大庆萨北油田抽油机降机型试验

针对常规的根据产能预测结果选择抽油机机型偏大、载荷利用率低、投资高等问题,开展了抽油机降机型试验研究。萨北油田抽油机降机型后,电机总装机功率下调了3.659 kW,平均机型降低1.3个级别,最大降低2个级别,保留38口对比井机型不变,节省投资415万元。对已投产的降机型试验井和对比井进行随机能耗测试,综合节电率达到20.4%,系统效率提高了4.2个百分点,吨液百米耗电下降了11.8%,163口井年节约电量355.9×104 kW.h。

Self-assembly synthesis of S-scheme g-C_(3)N_(4)/Bi_(8)(CrO_(4))O_(11) for photocatalytic degradation of norfloxacin and bisphenol A

To realize the high-efficiency photodegradation of antibiotics,a novel S-scheme heterojunction photocatalyst g-C_(3)N_(4)/Bi_(8)(CrO_(4))O_(11) was proposed and successfully prepared in this work.The 10%g-C_(3)N_(4)/Bi_(8)(CrO_(4))O_(11) heterojunction exhibits the highest degradation rate of norfloxacin(NOR)and bisphenol A(BPA).The degradation rate of NOR on 10%g-C_(3)N_(4)/Bi_(8)(CrO_(4))O_(11) is about 1.38 and 2.33 times higher than that of pure Bi_(8)(CrO_(4))O_(11) and g-C_(3)N_(4),respectively.Further,the degradation rate of BPA over 10%g-C_(3)N_(4)/Bi_(8)(CrO_(4))O_(11) heterojunction is bout 1.35 and 9.11 times higher than that of pure Bi_(8)(CrO_(4))O_(11) and g-C_(3)N_(4),respectively.The formation of S-scheme heterojunction facilitates the separation of photogenerated electron-hole pairs and reduces the recombination of charge carriers,which was confirmed by photocurrent,electrochemical impedance spectroscopy,steady-state and time-resolved transient photoluminescence spectrum,etc.The in-situ X-ray photoelectron spectroscopy,radical trapping experiments and electron paramagnetic resonance results demonstrate that the charge transfer is in accord with S-scheme mechanism.

Kinetic Modelling of Degradation of Organic Compounds in Soils

A set of equations is suggested to describe the kinetics of degradation of organic compounds applied tosoils and the kinetics of growth of the involved microorganisme:where x is the concentration of organic compound at time t, m is the number of forcroorganisms capableof degrading the organic compound at time t, while j, k, f and g are positive constaats. This model cansatisfactorily be used to explain the degradation curve of organic compounds and the growth curve of theinvolved microorganisms.

Degradation of lignite model compounds by the action of white rot fungi

Three compounds modeled on the lignite structure were chosen for experimental degradation by different fungi strains. Culture conditions and extracellular enzyme activities were optimized. The growth curves of the strains were determined to study mycelium dry weight and protein content changes. Gas chromatography and infrared spectroscopy were used to detect changes of functional groups before and after the action of the fungi on the model compounds. Possible decomposition products and degrada-tion mechanisms were proposed. The research findings show that C. Versicolor and Golden Mushroom can grow in presence of the model compounds. The optimum culture conditions were a pH of 6.0, a carbon-nitrogen ratio of five and a Tween-80 concentration of 0.1%. Newly produced substances were found by gas chromatography. Infrared analysis showed that the model compounds degraded under the action of the microorganisms.

Modeling of time dependent subsidence for coal and ore deposits

Coal and ore underground mining generates subsidence and deformation of the land surface. Those defor- mations may cause damage to buildings and infrastructures. The environmental impact of subsidence will not be accepted in the future by the society in many countries. Especially acceptance of the ground deformations decreases every year there, where the mining regions are densely urbanized, the The only solution is to limit the subsidence or its impact on the infrastructure. The first is not rentable for the mining industry, the second depends on the precise subsidence prediction and good preventing management involved in the mining areas. The precision of the subsidence prediction depends strictly on the mathematical model of the deformation phenomenon and on the uncertainty of the input data. The subsidence prediction in the geological conditions of the raw materials used to be made on the basis of numerical modeling or the stochastic models. A modified solution of the stochastic model by Knothe will be presented in the paper. The author focuses on the precise description of the deposit shape and on the time dependent displacements of the rock mass. A two parameters＇ time function has been introduced in the algorithm.

Prediction of dust fall concentrations in urban atmospheric environment through support vector regression

Support vector regression （SVR） method is a novel type of learning machine algorithms, which is seldom applied to the development of urban atmospheric quality models under multiple socio-economic factors. This study presents four SVR models by selecting linear, radial basis, spline, and polynomial functions as kernels, respectively for the prediction of urban dust fall levels. The inputs of the models are identified as industrial coal consumption, population density, traffic flow coefficient, and shopping density coefficient. The training and testing results show that the SVR model with radial basis kernel performs better than the other three both in the training and testing processes. In addition, a number of scenario analyses reveal that the most suitable parameters （insensitive loss function e, the parameter to reduce the influence of error C, and discrete level or average distribution of parameters σ） are 0.001, 0.5, and 2 000, respectively.

Modeling of Hillslope Runoff and Soil Erosion at Rainfall Events Using Cellular Automata Approach

A novel quantitative cellular automata (CA) model that simulates and predicts hillslope runoff and soil erosion caused by rainfall events was developed by integrating the local interaction rules and the hillslope surface hydraulic processes. In this CA model, the hillslope surface was subdivided into a series of discrete spatial cells with the same geometric features. At each time step, water and sediment were transported between two adjacent spatial cells. The flow direction was determined by a combination of water surface slope and stochastic assignment. The amounts of interchanged water and sediment were computed using the Chezy-Manning formula and the empirical sediment transport equation. The water and sediment discharged from the open boundary cells were considered as the runoff and the sediment yields over the entire hillslope surface. Two hillslope soil erosion experiments under simulated rainfall events were carried out. Cumulative runoff and sediment yields were measured, respectively. Then, the CA model was applied to simulate the water and soil erosion for these two experiments. Analysis of simulation results indicated that the size of the spatial cell, hydraulic parameters, and the setting of time step and iteration times had a large impact on the model accuracy. The comparison of the simulated and measured data suggested that the CA model was an applicable alternate for simulating the hillslope water flow and soil erosion.

An alternative lattice algorithm for option pricing

This paper proposes a dimension reduction technique on lattice model, an extension of the discrete CRR （1979） model, for option pricing. Applications are demonstrated on pricing some vulnerable options with the payoff functions including two stochastic processes： the underlying stock price and the assets value of the option writer. Instead of building a bivariate tree structure for these correlated processes, a univariate binomial tree for the underlying stock price is only constructed. The proposed univariate binomial tree model is sufficient to undertake, though two underlying assets are involved.

Evaluation of Data Replacement Strategies for CASTNET Dry Deposition Modeling

The U.S. EPA （Environmental Protection Agency） established the CASTNET （Clean Air Status and Trends Network） and its predecessor, the NDDN （national dry deposition network）, as national air quality and meteorological monitoring networks. Both CASTNET and NDDN were designed to measure concentrations of sulfur and nitrogen gases and particles. Both networks also estimate dry deposition using an inferential model. The design was based on the concept that atmospheric dry deposition flux could be estimated as the product of a measured air pollutant concentration and a modeled deposition velocity （Vd）. The MLM （multi-layer model）, the computer model used to simulate dry deposition, requires information on meteorological conditions and vegetative cover as model input. The MLM calculates hourly Fa for each pollutant, but any missing meteorological data for an hour renders Vd missing for that hour. Because of percent completeness requirements for aggregating data for long-term estimates, annual deposition rates for some sites are not always available primarily because of missing or invalid meteorological input data. In this work, three methods for replacing missing on-site measurements are investigated. These include （1） using historical values of deposition velocity or （2） historical meteorological measurements from the site being modeled or （3） current meteorological data from nearby sites to substitute for missing inputs and thereby improve data completeness for the network＇s dry deposition estimates. Results for a CASTNET site used to test the methods show promise for using historical measurements of weekly average meteorological parameters.