Jujun Ruan

A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

Key factors of eddy current separation for recovering aluminum from crushed e-waste.

Recovery of e-waste in China had caused serious pollutions. Eddy current separation is an environment-friendly technology of separating nonferrous metallic particles from crushed e-waste. However, due to complex particle characters, separation efficiency of traditional eddy current separator was low. In production, controllable operation factors of eddy current separation are feeding speed, (ωR-v), and Sp. There is little special information about influencing mechanism and critical parameters of these factors in eddy current separation. This paper provided the special information of these key factors in eddy current separation of recovering aluminum particles from crushed waste refrigerator cabinets. Detachment angles increased as the increase of (ωR-v). Separation efficiency increased with the growing of detachment angles. Aluminum particles were completely separated from plastic particles in critical parameters of feeding speed 0.5m/s and detachment angles greater than 6.61deg. Sp/Sm of aluminum particles in crushed waste refrigerators ranged from 0.08 to 0.51. Separation efficiency increased as the increase of Sp/Sm. This enlightened us to develop new separator to separate smaller nonferrous metallic particles in e-waste recovery. High feeding speed destroyed separation efficiency. However, greater Sp of aluminum particles brought positive impact on separation efficiency. Greater Sp could increase critical feeding speed to offer greater throughput of eddy current separation. This paper will guide eddy current separation in production of recovering nonferrous metals from crushed e-waste.

Application of fuzzy neural networks for modeling of biodegradation and biogas production in a full-scale internal circulation anaerobic reactor

ABSTRACT This paper presents the development and evaluation of three fuzzy neural network (FNN) models for a full-scale anaerobic digestion system treating paper-mill wastewater. The aim was the investigation of feasibility of the approach-based control system for the prediction of effluent quality and biogas production from an internal circulation (IC) anaerobic reactor system. To improve FNN performance, fuzzy subtractive clustering was used to identify models architecture and optimize fuzzy rule, and a total of 5 rules were extracted in the IF-THEN format. Findings of this study clearly indicated that, compared to NN models, FNN models had smaller RMSE and MAPE as well as bigger R for the testing datasets than NN models. The proposed FNN model produced smaller deviations and exhibited a superior predictive performance on forecasting of both effluent quality and biogas (methane) production rates with satisfactory determination coefficients greater than 0.90. From the results, it was concluded that FNN modeling could be applied in IC anaerobic reactor for predicting the biodegradation and biogas production using paper-mill wastewater.

Improving the efficiency of dissolved oxygen control using an on-line control system based on a genetic algorithm evolving FWNN software sensor

This work proposes an on-line hybrid intelligent control system based on a genetic algorithm (GA) evolving fuzzy wavelet neural network software sensor to control dissolved oxygen (DO) in an anaerobic/anoxic/oxic process for treating papermaking wastewater. With the self-learning and memory abilities of neural network, handling the uncertainty capacity of fuzzy logic, analyzing local detail superiority of wavelet transform and global search of GA, this proposed control system can extract the dynamic behavior and complex interrelationships between various operation variables. The results indicate that the reasonable forecasting and control performances were achieved with optimal DO, and the effluent quality was stable at and below the desired values in real time. Our proposed hybrid approach proved to be a robust and effective DO control tool, attaining not only adequate effluent quality but also minimizing the demand for energy, and is easily integrated into a global monitoring system for purposes of cost management.

Hydrodynamics of Plasma Fluidized Bed

This chapter systematically reviews the hydrodynamics of plasma fluidized bed and its progress. Firstly, the hydrodynamics of plasma spouted bed is introduced from the aspects of minimum spouted velocity, spoutable height, pressure drop and particle attrition, and the relevant formulas are given. Finally, the hydrodynamics of plasma fluidized bed was analyzed.

Heat Transfer and Mass Transfer in the Plasma Fluidized Bed

This chapter introduces the heat transfer and mass transfer of plasma fluidized bed from three aspects: temperature distribution, heat transfer, circulation and mass transfer in the plasma fluidized bed. In terms of heat transfer, the effects of gas ionization effects, radiation effects and evaporation effects are introduced in detail, and the specific calculation formulas are given. In addition, this chapter summarizes the conditions and parameters of many studies and practical applications, which provide references for future research and application.

Scientific and Industrial Application of Plasma Fluidized Bed

This chapter introduces the application of plasma fluidized bed in detail, including the following four fields: metallurgy process, coal gasification and pyrolysis, environmental protection and materials. The metallurgy process includes: metallurgy extraction, synthetic of calcium carbide, alloy granulation, etc. In the field of gasification/pyrolysis of coal, including gasification/pyrolysis of coal for acetylene, pyrolysis/gasification of coal to syngas, biomass pyrolysis/gasification, gasification/pyrolysis of biomass for syngas, gasification/pyrolysis of biomass for bio–oil, gasification of solid waste cracking of heavy hydrocarbon and reformation of biogas. In terms of environmental protection, there are applications of abatement of VOCs, control of NOx, sterilization of food, plasma modified catalyst for water purification and solid waste treatment. In the field of materials, there are applications of surface activation and functionalization, plasma enhanced chemical vapor deposition (PECVD) and synthesis of nanoparticles. The application of plasma fluidized bed has been widely used, and it has a wide application prospect.

Applicative Ability and Environmental Risk

This chapter analyses the application and environmental risks of plasma fluidized bed. Firstly, energy analysis and economic analysis are mentioned. Plasma fluidized bed has more advantages than traditional processes. Secondly, the application ability and environmental risk are mentioned. The problem of plasma fluidized bed has not been reported in the relevant literature. Therefore, further research and discovery are needed in this area. Finally, the prospect of future application of plasma fluidized bed is presented in this chapter, and several existing problems are proposed, which need further development and improvement.

Influencing Factors on Understanding Plasma Fluidized Bed

There is a comprehensive introduction about the influencing factors of plasma fluidized bed treatment effect in this chapter, which includes: the resident time, input power, gas flow rate, carrier gas composition, the design of the distributor, gas pressure, temperature, particle size and density, solid mass flow rate. All kinds of influencing factors are analyzed in detail, and the relevant precautions when using plasma fluidized bed are presented.

Plasma and Plasma Fluidized Bed

In this chapter, the topic of plasma is introduced and a comprehensive description of plasma fluidized bed is given. The development and application of thermal plasma and non-thermal plasma are briefly introduced. Then, the development course of plasma fluidized bed is introduced in chronological order. What’s more, the principle of the removal of pollutants by plasma fluidized bed is described, and the advantages of the plasma fluidized bed are listed in detail. It’s proved that the plasma fluidized bed has great potential. In the end, three sets of parameters of plasma fluidized bed are evaluated for the use of plasma fluidized bed.