• Title/Summary/Keyword: lead optimization

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A Method to Calculate Off-site Radionuclide Concentration for Multi-unit Nuclear Power Plant Accident (다수기 원자력발전소 사고 시 소외 방사성물질 농도 계산 방법)

  • Lee, Hye Rin;Lee, Gee Man;Jung, Woo Sik
    • 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.

A Study on the Optimization Model for the Project Portfolio Manpower Assignment Using Genetic Algorithm (유전자 알고리즘을 이용한 프로젝트 포트폴리오 투입인력 최적화 모델에 관한 연구)

  • Kim, Dong-Wook;Lee, Won-Young
    • Journal of Information Technology Services
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    • v.17 no.4
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    • pp.101-117
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    • 2018
  • Companies are responding appropriately to the rapidly changing business environment and striving to lead those changes. As part of that, we are meeting our strategic goals through IT projects, which increase the number of simultaneous projects and the importance of project portfolio management for successful project execution. It also strives for efficient deployment of human resources that have the greatest impact on project portfolio management. In the early stages of project portfolio management, it is very important to establish a reasonable manpower plan and allocate performance personnel. This problem is a problem that can not be solved by linear programming because it is calculated through the standard deviation of the input ratio of professional manpower considering the uniformity of load allocated to the input development manpower and the importance of each project. In this study, genetic algorithm, one of the heuristic methods, was applied to solve this problem. As the objective function, we used the proper input ratio of projects, the input rate of specialist manpower for important projects, and the equal load of workload by manpower. Constraints were not able to input duplicate manpower, Was used as a condition. We also developed a program for efficient application of genetic algorithms and confirmed the execution results. In addition, the parameters of the genetic algorithm were variously changed and repeated test results were selected through the independent sample t test to select optimal parameters, and the improvement effect of about 31.2% was confirmed.

A cylindrical shell model for nonlocal buckling behavior of CNTs embedded in an elastic foundation under the simultaneous effects of magnetic field, temperature change, and number of walls

  • Timesli, Abdelaziz
    • Advances in nano research
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    • v.11 no.6
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    • pp.581-593
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    • 2021
  • This model is proposed to describe the buckling behavior of Carbon Nanotubes (CNTs) embedded in an elastic medium taking into account the combined effects of the magnetic field, the temperature, the nonlocal parameter, the number of walls. Using Eringen's nonlocal elasticity theory, thin cylindrical shell theory and Van der Waal force (VdW) interactions, we develop a system of partial differential equations governing the buckling response of CNTs embedded on Winkler, Pasternak, and Kerr foundations in a thermal-magnetic environment. The pre-buckling stresses are obtained by applying airy's stress function and an adjacent equilibrium criterion. To estimate the nonlocal critical buckling load of CNTs under the simultaneous effects of the magnetic field, the temperature change, and the number of walls, an optimization technique is proposed. Furthermore, analytical formulas are developed to obtain the buckling behavior of SWCNTs embedded in an elastic medium without taking into account the effects of the nonlocal parameter. These formulas take into account VdW interactions between adjacent tubes and the effect of terms involving differences in tube radii generally neglected in the derived expressions of the critical buckling load published in the literature. Most scientific research on modeling the effects of magnetic fields is based on beam theories, this motivation pushes me to develop a cylindrical shell model for studying the effect of the magnetic field on the static behavior of CNTs. The results show that the magnetic field has significant effects on the static behavior of CNTs and can lead to slow buckling. On the other hand, thermal effects reduce the critical buckling load. The findings in this work can help us design of CNTs for various applications (e.g. structural, electrical, mechanical and biological applications) in a thermal and magnetic environment.

Research to Minimize Endoscope and Objective-lens Sensitivity Using Multi-configurations (다중 구성을 이용한 내시경 및 대물렌즈 광학계 공차 민감도 최소화 설계 기술)

  • Jung, Mee-Suk
    • Korean Journal of Optics and Photonics
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    • v.32 no.6
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    • pp.259-265
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    • 2021
  • Recently, lens manufacturing and assembly technology has greatly improved. However, tight requirements of manufacturing and assembly lead to an increase in cost and manufacturing time, and in some cases the performance of an optical system may deteriorate depending on the operating environment's conditions, such as temperature or vibration. In addition, the use of a compensator is an effective method to reduce sensitivity in an ultra-precision optical system, but in the case of a small lens, such as that in an endoscope, it is difficult to use a compensator due to the size limitation of the lens barrel. Therefore, minimizing lens sensitivity is the most important technology in lens design. For this reason, there have been various attempts to reduce the lens sensitivity, and there is a trend to add functions to reduce the sensitivity in the lens design S/W. In this paper, we introduce a design technology that minimizes lens sensitivity. We first design a lens with quite good performance, then analyze the sensitivity of this lens, make a multi-configuration with high-sensitivity element error, and then reoptimize it. We prove with an example that this design technique is very effective.

Script-based Test System for Rapid Verification of Atomic Models in Discrete Event System Specification Simulation

  • Nam, Su-Man
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.5
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    • pp.101-107
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    • 2022
  • Modeling and simulation is a technique used for operational verification, performance analysis, operational optimization, and prediction of target systems. Discrete Event System Specification (DEVS) of this representative technology defines models with a strict formalism and stratifies the structures between the models. When the atomic DEVS models operate with an intention different the target system, the simulation may lead to erroneous decision-making. However, most DEVS systems have the exclusion of the model test or provision of the manual test, so developers spend a lot of time verifying the atomic models. In this paper, we propose a script-based automated test system for accurate and fast validation of atomic models in Python-based DEVS. The proposed system uses both the existing method of manual testing and the new method of the script-based testing. As Experimental results in our system, the script-based test method was executed within 24 millisecond when the script was executed 10 times consecutively. Thus, the proposed system guarantees a fast verification time of the atomic models in our script-based test and improves the reusability of the test script.

Energy Management and Performance Evaluation of Fuel Cell Battery Based Electric Vehicle

  • Khadhraoui, Ahmed;SELMI, Tarek;Cherif, Adnene
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.37-44
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    • 2022
  • Plug-in Hybrid electric vehicles (PHEV) show great potential to reduce gas emission, improve fuel efficiency and offer more driving range flexibility. Moreover, PHEV help to preserve the eco-system, climate changes and reduce the high demand for fossil fuels. To address this; some basic components and energy resources have been used, such as batteries and proton exchange membrane (PEM) fuel cells (FCs). However, the FC remains unsatisfactory in terms of power density and response. In light of the above, an electric storage system (ESS) seems to be a promising solution to resolve this issue, especially when it comes to the transient phase. In addition to the FC, a storage system made-up of an ultra-battery UB is proposed within this paper. The association of the FC and the UB lead to the so-called Fuel Cell Battery Electric Vehicle (FCBEV). The energy consumption model of a FCBEV has been built considering the power losses of the fuel cell, electric motor, the state of charge (SOC) of the battery, and brakes. To do so, the implementing a reinforcement-learning energy management strategy (EMS) has been carried out and the fuel cell efficiency has been optimized while minimizing the hydrogen fuel consummation per 100km. Within this paper the adopted approach over numerous driving cycles of the FCBEV has shown promising results.

Optimization of SnO2 Based H2 Gas Sensor Along with Thermal Treatment Effect (열처리 효과에 따른 SnO2 기반 수소가스 센서의 특성 최적화)

  • Jung, Dong Geon;Lee, Junyeop;Kwon, Jinbeom;Maeng, Bohee;Kim, Young Sam;Yang, Yi Jun;Jung, Daewoong
    • Journal of Sensor Science and Technology
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    • v.31 no.5
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    • pp.348-352
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    • 2022
  • Hydrogen gas (H2) which is odorless, colorless is attracting attention as a renewable energy source in varions applications but its leakage can lead to disastrous disasters, such as inflammable, explosive, and narcotic disasters at high concentrations. Therefore, it is necessary to develop H2 gas sensor with high performance. In this paper, we confirmed that H2 gas detection ability of SnO2 based H2 gas sensor along with thermal treatment effect of SnO2. Proposed SnO2 based H2 gas sensor is fabricated by MEMS technologies such as photolithgraphy, sputtering and lift-off process, etc. Deposited SnO2 thin films are thermally treated in various thermal treatement temperature in range of 500-900 ℃ and their H2 gas detection ability is estimatied by measuring output current of H2 gas sensor. Based on experimental results, fabricated H2 gas sensor with SnO2 thin film which is thermally treated at 700 ℃ has a superior H2 gas detection ability, and it can be expected to utilize at the practical applications.

Pathogenesis and Prevention of Intraventricular Hemorrhage in Preterm Infants

  • Pei-Chen Tsao
    • Journal of Korean Neurosurgical Society
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    • v.66 no.3
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    • pp.228-238
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    • 2023
  • Intraventricular hemorrhage (IVH) is a serious concern for preterm infants and can predispose such infants to brain injury and poor neurodevelopmental outcomes. IVH is particularly common in preterm infants. Although advances in obstetric management and neonatal care have led to a lower mortality rate for preterm infants with IVH, the IVH-related morbidity rate in this population remains high. Therefore, the present review investigated the pathophysiology of IVH and the evidence related to interventions for prevention. The analysis of the pathophysiology of IVH was conducted with a focus on the factors associated with cerebral hemodynamics, vulnerabilities in the structure of cerebral vessels, and host or genetic predisposing factors. The findings presented in the literature indicate that fluctuations in cerebral blood flow, the presence of hemodynamic significant patent ductus arteriosus, arterial carbon dioxide tension, and impaired cerebral venous drainage; a vulnerable or fragile capillary network; and a genetic variant associated with a mechanism underlying IVH development may lead to preterm infants developing IVH. Therefore, strategies focused on antenatal management, such as routine corticosteroid administration and magnesium sulfate use; perinatal management, such as maternal transfer to a specialized center; and postnatal management, including pharmacological agent administration and circulatory management involving prevention of extreme blood pressure, hemodynamic significant patent ductus arteriosus management, and optimization of cardiac function, can lower the likelihood of IVH development in preterm infants. Incorporating neuroprotective care bundles into routine care for such infants may also reduce the likelihood of IVH development. The findings regarding the pathogenesis of IVH further indicate that cerebrovascular status and systemic hemodynamic changes must be analyzed and monitored in preterm infants and that individualized management strategies must be developed with consideration of the risk factors for and physiological status of each preterm infant.

MODELING ACCURATE INTEREST IN CASH FLOWS OF CONSTRUCTION PROJECTS TOWARD IMPROVED FORECASTING OF COST OF CAPITAL

  • Gunnar Lucko;Richard C. Thompson, Jr.
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.467-474
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    • 2013
  • Construction contactors must continuously seek to improve their cash flows, which reside at the heart of their financial success. They require careful planning, analysis, and optimization to avoid the risk of bankruptcy, remain profitable, and secure long-term growth. Sources of cash include bank loans and retained earnings, which are conceptually similar in that they both incur a cost of capital. Financial management therefore requires accurate yet customizable modeling capabilities that can quantify all expenses, including said cost of capital. However, currently existing cash flow models in construction engineering and management have strongly simplified the manner in which interest is assessed, which may even lead to overstating it at a disadvantage to contractors. The variable nature of cash balances, especially in the early phases of construction projects, contribute to this challenging issue. This research therefore extends a new cash flow model with an accurate interest calculation. It utilizes singularity functions, so called because of their ability to flexibly model changes across any number of different ranges. The interest function is continuous for activity costs of any duration and allows the realistic case that activities may begin between integer time periods, which are often calendar months. Such fractional interest calculation has hitherto been lacking from the literature. It also provides insights into the self-referential behavior of compound interest for variable cash balances. The contribution of this study is twofold; augmenting the corpus of financial analysis theory with a new interest formula, whose strengths include its generic nature and that it can be evaluated at any fractional value of time, and providing construction managers with a tool to help improve and fine-tune the financial performance of their projects.

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Lip-Synch System Optimization Using Class Dependent SCHMM (클래스 종속 반연속 HMM을 이용한 립싱크 시스템 최적화)

  • Lee, Sung-Hee;Park, Jun-Ho;Ko, Han-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.7
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    • pp.312-318
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    • 2006
  • The conventional lip-synch system has a two-step process, speech segmentation and recognition. However, the difficulty of speech segmentation procedure and the inaccuracy of training data set due to the segmentation lead to a significant Performance degradation in the system. To cope with that, the connected vowel recognition method using Head-Body-Tail (HBT) model is proposed. The HBT model which is appropriate for handling relatively small sized vocabulary tasks reflects co-articulation effect efficiently. Moreover the 7 vowels are merged into 3 classes having similar lip shape while the system is optimized by employing a class dependent SCHMM structure. Additionally in both end sides of each word which has large variations, 8 components Gaussian mixture model is directly used to improve the ability of representation. Though the proposed method reveals similar performance with respect to the CHMM based on the HBT structure. the number of parameters is reduced by 33.92%. This reduction makes it a computationally efficient method enabling real time operation.