• Advances in environmental research
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• v.7 no.2
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• pp.87-107
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• 2018

Water quality monitoring network needs periodic evaluations based on environmental demands and financial constraints. We used a genetic algorithm to optimize the existing water quality monitoring stations on the Sefid-Rud River, which is located in the North of Iran. Our objective was to optimize the existing stations for drinking and irrigation purposes, separately. The technique includes two stages called data preparation and the optimization. On the data preparation stage, first the basin was divided into four sections and each section was consisted of some stations. Then, the score of each station was computed using the data provided by the water Research Institute of the Ministry of energy. After that, we applied a weighting method by providing questionnaires to ask the experts to define the significance of each parameter. In the next step, according to the scores, stations were prioritized cumulatively. Finally, the genetic algorithm was applied to identify the best combination. The results indicated that out of 21 existing monitoring stations, 14 stations should remain in the network for both irrigation and drinking purposes. The results also had a good compliance with the previous studies which used dynamic programming as the optimization technique.

• KIEAE Journal
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• v.16 no.5
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• pp.21-28
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• 2016

Purpose: The Objective of this study is to explore the capabilities of an integrated modelling and simulation workflow when applied to an experiment-based research process, aimed at deriving daylight optimization strategies specific to tall buildings. Methods: Two methods were devised to apply this workflow with the help of DIVA and Rhino/Grasshopper. The first method is a multiple variant analysis by setting up an appropriate base case and analysing its daylight and energy performance, forming the basis of comparison for subsequent cases for design variants. The second method involved setting up the base case within a site context and conducting a solar irradiation study. An architectural variables such as overhang and shading device, were then defined as inputs in the parametric definition in Grasshopper to control the selected variable. Results: While the first method took advantage of the speed and efficiency of the integrated workflow, the second method was derived based on the ability to directly process simulation data within the integrated, single-software platform of the proposed workflow. Through these methods, different architectural strategies were explored, both to increase daylight penetration and to reduce radiant heat gain. The focus is on methods by which this workflow can be applied to facilitate the experimental derivation of daylight optimization strategies that are specific to tall building design.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.1
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• pp.1-9
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• 2009

The objective of this paper was to evaluate the auto-calibration with multi-objective optimization method to calibrate the parameters of the Soil and Water Assessment Tool (SWAT) model. The model was calibrated and validated by using nine years (1996-2004) of measured data for the 384-ha Baran reservoir subwatershed located in central Korea. Multi-objective optimization was performed for sixteen parameters related to runoff. The parameters were modified by the replacement or addition of an absolute change. The root mean square error (RMSE), relative mean absolute error (RMAE), Nash-Sutcliffe efficiency index (EI), determination coefficient ($R^2$) were used to evaluate the results of calibration and validation. The statistics of RMSE, RMAE, EI, and $R^2$ were 4.66 mm/day, 0.53 mm/day 0.86, and 0.89 for the calibration period and 3.98 mm/day, 0.51 mm/day, 0.83, and 0.84 for the validation period respectively. The statistical parameters indicated that the model provided a reasonable estimation of the runoff at the study watershed. This result was illustrated with a multi-objective optimization for the flow at an observation site within the Baran reservoir watershed.

• Journal of the Society of Naval Architects of Korea
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• v.42 no.6 s.144
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• pp.654-665
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• 2005

In this paper, we present a non-linear integer programming by genetic algorithm (GA) for available sizes of stiffener or thickness of plate in a job site. GA can rapidly search for the approximate global optimum under complicated design environment such as ship. Meanwhile it can handle the optimization problem involving discrete design variable. However, there are many parameters have to be set for GA, which greatly affect the accuracy and calculation time of optimum solution. The setting process is hard for users, and there are no rules to decide these parameters. In order to overcome these demerits, the optimization for these parameters has been also conducted using GA itself. Also it is proved that the parameters are optimal values by the trial function. Finally, we applied this method to compass deck of ship where the vibration problem is frequently occurred to verify the validity and usefulness of nonlinear integer programming.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Applied Chemistry for Engineering
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• v.34 no.6
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• pp.619-625
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• 2023

In order to solve problems caused by the heat load of hypersonic aircraft, this study examined the optimization of the Si/Al ratio of the catalyst and nickel ion exchange to improve the performance of the hydrocarbon decomposition reaction (endothermic reaction). It was confirmed that the catalysts prepared through Si/Al ratio optimization and nickel ion exchange showed about 10% improvement in heat absorption performance compared to thermal cracking at 4 MPa and 550 ℃. FT-IR and NH₃-TPD analyses were found to identify factors affecting activity changes, and it was observed that the Si/Al ratio of the HZSM-5 catalyst was closely correlated with acid site development and catalytic activity. In addition, TGA and O₂-TPO analyses were conducted to observe the carbon deposition inhibition properties of the nickel-added catalyst.

• Journal of the Korean Society of Safety
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• v.33 no.6
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• pp.144-156
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• 2018

Level 3 Probabilistic Safety Assessment (PSA) is performed for the risk assessment that calculates radioactive material dispersion to the environment. This risk assessment is performed with a tool of MELCOR Accident Consequence Code System (MACCS2 or WinMACCS). For the off-site consequence analysis of multi-unit nuclear power plant (NPP) accident, the single location (Center Of Mass, COM) method has been usually adopted with the assumption that all the NPPs in the nuclear site are located at the same COM point. It was well known that this COM calculation can lead to underestimated or overestimated radionuclide concentration. In order to overcome this underestimation or overestimation of radionuclide concentrations in the COM method, Multiple Location (ML) method was developed in this study. The radionuclide concentrations for the individual NPPs are separately calculated, and they are summed at every location in the nuclear site by the post-processing of radionuclide concentrations that is based on two-dimensional Gaussian Plume equations. In order to demonstrate the efficiency of the ML method, radionuclide concentrations were calculated for the six-unit NPP site, radionuclide concentrations of the ML method were compared with those by COM method. This comparison was performed for conditions of constant weather, yearly weather in Korea, and four seasons, and the results were discussed. This new ML method (1) improves accuracy of radionuclide concentrations when multi-unit NPP accident occurs, (2) calculates realistic atmospheric dispersion of radionuclides under various weather conditions, and finally (3) supports off-site emergency plan optimization. It is recommended that this new method be applied to the risk assessment of multi-unit NPP accident. This new method drastically improves the accuracy of radionuclide concentrations at the locations adjacent to or very close to NPPs. This ML method has a great strength over the COM method when people live near nuclear site, since it provides accurate radionuclide concentrations or radiation doses.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1145-1156
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• 2022

In order to effectively secure site suitability for the development of large-scale offshore wind farms, it is essential to minimize the environmental impact of development and analyze the conflicts of benefit between social, ecological, and economic core values. In addition, a preliminary review of site adequacy must be preceded in order not to collide with other used areas in the marine spatial plan. In addition, it is necessary to conduct local meteorological characteristics analysis including wind resources near Jeollanam-do area before project feasibility study. Therefore, wind resource analysis was performed using the observation data of the meteorological mast installed in Wangdeungnyeo near Anmado, Yeonggwang, and the optimal site was selected after excluding geographical constraints related to the location of the offshore wind farm. In addition, the annual energy production was calculated by deriving the optimal wind farm arrangement results suitable for the local wind resources characteristics based on WindSim SW, and it is intended to be used as basic research data for site discovery and selection of suitable sites for future offshore wind farm projects.

• Journal of Environmental Science International
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• v.19 no.9
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• pp.1169-1175
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• 2010

A case study for the design of a wind farm in complex terrain was carried out using the wind farm site analysis software OpenWind, which has an open-source platform and is free to use. The Youngdeok Wind Farm, constructed on mountainous terrain in Korea, was chosen as a model site; the design process reproduced using OpenWind. A comparison of the positions of the wind turbine derived from the OpenWind optimization process and the current positions were in good agreement. The annual energy production predicted by OpenWind compared with the prediction by the micrositing software, WindSim, were also validated to within 1%. Therefore, it was confirmed that OpenWind can be used for a practical wind farm design project. It is also anticipating that this paper will provide a prototype process for the design of a wind farm site and offer a database for the post-evaluation of a constructed wind farm in Korea.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.286-290
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• 2011

This paper introduces the optimum macro-siting of a potential site for an offshore wind farm around Jeju Island using the RDAPS sea wind model. The statistical model was developed by analyzing the sea wind data from RDAPS model, and the meso-scale digital wind map was prepared. To develop the high resolution spatial calibration model, Artificial Neural Network(ANN) models were used to construct the wind and bathymetric maps. Accuracy and consistency of wind/bathymetric spatial calibration models were obtained using analysis of variance. The optimization problem was defined to maximize the energy density satisfying the criteria of maximum water depth and maximum distance from the coastline. The candidate site was selected through Genetic Algorithm(GA). From the results, it is possible to predict roughly a candidate site location for the installation of the offshore wind jam, and to evaluate the wind resources of the proposed site.