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      KCI등재 SCIE SCOPUS

      Developing an optimal valve closing rule curve for real-time pressure control in pipes

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      https://www.riss.kr/link?id=A103789918

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      다국어 초록 (Multilingual Abstract)

      Sudden valve closure in pipeline systems can cause high pressures that may lead to serious damages. Using an optimal valve closing rule can play an important role in managing extreme pressures in sudden valve closure. In this paper, an optimal closing...

      Sudden valve closure in pipeline systems can cause high pressures that may lead to serious damages. Using an optimal valve closing rule can play an important role in managing extreme pressures in sudden valve closure. In this paper, an optimal closing rule curve is developed using a multi-objective optimization model and Bayesian networks (BNs) for controlling water pressure in valve closure instead of traditional step functions or single linear functions. The method of characteristics is used to simulate transient flow caused by valve closure. Non-dominated sorting genetic algorithms-II is also used to develop a Pareto front among three objectives related to maximum and minimum water pressures, and the amount of water passes through the valve during the valve-closing process. Simulation and optimization processes are usually time-consuming, thus results of the optimization model are used for training the BN. The trained BN is capable of determining optimal real-time closing rules without running costly simulation and optimization models. To demonstrate its efficiency, the proposed methodology is applied to a reservoir-pipe-valve system and the optimal closing rule curve is calculated for the valve. The results of the linear and BN-based valve closure rules show that the latter can significantly reduce the range of variations in water hammer pressures.

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      참고문헌 (Reference)

      1 N. Joukowsky, "Über den hydraulischen Stoss in Wasserleitungsröhren (On the hydraulic hammer in water supply pipes)" 8, 9 (8, 9): 1-71, 1898

      2 S. E. Fienberg, "When did Bayesian inference become Bayesian?" 1 (1): 1-40, 2006

      3 A. Abed-Elmdoust, "Wave height prediction using the rough set theory" 54 : 244-250, 2012

      4 M. R. Reed, "Striking the balance longterm groundwater monitoring design for conflicting objectives" 130 (130): 140-149, 2004

      5 K. Hariri-Asli, "Some aspects of physical and numerical modeling of water hammer in pipelines" 60 (60): 677-701, 2010

      6 M. Rohani, "Simulation of transient flow caused by pump failure: Point-Implicit Method of Characteristics" 37 (37): 1742-1750, 2010

      7 D. Mokeddem, "Optimal solutions of multiproduct batch chemical process using multiobjective genetic algorithm with expert decision system" 2009 : 2009

      8 W. Tian, "Numerical simulation and optimization on valve-induced water hammer characteristics for parallel pump feed water system" 35 (35): 2280-2287, 2008

      9 S. R. M. Yandamuri, "Multiobjective optimal waste load allocation models for rivers using Non-dominated sorting genetic algorithm-II" 132 (132): 133-143, 2006

      10 S. Dorner, "Multi-objective modelling and decision support using a Bayesian network approximation to a non-point source pollution model" 22 (22): 211-222, 2007

      1 N. Joukowsky, "Über den hydraulischen Stoss in Wasserleitungsröhren (On the hydraulic hammer in water supply pipes)" 8, 9 (8, 9): 1-71, 1898

      2 S. E. Fienberg, "When did Bayesian inference become Bayesian?" 1 (1): 1-40, 2006

      3 A. Abed-Elmdoust, "Wave height prediction using the rough set theory" 54 : 244-250, 2012

      4 M. R. Reed, "Striking the balance longterm groundwater monitoring design for conflicting objectives" 130 (130): 140-149, 2004

      5 K. Hariri-Asli, "Some aspects of physical and numerical modeling of water hammer in pipelines" 60 (60): 677-701, 2010

      6 M. Rohani, "Simulation of transient flow caused by pump failure: Point-Implicit Method of Characteristics" 37 (37): 1742-1750, 2010

      7 D. Mokeddem, "Optimal solutions of multiproduct batch chemical process using multiobjective genetic algorithm with expert decision system" 2009 : 2009

      8 W. Tian, "Numerical simulation and optimization on valve-induced water hammer characteristics for parallel pump feed water system" 35 (35): 2280-2287, 2008

      9 S. R. M. Yandamuri, "Multiobjective optimal waste load allocation models for rivers using Non-dominated sorting genetic algorithm-II" 132 (132): 133-143, 2006

      10 S. Dorner, "Multi-objective modelling and decision support using a Bayesian network approximation to a non-point source pollution model" 22 (22): 211-222, 2007

      11 R. E. Neapolitan, "Learning Bayesian networks" Prentice Hall Series in Artificial Intelligence 2003

      12 A. Bergant, "Further investigation of parameters affecting water hammer wave attenuation, shape and timing" 1-12, 2003

      13 A. Ismaier, "Fluid dynamic interaction between water hammer and centrifugal pumps" 239 (239): 3151-3154, 2009

      14 E. B. Wylie, "Fluid Transients in Systems" Prentice Hall 1993

      15 E. B. Wylie, "Fluid Transients" McGraw-Hill 1978

      16 I. Malekmohamadi, "Evaluating the efficacy of SVMs, BNs, ANNs and ANFIS in wave height prediction" 38 (38): 487-497, 2011

      17 S. M. Mesbah, "Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks" 24 (24): 238-246, 2009

      18 H. Afshar, "Developing a closing rule curve for valves in pipelines to control the water hammer impacts: Application of the NSGA-II optimization model" 1-10, 2008

      19 B. Malekmohammadi, "Developing Monthly Operating Rules for a Cascade System of Reservoirs: Application of Bayesian Networks" 24 (24): 1420-1432, 2009

      20 P. A. Aguilera, "Bayesian networks in environmental modeling" 26 (26): 1376-1388, 2011

      21 D. N. Barton, "Bayesian belief networks as a meta-modelling tool in integrated river basin management - Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin" 66 : 91-104, 2008

      22 P. Congdon, "Bayesian Statistical Modelling" Second Ed.Wiley 2001

      23 F. V. Jensen, "Bayesian Networks and Decision Graphs" Springer-Verlag 2001

      24 이준신, "Analysis of water hammer in pipelines by partial fraction expansion of transfer function in frequency domain" 대한기계학회 24 (24): 1975-1980, 2010

      25 W. Barten, "Analysis of the capability of system codes to model cavitation water hammers: Simulation of UMSCIT water hammer experiments with TRACE and RELAP5" 238 : 1129-1145, 2008

      26 M. S. Ghidaoui, "A review of water hammer theory and practice" 58 (58): 49-76, 2005

      27 W. Buntine, "A guide to the literature on learning probabilistic network from data" 8 (8): 195-210, 1996

      28 R. Kerachian, "A fuzzy game theoretic approach for groundwater resources management: Application of Rubinstein Bargaining Theory" 54 (54): 673-682, 2010

      29 K. Deb, "A fast elitist non-dominated sorting genetic algorithm for multiobjective optimization" Indian Institute of Technology 2000

      30 M. R. Bazargan-Lari, "A conflict resolution model for conjunctive use of surface and groundwater resources considering the water-quality issues: A case study" 43 (43): 470-482, 2009

      31 K. Deb, "A Fast and elitist multiobjective genetic algorithm" 6 (6): 182-197, 2002

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2023 평가예정 해외DB학술지평가 신청대상 (해외등재 학술지 평가)
      2020-01-01 평가 등재학술지 유지 (해외등재 학술지 평가) KCI등재
      2012-11-05 학술지명변경 한글명 : 대한기계학회 영문 논문집 -> Journal of Mechanical Science and Technology KCI등재
      2010-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2008-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2006-01-19 학술지명변경 한글명 : KSME International Journal -> 대한기계학회 영문 논문집
      외국어명 : KSME International Journal -> Journal of Mechanical Science and Technology
      KCI등재
      2006-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2004-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2001-01-01 평가 등재학술지 선정 (등재후보2차) KCI등재
      1998-07-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 1.04 0.51 0.84
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.74 0.66 0.369 0.12
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