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Effects of physical parameter range on dimensionless variable sensitivity in water flooding reservoirs

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Acta Mechanica Sinica 2006年第5期22卷 385-391页

作者： yu Hu Bai jia Chun Li ji Fu Zhou Division of Engineering Sciences Institute of MechanicsChinese Academy of Sciences Beijing 100080 China

The similarity criterion for water flooding reservoir flows is concerned with in the present paper. When finding out all the dimensionless variables governing this kind of flow, their physical meanings are subsequently elucidated. Then, a numerical approach of sensitivity analysis is adopted to quantify their corresponding dominance degree among the similarity parameters. In this way, we may finally identify major scaling law in different parameter range and demonstrate the respective effects of viscosity, permeability and injection rate.

关键词： Physical parameter range Dimensionless variable Sensitivity analysis Water flooding reservoir Two-phase flow in porous media

Multi-objective optimization design method of the high-speed train head

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2013年第9期14卷 631-641页

作者： Meng-ge yu ji-ye ZHANG Wei-hua ZHANG State Key Laboratory of Traction Power Southwest Jiaotong University

With the continuous improvement of the train speed, the dynamic environment of trains turns out to be aerodynamic domination. Solving the aerodynamic problems has become one of the key factors of the high-speed train head design. Given that the aerodynamic drag is a significant factor that restrains train speed and energy conservation, reducing the aerodynamic drag is thus an important consideration of the high-speed train head design. However, the reduction of the aerodynamic drag may increase other aerodynamic forces (moments), possibly deteriorating the operational safety of the train. The multi-objective optimization design method of the high-speed train head was proposed in this paper, and the aerodynamic drag and load reduction factor were set to be optimization objectives. The automatic multi-objective optimization design of the high-speed train head can be achieved by integrating a series of procedures into the multi-objective optimization algorithm, such as the establishment of 3D parametric model, the aerodynamic mesh generation, the calculation of the flow field around the train, and the vehicle system dynamics. The correlation between the optimization objectives and optimization variables was analyzed to obtain the most important optimization variables, and a further analysis of the nonlinear relationship between the key optimization variables and the optimization objectives was obtained. After optimization, the aerodynamic drag of optimized train was reduced by up to 4.15%, and the load reduction factor was reduced by up to 1.72%.

关键词： High-speed train Multi-objective optimization Parametric model Aerodynamic drag Load reduction factor

Vision based terrain reconstruction for planet rover using a special binocular bundle adjustment

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2008年第10期9卷 1341-1350页

作者： Min-yi SHEN Zhi-yu XIANG ji-lin LIU Institute of Information and Communication Engineering Zhejiang University Hangzhou 310027 China Zhejiang Provincial Key Laboratory of Information Network Technology Zhejiang University Hangzhou 310027 China

This paper presents a pure vision based technique for 3D reconstruction of planet terrain. The reconstruction accuracy depends ultimately on an optimization technique known as 'bundle adjustment'. In vision techniques, the translation is only known up to a scale factor, and a single scale factor is assumed for the whole sequence of images if only one camera is used. If an extra camera is available, stereo vision based reconstruction can be obtained by binocular views. If the baseline of the stereo setup is known, the scale factor problem is solved. We found that direct application of classical bundle adjustment on the constraints inherent between the binocular views has not been tested. Our method incorporated this constraint into the conventional bundle adjustment method. This special binocular bundle adjustment has been performed on image sequences similar to planet terrain circumstances. Experimental results show that our special method enhances not only the localization accuracy, but also the terrain mapping quality.

关键词： 3D reconstruction Binocular bundle adjustment (BBA) Scale-invariant feature transform (SIFT) Re-projectionerror RANSAC

Influence of solution concentration and temperature on the dissolution process and the internal structure of glauberite

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International Journal of Minerals,Metallurgy and Materials 2018年第11期25卷 1246-1255页

作者： Yan-mei yu Wei-guo Liang ji-shan Liu Mining Technology Institute Taiyuan University of Technology Key Lab of In-situ Property-improving Mining of Ministry of Education Taiyuan University of Technology Department of Chemical Engineering School of EngineeringThe University of Western Australia

Although transport in porous media under the influence of chemistry and temperature is a common phenomenon, the dissolution and internal structure evolution of glauberite during in-situ mining have been unique and challenging. This uniqueness indicates the complexity of mineral dissolutions, whereas the challenge represents the characterization of pore development and evolution during the dissolution processes. To investigate the microstructure development of glauberite under the influence of chemistry and temperature, experimental studies were performed with fine cuboid specimens of 4 mm × 4 mm × 9 mm soaked in solutions of different concentrations(fresh water, half-saturated, and saturated brine). The evolutions of internal structures were monitored through a micro computed tomography system. The statistical analysis indicated that the concentration and temperature of solutions significantly influenced the evolutions of pore size, porosity, and specific surface area of glauberite. The results showed that the increase in the rates of pore size, porosity, and specific surface area declined with time when glauberite was saturated in fresh water. The main reason for pore parameter variation is the differential concentration of solution. However, in the half-saturated and saturated solutions, the increase in rate increased with time. These observations suggest that the chloride ions contained in the saline solution could facilitate the dissolution of glauberite, whereas the existence of salt effect could contribute to the dissolution of calcium sulfate. Compared with the results at 20?C and 65?C, the studied parameters of glauberite have dramatically decreased when the mineral was soaked in the solutions at high temperature(95?C). This function was most striking in fresh water. The dissolution of glauberite soaked in fresh water or half-saturated brine solution was conditioned by the temperature and solution concentration. However, the dissolution of glauberite was les

关键词： solution mining porosity evolution glauberite dissolution pore characterization

Controlled Synthesis of Metal-Nanoparticles Decorated Block Copolymer Hybrid Particles via Emulsion Confined Self-assembly and Their Catalytic Applications

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Chinese Journal of Chemistry 2024年第8期42卷 835-840页

作者： Xiaohua Chang Qunli yu Dan ji yutian Zhu College of Material Chemistry and Chemical EngineeringKey Laboratory of Organosilicon Chemistry and Material TechnologyMinistry of EducationHangzhou Normal UniversityHangzhouZhejiang311121 China

Comprehensive Summary Metal nanoparticles(NPs)decorated block copolymer(BCP)hybrid nanoparticles have attracted enormous attention for their actual value in catalysis,medical therapy,and *** confined assembly of BCPs within evaporative emulsion droplet is verified as an effective method to provide polymeric scaffolds to load metal ***,to date,it remains challenging to generate different types of metal NPs decorated BCP hybrid ***,we employed the emulsion confined self-assembly of poly(styrene-b-2-vinylpyridine)(PS-b-P2VP)and the followed seed-mediated growth of Au and palladium(Pd)NPs onto well-defined BCP particles to design a series of Au/Pd decorated BCP hybrid nanoparticles,which exhibited excellent catalytic activity for the reduction of 4-nitrophenol to 4-aminophenol with the reductant of *** work may inspire more researchers to investigate the selective decoration of different metal NPs onto the polymeric scaffolds,broadening the potential applications of the inorganic/organic hybrid nanoparticles.

关键词： Block copolymers Emulsion confined self-assembly Hybrid nanoparticles Catalytic activity Recyclability

Prediction of dissolved oxygen content changes based on two-dimensional behavior features of fish school and T-S fuzzy neural network

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Water Science and Engineering 2022年第3期15卷 210-217页

作者： yu-jun Bao Chang-ying ji Bing Zhang College of Engineering Nanjing Agricultural UniversityNanjing 210031China School of Electrical and Information Engineering Changzhou Institute of TechnologyChangzhou 213032China

Dissolved oxygen(DO)content is an important index of river water *** quality sensors have been used in China for urban river water monitoring and DO content ***,water quality sensors are expensive and difficult to maintain,and have a short operation period and difficult to *** study developed a scientific and accurate method for prediction of DO content changes using fish school *** behavioral features of the Carassius auratus fish school were described using two-dimensional fish school *** degree of DO content decline was graded into five levels,and the corresponding numerical ranges of cluster characteristic parameters were determined by considering the opinions of ***,the variation of DO content was predicted using the characteristic parameters of the fish school and the multiple-input single-output Takagi-Sugeno fuzzy neural *** prediction results were basically consistent with the actual variations of DO ***,it is feasible to use the behavioral features of the fish school to dynamically predict the level of DO content in water,and this method is especially suitable for prediction of sharp decline of DO content in a relatively short time.

关键词： Fish behavior Cluster feature DO Fuzzy neural network Water quality monitoring

Molecular test shows the color pattern is not so reliable in diagnostic of genus Dysphaea Selys(Odonata:Euphaeidae)

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Zoological Systematics 2019年第2期44卷 91-99页

作者： Yao ji Xin yu Institute of Entomology College of Life Sciences Nankai University College of Life Sciences Chongqing Normal University

A molecular study based on COI, 16S and 28S genes reveals that a batch of specimens(7 males and 4 females) of Dysphaea Selys, 1853 collected from central Vietnam,which include different color patterns of wings and body, and were originally identified as three different species, are all the same species. This study implies that, in some group of Odonata,identification only depending on color pattern may be unreliable, no matter what huge variations there are.

关键词： Odonata dragonfly wing color pattern variation molecular phylogeny

Deep learning characterization of rock conditions based on tunnel boring machine data

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Underground Space 2023年第5期12卷 89-101页

作者： Xu Li Min Yao ji-dong yuan yu-jie Wang Peng-yu Li Key Laboratory of Urban Underground Engineering of Ministry of Education Beijing Jiaotong UniversityBeijing 100044China School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 100044China China Institute of Water Resources and Hydropower Research Beijing 100048China China Railway Engineering Equipment Group Co. Ltd.Zhengzhou 450000China

Rock condition perception based on tunnel boring machine(TBM)data is of great importance for not only ensuring tunnel boring safety but also improving construction *** prediction of TBM boring responses(i.e.,torque and total thrust of the cutterhead)largely determines the reliability of rock condition *** this paper,a new architecture of a two-dimensional convolutional neural network(2D-CNN)with a dual-input strategy is proposed to predict the TBM *** TBM Lot 3 of the Yinsong project in jilin province,China,is taken as the case study in this *** types of models that follow different learning strategies are compared:one is defined as the point model,which only learns data of the stable phase,and the other is defined as the line model,which learns data from both the loading and stable boring *** line model is further improved by the weighted loss function *** results indicate that the strategy of learning data from both the loading phase and stable boring phase and increasing the weight of samples from the stable phase is shown to be optimal in predicting TBM boring *** terms of learning strategies,the line model can learn the influence of active control parameters on passive response parameters,but the point model *** terms of machine learning algorithms,2D-CNN has the best performance,with R2 values of 0.865 and 0.923 for torque and total thrust,*** proposed line model can overcome the problem that the traditional model failed to learn the influence of control *** a model can provide a solid base for the timely optimization of the control parameters in TBM boring process.

关键词： TBM Rock condition perception 2D-CNN Weighted loss function Line model

Active switching multiple model method for tracking a noncooperative gliding flight vehicle

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Science China(Information Sciences) 2020年第9期63卷 156-174页

作者： Tianyu ZHENG yu YAO Fenghua HE Denggao ji Xinran ZHANG School of Astronautics Harbin Institute of Technology Beijing Institute of Nearspace Vehicle's Systems Engineering

The study investigates the trajectory estimation problem of a noncooperative gliding flight vehicle with complex and atypical maneuvers. An active switching multiple model(ASMM) method is *** method employs a motion behavior model set(MBMS), a motion behavior recognition algorithm, and an active switching estimation and fusion algorithm. First, a recognizable MBMS, which can capture all the motion behaviors of a gliding flight vehicle, is established. Then, a motion behavior recognition algorithm based on recurrent neural networks(RNNs) is developed to obtain the current probability of each motion behavior. Then, an active switching estimation and fusion algorithm is proposed, in which the adopted models are actively chosen at each time instant according to a model selection strategy. Last, the proposed ASMM method is applied to a noncooperative gliding flight vehicle. The simulation results show that the proposed method has higher estimation precision and better dynamic performance.

关键词： gliding flight vehicle target tracking multiple model estimation and fusion motion behavior recurrent neural networks