An attempt to compare the performance of bioscrubbers and biotrickling filters for degradation of ethyl acetate in gas streams

This study presents a comparison of the efficiency of a bioscrubber and a biotrickling filter (BTF) for the removal of ethyl acetate (EA) vapour from a waste gas stream, under the same operating conditions. The maximum EA elimination capacity achieved in the bioscrubber was 550 g m^?3 h^?1 with removal efficiency higher than 96%. For higher EA loadings the bioscrubber was oxygen limited, which caused incomplete EA biodegradation. When pure oxygen was fed to the bioscrubber at a rate of 0.02 L min^?1, the bioscrubber recovered and could treat higher EA loadings without any oxygen limitation. The BTF achieved EA elimination capacity of 600 g m^?3 h^?1 with removal efficiency higher than 97% and the dissolved oxygen concentration remained substantially higher than in the bioscrubber. However, severe channelling and blockage of the spray nozzle occurred due to the excessive biomass growth. Overall, the bioscrubber system was easier to operate and control than the BTF, while an enhancement of the oxygen mass transfer in the bioscrubber could potentially increase its performance by up to three times. Copyright © 2005 Society of Chemical Industry     

对水厂一期滤池技术改造后的经济评价

本文主要从经济角度分析净水厂实际生产情况及经济技术指标等方面的数据。阐述福州西区水厂一期滤池由原先双阀滤池改造成V型滤池的经济性。     

A New Algorithm for the Elimination of Common Subexpressions in Hardware Implementation of Digital Filters by Using Genetic Programming

A new algorithm based on Genetic Programming (GP) for the problem of optimization of Multiple constant Multiplication (MCM) by Common Subexpression Elimination(CSE) is developed. This method is used for hardware optimization for DSP systems. A solution based on Genetic Programming is shown in this paper. The performance of the technique is demonstrated in one- and multi-dimensional digital filters with constant coefficients.     

指状椭圆函数滤波器的研究与设计

阐述了指状椭圆函数滤波器的特点、适用范围，基本理论以及设计方法。用本文导出的公式进行设计有工程应用价值，介绍了一个L波段滤波器的例子。     

一种适用于有限长度混合相位未知脉冲的最小平方反褶积新方法

普通的最小平方反褶积只有在子波为最小相位脉冲和反射序列为白噪声的假设下才是成立的,而对于混合相位未知脉冲来说,这种最小平方反褶积就不再适用了。本文提出一种适合于有限长度混合相位未知脉冲的最小平方反褶积方法。运用此法只需预先估计一个混合相位子波的长度。合成数据的试验结果表明,该方法有较好的效果,且对预先估计出的子波长度不敏感。文中还证明混合相位未知脉冲最小平方反褶积等效于一种有间隙的平滑误差滤波器的作用,而这种有间隙的平滑误差滤波又可分解为一个前向多步预测误差滤波与一个后向多步预测误差滤波之和。可以预计这种新的反滤积方法将在地震数据处理中得到有效的应用。     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Hybrid LES — Review and assessment

In the late eighties and up to the beginning of nineties computation of turbulent flows is mostly dominated by RANS (Reynolds Averaged Navier-Stokes Simulation) type modelling. During the last few years URANS (Unsteady RANS) and LES (Large Eddy Simulation) type of approaches have been attempted with some success. Yet, there have been many difficulties when LES is applied to practical engineering problems and to high Reynolds number flows as energy dissipating eddies become really small and mesh resolution required for a reasonably resolved LES approaches that of DNS (Direct Numerical Simulation). An alternative solution suggested was to combine RANS and LES, which in general referred to as Hybrid LES. There have been many proposals for combining RANS and LES in different ways. In this article, some of the issues involved in performing hybrid LES reported in the recent literature is briefly reviewed.     

运用PLC技术改造385m~2凯利式叶滤机控制系统

根据生产实践 ,结合PLC的技术特点和 385m2 凯利式叶滤机的电气联锁特性 ,阐述了应用PLC技术 ,可进一步提高 385m2 凯利式叶滤机的运转率和自动化水平。     

An Area Optimization Method for Digital Filter Design

In this paper, we propose an efficient design method for area optimization in a digital filter. The conventional methods to reduce the number of adders in a filter have the problem of a long critical path delay caused by the deep logic depth of the filter due to adder sharing. Furthermore, there is such a disadvantage that they use the transposed direct form (TDF) filter which needs more registers than those of the direct form (DF) filter. In this paper, we present a hybrid structure of a TDF and DF based on the flattened coefficients method so that it can reduce the number of flip‐flops and full‐adders without additional critical path delay. We also propose a resource sharing method and sharing‐pattern searching algorithm to reduce the number of adders without deepening the logic depth. Simulation results show that the proposed structure can save the number of adders and registers by 22 and 26%, respectively, compared to the best one used in the past.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.