• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.316-329
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• 2008

Recently the increased attention pays on the processing of multiple, relatively low quantity, high value-added products resulted in adoption of batch process in the chemical process industry such as pharmaceuticals, polymers, bio-chemicals and foods. As there are more possibilities of the improvement of operations in batch process than continuous processes, a lot of effort has been made to enhance the productivity and operability of batch processes. But the chemical process industry faces a range of uncertainties factors such as demands for products, prices of product, lead time for the supply of raw materials and in the production, and the distribution of product. And global competition has made it imperative for the process industries to manage their supply chains optimally. Supply chain management aims to integrate plants with their supplier and customers so that they can be managed as a single entity and coordinate all input/output flows (of materials, information) so that products are produced and distributed in the right quantities, to the right locations, and at the right time.The objective of this study is to solve the purchase, distribution, production planning and scheduling problem, which minimizes the total costs of production, inventory, and transportation under uncertainty. And development of SCM model in chemical industry including batch mode operations. Through that, the enterprise can respond to uncertainty. Also integrated process optimal planning and scheduling model for manufacturing supply chain. The result shows that, the advantage of supply chain integration are quality matters seen by customers and suppliers, order schedules, flexibility, cost reduction, and increase in sales and profits. Also, an integration of supply chain (production and distribution system) generates significant savings by trading off the costs associated with the whole, rather than minimizing supply chain costs separately.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.59-69
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• 2018

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) - non-orthogonal multipleaccess (NOMA) downlink system for 5G wireless communications. This work consider the imperfectchannel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as on-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beam forming design which establishes on majorization minimization (MM) technique to find the optimal transmit beam forming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.2
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• pp.159-173
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• 2017

The Weather Research and Forecast (WRF) - Community Multiscale Air Quality (CMAQ) system was applied to investigate the influence of major point sources located in Chungcheongnam-do (CN) on surface $PM_{2.5}$ (Particulate Matter of which diameter is $2.5{\mu}m$ or less) concentrations in its surrounding areas. Uncertainties associated with contribution estimations were examined through cross-comparison of modeling results using various combinations of model inputs and setups; two meteorological datasets developed with WRF for 2010 and 2014, and two domestic emission inventories for 2010 and 2013 were used to estimate contributions of major point sources in CN. The results show that contributions of major point sources in CN to annual $PM_{2.5}$ concentrations over Seoul, Incheon, Gyeonggi, and CN ranged $0.51{\sim}1.63{\mu}g/m^3$, $0.71{\sim}1.62{\mu}g/m^3$, $0.63{\sim}1.66{\mu}g/m^3$, and $1.04{\sim}1.86{\mu}g/m^3$, respectively, depending on meteorology and emission inventory choice. It indicates that the contributions over the surrounding areas can be affected by model inputs significantly. Nitrate was the most dominant $PM_{2.5}$ component that was increased by major point sources in CN followed by sulfate, ammonium, and others. Based on the model simulations, it was estimated that primary $PM_{2.5}$ $(PPM)-to-PM_{2.5}$ conversion rates were 41.3~50.7 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 12.4~18.3 ($10^{-6}{\mu}g/m^3/TPY$) for Seoul, Incheon, and Gyeonggi, respectively. In addition, spatial gradients of PPM contributions show very steep trends. $NO_X$-to-nitrate conversion rates were 7.61~12.3 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 3.94~11.3 ($10^{-6}{\mu}g/m^3/TPY$) for the sub-regions in the SMA. $SO_2$-to-sulfate conversion rates were 4.04~5.28 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 3.73~4.43 ($10^{-6}{\mu}g/m^3/TPY$) for the SMA, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.219-233
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• 2013

We employed the ecological niche modeling framework using GARP (Genetic Algorithm for Ruleset Production) to model the current and future geographic distribution of Pinus densiflora based on environmental predictor variable datasets such as climate data including the RCP 8.5 emission climate change scenario, geographic and topographic characteristics, soil and geological properties, and MODIS enhanced vegetation index (EVI) at 4 $km^2$ resolution. National Forest Inventory (NFI) derived occurrence and abundance records from about 4,000 survey sites across the whole country were used for response variables. The current and future potential geographic distribution of Pinus densiflora, one of the tree species dominating the present Korean forest was modeled and mapped. Future models under RCP 8.5 scenarios for Pinus densiflora suggest large areas predicted under current climate conditions may be contracted by 2090 showing range shifts northward and to higher altitudes. Area Under Curve (AUC) values of the modeled result was 0.67. Overall, the results of this study were successful in showing the current distribution of major tree species and projecting their future changes. However, there are still many possible limitations and uncertainties arising from the select of the presence-absence data and the environmental predictor variables for model input. Nevertheless, ecological niche modeling can be a useful tool for exploring and mapping the potential response of the tree species to climate change. The final models in this study may be used to identify potential distribution of the tree species based on the future climate scenarios, which can help forest managers to decide where to allocate effort in the management of forest ecosystem under climate change in Korea.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.4
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• pp.245-255
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• 2008

Korea Hydro and Nuclear Power Company(KHNP) conducted site investigations for a low and intermediate-level nuclear waste repository in the Gyeong Ju site. The site characterization work constitutes a description of the site, its regional setting and the current state of the geosphere and biosphere. The main objectives of hydogeological investigation aimed to understand the hydrogeological setting and conditions of the site, and to provide the input parameters for safety evaluation. The hydogeological characterization of the site was performed from the results of surface based investigations, i.e geological mapping and analysis, drilling works and hydraulic testing, and geophysical survey and interpretation. The hydro-structural model based on the hydrogeological characterization consists of one-Hydraulic Soil Domain, three-Hydraulic Rock Domains and five-Hydraulic Conductor Domains. The hydrogeological framework and the hydraulic values provided for each hydraulic unit over a relevant scale were used as the baseline for the conceptualization and interpretation of flow modeling. The current hydrogeological characteristics based on the surface based investigation include some uncertainties resulted from the basic assumption of investigation methods and field data. Therefore, the reassessment of hydrostructure model and hydraulic properties based on the field data obtained during the construction is necessitated for a final hydrogeological characterization.

• Geotechnical Engineering
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• v.3 no.4
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• pp.41-54
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• 1987

A stochastic numerical analysis for predicting the groundswater fluctuations in hillside slopes is performed in this paper to account for the uncertainties associated with the rainfall and site characteristics. The effect of spatial variabilities of aquifer parameters and the effect of temporal variability of recharge on the groundwater fluctuations are studied in depth. The Kriging is used to account for the spatial tariabilities of aquifer parameters. This technique prolevides the best linear unbiased estimator of a parameter and its minimum variance from a litsitem number of measured data. A stochastic one-dimensional numerical model is delreloped b) combining the groundwater flow model, the Kriging, and the first-order second-moment analysis. In addition, a two dimensional detelministic groundwater model is developed to study the change of ground water surfas in the transverse direction as well as in the downslope direction. It is revealed that the undulations of the impervious bedrock in addition to the permeability and the specific yield have an important influence on the fluctuations of the groundwater surface. It is also found that th'e groundwater changes significantly in the transverse direction as well as in the downslope direction. The results obtained in this analysis may be used for evaluation of landslide risks due to high porewater pressure.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.14 no.2
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• pp.136-150
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• 2002

To improve the water quality of the recently constructed Siwhaho, sluice gates were operated to allow free exchange of water with the sea. This estuarine lake connected to the outer sea through narrow gates is affected mainly by flushing by gate operation and river flows and wind forcing sometimes. As a predicting tool far the water qualities, a three-dimensional finite volume model CE-QUAL-ICM is incorporated into a finite element hydrodynamic model, TIDE3D. In coupling these two different modules, a new error minimization technique is applied by considering conservation of mass. Model tests for one year after calibration and validation using field observation show that eutrophication and other biological changes reach quasi-steady state after initial 60 days of simulation, thus it would be necessary to consider moderate ramp up option to remove initial uncertainties due to cold start option. Sediment-water interaction might not be a concern in the long-term simulation, since its effect is negligible. Simulated results show the newly applied scheme can be applied with satisfaction not only fur lessening of eutrophic processes in an estuarine lake but also looking for some active circulation to improve water quality.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.769-782
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• 2018

Estimation of design floods is typically required for hydrologic design purpose. Design floods are routinely estimated for water resources planning, safety and risk of the existing water-related structures. However, the hydrologic data, especially streamflow data for the design purposes in South Korea are still very limited, and additionally the length of streamflow data is relatively short compared to the rainfall data. Therefore, this study collected a large number design flood data and watershed characteristics (e.g. area, slope and altitude) from the national river database. We further explored to formulate a scaling approach for the estimation of design flood, which is a function of the watershed characteristics. Then, this study adopted a Hierarchical Bayesian model for evaluating both parameters and their uncertainties in the regionalization approach, which models the hydrologic response of ungauged basins using regression relationships between watershed structure and model. The proposed modeling framework was validated through ungauged watersheds. The proposed approach have better performance in terms of correlation coefficient than the existing approach which is solely based on area as a predictor. Moreover, the proposed approach can provide uncertainty associated with the model parameters to better characterize design floods at ungauged watersheds.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.23-34
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• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.5
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• pp.339-346
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• 2023

The uncertainties of microstructural features affect the properties of materials. Numerous pores that are randomly distributed in materials make it difficult to predict the properties of the materials. The distribution of pores in cementitious materials has a great influence on their mechanical properties. Existing studies focus on analyzing the statistical relationship between pore distribution and material responses, and the correlation between them is not yet fully determined. In this study, the mechanical response of cementitious materials is predicted through an image-based data approach using a convolutional neural network (CNN), and the correlation between pore distribution and material response is analyzed. The dataset for machine learning consists of high-resolution micro-CT images and the properties (tensile strength) of cementitious materials. The microstructures are characterized, and the mechanical properties are evaluated through 2D direct tension simulations using the phase-field fracture model. The attributes of input images are analyzed to identify the spot with the greatest influence on the prediction of material response through CNN. The correlation between pore distribution characteristics and material response is analyzed by comparing the active regions during the CNN process and the pore distribution.