• Plant Journal
• /
• v.17 no.1
• /
• pp.50-57
• /
• 2021

It is very difficult to accurately calculate efficiency of each accessory device constituting the pump system and pump efficiency by the Conventional efficiency measurement method only. Therefore, this study introduced the lastest Thermodynamic pump efficiency measurement method in the district heating pump system for the first time in Korea. As a result, data uncertainty was high by the Conventional method, but the pump and Hydraulic Coupling efficiency values applied the Thermodynamic and Conventional method parallel measurement data were able to derive meaningful results that verified the reliability and adequancy of the pump performance measurement method by performing complementary roles. In additon, as a result of applying the Thermodynamic method to the distirct heating pump system, despite the high temperature environment of up to 120 ℃, it was possible to verify the reliability of the Thermodynamic method, such as high stable data mesurement, and durability of the measurement equipment.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.33 no.4
• /
• pp.368-375
• /
• 2013

Failure of small bore piping welds is a recurring problem at nuclear power plants. And the socket weld cracking in small bore piping has caused unplanned plant shutdowns for repair and high economic impact on the plants. Consequently, early crack detection, including the detection of manufacturing defects, is of the utmost importance. Until now, the surface inspection methods has been applied according to ASME Section XI requirements. But the ultrasonic inspection as a volumetric method is also applying to enforce the inspection requirement. However, the conventional manual ultrasonic inspection techniques are used to detect service induced fatigue cracks. And there was uncertainty on manual ultrasonic inspection because of limited access to the welds and difficulties with contact between the ultrasonic probe and the OD(outer diameter) surface of small bore piping. In this study, phased array ultrasonic inspection technique is applied to increase inspection speed and reliability. To achieve this object, the 3.5 MHz phased array ultrasonic transducer are designed and fabricated. The manually encoded scanner was also developed to enhance contact conditions and maintain constant signal quality. Additionally inspection system is configured and inspection procedure is developed.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.16 no.3
• /
• pp.227-232
• /
• 2014

Ageratina altissima is an invasive plant species known to threaten native plant communities in Korea. A. altissima is thought to invade shady forests from disturbed open areas; however, uncertainty remains as to how shade and litter depth might affect establishment. A study of A. altissima distribution characteristics in areas adjacent to trails was undertaken at Mt. Umyeon in Seoul, Korea. Increasing densities of A. altissima were found to correlate with greater light availability and decreasing litter depth (p < 0.001) within 10 m distance from trail locations and on ridges rather than further within forests and valleys. The effects of soil moisture content, soil gravel content and soil pH on distribution were not found to be significant, suggesting that A. altissima is adaptable to a broad range of soil conditions. Results indicate that forest areas close to trails may be particularly susceptible place to A. altissima invasion, demonstrating the need to carefully consider implications for A. altissima expansion in trail management.

• Journal of Environmental Health Sciences
• /
• v.44 no.1
• /
• pp.63-75
• /
• 2018

Objectives: The aim of this research is to explore the total heavy metals from a coal-fired power plant burning bituminous coal with wood pellets due to the implementation of the Renewable Portfolio Standard policy (RPS, 10% of electricity from renewable energy resources by 2023). Methods: The research was carried out by collecting archival data and using the USEPA's AP-42 & EMEP/EEA compilation of emission factors for use in calculating emissions. The Monte Carlo method was also applied for carrying out the calculations of measurement uncertainty. Results: In this paper, the results are listed as follows. Sb was measured at 110 kg (2015) and calculated as 165 kg (2019) and 201 kg (2023). Cr was measured at 1,597 kg (2015) and calculated as 1,687 kg (2019) and 1,728 kg (2023). Cu was measured at 2,888 kg (2015) and calculated as 3,133 kg (2019) and 3,264 kg (2023). Pb was measured at 2,580 kg (2015) and calculated as 2,831 kg (2019) and 2,969 kg (2023). Mn was measured at 3,011 kg (2015) and calculated as 15,034 kg (2019) and 23,014 kg (2023). Hg was measured at 510 kg (2015) and calculated as 513 kg (2019) and 537 kg (2023). Ni was measured at 1,720 kg (2015) and calculated as 1,895 kg (2019) and 1,991 kg (2023). Zn was measured at 7,054 kg (2015) and calculated as 9,938 kg (2019) and 11,778 kg (2023). Se was measured at 7,988 kg (2015) and calculated as 7,663 kg (2019) and 7,351 kg (2023). Conclusion: This shows that most heavy metals would increase steadily from 2015 to 2023. However, Se would decrease by 7.9%. This analysis was conducted with EMEP/EEA's emission factors due to the limited emission factors in South Korea. Co-firewood pellets in coal-fired power plants cause the emission of heavy metals. For this reason, emission factors at air pollution control facilities would be presented and the replacement of wood pellets would be needed.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.8 no.2
• /
• pp.167-174
• /
• 2020

Many researches have been conducted to utilize recycled aggregates in Korea, but since most sources of recycled aggregates are not clear, there is a lot of uncertainty in applying the existing research results on recycle of aggregates generated from nuclear power plants. In this study, therefore, in order to investigate the possibility of recycling coarse aggregates generated through dismantling of nuclear power plants in Korea, recycled coarse aggregates were produced from concrete simulating nuclear power plants in Korea. Using the recycled coarse aggregates, concrete was mixed in consideration of the mixing ratio of the recycled coarse aggregates, and the mechanical properties were experimentally investigated. From the test results, as the mixing ratio of recycled coarse aggregates increased. concrete compressive strength, tensile strength, and elastic modulus generally decreased up to 36, 37, and 27% from the mechanical properties of normal concrete, respectively. Therefore, it can be concluded that limitation on the mixing ratio of recycled coarse aggregates is necessary when coarse aggregates are recycled through dismantling of nuclear power plants.

• Journal of the Korean Institute of Gas
• /
• v.22 no.6
• /
• pp.136-143
• /
• 2018

Cellular automata have been applied to simulations in many fields such as astrophysics, social phenomena, fire spread, and evacuation. Using cellular automata, this study develops a model for consequence analysis of the dispersion of hazardous chemicals, which is required for risk assessments of and emergency responses for frequent chemical accidents. Unlike in cases of detailed plant safety design, real-time accident responses require fast and iterative calculations to reduce the uncertainty of the distribution of damage within the affected area. EPA ALOHA and KORA of National Institute of Chemical Safety have been popular choices for these analyses. However, this study proposes an initiative to supplement the model and code continuously and is different in its development of free software, specialized for small and medium enterprises. Compared to the full-scale computational fluid dynamics (CFD), which requires large amounts of computation time, the relative accuracy loss is compromised, and the convenience of the general user is improved. Using Python open-source libraries as well as meteorological information linkage, it is made possible to expand and update the functions continuously. Users can easily obtain the results by simply inputting the layout of the plant and the materials used. Accuracy is verified against full-scale CFD simulations, and it will be distributed as open source software, supporting GPU-accelerated computing for fast computation.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.1
• /
• pp.35-47
• /
• 2022

Expansion of potato production areas can improve the food security in North Korea because the given crop has less requirements for agricultural materials and facilities. The Global Agro-Ecological Zones (GAEZ) model, which was developed to evaluate climate suitability under different cultivation conditions, was used to identify potential areas for the potato production. The spatial estimates of crop suitability under low and high input management conditions were downloaded from the GAEZ data portal. The values of suitability were obtained at the potato occurrence sites retrieved from the Global Biodiversity Information Facility (GBIF) database. The suitable areas for the potato production were identified using a threshold value derived from the suitability estimates at the occurrence sites. It was found that 90% of the occurrence sites had the suitability index value >3,333, which was set to be the threshold value. The suitable areas in North Korea were summarized by province and county. Rice cultivation areas were excluded from the analysis. The reported relative acreage of potato production was better represented by the suitable areas under the low input management options than the high input conditions. The suitable areas also had a similar distribution to the reported acreage of potato production by county. These results indicated that the GAEZ model would be useful to identify the candidate production areas, which would facilitate the increases in potato production especially under future climate conditions. Furthermore, monthly maps of crop suitability can be used to design cropping systems that would improve crop production under the limited use of agricultural materials and facilities.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.16 no.2
• /
• pp.103-113
• /
• 2014

Under climate change, it is likely that the suitable area for forage crop cultivation would change in Korea. The potential cultivation areas for italian ryegrass (Lolium multiflorum L.), which has been considered one of an important forage crop in Korea, were identified using the EcoCrop model. To minimize the uncertainty associated with future projection under climate change, an ensemble approach was attempted using five climate change scenarios as inputs to the EcoCrop model. Our results indicated that most districts had relatively high suitability, e.g., >80, for italian ryegrass in South Korea. Still, suitability of the crop was considerably low in mountainous areas because it was assumed that a given variety of italian ryegrass had limited cold tolerance. It was predicted that suitability of italian ryegrass would increase until 2050s but decrease in 2080s in a relatively large number of regions due to high temperature. In North Korea, suitability of italian ryegrass was considerably low, e.g., 28 on average. Under climate change, however, it was projected that suitability of italian ryegrass would increase until 2080s. For example, suitability of italian ryegrass was more than 80 in 10 districts out of 14 by 2080s. Because cold tolerance of italian ryegrass varieties has been improved, it would be preferable to optimize parameters of the EcoCrop model for those varieties. In addition, it would be possible to grow italian ryegrass as the second crop following rice in Korea in the future. Thus, it merits further study to identify suitable areas for italian ryegrass cultivation after rice using new varieties of italian ryegrass.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.2
• /
• pp.108-125
• /
• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• The Journal of Engineering Geology
• /
• v.30 no.4
• /
• pp.457-468
• /
• 2020

Problems arising during pile design works for plant construction, civil and architecture work are mostly come from uncertainty of geotechnical characteristics. In particular, obtaining the N-value measured through the Standard Penetration Test (SPT) is the most important data. However, it is difficult to obtain N-value by drilling investigation throughout the all target area. There are many constraints such as licensing, time, cost, equipment access and residential complaints etc. it is impossible to obtain geotechnical characteristics through drilling investigation within a short bidding period in overseas. The geotechnical characteristics at non-drilling investigation points are usually determined by the engineer's empirical judgment, which can leads to errors in pile design and quantity calculation causing construction delay and cost increase. It would be possible to overcome this problem if N-value could be predicted at the non-drilling investigation points using limited minimum drilling investigation data. This study was conducted to predicted the N-value using an Artificial Neural Network (ANN) which one of the Artificial intelligence (AI) method. An Artificial Neural Network treats a limited amount of geotechnical characteristics as a biological logic process, providing more reliable results for input variables. The purpose of this study is to predict N-value at the non-drilling investigation points through patterns which is studied by multi-layer perceptron and error back-propagation algorithms using the minimum geotechnical data. It has been reviewed the reliability of the values that predicted by AI method compared to the measured values, and we were able to confirm the high reliability as a result. To solving geotechnical uncertainty, we will perform sensitivity analysis of input variables to increase learning effect in next steps and it may need some technical update of program. We hope that our study will be helpful to design works in the future.