Tae-Kyung Lim;Chang-Baek Son;Jae-Jin Son;Dong-Eun Lee
International conference on construction engineering and project management
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2009.05a
/
pp.409-416
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2009
This paper presents a tool called Quality-Cost optimization system (QCOS), which integrates Multi-Objective Genetic Algorithm (MOGA) and Quality Function Deployment (QFD), for tradeoff between quality and cost of the unitized metal curtain-wall unit. A construction owner as the external customer pursues to maximize the quality of the curtain-wall unit. However, the contractor as the internal customer pursues to minimize the cost involved in designing, manufacturing and installing the curtain-wall unit. It is crucial for project manager to find the tradeoff point which satisfies the conflicting interests pursued by the both parties. The system would be beneficial to establish a quality plan satisfying the both parties. Survey questionnaires were administered to the construction owner who has an experience of curtain-wall project, the architects who are the independent assessor, and the contractors who were involved in curtain-wall design and installation. The Customer Requirements (CRs) and their importance weights, the relationship between CRs and Technical Attributes (TAs) consisting of a curtain-wall unit, and the cost ratios of each components consisting curtain-wall unit are obtained from the three groups mentioned previously. The data obtained from the surveys were used as the QFD input to compute the Owner Satisfaction (OS) and Contractor Satisfaction (CS). MOGA is applied to optimize resource allocation under limited budget when multi-objectives, OS and CS, are pursued at the same time. The deterministic multi-objective optimization method using MOGA and QFD is extended to stochastic model to better deal with the uncertainties of QFD input and the variability of QFD output. A case study demonstrates the system and verifies the system conformance.
Korean Journal of Construction Engineering and Management
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v.24
no.2
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pp.37-49
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2023
In this study, we proposed resource allocation methodologies to improve the productivity of steel bridge manufacturing plants based on the constraint theory which is very popular in the area of manufacturing industries. To this end, after defining the painting process as a bottleneck, three resource allocation methodologies were developed: Operation Specific Resource Allocation (OSRA), Product Specific Resource Allocation (PSRA), and General Resource Allocation (GRA). As a result of experiments for performance evaluation using a simulation model of the steel bridge supply chain, GRA showed the best performance in terms of the Number of Work-In-Process (NWIP) and Waiting Time (WT), in particular, as workload itself and its variability were increased, the performance gap with the specific resource allocation became further deepened. On average, GRA reduced NWIP by 36.2% and WT by 34.6% compared to OSRA, and reduced NWIP by 71.0% and WT by 70.4% compared to PSRA. The reduction of NWIP and WT means alleviating the bottleneck of the painting process, which eventually means that the productivity of the steel bridge manufacturing plant has improved.
We investigated Soil respiration in Bluepine forest of western Bhutan, in relation to soil temperature, moisture content and soil pH and it was aimed at establishing variability in space and time. The Bluepine forest thrives in the typical shallow dry valleys in the inter-montane Bhutan Himalaya, which is formed by ascending wind from the valley bottom, which carries moisture from the river away to the mountain ridges. Stratified random sampling was applied and the study site was classified into top, mid, low slope and further randomized sample of n=20 from 30 m×30 m from each altitude. The overall soil respiration mean for the forest was found 2248.17 CO2 g yr-1 and it is ~613.58 C g yr-1. The RS from three sites showed a marginal variation amongst sites, lower slope (2,309 m) was 4.64 μ mol m-2 s-1, mid slope (2,631 m) was 6.78 μ mol m-2 s-1 and top slope (3,027 m) was 6.33 μ mol m-2 s-1 and mean of 5.92 μ mol m-2 s-1, SE=0.25 for the forest. Temporal distribution and variations were observed more pronounced than in the space variation. Soil respiration was found highest during March and lowest in September. Soil temperature had almost inverse trend against soil respiration and dropped a low in February and peak in July. The moisture in the soil changed across months with precipitation and pH remained almost consistent across the period. The soil respiration and soil temperature had significant relationship R2=-0.61, p=0.027 and other variables were found insignificant. Similar relationship are reported for dry season in a tropical forest soil respiration. Soil temperature was found to have most pronounced effect on the soil respiration of the forest under study.
Jiwoo Han;Yong-Chul Cho;Soyoung Lee;Sanghun Kim;Taegu Kang
Journal of Korean Society on Water Environment
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v.39
no.1
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pp.46-60
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2023
Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.
Kim, Dong-Hee;Bae, Kyung-Doo;Ko, Seong-Kwon;Lee, Woo-Jin
Journal of the Korean Geotechnical Society
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v.26
no.9
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pp.25-35
/
2010
Settlement at reclamation area caused by secondary compression should be considered using spatial evaluating method because the thickness of consolidation layer varies at every location. Probabilistic method can be implemented to evaluate uncertainty of spatial distribution of secondary compression. This study spatially evaluated mean and standard deviation of secondary compression in the overall analyzing region using spatial distribution of consolidation thickness estimated by ordinary kriging method and statistical values of soil properties. And then, the area where secondary compression exceeds a design criterion at the specific time was evaluated using probabilistic method. It was observed that the area exceeding the design criterion increased as the variability of $C_{\alpha}/(1+e_o)$ increased or the probabilistic design criterion 0: decreased. It is considered that the probabilistic method can be used for the geotechnical design of soft ground when a probabilistic design criterion is established in the specification.
MESSIER is a science satellite project to observe the Low Surface Brightness (LSB) sky at UV and optical wavelengths. The wide-field, optical system of MESSIER is optimized minimizing optical aberrations through the use of a Linear Astigmatism Free - Three Mirror System (LAF-TMS) combined with freeform mirrors. One of the key factors in observations of the LSB is the shape and spatial variability of the Point Spread Function (PSF) produced by scatterings and diffraction effects within the optical system and beyond (baffle). To assess the various factors affecting the PSF in this design, we use PhoSim, the Photon simulator, which is a fast photon Monte Carlo code designed to include all these effects, and also atmospheric effects (for ground-based telescopes) and phenomena occurring inside of the sensor. PhoSim provides very realistic simulations results and is suitable for simulations of very weak signals. Before the application to the MESSIER optics system, PhoSim had not been validated for confocal off-axis reflective optics (LAF-TMS). As a verification study for the LAF-TMS design, we apply Phosim sequentially. First, we use a single parabolic mirror system and compare the PSF results of the central field with the results from Zemax, CODE V, and the theoretical Airy pattern. We then test a confocal off-axis Cassegrain system and check PhoSim through cross-validation with CODE V. At the same time, we describe the shapes of the freeform mirrors with XY and Zernike polynomials. Finally, we will analyze the LAF-TMS design for the MESSIER optical system.
Vetriselvi Sampath;Shanmugam Sureshkumar;Woo Jeong Seok;In Ho Kim
Journal of Animal Science and Technology
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v.65
no.3
/
pp.479-489
/
2023
Livestock production depends on the utilization of nutrients, and when this is accomplished, there is accelerated momentum toward growth with a low cost-to-feed ratio. Public concern over the consumption of pork with antibiotic residues in animals fed antibiotic growth promoters (AGP) has paved the way for using other natural additives to antibiotics, such as herbs and their products, probiotics, prebiotics, etc. Numerous feed additives are trending to achieve this goal, and a classic example is vitamins and minerals. Vitamins and minerals represent a relatively small percentage of the diet, but they are critical to animal health, well-being, and performance; both play a well-defined role in metabolism, and their requirements can vary depending on the physiological stage of the animals. At the same time, the absence of these vitamins and minerals in animal feed can impair the growth and development of muscles and bones. Most commercial feeds contain vitamins and trace minerals that meet nutrient requirements recommended by National Research Council and animal feeding standards. However, the potential variability and bioavailability of vitamins and trace elements in animal feeds remain controversial because daily feed intake varies, and vitamins are degraded by transportation, storage, and processing. Accordingly, the requirement for vitamins and minerals may need to be adjusted to reflect increased production levels, yet the information presented on this topic is still limited. Therefore, this review focuses on the role and function of different sources of minerals, the mode of action, the general need for micro and macro minerals in non-ruminant diets, and how they improve animal performance.
Journal of the Society of Naval Architects of Korea
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v.60
no.3
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pp.202-211
/
2023
The profile shops in shipyards produce section steels required for block production of ships. Due to the limitations of shipyard's production capacity, a considerable amount of work is already outsourced. In addition, the need to improve the productivity of the profile shops is growing because the production volume is expected to increase due to the recent boom in the shipbuilding industry. In this study, a scheduling optimization was conducted for a parallel welding line of the profile process, with the aim of minimizing tardiness and the number of set-up changes as objective functions to achieve productivity improvements. In particular, this study applied a dynamic scheduling method to determine the job sequence considering variability of processing time. A Markov decision process model was proposed for the job sequence problem, considering the trade-off relationship between two objective functions. Deep reinforcement learning was also used to learn the optimal scheduling policy. The developed algorithm was evaluated by comparing its performance with priority rules (SSPT, ATCS, MDD, COVERT rule) in test scenarios constructed by the sampling data. As a result, the proposed scheduling algorithms outperformed than the priority rules in terms of set-up ratio, tardiness, and makespan.
Reliable prediction of the motion of FOWT (floating offshore wind turbine) and associated mooring line tension is important in both design and operation/monitoring processes. In the present study, a 5MW OC4 semisubmersible wind turbine is numerically modeled, simulated, and analyzed by the open-source numerical tool, OpenFAST and in-house numerical tool, Charm3D-FAST. Another commercial-level program FASTv8-OrcaFlex is also introduced for comparison for selected cases. The three simulation programs solve the same turbine-floater-mooring coupled dynamics in time domain while there exist minor differences in the details of the program. Both the motions and mooring-line tensions are calculated and compared with the DeepCWind 1/50 scale model-testing results. The system identification between the numerical and physical models is checked through the static-offset test and free-decay test. Then the system motions and mooring tensions are systematically compared among the simulated results and measured values. Reasonably good agreements between the simulation and measurement are demonstrated for (i) white-noise random waves, (ii) typical random waves, and (iii) typical random waves with steady wind. Based on the comparison between numerical results and experimental data, the relative importance and role of the differences in the numerical methodologies of those three programs can be observed and interpreted. These comparative-study results may provide a certain confidence level and some insight of potential variability in motion and tension predictions for future FOWT designs and applications.
Proceedings of the Korea Water Resources Association Conference
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2022.05a
/
pp.329-329
/
2022
Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.
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