• International Journal of Highway Engineering
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• v.17 no.4
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• pp.11-18
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• 2015

PURPOSES: This study aims to evaluate the runoff reduction with permeable pavements using the SWMM analysis. METHODS: In this study, simulations were carried out using two different models, simple and complex, to evaluate the runoff reduction when an impermeable pavement is replaced with a permeable pavement. In the simple model, the target area for the analysis was grouped into four areas by the land use characteristics, using the statistical database. In the complex model, simulation was performed based on the data on the sewer and road network configuration of Yongsan-Gu Bogwang-Dong in Seoul, using the ArcGIS software. A scenario was created to investigate the hydro-performance of the permeable pavement based on the return period, runoff coefficient, and the area of permeable pavement that could be laid within one hour after rainfall. RESULTS : The simple modeling analysis results showed that, when an impervious pavement is replaced with a permeable pavement, the peak discharge reduced from $16.7m^3/s$ to $10.4m^3/s$. This represents a reduction of approximately 37.6%. The peak discharge from the whole basin showed a reduction of approximately 11.0%, and the quantity decreased from $52.9m^3/s$ to $47.2m^3/s$. The total flowoff reduced from $43,261m^3$ to $38,551m^3$, i.e., by approximately 10.9%. In the complex model, performed using the ArcGIS interpretation with fewer permeable pavements applicable, the return period and the runoff coefficient increased, and the total flowoff and peak discharge also increased. When the return period was set to 20 years, and a runoff coefficient of 0.05 was applied to all the roads, the total outflow reduced by $5195.7m^3$, and the ratio reduced to 11.7%. When the return period was increased from 20 years to 30 and 100 years, the total outflow reduction decreased from 11.7% to 8.0% and 5.1%, respectively. When a runoff coefficient of 0.5 was applied to all the roads under the return period of 20 years, the total outflow reduction was 10.8%; when the return period was increased to 30 and 100 years, the total outflow reduction decreased to 6.5% and 2.9%, respectively. However, unlike in the simple model, for all the cases in the complex model, the peak discharge reductions were less than 1%. CONCLUSIONS : Being one of the techniques for water circulation and runoff reduction, a high reduction for the small return period rainfall event of penetration was obtained by applying permeable pavements instead of impermeable pavement. With the SWMM analysis results, it was proved that changing to permeable pavement is one of the ways to effectively provide water circulation to various green infrastructure projects, and for stormwater management in urban watersheds.

• Journal of the Korea Institute of Building Construction
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• v.24 no.4
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• pp.447-458
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• 2024

This study investigates the effectiveness of Building Information Modeling(BIM) software, specifically SketchUp and Revit, in reducing errors during quantity take-off(QTO) for complex building elements. While 3D modeling offers advantages, existing software may not fully account for manufacturing discrepancies, such as variations in concrete cover thickness and reinforcing bar radius. To address this limitation, this research proposes a BIM-based QTO method for high-insulation wall panels with intricate details. The method utilizes a BIM family library, focusing on key parameters like concrete cover thickness and inner radius of shear reinforcement. A case study compared the cross-sectional details of a wall panel modeled in Revit with the actual manufactured specimen. The analysis revealed a 12% reduction in modeled concrete cover thickness and a 1.27 times larger modeled inner radius of the shear bar compared to the real-world values. The proposed method incorporates these manufacturing variations into the Revit model of the high-insulation wall panel. Software like Navisworks facilitates the identification and correction of any material interferences arising from these adjustments. Furthermore, the method employs a unit wall concept(1m²) to account for the volume of various materials, including insulation and splice sleeves at joints. This allows for the identification of a similar existing family within the BIM library(e.g., "Double RC wall with embedded insulation") that reflects the actual material quantities used in the wall panel. By incorporating these manufacturing-induced variations, the proposed method offers a more accurate QTO process for complex high-insulation wall panels. The "Double RC wall with embedded insulation" family within the Revit program serves as a valuable tool for material quantity estimation in such scenarios.

• Journal of the Korea Institute of Building Construction
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• v.24 no.5
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• pp.541-552
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• 2024

This study introduces a new analytical model known as the Cellular Automaton Method(CAM) designed to predict the degree of deterioration in concrete, taking into account its complex pore structure. The CAM model assesses the impacts of moisture migration, driven by capillary action and pressure differentials at the gas-liquid interface, which are influenced by the distribution of pores. It also evaluates how porosity and diffusion coefficients affect the penetration of chloride ions. The model's application revealed distinct moisture movement patterns in concrete structures, distinguishing between those with porosity levels below and above 40 percent. Additionally, it facilitated a comparison and analysis of chloride ion diffusion phenomena, based on diffusion coefficients in areas penetrated by moisture, against results obtained from the Finite Element Method(FEM). The comparison showed a maximum deviation of only 0.989 percent between the predicted outcomes of the FEM and CAM, demonstrating substantial agreement and validating CAM's efficacy in simulating the diffusion processes of chloride ions within concrete under actual salt damage conditions. Thus, CAM proves to be a reliable tool for modeling and anticipating deterioration in concrete structures exposed to saline environments.

• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.73-84
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• 2007

This paper was concerned about design and implementation of supply chain management for auto-part company by adopting a UML(Unified Modeling Language). The part of SCM and e-business have interested by larger company, researcher and academic professor. There has been known about a little implementing SCM and it's initiatives for SME(small-medium sized enterprise). We, in this paper, dealt with design and implementing the SCM on supply chain auto part SMEs. The UML is a standard language for specifying, visualizing, constructing, and documenting the artifacts of software systems. It simplifies the complex process of software design, making a blueprint for the SCM implementation. In this paper, we also adopt some methods for the systematic system analysis, design, and implementation by applying UML to a SCM system.

• Journal of Microbiology and Biotechnology
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• v.25 no.11
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• pp.1928-1935
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• 2015

Microbial growth kinetics is often used to optimize environmental processes owing to its relation to the breakdown of substrate (contaminants). However, the quantification of bacterial populations in the environment is difficult owing to the challenges of monitoring a specific bacterial population within a diverse microbial community. Conventional methods are unable to detect and quantify the growth of individual strains separately in the mixed culture reactor. This work describes a novel quantitative PCR (qPCR)-based genomic approach to quantify each species in mixed culture and interpret its growth kinetics in the mixed system. Batch experiments were performed for both single and dual cultures of Pseudomonas putida and Escherichia coli K12 to obtain Monod kinetic parameters (μ_max and K_s). The growth curves and kinetics obtained by conventional methods (i.e., dry weight measurement and absorbance reading) were compared with that obtained by qPCR assay. We anticipate that the adoption of this qPCR-based genomic assay can contribute significantly to traditional microbial kinetics, modeling practice, and the operation of bioreactors, where handling of complex mixed cultures is required.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

• 한국전산유체공학회:학술대회논문집
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• 2007.04a
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• pp.120-124
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• 2007

Helicopters and rotary-wing vehicles encounter a wide variety of complex aerodynamic phenomena and these phenomena present substantial challenges for computational fluid dynamics(CFD) models. This investigation presents the rotor aerodynamic analysis items for the helicopter development and variety aerodynamic analysis methods to provide the better solution to researchers and helicopter developers between aerodynamic problems and numerical aerodynamic analysis methods. The numerical methods to make an analysis of helicopter rotor are as below - CFD Modelling : actuator disk model, BET model, fully rotor model,... - Grid : sliding mesh, chimera mesh / structure mesh, unstructure mesh,... - etc. : panel method periodic boundary, quasi-steady simulation, incompressible,... The choice of CFD methodology and the numerical resolution for the overall problem have been driven mostly by available computer speed and memory at any point in time. The combination of the knowledge of aerodynamic analysis items, available computing power and choice of CFD methods now allows the solution of a number of important rotorcraft aerodynamics design problems.

• Nuclear Engineering and Technology
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• v.37 no.3
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• pp.207-220
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• 2005

Nuclear power plants (NPP) are complex socio-technological systems that rely on the success of both hardware and human components. Empirical studies of plant operating experience show that human errors are important contributors to accidents and incidents, and that organizational factors play an important role in creating contexts for human errors. Current probabilistic safety assessments (PSA) do not explicitly model the systematic contribution of organizational factors to safety. As some countries, like the United States, are moving towards increased use of risk information in the regulation and operation of nuclear facilities, PSA quality has been identified as an area for improvement. The modeling of human errors, and underlying organizational weaknesses at the root of these errors, are important sources of uncertainty in existing PSAs and areas of on-going research. This paper presents a review of research into the following questions: Is there evidence that organizational factors are important to NPP safety? How do organizations contribute to safety in NPP operations? And how can these organizational contributions be captured more explicitly in PSA? We present a few past incidents that illustrate the potential safety implications of organizational deficiencies, some mechanisms by which organizational factors contribute to NPP risk, and some of the methods proposed in the literature for performing root-cause analyses and including organizational factors in PSA.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.142-150
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• 2014

The key to model-based iterative reconstruction (MBIR) algorithms for transmission computed tomography lies in the ability to accurately model the data formation process from the emitted photons produced in the transmission source to the measured photons at the detector. Therefore, accurately modeling the system matrix that accounts for the data formation process is a prerequisite for MBIR-based algorithms. In this work we compared quantitative performance of the three representative ray-driven methods for calculating the system matrix; the ray-tracing method (RTM), the distance-driven method (DDM), and the strip-area based method (SAM). We implemented the ordered-subsets separable surrogates (OS-SPS) algorithm using the three different models and performed simulation studies using a digital phantom. Our experimental results show that, in spite of the more advanced features in the SAM and DDM, the traditional RTM implemented in the OS-SPS algorithm with an edge-preserving regularizer out-performs the SAM and DDM in restoring complex edges in the underlying object. The performance of the RTM in smooth regions was also comparable to that of the SAM or DDM.

• Journal of Power Electronics
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• v.6 no.2
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• pp.104-113
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• 2006

Satellites have provided the impetus for the orderly development of reliability engineering research and analysis because they tend to have complex systems and hence acute problems. They were instrumental in developing mathematical models for reliability, as well as design techniques to permit quantitative specification, prediction and measurement of reliability. Reliability engineering is based on implementing measures which insure an item will perform its mission successfully. The discipline of reliability engineering consists of two fundamental aspects; $(1^{st})$ paying attention to details, and $(2^{nd})$ handling uncertainties. This paper uses some of the basic concepts, formulas and examples of reliability theory in application. This paper emphasizes the practical reliability analysis of a Low Earth Orbit (LEO) Micro-satellite power subsystem. Approaches for specifying and allocating the reliability of each element of the power system so as to meet the overall power system reliability requirements, as well as to give detailed modeling and predicting of equipment/system reliability are introduced. The results are handled and analyzed to form the final reliability results for the satellite power system. The results show that the Electric Power Subsystem (EPS) reliability meets the requirements with quad microcontrollers (MC), two boards working as main and cold redundant while each board contains two MCs in a hot redundant.