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Abstract:Environmental protection measures regarding industrial emissions and tightened regulations for air pollution led to the selection of a counter-flow wet scrubber system based on applicability and economic considerations. The flow dynamics of gas transporting particulate matter and gaseous contaminants is a key factor which should be considered in the scrubber design. In this study, gas flow field were simulated using ANSYS Fluent computational fluids dynamic (CFD) software based on the continuity, momentum and k-ε turbulence model so as to obtain optimum design of the system, improve efficiency, shorten experimental, period and avoid dead zone. The result shows that the residuals have done a very good job of converging at minimum number of iterations and error of 1E-6. The velocity flow contours and vectors at the inlet, across the scrubbing chamber and the outlet shows a distributed flow and the velocity profiles have fully conformed to the recommended profile for turbulent flows in pipes. The total pressure within the scrubber cross-section is constant while the minimum and maximum pressure drops was obtained to be 0.30pa and 3.03pa which has conformed to the recommended pressure drop for wet scrubbers. From the results obtained, it can be deduced that the numerical simulation using CFD is an effective method to study the flow characteristics of a counter-flow wet scrubber system.

Wet scrubber system has been used for the control of gas and particulate matter (PM) emissions from production industries. Due to non-linear characteristics, wet scrubbers are limited to the control of PM that is less than 5μm. In this study, an intelligent control technique based on Adaptive Neuro-Fuzzy Inference System (ANFIS) has been designed using MATLAB software. The ANFIS Controller has the advantage of solving non-linearities in the proposed wet scrubber system by manipulating the scrubbing liquid droplet size for the effective control of particulate matter that is less than 5μm. From the simulation results, the controller was able to set PM concentration below the set-point and provides smooth control response within short settling time. Hardware implementation of the ANFIS controller was performed using prototype wet scrubber system by considering Arduino Duemilanove microcontroller and MATLAB interface. The results show that the intelligent controller has achieved the desired objectives of controlling the PM concentration effectively by setting the value below the set point (20μg/m ) which is the allowable PM concentration standard recommended by World Health Organization. © 2014 IEEE.Author keywords ANFIS controller gas-particle separations hardware implementation wet scrubber system

Thenon-linear characteristics of wet scrubbing process have led to the application of intelligent control technique to adequately deal with these complexities by manipulating the liquid droplet size for the effective control of particulate matter (PM) contaminants. This includes the use of adaptive neuro-fuzzy inference system (ANFIS) to design an intelligent controller based on direct inverse model control strategy using default input and output membership functions (gaussmf and linear) and different number of input membership functions. This is followed by training of the fuzzy inference system to obtain inverse model which was tested as the intelligent controller. The controller developed using two-input membership functions have successfully achieved the main target of setting the PM concentration (process output) below the set point which is the allowable World health organization (WHO) emission level for 20g/μm within a short settling time of 2s.

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