent tending which will increase in resistance of snow damage. As avalanches from the flank of soil erosion rise in an importance matter in present, it should also be considered to measures for prevention and restoration.

• International Journal of Highway Engineering
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• v.16 no.3
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• pp.59-66
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• 2014

PURPOSES : This study is to suggest heavy snow risk analysis in Seoul. METHODS : Recently, the increase of extreme weather caused by global warming raises the occurrences of unpredictable natural disasters and the loss potential of human disasters by land use facilities accumulation. It is necessary to develop the risk analysis for the natural and human disasters. RESULTS : In this study, heavy snow risk analysis among natural disasters in Seoul was suggested. The spatial unit of risk analysis level was established for the lines and administrative districts. CONCLUSIONS : The risk analysis was performed using risk matrix of disaster occurrence score and disaster damage score. The components affecting the risk disaster analysis by types were analyzed and the application of heavy snow risk analysis was suggested.

• Journal of the Korean Professional Engineers Association
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• v.45 no.2
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• pp.28-32
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• 2012

The European Alps face a number of major threats - from habitat loss to pollution, from mass tourism to the impacts of climate change. The European alpine climate has changed significantly during the past century, with temperatures increasing more than twice the global average. This makes alpine mountains especially vulnerable to changes in the hydrological cycle and decreases in snow and glacier cover, which are already occurring. In winter, artificial snow-making is currently the most widespread strategy to extend and supplement natural snow cover and secure winter tourism. Artificial snow-making is not only very costly, but also has knock-on effects such as increased water consumption and energy demand or ecological damage, which may lead to negative externalities. The European Alps facing the challenge of changing climate and anthropogenic pressures.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.61-74
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• 2021

Agriculture is most closely related to weather, and the government pursues stable food production by weather research. However, abnormal weather conditions have occurred frequently around the world in recent years, and stable food production has been threatened. Among them, heavy snow in winter tends to increase in frequency and size, which causes serious damage to greenhouses. Therefore, it is imperative to build a system reflecting various demands to reduce the damage to agricultural facilities caused by heavy snow. A business model can realize this as a way of commercialization, however, no suitable model has been presented to date. Therefore, this study aims to design a representative business model that can establish a safety system by distributing a greenhouse disaster prevention warning system for heavy snow to farms.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.3
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• pp.95-102
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• 2003

To Prevent the damage of power system facilities by snow accretion on transmission lines, a prototype expert system has been developed. The system has the basic functions of forecasting snow accretion on transmission lines and making a list of all feasible and effective deicing countermeasures to assist power system operators. As estimating of snow accretion on power lines and making countermeasure plans are very difficult to solve analytically, knowledge engineering can be an effective method for this problem. The heuristics about the effect of weather conditions on the snow accretion process on power lines and power system operation for the deicing constitutes main nile base. Simulation results based on past snow accretion accident data show that the proposed system is very premising.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.35-41
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• 2022

Heavy snow damage can be prevented in advance with an appropriate security system. To develop the security system, we developed a model that predicts snow depth after a few hours when the snow depth is observed, and utilized it to calculate a failure probability with various types of greenhouses and observed snow depth data. We compared the Markov chain model and Bayesian long short-term memory models with varying input data. Markov chain model showed the worst performance, and the models that used only past snow depth data outperformed the models that used other weather data with snow depth (temperature, humidity, wind speed). Also, the models that utilized 1-hour past data outperformed the models that utilized 3-hour data and 6-hour data. Finally, the Bayesian LSTM model that uses 1-hour snow depth data was selected to predict snow depth. We compared the selected model and the shifting method, which uses present data as future data without prediction, and the model outperformed the shifting method when predicting data after 11-24 hours.

• Water for future
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• v.51 no.9
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• pp.46-52
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• 2018