Evaluation of hydrodynamic behavior of the perforated gas distributor of industrial gas phase polymerization reactor using CFD-PBM coupled model

A 2D computational fluid dynamics (Eulerian–Eulerian) multiphase flow model coupled with a population balance model (CFD-PBM) was implemented to investigate the fluidization structure in terms of entrance region in an industrial-scale gas phase fluidized bed reactor. The simulation results were compared with the industrial data, and good agreement was observed. Two cases including perforated distributor and complete sparger were applied to examine the flow structure through the bed. The parametric sensitivity analysis of time step, number of node, drag coefficient, and specularity coefficient was carried out. It was found that the results were more sensitive to the drag model. The results showed that the entrance configuration has significant effect on the flow structure. While the dead zones are created in both corners of the distributors, the perforated distributor generates more startup bubbles, heterogeneous flow field, and better gas–solid interaction above the entrance region due to jet formation.     

Relationships between urbanization and the oak resource of the Minneapolis/St. Paul Metropolitan area from 1991 to 1998

Urbanization was associated with loss and transformation of the oak forest in the Twin Cities (Minneapolis and St. Paul) metropolitan area (TCMA) over a recent 7-year interval. Between 1991 and 1998, urbanization increased based on several indicators: population density, area of developed land, and area of impervious surface—total impervious area and area within three classes of increasing degree of imperviousness (protected, affected, and degraded). We quantified relationships between changes in urbanization and changes in several parameters describing the oak forest at the scale of ecological subsection. Increased total and affected impervious area were strongly correlated with decreased area of oak forest when changes of the urbanization indicators and oak were expressed as percentages of the subsection area. Relationships were reversed when changes were expressed as percentages of the 1991 values. Increased population density was strongly correlated with increased loss in numbers and increased isolation of oak patches, but weakly correlated with loss of oak forest area. This is the first study to quantify relationships between changes in urbanization and changes in a specific forest cover type. Our results demonstrate complexities of urbanization impacts on a metropolitan forest resource, and highlight the importance of selected variables, spatial and temporal scales, and expressions of change when quantifying these relationships.     

基于VW2010芯片的嵌入式多媒体监控系统压缩/解压卡设计

在简要分析了多媒体监控系统发展现状的基础上，提出了一种基于VW2010压缩／解压芯片的多媒体压缩／解压卡的设计方案，给出了基于VW2010的多媒体监控系统压缩和解压卡的硬件结构图以及在Linux系统下VW2010的驱动程序，同时给出了在Linux Redhat7．3下编写的测试程序，并进行了全面的测试。     

Surveillance test policy optimization through genetic algorithms using non-periodic intervention frequencies and considering seasonal constraints

In order to maximize systems average availability during a given period of time, it has recently been developed a non-periodic surveillance test optimization methodology based on genetic algorithms (GA). The fact of allowing non-periodic tests turns the solution space much more flexible and schedules can be better adjusted, providing gains in the overall system average availability, when compared to those obtained by an optimized periodic test scheme. This approach, however, turns the optimization problem more complex. Hence, the use of a powerful optimization technique, such as GA, is required.Considering that some particular features of certain systems can turn it advisable to introduce other specific constraints in the optimization problem, this work investigates the application of seasonal constraints for the set of the Emergency Diesel Generation of a typical four-loop pressurized water reactor in order to planning and optimizing its surveillance test policy. In this analysis, the growth of the blackout accident probability during summer, due to electrical power demand increases, was considered. Here, the used model penalizes surveillance test interventions when the blackout probability is higher.Results demonstrate the ability of the method in adapting the surveillance test policy to seasonal constraints. The knowledge acquired by the GA during the searching process has lead to test schedules that drastically minimize test interventions at periods of high blackout probability. It is compensated by more frequent redistributed tests through the periods of low blackout probability in order to improve on the overall average availability at the system level.     

Improved accuracy and convergence of discretized population balance for aggregation: The cell average technique

A new discretization method for aggregation equations is developed. It is compared to the fixed pivot technique proposed by Kumar and Ramkrishna (1996a. On the solution of population balance equations by discretization—I. A fixed pivot technique. Chemical Engineering Science 51, 1311-1332). The numerical results for aggregation problems by discretized population balances are consistently overpredicting and diverge before the gelling point in the case of a gelling kernel. The present work establishes a new technique which assigns the particles within the cells more precisely. This is achieved by taking first the average of the newborn particles within the cell and then assigning them to the neighboring nodes such that pre-chosen properties are exactly preserved. The new technique preserves all the advantages of the conventional discretized methods and provides a significant improvement in predicting the particle size distribution (PSD). In addition, it is found that the technique is a powerful tool for the computation of gelling problems. The effectiveness of the technique is illustrated by application to several aggregation problems for suitably selected aggregation kernels including physically relevant kernels.     

Optimal control and operation of drum granulation processes

Process optimisation and optimal control of batch and continuous drum granulation processes are studied in this paper. The main focus of the current research has been: (i) construction of optimisation and control relevant, population balance models through the incorporation of moisture content, drum rotation rate and bed depth into the coalescence kernels; (ii) investigation of optimal operational conditions using constrained optimisation techniques; (iii) development of optimal control algorithms based on discretized population balance equations; and (iv) comprehensive simulation studies on optimal control of both batch and continuous granulation processes. The objective of steady state optimisation is to minimise the recycle rate with minimum cost for continuous processes. It has been identified that the drum rotation-rate, bed depth (material charge), and moisture content of solids are practical decision (design) parameters for system optimisation. The objective for the optimal control of batch granulation processes is to maximize the mass of product-sized particles with minimum time and binder consumption. The objective for the optimal control of the continuous process is to drive the process from one steady state to another in a minimum time with minimum binder consumption, which is also known as the state-driving problem. It has been known for some time that the binder spray-rate is the most effective control (manipulative) variable. Although other possible manipulative variables, such as feed flow-rate and additional powder flow-rate have been investigated in the complete research project, only the single input problem with the binder spray rate as the manipulative variable is addressed in the paper to demonstrate the methodology. It can be shown from simulation results that the proposed models are suitable for control and optimisation studies, and the optimisation algorithms connected with either steady state or dynamic models are successful for the determination of optimal operational conditions and dynamic trajectories with good convergence properties.     

Two methods for sensitivity analysis of coagulation processes in population balances by a Monte Carlo method

We consider two stochastic simulation algorithms for the calculation of parametric derivatives of solutions of a population balance equation, namely, forward and adjoint sensitivity methods. The dispersed system is approximated by an N-particle stochastic weighted ensemble. The infinitesimal deviations of the solution are accounted for through infinitesimal deviation of the statistical weights that are recalculated at each coagulation. In the forward method these deviations of the statistical weights immediately give parametric derivatives of the solution. In the second method the deviations of the statistical weights are used to calculate a finite-mode approximation of the linearized version of the population balance equation. The linearized equation allows for the calculation of the eigenmodes and eigenvalues of the process, while the parametric derivatives of the solution are given by a Lagrange formalism.     

A probabilistic simulator for population dynamics of quasispecies

We constructed a probabilistic simulator that allows all the events in population dynamics such as death, birth, mutation, and suppression/stimulation to be described by probabilistic rules. The simulator also facilitates a lattice used for expressing distribution and diversity (number of distinct strains) of quasispecies. The simulator is used to investigate the diversity threshold in HIV and T-cell interaction. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Development of intelligent multisensor surveillance systems with agents

Intelligent multisensor surveillance systems consist of several types of sensors, which are installed on fixed and mobile devices. These components provide a huge quantity of information that has to be contrasted, correlated and integrated in order to recognize and react on special situations. These systems work in highly dynamic environments, with severe security and robustness requirements. All these characteristics imply the need for distributed solutions. In these solutions, scattered components can decide and act with some degree of autonomy (for instance, if they become isolated), or cooperate and coordinate for a complete tracking of special situations. In order to cope with these requirements and to better structure the solution, we have decided to design surveillance system control as a multiagent system. This is done by applying an agent-orientated methodology, which is assessed with concrete scenarios.     

Efficient solution of population balance equations with discontinuities by finite elements

Two refinements of Galerkin's method on finite elements were evaluated for the solution of population balance equations for precipitation systems. The traditional drawbacks of this approach have been the time required for computation of the two-dimensional integrals arising from the aggregation integrals and the difficulty in handling discontinuities that often arise in simulations of seeded reactors. The careful arrangement of invariant integrals for separable aggregation models allows for a thousandfold reduction in the computational costs. Discontinuities that may be present due to the hyperbolic nature of the system may be specifically tracked by the method of characteristics. These discontinuities will arise only from the initial distribution or nucleation and are readily identified. A combination of these techniques can be used that is intermediate in computational cost while still allowing discontinuous number densities. In a case study of calcium carbonate precipitation, it is found that the accuracy improvement gained by tracking the slope discontinuity may not be significant and that the computation speed may be sufficient for dynamic online optimization.