油水井化学封窜堵漏新工艺

通过分析中原油田注水开发的两大问题，阐明了新型堵剂YLD-1的适应性，结合室内试验，重点分析了该堵剂的性能特点，深入探讨了封窜堵漏的选井原则和施工工艺，经过在文留油田的现场应用，展示了该技术良好的发展前景。     

Reaction kinetics study of asymmetric polymer-polymer interface

In this study, the reaction kinetics of asymmetric polymer-polymer interface was experimentally and theoretically studied. A new rheological method correlating the change of rheological property of reactive system with the conversion of the in situ formed copolymers was applied to study the reaction kinetics of PBT/epoxy reactive system. Then, the new method was proved to be useful by comparing its results with that obtained from the conventional endgroup determination method. Moreover, the conversion of PBT/epoxy reactive system from rheological method could be well fitted by the numerical analysis, from which the kinetic constant and the diffusion constant of epoxy in PBT could be determined simultaneously.     

TRANSIENT ANALYSIS OF CRYSTALLIZATION: EFFECT OF THE SIZE DEPENDENT GROWTH RATE

The dynamics of the crystal size distribution in a continuous mixed suspension, mixed product removal crystallizer is modeled stochastically. The model is fairly general in that it involves a size-dependent growth rate function: this size-dependent growth rate as a possible cause of deviation on the behavior of the crystallizer from that of an idealized or simplified counterpart has been investigated based upon the model.     

Stochastic modeling of segregation in a motionless mixer

The mixing of particles with different characteristics is generally accompanied by segregation which prevents the particles from attaining the randomly mixed state. A discrete steady-state Markov chain model was employed to model the axial segregation of solid particles in a motionless mixer. Three systems containing particles of different sizes and/or densities were studied. One step transition probabilities of the model were experimentally determined. The model can predict the concentration profiles, the degrees of mixedness, and the equilibrium states of these particle systems blended by passing the particles through a motionless mixer. Experimental results are in good agreement with those predicted from the model.     

Optimal synthesis of process systems Necessary condition for optimal system and its use in synthesis of systems

The necessary condition for the optimal process system structure which includes both the optimal interconnection and optimal design of processing units is derived in terms of the structural parameters. The structural parameters are essentially splitting factors of process streams connecting processing units. The necessary condition requires the structural parameters and the design vectors to satisfy the weak maximum condition of the Hamiltonian type scalar functions. On the basis of the condition, a search method, evolutionary search for optimal structure (ESOS), for attaining the optimal structure starting from a simple structure is developed and its convergence is proved. An example of synthesizing a reactor-separator system illustrates its use.     

Multivariate statistical analysis of solids mixing

The applicability of multivariate statistics to the analysis of mixing processes and mixtures of multicomponent solid particles in a drum mixer has been successfully demonstrated. The applications include (1) test of sampling techniques, (2) test of the completely random state, (3) test of the completely segregated state, and (4) definition of a mixing index for a multicomponent mixture.     

Discriminative multi-task objects tracking with active feature selection and drift correction

In this paper, we propose a discriminative multi-task objects tracking method with active feature selection and drift correction. The developed method formulates object tracking in a particle filter framework as multi-Task discriminative tracking. As opposed to generative methods that handle particles separately, the proposed method learns the representation of all the particles jointly and the corresponding coefficients are similar. The tracking algorithm starts from the active feature selection scheme, which adaptively chooses suitable number of discriminative features from the tracked target and background in the dynamic environment. Based on the selected feature space, the discriminative dictionary is constructed and updated dynamically. Only a few of them are used to represent all the particles at each frame. In other words, all the particles share the same dictionary templates and their representations are obtained jointly by discriminative multi-task learning. The particle that has the highest similarity with the dictionary templates is selected as the next tracked target state. This jointly sparsity and discriminative learning can exploit the relationship between particles and improve tracking performance. To alleviate the visual drift problem encountered in object tracking, a two-stage particle filtering algorithm is proposed to complete drift correction and exploit both the ground truth information of the first frame and observations obtained online from the current frame. Experimental evaluations on challenging sequences demonstrate the effectiveness, accuracy and robustness of the proposed tracker in comparison with state-of-the-art algorithms.     

Mechanical properties of (ethylene acrylate copolymer)‐modified polypropylene/TiO2 blends

An ethylene‐(methyl acrylate) (EMA) copolymer produced from a tubular reactor was found to be effective in toughening polypropylene, even at low concentrations. The addition of a small amount of TiO₂ pigment enhanced the EMA toughening effect. Microscopy and thermal analysis helped to reveal the possible EMA toughening mechanisms. The effects of two processing methods, dry blending and melt blending, on the mechanical properties of the formulation were also studied. J. VINYL ADDIT. TECHNOL., 13:65–70, 2007. © 2007 Society of Plastics Engineers.     

Seasonal evolution of the interannual variability of chlorophyll-a concentration and its forcing factors in the northwestern Pacific from 1998 to 2010

The northwestern Pacific Ocean is a complex region with significant biological spatial variations on a seasonal timescale. To investigate the joint variation patterns on both seasonal and interannual timescales, a season-reliant empirical orthogonal function (S-EOF) analysis was applied to seasonal mean chlorophyll-a concentration (chl-a) anomalies in the northwestern Pacific Ocean during the period 1998–2010. The first two dominant modes accounted for nearly 31% of the total interannual variance, with the second S-EOF mode (S-EOF2) lagging behind the first S-EOF mode (S-EOF1) by one year. S-EOF1 featured a strong variation pattern to the north of 30° N, with maximum chl-a in winter and minimum chl-a in summer. However, S-EOF2 indicated an opposite seasonally evolving pattern compared with S-EOF1, with chl-a increasing along the Kuroshio and extension current from boreal winter to autumn. Both these modes revealed significant relationships with climate-related indices. The two modes corresponded to the central Pacific (CP) La Niña developing episodes and the turnaround from eastern Pacific (EP) La Niña to CP El Niño, respectively. Both modes were associated with the cold phase of the Pacific Decadal Oscillation, which played an important role in prolonging the impact of the El Niño/Southern Oscillation on chl-a seasonal evolution from 1998 to 2010. In addition, we discuss the possible factors dominating chl-a seasonal variation, in terms of the subregions of the northwestern Pacific Ocean. In the subtropical northwestern Pacific Ocean (15° N – 30° N), the chl-a growth was primarily nutrient-limited, whereas in the mid-latitude northwestern Pacific Ocean (35° N – 50° N), the chl-a growth was mainly light-limited.