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Thermal energy storage (TES) is vital to the absorption and release of plenty of external heat for various applications. For such storage, phase change material (PCM) has been considered as a sustainable energy material that can be integrated into a power generator. However, pure PCM has a leakage problem during the phase transition process, and we should fabricate a form stable PCM composite using some supporting materials. To prevent the leakage problem during the phase transition process, two different methods, microencapsulation and 3D porous infiltration, were used to fabricate PCM composites in this work. It was found that both microsphere and 3D porous aerogel supported PCM composites maintained their initial solid state without any leakage during the melting process. Compared with the microencapsulated PCM composite, the 3D porous aerogel supported PCM exhibited a relatively high weight fraction of working material due to its high porosity. In addition, the cross-linked graphene aerogel (GCA) could reduce volume shrinkage effectively during the infiltration process, and the GCA supported PCM composite kept a high latent heat (∆H) and form stability.

This paper evaluates a one-year treatment outcome after full or reduced photodynamic therapy (PDT) and anti-vascular endothelial growth factor (VEGF) combination therapy for pachychoroid neovasculopathy (PNV). After the initial combination therapy, a total of 29 eyes from 29 patients (16 for full treatment and 13 for reduced treatment), exhibited reduced, central retinal thickness and central choroidal thickness, and the improvements were maintained for 1 year after the initial combination therapy. Twenty-two eyes (75.9%) required no additional treatments for 1 year. The recurrence rate was 31.3% in the full treatment and 15.4% in the reduced treatment, with no significant differences between them. One shot of anti-VEGF and full or reduced PDT combination therapy had similar efficacy in treating PNV. Further prospective, large-scale, and long-term studies are required to determine a better treatment for PNV.

Recently, unmanned aerial vehicles (UAVs) have been used in various fields, such as military, logistics, transportation, construction, and agriculture, making it possible to apply the limited activities of humans to various and wide ranges. In addition, UAVs have been utilized to construct topographic data that are more precise than existing satellite images or cadastral maps. In this study, a monitoring point for preventing flood damage in an urban area was selected using a UAV. In addition, the topographic data were constructed using a UAV, and the flow of rainwater was examined using the watershed analysis in an urban area. An orthomosaic, a digital surface model (DSM), and a three-dimensional (3D) model were constructed for the topographic data, and a precision of 0.051 m based on the root mean square error (RMSE) was achieved through the observation of ground control points (GCPs). On the other hand, for the watershed analysis in the urban area, the point in which the flow of rainwater converged was analyzed by adjusting the thresholds. A monitoring point for preventing flood damage was proposed by examining the topographic characteristics of the target area related to the inflow of rainwater.

With the climate change adding to the frequency and intensity of natural disasters, drought has devastated large areas of lands in South Korea. Still, the exact beginning and end of the drought is difficult to identify, and this impedes the development and implementation of disaster predictions. Although the drought phenomenon has been well-documented, predictions thereof are limited due to the non-linear and complex temporal fluctuations of the hydrologic factors. Hence, this study set up some reference points for disaster-prediction rainfall based on South Korea&rsquo, s agricultural drought damage data, to help in drought relief. To set up the proposed reference points for disaster-prediction rainfall, we analyzed rainfall in light of the disaster-prevention relevance to agricultural droughts and the disaster reduction. As an analysis method, rainfall of municipality was calculated through Thiessen&rsquo, s polygonal method, to apply rainfall weighting value for each rainfall observatory. In addition, the linear regression analysis was applied to suggest the calculation formula for setting the annual disaster reduction rainfall. The results of this study, standard of judgment point for disaster prevention of agricultural drought at the time of disaster management, were analyzed for rainfall for local governments and the whole country. Rather than using various drought indices that are currently developed, policy makers or public servant made suggestions based on rainfall that is most accessible and convenient for judging the timing of agricultural drought. As the disaster-prevention rainfall with agricultural droughts is expected to occur, we established the average annual rainfall of &le, 1200 or 100 mm below the preceding year&rsquo, s average annual rainfall. Moreover, as the disaster-reduction rainfall for agricultural droughts to end, we determined the average monthly rainfall of &ge, 150 mm.

Inundation damage occurs in urban regions due to short flood reach time and increased surface runoff caused by urbanized impervious areas. Furthermore, heavy rainfall frequency has increased because of climate change, thus exceeding the design frequency and resulting in sewer pipes&rsquo, lack of flood control capacity, with damage expanding from low-lying areas. Despite many urban disaster-mitigation policies, complex causes and uncertainties make reducing urban inundation damage difficult. This study established a rainfall-related disaster-prevention standard by time duration considering rainfall characteristics targeting urban disaster-induced inundation damage. Based on the South Korean urbanization rate and population, seven target regions were selected. Rainfall by time duration was analyzed with respect to disaster length (number of days) from 2010&ndash, 2017. The average rainfall for durations from 1&ndash, 24 hours were analyzed according to disaster length (1&ndash, 13 days). Using the results, an equation was proposed for rainfall estimation by length of disaster resulting in urban inundation damage, through multiple regression analysis. An equation was developed for rainfall-related disaster-prevention in urban areas considering the length of disaster and rainfall duration. This was accomplished by selecting a duration whereby the average rainfall of duration corresponded to 50% of total rainfall during the disaster period.

The runoff from heavy rainfall reaches urban streams quickly, causing them to rise rapidly. It is therefore of great importance to provide sufficient lead time for evacuation planning and decision making. An efficient flood forecasting and warning method is crucial for ensuring adequate lead time. With this objective, this paper proposes an analysis method for a flood forecasting and warning system, and establishes the criteria for issuing urban-stream flash flood warnings based on the amount of rainfall to allow sufficient lead time. The proposed methodology is a nonstructural approach to flood prediction and risk reduction. It considers water level fluctuations during a rainfall event and estimates the upstream (alert point) and downstream (confluence) water levels for water level analysis based on the rainfall intensity and duration. We also investigate the rainfall/runoff and flow rate/water level relationships using the Hydrologic Engineering Center&rsquo, s Hydrologic Modeling System (HEC-HMS) and the HEC&rsquo, s River Analysis System (HEC-RAS) models, respectively, and estimate the rainfall threshold for issuing flash flood warnings depending on the backwater state based on actual watershed conditions. We present a methodology for issuing flash flood warnings at a critical point by considering the effects of fluctuations in various backwater conditions in real time, which will provide practical support for decision making by disaster protection workers. The results are compared with real-time water level observations of the Dorim Stream. Finally, we verify the validity of the flash flood warning criteria by comparing the predicted values with the observed values and performing validity analysis.

Damage caused by natural disasters produces the difference of damage size not only according to damage volume or size, but a national economic level. In addition, budgets and aids should be constantly acquired for disaster management since natural disasters sporadically or irregularly occur. This study proposed disaster management methods by countries considering natural disaster damage documents and economic indicators from 1900 to 2017 among 187 countries in the world. It developed a damage prediction formula considering damage documents of previous natural disasters, economic indicators by countries, and basic indicators as disaster management methods by countries. Independent variables of the damage prediction formula include GDP, population, and area. It applied multiple regression analysis and calculated average human losses due to death, human losses affected, and damage costs by countries. Regarding the adjusted R&sup2, of the natural disaster damage prediction formula, the human losses from deaths mean was 0.893, the human losses affected mean was 0.915, and the damage costs mean was 0.946, which had higher explanatory powers. Therefore, results from this study are considered to calculate quantitative damage sizes considering uncertain damage sizes of natural disasters, economic indicators by countries, and are used as indicators for disaster management.