• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.213-219
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• 2009

In densely urban areas, features such as the sewer system, buildings and river banks have an effect on flow dynamics and flood propagation, and will therefore be accounted for in the model set-up. While two-dimensional (2D) flood models of urban areas are at the forefront of current research into flood inundation mechanisms, they are however constrained by inadequate parameters of topography, and insufficient and inaccurate data. In this study, an urban flood model (overland flow, 2D urban flood flow and sewer flow) was combined and applied at Samcheok city which was damaged by inundation in 2002, in order to simulate inundation depth. The influence of buildings and pumping capacity was also analyzed to estimate the inundated depth in the study area. As a result, it was found that urban inundated depth are affected by pumping capacity directly and it increased about 20-30 cm on most of the modeled area with a building share rate of 0.2-0.6 per unit grid.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.85-93
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• 2009

The primary objective of this study is to construct more simple and reasonable rheological model and propose a methodology for predicting a phenomenon of concrete creep. Deformations of concrete under sustained stress can be expressed by the sum of immediately elastic deformation, time-dependent and time-independent short-term creep, and long-term creep according to the mechanism and time-dependency. To simulate these deformations, a rheological model having six parameters was constructed. In the composing of each parameter, the microprestress-solidification theory and design model code were incorporated together with the numerical approach for the components which can not be theoretically approached. Finally, actual test data were applied in the verification of the proposed model, and suitability of the model was confirmed by comparisons with existing predicting models and design codes.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.157-166
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• 2020

Automated rebar fabrication, which requires effective information exchange between model designers and fabricators, has brought the integration and interoperability of data from different sources to the notice of both academics and industry practitioners. Industry Foundation Classes (IFC) was one of the most commonly used data formats to represent the semantic information of prefabricated components in buildings, whereas the data format utilized by rebar fabrication machine is BundesVereinigung der Bausoftware (BVBS), which is a numerical data structure exchanging reinforcement information through ASCII encoded files. Seamless transformation between IFC and BVBS empowers the automated rebar fabrication and improve the construction productivity. In order to improve data interoperability between IFC and BVBS, this study presents an IFC extension based on the attributes required by automated rebar fabrication machines with the help of Information Delivery Manual (IDM) and Model View Definition (MVD). IDM is applied to describe and display the information needed for the design, construction and operation of projects, whereas MVD is a subset of IFC schema used to describe the automated rebar fabrication workflow. Firstly, with a rich pool of vocabularies practitioners, OmniClass is used in information exchange between IFC and BVBS, providing a hierarchy classification structure for reinforcing elements. Then, using International Framework for Dictionaries (IFD), the usage of each attribute is defined in a more consistent manner to assist the data mapping process. Besides, in order to address missing information within automated fabrication process, a schematic data mapping diagram has been made to deliver IFC information from BIM models to BVBS format for better data interoperability among different software agents. A case study based on the data mapping will be presented to demonstrate the proposed IFC extension and how it could assist/facilitate the information management.

• Atmosphere
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• v.34 no.1
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• pp.69-81
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• 2024

In this paper, Annual flux variations in the Boseong Tall Tower (BTT) from 2016 to 2020 were analyzed using data from three levels (2.5 m, 60 m, and 300 m). BTT was installed in Boseong-gun, Jeollanam-do in February 2014 and continued to conduct energy exchange observations such as CO2, sensible heat, and latent heat using the eddy covariance method until March 2023. The BTT was located in a very flat and uniform paddy field, and flux observations were conducted at four levels: 2.5 m, 60 m, 140 m, and 300 m above ground. Surface energy balance was confirmed from observed data of net radiation flux, soil heat flux, sensible heat flux, and latent heat flux. Additionally, 2.5 m height surface fluxes, which are most influenced by agricultural land, were compared with data from Local Data Assimilation and Prediction System (LDAPS) of the Korea Meteorological Administration to evaluate the accuracy of LDAPS flux data. The correlation coefficient between LDAPS flux data and observed values was 0.95 or higher. Excluding summer latent heat flux data, there was a general tendency for LDAPS data to be higher than observed values. The footprint areas estimated below 60 m height mainly covered agricultural land, and flux observations at 2.5 m and 60 m heights showed typical agricultural characteristics. In contrast, the footprint estimated at 300 m height did not show agricultural characteristics, indicating that observations at this height encompassed a wide range, including mountains, sea, and roads. The analysis results of long-term flux observations can contribute to understanding the energy and carbon dioxide fluxes in agricultural fields. Furthermore, these results can be utilized as essential data for validating and improving numerical models related to such fluxes.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.67-75
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• 2023

This paper deals with the operation of air taxis, which is one of the latest innovative technologies aimed at solving the issue of traffic congestion in cities. A key challenge for the successful introduction of the technology and efficient operation is a vertiport location problem. This paper employs a discrete choice model to calculate choice probabilities of transportation modes for each route, taking into account factors such as cost and travel time associated with different modes. Based on this probability, a mathematical formulation to maximize the utilization rate for air taxi is proposed. However, the proposed model is NP-hard, effective and efficient solution methodology is required. Compared to previous studies that simply proposed the optimization models, this study presents a solution methodology using the cross-entropy algorithm and confirms the effectiveness and efficiency of the algorith through numerical experiments. In addition to the academic excellence of the algorithm, it suggests that decision-making that considers actual data and air taxi utilization plans can increase the practial usability.

• Explosives and Blasting
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• v.41 no.4
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• pp.17-28
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• 2023

Recently, the utilization of underground space for research facilities and resource development has been on the rise, expanding development from shallow to deep underground. The establishment of deep underground spaces necessitates a thorough examination of rock stability under conditions of elevated stress and temperature. In instances of greater depth, the stability is influenced not only by the geological structure and discontinuity of rock but also by the propagation of ground vibrations resulting from earthquakes and rock blasting during excavation, causing stress changes in the underground cavity and impacting rock stability. In terms of blasting engineering, empirical regression models and numerical analysis methods are used to predict ground vibration through statistical regression analysis based on measured data. In this study, single-hole blasting was conducted, and the pressure of the blast hole and observation hole and ground vibration were measured. Based on the experimental results, the blast pressure blasting vibration at a distance, and the response characteristics of the tunnel floor, side walls, and ceiling were analyzed.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.31 no.3
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• pp.59-70
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• 2023

In order to predict low-level wind shear at Incheon International Airport (RKSI), a Low-Level Wind Shear prediction system (KMAP-LLWS) along the runway take-off and landing route at RKSI was established using Korea Meteorological Administration Post-Processing (KMAP). For the performance evaluation, the case of low-level wind shear cases calculated from Aircraft Meteorological Data Relay (AMDAR) from July 2021 to June 2022 was used. As a result of verification using the performance evaluation index, POD, FAR, CSI, and TSS were 0.5, 0.85, 0.13, and 0.34, respectively, and the prediction performance was improved by POD, CSI, and TSS compared to the Low-Level Wind Shear prediction system (LDPS-LLWS) calculated using the Korea Meteorological Administration's Local Data Assimilation and Prediction System (LDAPS). This means that the use of high-resolution numerical models improves the predictability of wind changes. In addition, to improve the high FAR of KMAP-LLWS, the threshold for low-level wind shear strength was adjusted. As a result, the most effective low-level wind shear threshold at 8.5 knot/100 ft was derived. This study suggests that it is possible to predict and respond to low-level wind shear at RKSI. In addition, it will be possible to predict low-level wind shear at other airports without wind shear observation equipment by applying the KMAP-LLWS.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.251-259
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• 2024

Fine particulate matter, especially PM2.5 with a diameter of less than 2.5 micrometers, poses significant health and economic risks. This study focuses on the Seoul region of South Korea, aiming to analyze PM2.5 data and trends from 2017 to 2022 and develop a mid-term prediction model for PM2.5 concentrations. Utilizing collected and produced air quality and weather data, reanalysis data, and numerical model prediction data, this research proposes an ensemble evaluation method capable of adapting to trend changes. The ensemble method proposed in this study demonstrated superior performance in predicting PM2.5 concentrations, outperforming existing models by an average F1 Score of approximately 42.16% in 2019, 58.92% in 2021, and 34.79% in 2022 for future 3 to 6-day predictions. The model maintains performance under changing environmental conditions, offering stable predictions and presenting a mid-term prediction model that extends beyond the capabilities of existing deep learning-based short-term PM2.5 forecasts.

• Earthquakes and Structures
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• v.26 no.5
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• pp.349-361
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• 2024

Excessive torsional behaviour is one of the major reasons for failure of buildings, as inferred from past earthquakes. Numerous seismic codes across the world specify a displacement-based or drift-based criterion for classifying buildings as torsionally irregular. In recent years, quite a few researchers have pointed out some of the inherent deficiencies associated with the current codal guidelines on torsional irregularity. This short communication paper aims to envisage the need for a revision of the displacement-based guidelines on torsional irregularity, and further highlight the appropriateness of a rotation-based criterion. A set of 6 reinforced concrete building models with asymmetric shear walls are analysed using ETABS v18.0.2, by varying the number of stories from 1 to 9, and the torsional irregularity coefficient of various stories is calculated using the displacement-based formula. Since rotation about the vertical axis is a direct indication of the twist experienced by a building, the calculated torsional irregularity coefficients of all stories are compared with the corresponding floor rotations. The conflicting results obtained for the torsional irregularity coefficients are projected through five categories, namely mismatch with floor rotations, inconsistency in trend, lack of clarity in incorporation of negative values, sensitivity to low values of displacement and error conceived in the mathematical formulation. The findings indicate that the irregularity coefficient does not accurately represent the torsional behaviour of buildings in a realistic sense. The Indian seismic code-based values of 1.2 and 1.4, which are used to characterize buildings as torsionally irregular are observed to be highly sensitive to the numerical values of displacements, rather than the actual degree of rotation. The study thus emphasizes the revision of current guidelines based on a more relevant rotation-based or eccentricity-based approach.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.103-118
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• 2024

The horseshoe prior is notably one of the most popular priors in sparse regression models, where only a small fraction of coefficients are nonzero. The parameter space of the horseshoe prior is much smaller than that of the spike and slab prior, so it enables us to efficiently explore the parameter space even in high-dimensions. However, on the other hand, the horseshoe prior has a high computational cost for each iteration in the Gibbs sampler. To overcome this issue, various MCMC algorithms for the horseshoe prior have been proposed to reduce the computational burden. Especially, Johndrow et al. (2020) recently proposes an approximate algorithm that can significantly improve the mixing and speed of the MCMC algorithm. In this paper, we compare (1) the traditional MCMC algorithm, (2) the approximate MCMC algorithm proposed by Johndrow et al. (2020) and (3) its variant in terms of computing times, estimation and variable selection performance. For the variable selection, we adopt the sequential clustering-based method suggested by Li and Pati (2017). Practical performances of the MCMC methods are demonstrated via numerical studies.