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| 1 | VISUALIZATION OF TURBULENT REACTIVE JET BY USING DIRECT NUMERICAL SIMULATION显示文摘Direct numerical simulation(DNS)of turbulent planar jet with a second-order chemical reaction(A+B→R)is performed to investigate the processes of mixing and chemical reactions in spatially developing turbulent free shear flows.Reactant A is premixed into the jet flow,and reactant B is premixed into the ambient flow.DNS is performed at three different Damk¨ohler numbers(Da=0.1,1,and 10).Damk¨ohler number is a ratio of a time scale of a flow to that of chemical reactions,and in this study,the large Da means a fast chemical reaction,and the small Da means a slow chemical reaction.The visualization of velocity field shows that the jet flow is developed by entraining the ambient fluid.The visualization of concentration of reactant A shows that concentration of reactant A for Da=1 and 10 becomes very small in the downstream region because the chemical reaction consumes the reactants and reactant A is diffused with the jet development.By comparison of the profiles of chemical reaction rate and concentration of product R,it is found that product R for Da=10 is produced by the chemical reaction at the interface between the jet and the ambient fluids and is diffused into the jet flow,whereas product R for Da=0.1 is produced in the jet flow after reactants A and B are well mixed. | TOMOAKI WATANABE YASUHIKO SAKAI KOUJI NAGATA OSAMU TERASHIMA HIROKI SUZUKI TOSHIYUKI HAYASE YASUMASA ITO | 2013 | International Journal of Modeling, Simulation, and Scientific Computing2013，4，S01： | 2 |
| 2 | Unsupervised method of clustering and labeling of the online product based on reviews显示文摘This paper presents an unsupervised approach to cluster reviews of products collected from Amazon and then generates its labels of each cluster.Instead of using a complete review,this paper splits a review into sentences and considers all sentences from the reviews as inputs for Clustering.Hierarchical Agglomerative Clustering(HAC)is used to cluster sentences.The approaches of cluster labeling are also unsupervised.For labeling,three different methods have been used to find a limited number of essential words for each cluster.Extracted essential words are used to construct phrases.Constructed phrases are used as labels for each cluster.This paper compares the result of the labeling method with baseline labeling.In the result evaluation,all the labeling methods outperform the baseline method.The aim of this research is cluster labeling that makes a set of labels to describe a cluster content and distinguishes the labels from other cluster labels. | Md Masum Billah Mohammad Nuruzzaman Bhuiyan Md.Akterujjaman | 2021 | International Journal of Modeling, Simulation, and Scientific Computing2021，12，2： | 2 |
| 3 | A study of container yard equipment al- location strategy in Hongkong显示文摘 | LAI K LAM K | 1994 | International Journal of Modeling and Simulation1994，14，3： | 1 |
| 4 | Tandem nozzles supersonic wind tunnel design 显示文摘 | WU JIE | 2013 | International Journal of Engineering systems Modeling and Simulation2013，5，1： | 1 |
| 5 | Harmony search optimization: Application to pipe network design显示文摘 | Gecrn Z Kim J Loganathan G | 2002 | International Journal of Model Simulation2002，22，2： | 1 |
| 6 | A study of container yard equipment allocation strategy in Hong Kong 显示文摘 | LAI K LAM K | 1994 | International Journal of Modeling and Simulation1994，14，3： | 1 |
| 7 | Harmonysearch optimization : applicationto pipe net work design 显示文摘 | Geem Z W Kim J H Loganathan G V | 2002 | International Journal of Model Simulation2002，22，2： | 1 |
| 8 | Agent-based dynamic simulation of an electricity market with multilateral bidding显示文摘The electricity market is a complex system in which participants interact and compete with each other,which makes description of them with mathematical models difficult.To solve these difficulties,computer simulation has become one of the main methods for studying electricity market problems.How to establish a reasonable electricity market has always been a major research issue in the electric power industry,for which a key point is the bidding mechanism.Agent-based modeling and a simulation(ABMS)method are used in this paper to study the imperfect competitive electricity market.An agent-based simulation method of multilateral bargaining game theory in the dynamics of the power bidding market is presented,and a multi-agent power market bidding dynamics simulation model based on game theory is established.The dynamic bidding game behavior among the government,power grid companies,power plant companies,and consumer parties is simulated in the market,and the simulation method is realized by Anylogic software.Finally,an agent-based four-party competitive dynamic game simulation in the electricity market is implemented,which provides a theoretical reference for further understanding resource optimization problems in the electricity market. | Jiahui Wu Jidong Wang Yuanyuan Yan | 2019 | International Journal of Modeling, Simulation, and Scientific Computing2019，10，3： | 1 |
| 9 | Fuzzy comprehensive evaluation model for construction risk analysis in urban subway显示文摘On the basis of expert questionnaire and the relevant specification,multi-factors influencing weight matrix was constructed by Analytic Hierarchy Process(AHP)improved in transfer matrix algorithm,and influential factors were fuzzy classified to construct the fuzzy evaluation matrix by using trapezoidal fuzzy membership function.Fuzzy evaluation analysis was carried out through multistage fuzzy comprehensive evaluation method,and verified in combination with engineering construction condition of shallow buried tunnel with large span of Zhongshan Park Station in Qingdao Metro,and four kinds of risk control schemes were established and compared on the analysis of tunnel construction risk.Results show that the model was feasible and the improved construction scheme was very effective to reduce the construction risk. | Chun-Quan Dai Zeng-Hui Zhao | 2015 | International Journal of Modeling, Simulation, and Scientific Computing2015，6，3： | 1 |
| 10 | Analytical Design of an Air Curtain显示文摘 | PARTY J | 1995 | International Journal of Modeling and Simulation1995，，15： | 1 |
| 11 | Survey of telesensation and teleoperation technology with virtual reality and force reflection capabilities显示文摘 | Batsomboon P Tosunoglu S Repperger D | 2000 | International Journal of Modelling and Simulation2000，20，1： | 1 |
| 12 | Simulation studies of heuris- tic approaches for dynamic scheduling of container terminal op- erations显示文摘 | ZHANG Hailin JIANG Zhibin | 2008 | International Journal of Modeling and Simulation2008，28，4： | 1 |
| 13 | BDI-Based Human Decision-Making Model in Automated Manufacturing Systems显示文摘 | ZHAO X SON Y J | 2008 | International Journal of Modeling and Simulation2008，28，3： | 1 |
| 14 | Gasoline blending system modelling via static and dynamic neural networks显示文摘 | YU W MORALES A | 2004 | International Journal of Modeling and Simulation2004，24，3： | 1 |
| 15 | Harmony search opti mization application to pipe network design显示文摘 | GEEM Z KIM J LOGANATHAN G | 2002 | International Journal of Model Simulation2002，22，2： | 1 |
| 16 | Genetic algorithm approach for multiple depot capacitated vehicle routing problem solving with heuristic improvements built-in 显示文摘 | Filipec M Skrlec D Krajcar S | 2000 | International Journal of Modeling and Simulation2000，20，4： | 1 |
| 17 | Time-dependent reliability analysis of steel miter gates显示文摘 | Pitcha C S Patev R C Leggett M A | 2003 | International Journal of Modelling and Simulation2003，23，1： | 1 |
| 18 | Development of fault trees for risk assessment of dam gates and associated operating equipment显示文摘 | Patev R C Putcha C S | 2005 | International Journal of Modelling and Simulation2005，25，3： | 1 |
| 19 | Elasto-plastic leaf spring model显示文摘 | Kat Cor-Jacques Els Pieter Schalk | 2011 | International Journal of Engineering Systems Modelling and Simulation2011，3，3： | 1 |
| 20 | Film condensation in horizon- tal circular- Section microchannels 显示文摘 | WANG H S ROSE J W | 2009 | International Journal of Engineering System Model Simulation2009，，1： | 1 |
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