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The main objective of the optimal reagent addition was to maximize the quantity of product with minimal quantity of feed. In the present study, the optimal addition of reagents during the chemical leaching of coal was computed. Chemical leaching of coal was carried out using aqueous solution of caustic to dissolve and remove the mineral matter. Simulation studies were carried out using the optimal reagent addition for chemical leaching of coal in batch reactors. This was experimentally validated, using the bench-scale reactor setup with hierarchical optimization architecture. Chemical leaching experiments were conducted using West Bokaro coal. Samples collected at various time intervals during the experiment were analyzed. Variations in silica (SiO 2 ) and alumina (Al 2 O 3 ) concentrations, which were main constituents present in coal ash, were evaluated with respect to time for different concentrations of caustic. The simulation studies for optimal addition were carried out at 6, 8 and 10 intervals. An objective function, required for maximum ash removal, was solved, using sequential quadratic programming (SQP) algorithm to find out the optimum sequence for reagent dosing. An improvement of about 1% (wt) ash reduction on an average was observed with implementation of optimal reagent addition.

The important parameters in mineralization treatment of petroleum refinery wastewater by electro-Fenton process were successfully simulated by Computational Fluid Dynamics (CFD). The effects of H 2 O 2 /PRW (ratio of mole of H 2 O 2 per petroleum refinery wastewater volume), H 2 O 2 /Fe 2+ molar ratio, current density, pH and reaction time were numerically investigated. Materials distribution in the electrochemical cell was studied and CFD results demonstrated that distance between electrodes had no significant effect on the Chemical oxygen demand (COD) removal. Furthermore, the results were compared with the experimental data. The simulated data showed that maximum COD removal was around 82.55% at H 2 O 2 /PRW of 0.04, H 2 O 2 /Fe 2+ molar ratio of 2.75, pH of 3.5, current density of 52.5 mA/cm 2 and reaction time of 90 min while the experimental data obtained from the literature showed maximum COD removal of 77% in the same operating conditions. The simulated data showed a good agreement with the experimental ones.

The computational fluid dynamics approach is applied to packed bed reactors with moderate tube-to-particle diameter ratios. In order to generate irregular particle arrangements within the reactors, a modified ballistic deposition method is used. While our previous studies were focused on pressure drop and mass transfer characteristics, the present paper uses the same framework to investigate the dispersion phenomena occurring in such reactors. Two different methods, namely the tracer and the post-processing method, are applied. The first method imitates the experimental procedure in which a non-diffusive tracer is injected into the packed bed. The residence time can be evaluated from the evolution of the tracer concentration. The second method is purely numerical and allows fast residence time estimation. Simulation results are successfully validated against experimental data from literature. The suggested numerical analysis is a valuable tool toward a deeper understanding of the fundamental transport phenomena in such reactors and, consequently, for the improvement of the packed bed performance.

We analyse the steady-state operation of two types of reactor cascade without recycle. The first is a standard reactor cascade in which the feed stream enters into the first reactor. The second is a step-feed reactor cascade in which an equal proportion of the feed stream enters each reactor in the cascade. The reaction is assumed to be a biological process governed by Monod growth kinetics with a decay coefficient for the microorganisms. The steady-states of both models are found for an arbitrary number of reactors and their stability determined as a function of the residence time. We show that in a step-feed reactor cascade the substrate and biomass concentrations leaving the reactor of the cascade are identical to those leaving the first reactor of the cascade. We further show that this result is true for a general specific growth rate of the form μ ( S , X ). Thus for such processes the non-standard cascade offers no advantage over that of a single reactor. This is surprising because the use of a non-standard cascade has been proposed as a mechanism to improve the biological treatment of wastewater.

This paper studies empirical modeling and control of a biotrickling filter (BTF) used for air pollution control. Step response transfer function (TF) with first-order-plus-time-delay model and steady-state artificial neural network (NN) model were developed for BTF based on input–output (I/O) data obtained from simulation of a rigorous model. These simple models offer fast predictions compared to the rigorous model and render control implementation for BTF feasible. Gas velocity and inlet concentration of hydrogen sulfide (H 2 S) (target pollutant) were considered as the main process inputs while outlet concentration of H 2 S was selected as the BTF performance variable (output). The TF and NN models fitted well with the I/O data and the resulting regression coefficient values were above 0.97. Different simulations with the fitted NN model were performed and compared with the rigorous model data at steady state. The NN model perfectly captured the steady-state behavior of the BTF process. Two control strategies were implemented, namely proportional–integral/feedback control and model predictive control, also known as receding-horizon control. The controllers were based on the fitted TF model representation of BTF under study. For the control structure, gas velocity, inlet concentration, and outlet concentration were selected as manipulated, disturbance and controlled variables, respectively. Through set-point and disturbance change tests, it was observed that the model predictive controller offered superior set-point tracking capabilities while the feedback controller showed better control in dealing with disturbances. However, both controllers provided adequate control in general.

Attempts have been made to perform computer-aided analysis and simulation of the performance of a three-phase semifluidized bed bioreactor. The bioreactor is of biofilm type. Cocurrent operation with liquid (substrate solution) forming the continuous phase has been considered. Both air and feed solution are thus admitted from the bottom, the air moving up as tiny bubbles. Being semifluidized, the bioreactor is composed of a fully fluidized bed at the bottom and a packed bed at the top. The performance of the bioreactor is analysed by assuming it to be equivalent to two plug flow dispersion reactors (PFDRs) in series, each with a different value of dispersion number/axial dispersion coefficient. The performance equations (assuming dispersed flow) for both sections are written separately and then solved numerically using fourth-order Runge–Kutta method/successive over-relaxation method, based on appropriate boundary conditions. The specific case considered is the aerobic synthesis of Xanthan gum from cheese whey permeate, which follows Contois-type kinetic equation. The fractional gas holdup in both sections, height ratio of fluidized section to packed section and the semifluidization velocity are computed at the outset from selected experimental correlations (compiled from available literature). The results obtained from the developed software package, after verifying experimentally, are used to study and illustrate the performance characteristics of the bioreactor. It is observed that the three-phase semifluidized bed biofilm reactor of proposed design provides substantially large fractional conversion of substrate at large capacities, with relatively low reactor volume requirement.