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| 1 | Predicting lean blow-off of bluffbody stabilized flames based on Damkohler number显示文摘Lean Blow-Off(LBO) prediction is important to propulsion system design. In this paper,a hybrid method combining numerical simulation and Da(Damk?hler) model is proposed based on bluffbody stabilized flames. In the simulated reacting flow, Practical Reaction Zone(PRZ) is built based on OH radical concentration, and it is considered to be the critical zone that controls LBO.Da number is obtained based on the volume-averaged parameters of PRZ. The flow time scale(s_f)indicates the residence time of the fresh mixture flowing through the PRZ. It is obtained based on the characteristic length and volume-averaged axial velocity of the PRZ. The chemical time scale(s_c) indicates the shortest time needed to trigger the reaction of the mixture. It is obtained by commercial software CHEMKIN through monitoring the transient variation of the reactor temperature. The result shows that the average Da number under different LBO conditions is 1.135(the Da number under each LBO condition ranges from 0.673 to 1.351). This indicates that the flow time scale and chemical time scale are comparable. The combustion is in a critical state where LBO is easy to occur. With the increase of the fuel mass flow rate(the global fuel/air ratio increases from 0.004761 to 0.01095), s_f increases from 0.001268 s to 0.007249 s, and s_c decreases from 0.00124 s to0.00089 s. Accordingly, Da number increases from 1.023 to 8.145, which shows that the combustion becomes more stable. The above results show that the method proposed in the present study can properly predict the LBO limits of combustors, which provides important technical supports for combustor design and optimization. | Zhonghao WANG Bin HU Aiming DENG Junhua ZHANG Qingjun ZHAO | 2019 | Chinese Journal of Aeronautics2019，32，2： | 2 |
| 2 | Carbon Isotopic Evolution of the Late Ediacaran Gaojiashan Biota on the Northern Yangtze Platform,South China显示文摘Metazoan fossils in the Gaojiashan Biota are famous for being well preserved and may provide new insights into the early evolution and skeletonization of Metazoans. We are studying the isotopic compositions of organic and carbonate carbon from a sequence of sedimentary rocks at the Gaojiashan section, northern Yangtze Platform, Shaanxi Province of China. Organic carbon isotope values display a range between -30.8‰ and -24.7‰ with clear stratigraphic variations. Carbonate carbon isotope data vary between 0.1‰ and +6‰. Positive δ13C values from sediments with Gaojiashan biota reflect temporal variations in carbon turnover, i.e. an increasing in photosynthetic carbon fixation followed by an increasing subsequent fractional organic carbon burial, and that related to bio-radiation such as increasing algae, bacteria, and original creatures productivity in biomass. These secular variations are interpreted to reflect perturbations of the regional carbon cycle, specifically changes in the fractional burial of organic carbon, and discuss the relationship between Gaojiashan biota and paleoenvrionmental variation. | GUO Qingjun DENG Yinan YANG Xinglian | 2012 | Acta Geologica Sinica(English Edition)2012，86，6： | 2 |
| 3 | Projected Runge-Kutta methods for constrained Hamiltonian systems显示文摘Projected Runge-Kutta(R-K) methods for constrained Hamiltonian systems are proposed.Dynamic equations of the systems,which are index-3 differential-algebraic equations(DAEs) in the Heisenberg form,are established under the framework of Lagrangian multipliers.R-K methods combined with the technique of projections are then used to solve the DAEs.The basic idea of projections is to eliminate the constraint violations at the position,velocity,and acceleration levels,and to preserve the total energy of constrained Hamiltonian systems by correcting variables of the position,velocity,acceleration,and energy.Numerical results confirm the validity and show the high precision of the proposed method in preserving three levels of constraints and total energy compared with results reported in the literature. | Yi WEI Zichen DENG Qingjun LI Bo WANG | 2016 | Applied Mathematics and Mechanics(English Edition)2016，37，8： | 1 |
| 4 | The mechanism of hydraulic fracturing assisted oil displacement to enhance oil recovery in low and medium permeability reservoirs显示文摘Aiming at the technology of hydraulic fracturing assisted oil displacement which combines hydraulic fracturing,seepage and oil displacement,an experimental system of energy storage and flowback in fracturing assisted oil displacement process has been developed and used to simulate the mechanism of percolation,energy storage,oil displacement and flowback of chemical agents in the whole process.The research shows that in hydraulic fracturing assisted oil displacement,the chemical agent could be directly pushed to the deeper area of the low and medium permeability reservoirs,avoiding the viscosity loss and adhesion retention of chemical agents near the pay zone;in addition,this technology could effectively enlarge the swept volume,improve the oil displacement efficiency,replenish formation energy,gather and exploit the scattered residual oil.For the reservoir with higher permeability,this measure takes effect fast,so to lower cost,and the high pressure hydraulic fracturing assisted oil displacement could be adopted directly.For the reservoir with lower permeability which is difficult to absorb water,hydraulic fracturing assisted oil displacement with surfactant should be adopted to reduce flow resistance of the reservoir and improve the water absorption capacity and development effect of the reservoir.The degree of formation energy deficit was the main factor affecting the effective swept range of chemical agents.Moreover,the larger the formation energy deficit was,the further the seepage distance of chemical agents was,accordingly,the larger the effective swept volume was,and the greater the increase of oil recovery was.Formation energy enhancement was the most important contribution to enhanced oil recovery(EOR),which was the key to EOR by the technology of hydraulic fracturing assisted oil displacement. | LIU Yikun WANG Fengjiao WANG Yumei LI Binhui ZHANG Dong YANG Guang ZHI Jiqiang SUN Shuo WANG Xu DENG Qingjun XU He | 2022 | Petroleum Exploration and Development2022，49，4： | 0 |
| 5 | Effects of C60 on the Glass Transition Temperature of Carbazole-based Photorefractive Polyphosphazenes显示文摘The bi-functional carbazole-based photorefractive polyphosphazenes with different content of C_(60)-doped were fabricated. The glass transition temperature(T_g) of these polymer composite materials was determined using a differential scanning calorimetric(DSC) method. According to the DSC measurement results with different heating rates, the variation of T_g and the active energy of glass transition(E_g) were analyzed in detail. The analysis results indicate that the transition region shifts to higher temperatures with increasing heating rate, and C_(60) content(below 1.0 wt%) can influence the T_g of photorefractive polyphosphazenes. The T_g first increases and then decreases with the C_(60) content(below 1.0 wt%). The probable causes of the influence of C_(60) on T_g was proposed. | 陈百利 CHEN Shufan LUO Xuan FANG Yu ZHANG Qingjun HUANG Chuanqun DENG Qinghua 吴卫东 | 2018 | Journal of Wuhan University of Technology(Materials Science)2018，33，4： | 0 |
| 6 | Hadoop + Spark Platform Based on Big Data System Design of Agricultural Product Price Analysis and Prediction by HoltWinters显示文摘In the market of agricultural products, the price of agricultural products is affected by production cost, market supply and other factors. In order to obtain the market information of agricultural products, the price fluctuation can be analyzed and predicted. A distributed big data software platform based on Hadoop, Hive and Spark is proposed to analyze and forecast agricultural price data. Firstly, Hadoop, Hive and Spark big data frameworks were built to store the data information of agricultural products crawled into MYSQL. Secondly, the information of agricultural products crawled from MYSQL was exported to a text file, uploaded to HDFS, and mapped to spark SQL database. The data was cleaned and improved by Holt-Winters (three times exponential smoothing method) model to predict the price of agricultural products in the future. The data cleaned by spark SQL was imported and predicted by improved Holt-Winters into MYSQL database. The technologies of pringMVC, Ajax and Echarts were used to visualize the data. | Yun Deng Yan Zhu Qingjun Zhang Xiaohui Cheng | 2019 | 国际计算机前沿大会会议论文集2019，，1： | 0 |
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